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Economic Intelligence and
Knowledge Management
Competitiveness is based on knowledge.
The way companies acquire knowledge from their environment
and apply it, will determine their ability to survive into the
21st century volatile, complexe and uncertain world.
david.vallat@univ-lyon1.fr
@DavidVALLAT
https://www.researchgate.net/profile/David_Vallat
https://univ-lyon1.academia.edu/DVALLAT
Objectives…
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Competitive Intelligence: what for?
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Competitive Intelligence
(more seriously)
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So, is this Competitive
Intelligence?
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Competitive Intelligence, a
definition
« Competitive intelligence is the action
of defining, gathering, analyzing, and
distributing intelligence about
products, customers, competitors, and
any aspect of the environment needed
to support executives and managers
making strategic decisions for an
organization »http://en.wikipedia.org/
wiki/Competitive_intelligence
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To sum up Competitive
Intelligence
It’s about understanding the context…
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Competitive Intelligence
supports DECISION MAKING
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Why Competitive Intelligence?
Creating
knowledge
Understanding
the context
Making
decisions
Organizing this = Knowledge Management
SURVIVAL
@DavidVALLAT
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Why Competitive Intelligence?
Creating
knowledge
Understanding
the context
Making
decisions
Organizing this = Knowledge Management
SURVIVAL
@DavidVALLAT
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Survival
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HOW TO SURVIVE?
SURVIVAL
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SURVIVAL
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Some species evolved to perfectly
match their environment…
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We learn to
adapt.
Trial & Error (Tim HARFORD): https://www.youtube.com/watch?v=K5wCfYujRdE
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EMBRACING
CHANGE
SURVIVAL
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For adapting ourselves, we first
need to accept the idea of
change.
A video of the book:
https://www.youtube.com/wa
tch?v=16hxCB1Dvd4
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How to conduct change?
https://en.wikipedia.org/wiki/John_Kotter
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Why Competitive Intelligence?
Creating
knowledge
Understanding
the context
Making
decisions
Organizing this = Knowledge Management
SURVIVAL
@DavidVALLAT
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Understanding
the Context
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WHAT CONTEXT?
Understanding the context
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We live in a
hyperconnected world…
Hyperconnected
world:http://www3.weforum.org/docs/Global_IT_Report_
2012.pdf
Knowledge IS a competitive advantage:
- http://www3.weforum.org/docs/WEF_GCR_Report_201
1-12.pdf
- http://reports.weforum.org/global-competitiveness-
report-2012-2013/
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The Network Society
 « Our societies are increasingly structured around the
bipolar opposition of the Net and the Self » Castells, M. (1996,
second edition, 2000). The Rise of the Network Society, The Information Age: Economy, Society and Culture
Vol. I. Cambridge, MA; Oxford, UK: Blackwell, p. 3.
 « The promise of the Information Age is the unleashing
of unprecedented productive capacity by the power of
the mind ». (ibid. p. 390)
To go further:
http://globetrotter.be
rkeley.edu/people/Cas
tells/castells-
con4.html
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Digital World
« Thus, in the historical record, networks were the
domain of the private life, while the world of
production, power, and war was occupied by large,
vertical organizations, such as states, churches, armies,
and corporations that could marshall vast pools of
resources around the purpose defined by a central
authority. Digital networking technologies enable networks
to overcome their historical limits »
Castells, Manuel and Cardoso, Gustavo, eds., The Network Society: From
Knowledge to Policy. Washington, DC: Johns Hopkins Center for Transatlantic
Relations, 2005, p. 4)
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Knowledge Economy
« Researchers have found that productivity growth in this
period has been largely associated to three processes, all
of which are necessary conditions for productivity growth
to take place: generation and diffusion of new
microlectronics/digital technologies of information and
communication, on the basis of scientific research and
technological innovation; transformation of labor, with the
growth of highly educated, autonomous labor that is able
to innovate and adapt to a constantly changing global and
local economy; diffusion of a new form of organization
around networking. »
Castells, M. and Cardoso, G., eds., The Network Society: From Knowledge to Policy.
Washington, DC: Johns Hopkins Center for Transatlantic Relations, 2005, p. 8)
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3
levels
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Knowledge Worker
« Knowledge work can be differentiated from other forms of work by its
emphasis on "non-routine" problem solving that requires a combination of
convergent, divergent, and creative thinking. But despite the amount of
research and literature on knowledge work, there is no succinct
definition of the term » (Wikipedia, Knowledge Worker).
« Knowledge workers have high degrees of expertise,
education, or experience, and the primary purpose of their
jobs involves the creation, distribution or application of
knowledge » (Thomas Davenport, Thinking for a Living,
2005).
« To make knowledge work productive will be the great
management task of this century, just as to make manual
work productive was the great management task of the
last century » (Peter Drucker, Age of Discontinuity, 1969).
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CONTEXT IS MOVING
Understanding the context
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A little world…
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https://www.bcgperspectives.com/content/articles/corporate_strategy
_portfolio_management_future_of_strategy_most_adaptive_companies_
2012/
Full of Turbulences…
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A V.U.C.A. WORLD
Understanding the context
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It’s a V.U.C.A. World
 What is it? http://www.youtube.com/watch?v=72AzCY45fKU
 An US Army concept
http://www.carlisle.army.mil/usawc/dclm/slp2ndEd.pdf
 Complex and systemic problems:
 Example 1. http://youtu.be/zexit7Tk1GA
 Example 2. http://www.youtube.com/watch?v=9hXmyD9a4zg
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V.U.C.A.
http://hbr.org/2014/01/what-vuca-really-means-for-you/ar/1
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C.I. TOOLS TO GRASP
THE CONTEXT
Understanding the context
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A reminder about C.I.
 The basic starting point for competitive
intelligence is to define the problem.
 Competitive intelligence should be a value-added
service to managers who are facing critical
strategic decisions.
 What are the Key Intelligence Topics?
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How to grasp the context?
 More People/Method than Tools…
 SWOT Analysis => to understand your own
competitive advantages in relation to the
marketplace
 PESTEL analysis => to examine the external
macro-environment
 Porter’s Five Forces Model => industry analysis
 Porter’s Four Corners Analysis => to understand the
position of a competitor
 System thinking! & Key Intelligence Topics
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SWOT
 A method used to evaluate the strengths,
weaknesses, opportunities, and threats involved in
a project or in a business venture.
 http://en.wikipedia.org/wiki/SWOT_analysis
 SWOT Online: http://i-swot.com
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PESTEL Analysis
 Identifying "Big Picture"
Opportunities and Threats
 Objective: developping an
objective view of the
environment
 PESTEL & SWOT are often
linked
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PESTEL Analysis Examples
 Identifying "Big Picture" Opportunities and Threats
 Objectives
 PESTEL & SWOT
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Porter’s 5 forces (1)
Porter’s Five Forces analysis, developed by Michael E.
Porter of Harvard Business School, is a framework for
assessing and evaluating the competitive strength
and position of a business organization.
There are five forces which determine the
competitive intensity and attractiveness of a market:
supplier power, buyer power, competitive rivalry,
threat of substitute products/technology change, and
threat of new market entrants.
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Porter’s 5 forces (2)
 Threat of New Entrants: an industry with low
barriers of entry will have intense competition as
opposed to an industry with major barriers of
entry.
 Suppliers tend to have strong influence within an
industry when they are few/acting together.
 Power of Buyers: customers often dictate pricing
and they demand certain levels of quality.
 Substitute Products: new or emerging substitutes
for a product will change competitive forces
 Rivalry: this competitive rivalry may decline when
times are good and everyone can grow.
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Porter’s 5 forces (3)
http://www.cosxo.com/analysis/
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Porter's four corners model (1)
 « Porter’s four corners model is a predictive tool
designed by Michael Porter that helps in determining a
competitor’s course of action. Unlike other predictive
models which predominantly rely on a firm’s current
strategy and capabilities to determine future strategy,
Porter’s model additionally calls for an understanding of
what motivates the competitor. This added dimension of
understanding a competitor's internal culture, value
system, mindset, and assumptions helps in determining
a much more accurate and realistic reading of a
competitor’s possible reactions in a given situation »
http://en.wikipedia.org/wiki/Porter's_four_corners_mo
del
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Porter's four corners model (2)
http://www.cosxo.com/analysis/
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Key Intelligence Topics
 What are the Key Intelligence Topics (KIT)?
 What impact will bitechnology / internet have on our high
volume product line?
 How is our competitor able to retain major government
contracts year after year
 When these contracts come open for bid?
 What is the timeline for when our competitor will launch
their new US service?
 Should we expand our Saigon facility or build a new
facility in Hanoi?
 Who are the key customers of our competitor?
 How does this new regulation impact our business?
 How well does this supplier perform with other companies?
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Wargaming: a fun way to
implement these tools…
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Wargaming: what is it?
 Human-based simulations. These are intelligence-driven,
analytically and behaviorally modeled role-playing exercises
http://www.bengilad.com
 Simple - over-sophisticated, long and large scale games cost a lot
more but do not produce better results.
 Transparent - if you don't understand the exotic algorithm, how likely
are you to trust the strategy?
 Empowering - computer games don't understand internal politics, but
you have to.
 Fun - teams that learn how to role-play competitors with real market
intelligence and character-building techniques maintain enthusiastic
external focus for years.
 Inexpensive - there is no good reason for games to cost hundred of
thousands or even millions of dollars. If you know a good reason,
write us.
 Accessible - to truly improve the bottom line, managers at all levels
of the organization should be able to use this amazing tool, not just
few senior execs at the top.
 Realistic - intelligence-based, human games are magnitudes more
realistic than even the most sophisticated mathematical modeling.
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Wargaming: an example
 http://www.mckinsey.com/insights/strategy/playing_war_ga
mes_to_win
 « As the global downturn kicked in, a high-tech company’s
senior executives decided to run a war game to prepare
themselves for the uncertainties of the post-crisis landscape.
After two days of simulations—when teams representing
competitors and stakeholders role-played against a
“company” team—the executives understood that a strong
competitor on the sidelines was likely to enter the market
aggressively. The executives also realized that the low end of
the product range would face more price pressure than they
had been anticipating. Moreover, while there would probably
be industry mergers and acquisitions, as the company had
expected, the deals were unlikely to kick off a wave of M&A
or to have a material impact on the company’s share of any
market. »
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Wargaming: further readings
 http://www.mckinsey.com/insights/innovation/battle-
test_your_innovation_strategy
 http://www.mckinsey.com/insights/strategy/playing_w
ar_games_to_win
 Ben Gilad’s book: http://www.amazon.com/Business-
War-Games-Outmaneuver-Competition
 http://www.bengilad.com
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What you don’t need in a
VUCA World (1)
 A « God Complex »
http://www.ted.com/talks/tim_harford.html
 Scientific
managementhttp://en.wikipedia.org/wiki/Frederick_Wi
nslow_Taylor
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What you don’t need in a
VUCA World (2)
AND WHAT WE NEED?
 We need trial and error (and humility) => simulations
 We need to share, discuss, collaborate
 We need to manage Knowledge
http://www.ibicity.fr/blog/public/Leadership_Agility_--
_HRPS_Reprint_Permission__revised_.pdf
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Why Competitive Intelligence?
Creating
knowledge
Understanding
the context
Making
decisions
Organizing this = Knowledge Management
SURVIVAL
@DavidVALLAT
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Creating
Knowledge
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Why Knowledge Creation?
 Knowledge is the basis for innovation
 Innovation is the driving force behind long term
competitive advantage
 Competitive advantage ensures corporate
longevity
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WHAT IS
KNOWLEDGE?
Creating Knowledge
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Data/Information/Knowledge
(1)
 DATA is a set of objective facts about events
 Data as an abstract concept can be viewed as the lowest level
of abstraction, from which information and then knowledge are
derived.
 INFORMATION is a message
 As with any message, it has a sender and a receiver. Information
is meant to change the way the receiver perceives something,
to have an impact on his judgment and behavior. It is data that
makes a difference.
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Data/Information/Knowledge
(2)
 Information becomes knowledge, through:
 Comparison
 Consequences
 Connections
 Conversation
 Knowledge is meant for action
 A strong link between knowledge and
experience
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But what Knowledge
really is…? (1)
• Knowledge is what you see/feel?
• Knowledge is what you believe?
• Knowledge is what is true?
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But what Knowledge
really is…? (2)
• « Justified true belief » (notion derived from Plato’s
dialogue Theaetetus – IVth century BC ).
• « belief » = doxa = acceptance
• « true »: a false belief is not considered to be knowledge
(e.g. flat earth theory)
• « justified »: justification for believing it is true
The relationship between belief and knowledge is that a belief is
knowledge if the belief is true, and if the believer has a justification
(reasonable and necessarily plausible assertions/evidence) for
believing it is true.
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But what Knowledge
really is…? (3)
• The primary problem in epistemology
(study of knowledge) is to understand
exactly what is needed in order for us to
have knowledge.
• We need knowledge to take action…
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But what Knowledge
really is…? (4)
• Karl POPPER (1902-1994) took falsifiability as
his criterion of demarcation between what is,
and is not, genuinely scientific (The Logic of
Scientific Discovery, 1934). => « justified »
• So, science/knowledge is open to discussion.
• « justified »: with proofs that can be discussed
(falsifiability)
• « true »: reproducibility
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How to gather knowledge?
• a method of inquiry must be based on gathering
observable and measurable evidence subject to specific
principles of reasoning and experimentation. The
scientific method consists of the collection of data
through observation and experimentation, and the
formulation and testing of hypotheses (Wikipedia,
Knowledge)
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Knowledge Creation
=> By trial and error and collaboration
MOON CRASH…
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Moon Crash:
Lesson Learned Workshop (1)
 LLW: a simple method to discuss and transfer
experience
 What did we learn?
 In order to create real knowledge (Justified true
belief), we have to answer the question with a
scientific method:
 gathering observable and measurable evidences
 formulation and testing of hypotheses (+ reproducibility)
 All this is open to discussion (falsifiability)
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Moon Crash:
Lesson Learned Workshop (2)
 (Normally) a group creativity is more than the
added creativity of each member.
 Discussion and sometimes conflicts foster creativity
 What is the starting point of the decision-making
process? (KIT)
 What was your decision-making process (consensus,
vote)?
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The power of discussion
(in KM)
 Don’t try to impose your opinion. Expose your point of view
as logically as possible (with evidences when possible).
Listen carefully to the responses of other participants (they
may be right!) ≠ God complex
 If the discussion is in a dead end don’t try to adopt
majority’s point of view. Try to find the most acceptable
solution for all participants. = motivation
 Beware of superficial agreements reached too quickly and
too easily. Take your time to reach a consensus.
 Differences of opinion are normal and inevitable. They
often are a guarantee of success for the final decision.
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TACIT & EXPLICIT
KNOWLEDGE
Creating Knowledge
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Types of Knowledge:
Tacit vs Explicit (1)
Michael POLANYI, The Tacit Dimension, University of Chicago
Press, 1966.
“we can know more than we can tell.”
Tacit knowledge can be distinguished from explicit knowledge in
three major areas
 Transferring knowledge
 Methods for acquisition
 Potential of aggregation and modes of appropriation
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Types of Knowledge:
Tacit vs Explicit (2)
 Ikujiro NONAKA (1991): The
Knowledge Creating Company,
Harvard Business Review
http://hbr.org/2007/07/the-
knowledge-creating-company/es
http://en.wikipedia.org/wiki/Tacit_kn
owledge
His research suggested that a successful KM
effort needs to convert internalized tacit
knowledge into explicit knowledge to share it.
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The SECI Model
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meetings
brainstorming
quality circles
CoP
LLW
training programs
training manual
consolidated
annual financial
performance
report
Ikujiro NONAKA (1991), ’’The Knowledge
Creating Company’’, Harvard Business Review
 First read the article (explicit knowledge) from I. Nonaka:
http://hbr.org/2007/07/the-knowledge-creating-company/es
 2) Try to sum up / sort out the main ideas (explicit => tacit =
internalization)
 3) Try to use the SECI model to analyse your organization (tacit
knowledge creation)
 A) For each stage of the SECI model try to find precise examples in
your organization => write them (to learn you have to act)
 B) Then try to organize your ideas, try to prioritize questions to build
proposals to help knowledge creation in your organization (tacit =>
explicit = externalization) => write individually your proposals
 4) When you have finished share your ideas in a team of 3 to 5
(tacit=>tacit = socialization) => each in turn explains what he has
done (Community of Practice)
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’’The Knowledge Creating
Company’’ (1)
 P.2« In an economy where the only certainty is uncertainty,the one sure
source of lasting competitive advantage is knowledge. »
 P.3 Westernway≠Eastern way of thinking about knowledge (epistmology)
 P.3 Successful japenese companies => «These companies have become
famous for their ability to respond quickly to customers, create new
markets, rapidly develop new products, and dominate emergent
technologies. »
 P.3 The success comes from «their unique approach to managing the
creation of new knowledge. »
 P.3 How? => by «managing that serendipity to the benefit of the
company, its employees, and its customers. » (creativity)
 P3 « A company is not a machine but a living organism ». (learning
organization)
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 P.3 « The centerpiece of the Japanese approach is the
recognition that creating new knowledge is not simply a
matter of “processing” objective information. Rather, it
depends on tapping the tacit and often highly subjective
insights, intuitions, and hunches of individual employees
and making those insights available for testing and use by
the company as a whole. »
 P.3 It’s possible with a shared vision => «The key to this
process is personal commitment, the employees’ sense of
identity with the enterprise and its mission. » ; « a shared
understanding of what the company stand for, where it is
going, what kind of world it wants to live in, and, most
important, how to make that world a reality.» (pragmatism)
@DavidVALLAT
’’The Knowledge Creating
Company’’ (2)
81
 P.4 « New knowledge always begins with the individual. A
brilliant researcher has an insight that leads to a new patent. A
middle manager’s intuitive sense of market trends becomes the
catalyst for an important new product concept. A shop-floor
worker draws on years of experience to come up with a new
process innovation. In each case, an individual’s personal
knowledge is transformed into organizational knowledge valuable
to the company as a whole. »
 P.4 and « Making personal knowledge available to others is the
central activity of the knowledge- creating company. »
 P.4/5 How to use the SECI Model
 P.6 Why it’s easy for japanese people to convert tacit knowledge
into explicit knowledge? Because they are able to use «figurative
language and symbolism that managers can draw from to
articulate their intuitions and insights.»
@DavidVALLAT
’’The Knowledge Creating
Company’’ (3)
82
 P.6 Use of metaphor: « Through metaphors, people put
together what they know in new ways and begin to express
what they know but cannot yet say. »
 P.7 « Often, metaphoric images have multiple meanings and
appear logically contradictory or even irrational. But far
from being a weakness, this is in fact an enormous
strength. For it is the very conflict that metaphors embody
that jump-starts the creative process. »
 P.7 « But while metaphor triggers the knowledge-creation
process, it alone is not enough to complete it. The next
step is analogy. »
 P.7 Last step: TRIAL (and error) «Finally, the last step in the
knowledge-creation process is to create an actual model. »
@DavidVALLAT
’’The Knowledge Creating
Company’’ (4)
83
 a Metaphor is a figure of speech which makes an implicit,
implied or hidden comparison between two things that are
unrelated but share some common characteristics. In other
words, a resemblance of two contradictory or different
objects is made based on a single or some common
characteristics. Two ideas in one expression ; a connection
between two things distantly related: THEORY OF
AUTOMOBILE EVOLUTION
 Metaphor triggers the knowledge creation process because it
spurs creativity.
 Analogy: it’s more strutured than metaphor. A comparison
between two things, typically on the basis of their structure
and for the purpose of explanation or clarification. (computer
and brain ; aluminium beer can / aluminium copier drum).
@DavidVALLAT
Metaphor & Analogy
84
 P.7 Converting tacit knowldege into explicit: « first, by linking
contradictory things and ideas through metaphor; then, by
resolving these contradictions through analogy; and, finally,
by crystallizing the created concepts and embodying them in a
model, which makes the knowledge available to the rest of
the company. »
 P.7 Redundancy (to foster agility): « The fundamental principle
of organizational design at the Japanese companies I have
studied is redundancy—the conscious overlapping of company
information, business activities, and managerial responsibilities.
»
 P.8 With Redundancy you have dialogue. « This helps create a
“common cognitive ground” among employees and thus
facilitates the transfer of tacit knowledge. »
@DavidVALLAT
’’The Knowledge Creating
Company’’ (5)
85
 P.8 « The organizational logic of redundancy helps
explain why Japanese companies manage product
development as an overlapping process where
different functional divisions work together in a
shared division of labor. »
 P.8 This is a collaborative organization (which needs
transparency): « Free access to company information
also helps build redundancy. When information
differentials exist, members of an organization can no
longer interact on equal terms, which hinders the
search for different interpretations of new knowledge. »
@DavidVALLAT
’’The Knowledge Creating
Company’’ (6)
86
 P.9 In a VUCA world « Senior managers give voice to a company’s
future by articulating metaphors, symbols, and concepts that
orient the knowledge-creating activities of employees. They do
this by asking the questions, What are we trying to learn? What
do we need to know? Where should we be going? Who are we? If
the job of frontline employees is to know “what is,” then the job
of senior executives is to know “what ought to be.” »
 P.10 Managers give a vision:«Umbrella concepts and qualitative
criteria for justification are crucial to giving a company’s
knowledge-creating activities a sense of direction. »
 P.11 To end as we started:«middlemanagers synthesized the tacit
knowledge of both frontline employees and senior executives,
made it explicit, and incorporated it into new technologies and
products. In this respect, they are the true “knowledge
engineers” of the knowledge-creating company. » (middle-up-
down management: https://ai.wu.ac.at/~kaiser/birgit/Nonaka-
Papers/Toward-middle-up-down-mgmt-1988.pdf )
@DavidVALLAT
’’The Knowledge Creating
Company’’ (7)
87
To Sum up Nonaka’s approach
 « In an economy where the only certainty is uncertainty,the one
sure source of lasting competitive advantage is knowledge. »
 > «These companies have become famous for their ability to
respond quickly to customers, create new markets, rapidly
develop new products, and dominate emergent technologies. »
 HOW:
 « …by giving a company’s knowledge-creating activities a sense
of direction »
 « Making personal knowledge available to others is the central
activity of the knowledge- creating company. » (SECI process)
 «middlemanagers synthesized the tacit knowledge of both
frontline employees and senior executives, made it explicit, and
incorporated it into new technologies and products. In this
respect, they are the true “knowledge engineers” of the
knowledge-creating company. »
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@DavidVALLAT
Further Readings
89
@DavidVALLAT
Experimentation of the SECI Model
90
3) Try to use the SECI model to
analyse your organization (tacit
knowledge creation)
A) For each stage of the SECI
model try to find precise
examples in your
organization => write them
(to learn you have to act)
B) Then try to organize your
ideas, try to prioritize
questions to build proposals
to help knowledge creation
in your organization (tacit =>
explicit = externalization) =>
write individually your
proposals
4) When you have finished share
your ideas in a team of 3 to 5
(tacit=>tacit = socialization) =>
each in turn explains what he has
done (Community of Practice)
5) Share with me…
KNOWLEDGE
CREATION TOOLS
Creating Knowledge
@DavidVALLAT
91
Classical Knowledge Creation
Tools (= creativity)
 Outsourcing Knowledge Creation…
 Other methods to spur creativity:
 Brainstorming
 Mind Mapping http://www.mindomo.com
 6-3-5 Method (Brainwriting)
 6 participants. Each participant thinks up 3 ideas every 5
minutes. The ideas are written down on a worksheet and
passed on to the next participant. The participant reads the
ideas and uses them as inspiration for more ideas… After 6
rounds in 30 minutes the group has thought up a total of
108 ideas.
92
@DavidVALLAT
Brainstorming
david.vallat@univ-lyon1.fr
94
Mind Mapping
@DavidVALLAT
Creative Environment (1)
95
 To be creative, it helps to live in a creative
environment.
 What is a creative environment?
@DavidVALLAT
96
97
Creative Environment (2)
98
A pleaseant physical environment (calm, furnishings, light)
is not enough…
 No distraction (telephone, mail, other interruptions)
 Sufficient time
 Technical equipment (flipchart, projector, paper, sticky
notes, games, etc.)
 Creative skills
 Constructive communication culture
 Top management supports ceativity
@DavidVALLAT
LEADERSHIP
Less classical Tools
In a creative environment you can experience less
classical tools:
 Metaphor/Analogy/Symbol (Nonaka)
 Storytelling (in business):
https://en.wikipedia.org/wiki/Storytelling
 Wargaming
 Gamestorming:
http://www.youtube.com/watch?v=3mrtu4MmthE
http://en.wikipedia.org/wiki/Gamestorming
99
@DavidVALLAT
100
Transfer of Experience (1)
 The transfer of experience is a special form of
knowledge transfer.
 This type of transfer should serve to broaden the
spectrum of decision-making possibilities open to
employees and avoid unnecessary repeated learning
through trial and error.
 The transfer of experience can be through
INTERNALIZATION (tacit=>explicit) or SOCIALIZATION
(tacit=>tacit)
 INTERNALIZATION = LLW and CoP
 SOCIALIZATION = meetings (and ‘BA’)
@DavidVALLAT
101
Transfer of Experience (2)
Transfer of Experience
through :
Personalization Codification
Organisational level Human Network (expert
database, social
network)
Repository and
distribution source for
documented learning
experiences (Intranet)
Team level Support: Communities
of Practice
Support: Lessons
Learned Workshops
Individual level Transfer of experience
through processes of
communication and
mutual observation
Transfer of experience
through information and
documentation
@DavidVALLAT
102
Transfer of Experience (3)
Advantages and disadvantages
of a Codification strategy (Externalization)
+
+ knowledge is always available
+ particularly suitable for frequent re-use
+ can be passed on quickly and easily; high degree of distribution
-
- codification is complex and time-consuming
- documented knowledge can quickly become obsolete
- complicated wording or terminology makes knowledge difficult to
absorb
- context cannot be fully described/provided
- some knowledge cannot be made explicit
- different "mental models" prevent direct use of documented
knowledge
@DavidVALLAT
103
Transfer of Experience (4)
Advantages and disadvantages
of a Personalization strategy (Socialization)
+
+ knowledge is always up-to-date
+ complexity of knowledge transfer can be adapted to the situation
+ creative innovation possible during transfer
-
- complicated search for the right person
- the right person is not available
- personal aversion
@DavidVALLAT
104
Tools for Transfering
Experience (Internalization)
 Community of Practice (Personalization /
Team level) ≠ project
 Lessons Learned Workshop (Codification /
Team level) => project
@DavidVALLAT
105
Community of Practice (1)
« A community of practice (CoP) is a group of
people who share a craft and/or a profession.
The group can evolve naturally because of the
members' common interest in a particular
domain or area, or it can be created specifically
with the goal of gaining knowledge related to
their field.
It is through the process of sharing information
and experiences with the group that the
members learn from each other, and have an
opportunity to develop themselves personally
and professionally » (Wikipedia)
@DavidVALLAT
106
Community of Practice (2)
 Real / Virtual / Mobile CoP
 Origin: LAVE, Jean; WENGER, Etienne (1991).
Situated Learning: Legitimate Peripheral
Participation. Cambridge: Cambridge University
Press
 Example: Xerox customer service representatives
(Eureka
database)http://www.kmworld.com/Articles/Edito
rial/Features/Best-Practices-Eureka!-Xerox-
discovers-way-to-grow-community-knowledge.-.-
And-customer-satisfaction-9140.aspx
 CoP ≠ Project team
@DavidVALLAT
107
Community of Practice (3)
 CoP and KM => how to transfer tacit knowledge?
 CoPs bridge the gap between knowing what and
knowing how (sensemaking): while organizations
tend to provide manuals to meet the training needs
of their employees, CoPs help foster the process of
storytelling among colleagues which, in turn, helps
them strengthen their skills on the job.
 Motivation to share knowledge is critical to success
in communities of practice. Studies show that
members are motivated to become active
participants in a CoP when they view knowledge as
meant for the public good, a moral obligation
and/or as a community interest.
@DavidVALLAT
108
Community of Practice (4)
Cultivating CoP by:
 Design the community to evolve naturally
 Create opportunities for open dialog within and
outside
 Allow different levels of participation
 Develop both public and private exchanges
 CoPs should create opportunities for participants
to explicitly discuss the value and productivity of
their participation in the group
 Combine familiarity and novelty
 Find a regular rhythm for the community
@DavidVALLAT
Lessons Learned Workshop (1)
• Why closing a project with a LLW?
• A simple method to discuss and transfer
experience:
• What was done well in the project?
• What could have been improved?
• What would be the ideal situation for points that could have
been improved?
• What would I personally do differently in the next project?
• What should the organisation do differently in the next project?
@DavidVALLAT
Lessons Learned Workshop (2)
Defining the
relevant issues
Lessons Learned
Workshop
Processing and
applying the
results
@DavidVALLAT
• How to manage a Lessons Learned Workshop?
• Background (detailed presentations of the
project - from start to finish)
• Cluster building (brainstorming)
• Lessons learned (these are summarised to
produce a list of recommendations for the
organisation)
• After the workshop (initiate organisational
learning to implement changes).
david.vallat@univ-lyon1.fr
Lessons Learned Workshop (3)
@DavidVALLAT
Socialization: the ‘BA’ concept
 You have meetings…
 Knowledge is relational (SECI) ≠ Western epistemology has
traditionally viewed knowledge as explicit.
 Knowledge needs a context to be created.
 The context is a time and place (physical, virtual, mental) =
‘BA’ (Nonaka)
 TIME: when it’s the moment…
 PLACE:
- Physical = an office,
- Virtual = a social network
- Mental = shared culture and objectives
 It’s where/when people can interact to create situated
knowlegde (like a CoP with an objective).
112
@DavidVALLAT
Why Competitive Intelligence?
Creating
knowledge
Understanding
the context
Making
decisions
Organizing this = Knowledge Management
SURVIVAL
@DavidVALLAT
113
Making
Decisions
114
HOW TO MAKE
GOOD DECISIONS?
Making Decisions
@DavidVALLAT
115
Decision-making and
organization
 The decision-making process is an organizational
process.
116
@DavidVALLAT
A little game…
 Group of 4 or 5 people
 Try to solve the puzzle as fast as possible
 How do you learned to solve the problem?
117
HOW TO MAKE
GOOD DECISIONS?
1. ROUTINES
Making Decisions
@DavidVALLAT
118
Organizational Routines
 What is a routine?
 a sequence of actions regularly
followed; a fixed program.
 organisational routines are described as
the relatively mindless repetition of
actions that have been well-established
via evolution or voluntary design
119
@DavidVALLAT
 Why a routine?
 The right way to do things…
An organizational memory.
 A routine may be a trap…
Organizational Traps
 Competency Trap: The Innovator’s Dilemma (C.
Christensen)
http://www.forbes.com/sites/stevedenning/2012/
04/05/clayton-christensen-and-the-innovators-
smackdown/
http://www.youtube.com/watch?v=35z03U3wugs
 Surpersticious Learning
http://blogs.hbr.org/2011/07/superstitious-learning/
 A little God in his quiet realm= GOD
COMPLEXhttp://www.youtube.com/watch?v=K5wCfYujR
dE
120
@DavidVALLAT
The Innovator’s Dilemma
(C. Christensen) - 1
 The Innovator’s Dilemma (C. Christensen, 1997)
http://www.forbes.com/sites/stevedenning/2012/04/
05/clayton-christensen-and-the-innovators-
smackdown/
 “That book documents how market-leading companies have
missed game-changing transformations in industry after
industry—computers (mainframes to PCs), telephony (landline
to mobile), photography (film to digital), stock markets (floor
to online)—not because of ‘bad’ management, but because
they followed the dictates of ‘good’ management. They
listened closely to their customers. They carefully studied
market trends. They allocated capital to the innovations that
promised the largest returns. And in the process, they missed
disruptive innovations that opened up new customers and
markets for lower-margin, blockbuster products.”
david.vallat@univ-lyon1.fr
@DavidVALLAT
The Innovator’s Dilemma
(C. Christensen) - 2
 Examples:
 Example: “When Toyota was making rusty little subcompacts, it
made no sense for General Motors to go after the subcompact market,
when the profits they could get on bigger SUVs and pickup trucks made
all the sense in the world. Toyota just made their products better and
better, until eventually customers who used to bigger General Motors
cars could now buy cheaper ones. Now Toyota is making the best in
the world, while at the bottom, the Koreans, Kia and Hyundai, have
stolen the low end of the market. It’s not because Toyota is asleep at
the switch. They have to decide, ‘Should we go down and compete
against Kia? Or should we go up and compete against Mercedes?’”
david.vallat@univ-lyon1.fr
@DavidVALLAT
Surpersticious Learning
 Surpersticious Learning
http://blogs.hbr.org/2011/07/superstitious-learning/
 « Superstitious learning takes place when the
connection between the cause of an action and the
outcomes experienced aren’t clear, or are
misattributed. »
 « For instance, a major retailer prided itself on the
steady, profitable growth of its music CD business over a
long period of time. […] The real story was not one of
success. Rather, it was one of grabbing share from a
market that was in deep decline. »
@DavidVALLAT
Avoiding Organizational
Traps (routines)
 A lot of traps…
 How to avoid them?
 Meet Chris ARGYRIS
http://en.wikipedia.org/wiki/Chris_Argyris
 Organizations need to learn to adapt
 Argyris, C., & Schön, D. (1974) Theory in practice: Increasing
professional effectiveness. San Francisco: Jossey Bass.
 Espoused theory and Theory-in-use
@DavidVALLAT
Espoused theory and
Theory-in-use
 Espoused theory: values people believe their behaviour is
based on - what individuals believe is how they would behave
in a particular circumstance.
 Theory-in-use: values implied by their behaviour, or the maps
they use to take action - how individuals actually behave in
that circumstance.
david.vallat@univ-lyon1.fr
When someone is asked how he would behave under certain circumstances,
the answer he usually gives is his espoused theory of action for that
situation. This is the theory of action to which he gives allegiance and
which, upon request, he communicates to others. However, the theory
that actually governs his actions is his theory-in-use; furthermore, the
individual may or may not be aware of the incompatibility of the two
theories (Argyris and Schön, Theory in Practice, Jossey-Bass, 1974, p 11.)
A Loop Story…(i)
 Organizational learning is about detecting
and correcting error
Source: http://www.afs.org/blog/icl/?p=2653
david.vallat@univ-lyon1.fr
A Loop Story…(ii)
 C. Argyris, “Double-Loop Learning in Organisations“, Harvard
Business Review Vol 55, No 5, 1977, pp 115–125.
 C. Argyris & D. Schön, Organizational Learning: A Theory of Action
Perspective, Addison-Wesley, 1978.
 Single-Loop learning => Model I (Theory-in-
use)
 Double-Loop learning => Model II (Espoused
theory)
david.vallat@univ-lyon1.fr
Model I (i)
 The governing Values of Model I are:
 Achieve the purpose as the actor defines it
 Win, do not lose
 Suppress negative feelings
 Emphasise rationality
 Primary Strategies are:
 Control environment and task unilaterally
 Protect self and others unilaterally
david.vallat@univ-lyon1.fr
Model I (ii)
 Usually operationalised by:
 Unillustrated attributions and evaluations eg. "You seem
unmotivated"
 Advocating courses of action which discourage inquiry
eg. "Lets not talk about the past, that's over."
 Treating ones' own views as obviously correct (God complex)
 Making covert attributions and evaluations ("he has no
strategic vision »)
 Face-saving moves such as leaving potentially embarrassing
facts unstated
 Consequences include:
 Defensive relationships
 Low freedom of choice
 Reduced production of valid information
 Little public testing of ideas
david.vallat@univ-lyon1.fr
Model I (iii)
Source:
http://www.reallylearning.com/Free_Resources/Organisational_
Learning/organisational_learning.html
@DavidVALLAT
Model I (iv)
 « Skilled Incompetence »
 Organizational Defensive Routines (ODR)
 Organizational Defensive Pattern (ODP)
Defensive
Reasoning
≠
Productive
Reasoning
david.vallat@univ-lyon1.fr
Model II (i)
 The governing values of Model II include:
 Valid information
 Free and informed choice
 Internal commitment
 Strategies include:
 Sharing control
 Participation in design and
implementation of action
david.vallat@univ-lyon1.fr
Model II (ii)
 Operationalised by:
 Attribution and evaluation illustrated with
relatively directly observable data
 Conflicting views allowed
 Encouraging public testing of evaluations
 Consequences should include:
 Minimally defensive relationships
 High freedom of choice
 Increased likelihood of double-loop learning
david.vallat@univ-lyon1.fr
Model II (c)
Source:
http://www.reallylearning.com/Free_Resources/Organisational_
Learning/organisational_learning.html
david.vallat@univ-lyon1.fr
Model I Observed
 C. Argyris, “Teaching Smart People How to Learn“,
Harvard Business Review, 1991.
 Learning behaviours in US consultancies
 Inability to learn from failure (because of the God
complex)
david.vallat@univ-lyon1.fr
Does Organizational
Development is Possible?
 From Organizational I (O-I) learning systems to
Organizational II (O-II) learning system
 Intervention strategy in 6 phases
 Phase 1 Mapping the problem as clients see it
 Phase 2 Internalization of the map by clients
 Phase 3 Test the model
 Phase 4 Invent solutions
 Phase 5 Produce the intervention
 Phase 6 Study the impact
david.vallat@univ-lyon1.fr
Summary (1)
http://instep.net.nz/Communication-and-relationships/Models-and-theories/Model-I-
and-Model-II
@DavidVALLAT
Summary (2)
 Organizational learning is about detecting
and correcting error
Source: http://www.afs.org/blog/icl/?p=2653
david.vallat@univ-lyon1.fr
An exercise
 Try to identify and describe a case of single-loop
learning in your company. Why people are acting like
this?
 Try to identify and describe a case of double-loop
learning in your company. What are the levers for
learning in this environment?
 Share with others in your group.
139
An exercise: Left hand
column
 Think of a work situation you are concerned about
 Divide a piece of paper into two columns
 Ladder of inference
david.vallat@univ-lyon1.fr
Ladder of inference
http://gwynteatro.wordpress.com/2011/03/13/climbing-the-ladder-of-inference/
david.vallat@univ-lyon1.fr
HOW TO MAKE
GOOD DECISIONS?
2. WE ARE BLIND
Making Decisions
@DavidVALLAT
142
A triple blindness
 1) Because we don’t understand probabilities
 Black Swan
 Two brains
 2) We don’t see weak signals
 3) We are not aware of consequences (system thinking)
143
Black Swan Theory
144
 Rare and improbable events do occur
much more than we dare to think:
these events are black swans.
Why Black Swans?
 Because of the Ludic Fallacy (too much faith in statistics)
 statistics is applicable only in some domains, for instance
Casinos.
 It is impossible to be in possession of the entirety of available
information.
 Small unknown variations in the data could have a huge
impact.
 Because of the Narrative Fallacy
 the narrative fallacy addresses our limited ability to look at
sequences of facts without weaving an explanation into them,
or, equivalently, forcing a logical link, an arrow of relationship
upon them. We like to find stories…
145
We don’t understand statistics…
146
Two brains:
ONE FAST (system 1) to take every day decisions but also
quick decisions => fast, instinctive and emotional
ONE SLOW (system 2) to solve difficult problems => Slow,
effortful, infrequent, logical, calculating, conscious.
 Selective attention test
https://www.youtube.com/watch?v=vJG698U2Mvo
‘halo effect’
https://en.wiki
pedia.org/wiki
/Thinking,_Fast
_and_Slow
Don’t forget weak signals
david.vallat@univ-lyon1.fr
Weak signals - Definition
 Weak Signals are past or current developments/issues
with ambiguous interpretations of their origin, meaning
and/or implications. They are unclear observables
warning us about the probability of future events.
david.vallat@univ-lyon1.fr
Some weak signals…
 New unmet consumer or customer needs
 The entry of new competitors and new suppliers
 The advent of new breakthrough technologies
 Changes in your organization’s core performance
metrics
 Unfulfilled business and other potential opportunities
 Broad disruptive events
 Premonitions, anxieties, and/or intuitions
http://www.forbes.com/sites/martinzwilling/2013/12/14/how-good-is-your-business-at-reading-weak-s
david.vallat@univ-lyon1.fr
Bad ideas for sorting out
weak signals
 Remember the God complex?
 Relying (only) on Tools (SWOT Analysis,
etc.)
 Denial (=> Kodak)
david.vallat@univ-lyon1.fr
What to do then?
 People + Tools
 Understand the context (VUCA)
 SWOT Analysis => to understand your own competitive
advantages in relation to the marketplace.
 Porter’s Five Forces Model => industry analysis
 Porter’s Four Corners Analysis => to understand the
position of a competitor.
 Key Intelligence Topics
 Wargame
 KNOWLEDGE CREATION
 System thinking!
david.vallat@univ-lyon1.fr
SYSTEM THINKING
Making Decisions
@DavidVALLAT
152
From O.L. to the L.O.
 Peter SENGE and the concept of the ‘learning
organization’ in The Fifth Discipline (1990)
 An ‘idealistic pragmatist’:
 He wants to transform the workplace, bringing human values
in it.
 He wants to decentralize the role of leadership in
organizations (to enhance the capacity of all people to work
productively toward common goals)
 Society for Organizational Learning
(SoL)http://www.solonline.org
 System thinking:
http://www.youtube.com/watch?v=iLFCrv7-
XlIhttps://www.youtube.com/watch?v=rDxOyJxgJeA
david.vallat@univ-lyon1.fr
Toward the LO (1)
 What is a LO?
 « …organizations where people continually expand their
capacity to create the results they truly desire, where new and
expansive patterns of thinking are nurtured, where collective
aspiration is set free, and where people are continually
learning to see the whole together. » (P. Senge, The Fifth
Discipline: The art and practice of the learning organization,
London: Random House. 424 + viii pages, 1990, p.3).
 Learning organizations are possible because we are all
learners:http://www.ted.com/talks/sugata_mitra_shows_how_kids
_teach_themselves.html
 J. Medina, Brain Rules: http://brainrules.net
Toward the LO (2)
 Benefits of a LO:
- Maintaining levels of innovation and remaining competitive
- Being better placed to respond to external pressures
- Having the knowledge to better link resources to customer
needs
- Improving quality of outputs at all levels
- Improving Corporate image by becoming more people oriented
- Increasing the pace of change within the organization
david.vallat@univ-lyon1.fr
Five Disciplines
david.vallat@univ-lyon1.fr
A shift of mind from seeing parts to seeing wholes
The Fifth Discipline
 Systems thinking – the cornerstone of the learning
organization
An famous example of system thinking:
M. Porter’s 5 forces
http://www.youtube.com/watch?v=mY
F2_FBCvXw
interview with P. Senge:
http://www.mutualresponsib
ility.org/science/what-is-
systems-thinking-peter-
senge-explains-systems-
thinking-approach-and-
principles
david.vallat@univ-lyon1.fr
These are not systems…
 Systems are complexe ≠ complicated
 This is complicated:
 Dominos http://www.youtube.com/watch?v=vDy2xWpZWVc
 Chain Reaction
http://www.youtube.com/watch?v=qybUFnY7Y8w
david.vallat@univ-lyon1.fr
Systems thinking (1)
 What Is Systems Thinking?
 « Whenever I’m trying to help people understand what this
word ‘system’ means, I usually start by asking: ‘Are you a
part of a family?’ Everybody is a part of a family. ‘Have you
ever seen in a family, people producing consequences in
the family, how people act, how people feel, that aren’t
what anybody intends?’ Yes. ‘How does that happen?’
Well… then people tell their stories and think about it. But
that then grounds people in not the jargon of ‘system’ or
‘systems thinking’ but the reality – that we live in webs of
interdependence.” (=> VUCA)
david.vallat@univ-lyon1.fr
http://www.mutualresponsibility.org/science/what-is-systems-thinking-peter-senge-
explains-systems-thinking-approach-and-principles
Systems thinking (2)
 3 Characteristics Of A Systems Thinking Approach
 ”A very deep and persistent commitment to ‘real learning.’
 I have to be prepared to be wrong. If it was pretty obvious
what we ought to be doing, then we’d be already doing it.
So I’m part of the problem, my own way of seeing things,
my own sense of where there’s leverage, is probably part
of the problem. This is the domain we’ve always called
‘mental models.’ If I’m not prepared to challenge my own
mental models, then the likelihood of finding non-obvious
areas of leverage are very low.
 The need to triangulate. You need to get different people,
from different points of view, who are seeing different
parts of the system to come together and collectively start
to see something that individually none of them see.”
david.vallat@univ-lyon1.fr
http://www.mutualresponsibility.org/science/what-is-systems-thinking-peter-senge-
explains-systems-thinking-approach-and-principles
Systems thinking (3)
 A Fundamental Principle Of Systems Thinking: Smart
Individuals Are No Longer Needed, Collective Intelligence Is
 « We all have probably spent too much time thinking about
‘smart individuals.’ That’s one of the problems with schools.
They are very individualistic, very much about ‘the smart kids
and the dumb kids.’ That’s not the kind of smartness we need.
 The smartness we need is collective. We need cities that work
differently. We need industrial sectors that work differently.
We need value change and supply change that are managed
from the beginning until the end to purely produce social,
ecological and economic well-being. That is the concept of
intelligence we need, and it will never be achieved by a
handful of smart individuals.
 It’s not about ‘the smartest guys in the room.’ It’s about what
we can do collectively. So the intelligence that matters is
collective intelligence, and that’s the concept of ‘smart’ that
I think will really tell the tale. »
david.vallat@univ-lyon1.fr
http://www.mutualresponsibility.org/science/what-is-systems-thinking-peter-senge-
explains-systems-thinking-approach-and-principles
Systems thinking (4)
 In management, rather simplistic frameworks are applied to what are complex
systems (scientific management)
 Focus on the parts rather than seeing the whole (scientific management)
 Fail to see organization as a dynamic process (=> knowledge creation)
 Learning from experience? (=AMBIGUITY)
 Delays and the decline in visibility
 Short-term improvements often involve very significant long-term costs.
 Emergence: From the mutual interaction of the parts of a system there arise
characteristics which can not be found as characteristic of any of the
individual parts.
 Systems maps: diagrams that show the key elements of systems and how they
connect
david.vallat@univ-lyon1.fr
Systems maps…
david.vallat@univ-lyon1.fr
How does it work? (1)
david.vallat@univ-lyon1.fr
Page 1 sur 4htm
Figure 2: Subtract Relationship
The alternative is that thing 1 can subtract from thing 2, as
indicated by the "-" sign in Figure 2, thus decreasing thing 2.
All this thingness may a bit difficult to connect with so let's
consider a couple specific examples.
Figure 3: Sales Increases Revenue
Figure 3 indicates that sales adds to revenue. Even if sales
decrease it will still add to revenue, just not quite as rapidly as
before. On the other hand, if sales increases it will add even more
readily to revenue.
To practice system thinking: http://www.systems-thinking.org/intst/int.htm
07/ 03/ 14 04:27o Systems Thinking
Figure 4: Product Sales and Inventory
Figure 4 indicates that product sales subtracts from finished
goods inventory. If product sales increase it will subtract even
more from finished goods inventory. On the other hand, if
product sales decrease it will still subtract from finished goods
inventory, just not quite so much.
Within systems diagrams there are often items that are held
constant within the context of what is being considered. These
07/ 03/ 14 04Introduction to Systems Thinking
Introduction to
Systems Thinking
The Way of
Systems
Figure 4: Product Sales and Inventory
Figure 4 indicates that product sales subtracts from finished
goods inventory. If product sales increase it will subtract even
more from finished goods inventory. On the other hand, if
product sales decrease it will still subtract from finished goods
inventory, just not quite so much.
Within systems diagrams there are often items that are held
constant within the context of what is being considered. These
items will have neither a "+" nor a "-" attached to them.
Figure 5: Constant Contribution
Figure 5 indicates that resources interact with productivity in
How does it work? (2)
david.vallat@univ-lyon1.fr
To practice system thinking: http://www.systems-thinking.org/intst/int.htm
Page 2 sur 4
omplete to form loops. There are only two types of loops,
einforcing and balancing.
Reinforcing Loop
A reinforcing loop is one in which the interactions are such that
ach action adds to the other. Any situation where action produces
result which promotes more of the same action is representative
f a reinforcing loop.
Figure 6: Reinforcing Loop
and adds to the interest. Note that interest rate is considere
a constant in this example. Interest then adds to the princip
This reinforcing action happens every so many months depe
on the period over which the institution computes the intere
snowball rolling down hill is your signal that the loop is a
reinforcing loop. The small graph to the right of principle
indicates that the growth of principal is exponential.
Typical examples of reinforcing loops are population growt
decline, uncontrolled nuclear reactions, snow balls rolling d
hill of course, runs on banks, wall street market crashes, etc
Balancing Loop
A balancing loop is one in which action attempts to bring tw
things to agreement. Any situation where one attempts to so
problem or achieve a goal or objective is representative of a
balancing loop.
Figure 7: Balancing Loop
How does it work? (3)
david.vallat@univ-lyon1.fr
To practice system thinking: http://www.systems-thinking.org/intst/int.htm
Figure 6
re you let yourself become overwhelmed by the complexity of this
ram you had best fasten your seat belt as we're only about half way there.
rtime has this real nasty habit of costing more than regular time so there
ome implications of increasing Overtime.
Figure 7
ncrease in Overtime brings with it an increase in Overtime Cost. As
rtime Cost increases there is an increased emphasis on cost which shows
s Cost Pressure. The Cost Pressure is interpreted by the management of
ect in such a way that it shows up as additional Schedule Pressure. This
eased Schedule Pressure then leads to even more Overtime. Here we
but one more viscous reinforcing loop in which actions influence the
all effect to be just the opposite of what is desired.
rtime and Overtime Cost have a couple more influences.
Project Systems
Figure 8
Prolonged Overtime has a tendency to lead to Burnout which means H
How does it work? (4)
david.vallat@univ-lyon1.fr
To practice system thinking: http://www.systems-thinking.org/intst/int.htm07/ 03/ 14 04:50tems
Figure 12
Schedule Pressure has a couple additional influences that should be
When using system thinking?
 The following are some of the signs that indicate a
systems thinking approach is most likely warranted.
 There are multiple perspectives on just what the situation
is, and how to deal with it
 A previously applied fix has created problems elsewhere
 After a fix is applied the problem returns in time
 The same fix is used repeatedly
 Growth slows over time
 Partners for growth become adversaries
 Limitations experienced are believed to result from
insufficient capacity
 There is more than one limit to growth
 Limited resources are shared by others
 Growth leads to decline elsewhere
david.vallat@univ-lyon1.fr
The four other disciplines
 The 5 core disciplines are :
 System thinking
 Personal mastery
 Mental models
 Building shared vision
 Team learning
david.vallat@univ-lyon1.fr
Personal mastery
 « Organizations learn only through individuals who learn.
Individual learning does not guarantee organizational
learning. But without it no organizational learning occurs »
(Senge 1990: 139).
 « People with a high level of personal mastery live in a
continual learning mode. They never ‘arrive’. Sometimes,
language, such as the term ‘personal mastery’ creates a
misleading sense of definiteness, of black and white. But
personal mastery is not something you possess. It is a process.
It is a lifelong discipline. People with a high level of personal
mastery are acutely aware of their ignorance, their
incompetence, their growth areas. And they are deeply self-
confident. Paradoxical? Only for those who do not see the
‘journey is the reward’» (Senge 1990: 142).
david.vallat@univ-lyon1.fr
Mental models
 These are « deeply ingrained assumptions,
generalizations, or even pictures and images that
influence how we understand the world and how we
take action » (Senge 1990: 8).
 « The discipline of mental models starts with turning
the mirror inward; learning to unearth our internal
pictures of the world, to bring them to the surface and
hold them rigorously to scrutiny. It also includes the
ability to carry on ‘learningful’ conversations that
balance inquiry and advocacy, where people expose
their own thinking effectively and make that thinking
open to the influence of others » (Senge 1990: 9).
david.vallat@univ-lyon1.fr
Building shared vision
 « When there is a genuine vision (as opposed to the all-to-
familiar ‘vision statement’), people excel and learn, not
because they are told to, but because they want to. But many
leaders have personal visions that never get translated into
shared visions that galvanize an organization… What has been
lacking is a discipline for translating vision into shared vision –
not a ‘cookbook’ but a set of principles and guiding practices.
The practice of shared vision involves the skills of unearthing
shared ‘pictures of the future’ that foster genuine
commitment and enrolment rather than compliance. In
mastering this discipline, leaders learn the counter-
productiveness of trying to dictate a vision, no matter how
heartfelt » (Senge 1990: 9).
david.vallat@univ-lyon1.fr
Team learning
 Such learning is viewed as « the process of aligning and
developing the capacities of a team to create the
results its members truly desire » (Senge 1990: 236).
 « The discipline of team learning starts with ‘dialogue’,
the capacity of members of a team to suspend
assumptions and enter into a genuine ‘thinking
together’. To the Greeks dia-logos meant a free-flowing
if meaning through a group, allowing the group to
discover insights not attainable individually…. [It] also
involves learning how to recognize the patterns of
interaction in teams that undermine learning » (Senge
1990: 10). (group as a commons=> E. Ostrom)
david.vallat@univ-lyon1.fr
Issues with
 Companies’ priorities are overwhelmingly financial
BUT: « Productivity and competitiveness are, by and large, a
function of knowledge generation and information processing:
firms and territories are organized in networks of production,
management and distribution; the core economic activities are
global – that is they have the capacity to work as a unit in real
time, or chosen time, on a planetary scale » - Castells, M.
(2001), « Information technology and global capitalism » in W.
Hutton and A. Giddens (eds.) On the Edge. Living with global
capitalism, London: Vintage, p. 52.
 Problem of competencies: the approach entails
significant effort on the part of the practitioner
david.vallat@univ-lyon1.fr
WHO MAKES
DECISIONS?
Making Decisions
@DavidVALLAT
175
Leading the learning
organization (1)
 A new view of leadership…
 Traditional leaders: set the direction, make key
decisions and energize the troops
 The traditional view of leadership, « is based on
assumptions of people’s powerlessness, their lack of
personal vision and inability to master the forces of
change, deficits which can be remedied only by a few
great leaders » (Senge 1990: 340).
david.vallat@univ-lyon1.fr
Leading the learning
organization (2)
 In a learning organization, leaders are designers, stewards and
teachers.
 Leader as designer: « the leader’s task is designing the learning
processes whereby people throughout the organization can deal
productively with the critical issues they face, and develop their
mastery in the learning disciplines » (Senge 1990: 345).
 Leader as steward: « the leader develops a unique relationship
to his or her own personal vision. He or she becomes a steward
of the vision » (Senge 1990: 346). (=> Nonaka)
 Leader as teacher: « much of the leverage leaders can actually
exert lies in helping people achieve more accurate, more
insightful and more empowering views of reality » (Senge 1990:
353).
david.vallat@univ-lyon1.fr
Phronetic leaders (Nonaka)
 Phronetic leaders : https://hbr.org/2011/05/the-big-idea-the-wise-leader
 “Phronesis” is a capability of finding the “right answer” for the overall good
(common good) in an individual specific context, and a phronetic leader is a
leader who has this capability. The capability of a phronetic leader has six factors:
 1) Ability to make a judgment on “goodness” (ethics)
 2) Ability to share contexts with others to create the Ba (and shared sense in a
timely manner)
 3) Ability to grasp the essence of particular situations/things (context)
 4) Ability to reconstruct the particulars into universals using
language/concepts/narratives (system thinking)
 5) Ability to use any necessary political means well to realize concepts for the
common good
 6) Ability to foster practical wisdom in others to build a resilient organization
178
The leader, a person and a
method (1)
 1. Wise Leaders Can Judge Goodness. Phronetic leaders
practice moral discernment about what’s good and act
on it in every situation.
 VISION (≠VOLATILITY), BENEVOLENCE (CULTURE of
creativity)
 2. Wise Leaders Can Grasp the Essence. Before making
judgment calls, wise leaders quickly sense what lies
behind a situation, project a vision of the future or the
consequences, and decide on the action needed to
realize that vision.
 CLARITY, SYSTEM THINKING (≠COMPLEXITY), AGILITY
(≠ROUTINE, AMBIGUITY)
179
The leader, a person and a
method (2)
 3. Wise Leaders Create Shared Contexts. Phronetic leaders
constantly create opportunities for senior executives and
employees to learn from one another. In Japan a ba (place,
space, or field) refers to the context in which relationships
are forged and interactions occur.
 KNOWLEDGE CREATION (INNOVATION) => UNDERSTANDING
(≠UNCERTAINTY)
 4. Wise Leaders Communicate the Essence. Phronetic leaders
must be able to communicate in a way that everyone can
understand. The essence of a situation is often hard to
express, so they must use stories, metaphors, and other
figurative language.
 KEY INTELLIGENCE TOPICS, SENSEMAKING, STORYTELLING,
SYSTEM THINKING => VISION (≠VOLATILITY)
180
 5. Wise Leaders Exercise Political Power. It isn’t enough to
identify the essence or communicate it; phronetic leaders
must bring people together and spur them to act, combining
and synthesizing everyone’s knowledge and efforts in the
single-minded pursuit of their goals.
 CREATIVE CULTURE, BENEVOLENCE => UNDERSTANDING
(≠UNCERTAINTY)
 6. Wise Leaders Foster Practical Wisdom in Others. Practical
wisdom should never be treated as if it were the preserve of
the company’s chief executive or top management team. It
must be distributed as much as possible through the
organization, and employees at all levels can be trained in its
use.
 CREATIVE CULTURE, BENEVOLENCE => UNDERSTANDING
(≠UNCERTAINTY)
181
The leader, a person and a
method (3)
Benevolence and Business Agility
 All about people…
 Theory X and Y (D. McGregor):
http://en.wikipedia.org/wiki/Theor
y_X_and_Theory_Y
 Freedom Inc (Getz & Carney).
http://www.amazon.com/Freedom-
Inc-Employees-Business-
Productivity/dp/0307409384
 SEMCO:
http://en.wikipedia.org/wiki/Maveric
k_(book)
 GORE:
http://en.wikipedia.org/wiki/W._L._
Gore_and_Associates
 IDEO:
http://en.wikipedia.org/wiki/IDEO
david.vallat@univ-lyon1.fr
Motivation
 Strong link between knowledge worker motivation and
benevolence in management (≠ scientific management)
183
The book in a video:
https://www.youtube.com/watch?v=u6XAPnuFjJc
The book in a TED conference:
http://www.ted.com/talks/dan_pink_on_motivatio
n?language=en
We are motivated when we can be creative…
Business Agility (vucA)
 An imperative for survival in a VUCA world.
 Business agility is the ability of a business to adapt
rapidly and cost efficiently in response to changes in the
business environment. => LO
 History: http://agilemanifesto.org
david.vallat@univ-lyon1.fr
Business Agility (definition)
 Business agility is the ability of a business to adapt
rapidly and cost efficiently in response to changes in the
business environment. Business agility can be
maintained by maintaining and adapting goods and
services to meet customer demands, adjusting to the
changes in a business environment and taking advantage
of human resources.
 Agility is a concept that incorporates the ideas of
flexibility, balance, adaptability, and coordination under
one umbrella. In a business context, agility typically
refers to the ability of an organization to rapidly adapt
to market and environmental changes in productive and
cost-effective ways.
 http://www.cise.ufl.edu/~manuel/Agile-for-Dummies
185
Conclusion
@DavidVALLAT
186
Why Competitive Intelligence?
Creating
knowledge
Understanding
the context
Making
decisions
Organizing this = Knowledge Management
SURVIVAL (Innovation)
@DavidVALLAT
187
Why Competitive Intelligence?
@DavidVALLAT
188
SURVIVAL (Innovation)
V.U.C.A.
C.I. Tools (swot, etc.)
Knowledge Creation
Why Competitive Intelligence?
@DavidVALLAT
189
Knowledge Creation
PEOPLE (collaboration)
Tacit & Explicit Knowledge
(SECI Model)
Knowledge Creation Tools (LLW,
CoP, Ba)
Why Competitive Intelligence?
@DavidVALLAT
190
Knowledge Creation to make decisions
Struggle against routines and
blindness…
… and finally adopt system thinking in order
to foster a learning organization
Why Competitive Intelligence?
@DavidVALLAT
191
A learning organization...
… relies upon a phronetic leader...
… that everyone can be
PEOPLE (collaboration = motivation)
What to do next?
 Drivers/Vision/Sensemaking for yourself
 Learning and continuous improvement (MOOC, TED,
etc.)
 Implementation of knowledge creation (Ba, LLW,
CoP)
 Train to be a phronetic leader
 Train others
 Measure results (BSC) => feebacks
192
@DavidVALLAT
Recommended Readings (1)
 Fun and useful for business:
 S. Johnson et al., The One Minute Manager (in the Google
doc files)
 S. Johnson, Where is my cheese? (in the Google doc files)
193
@DavidVALLAT
Recommended Readings (2)
 Less fun but very useful for business:
194
@DavidVALLAT
Recommended Readings (3)
 Less fun but very useful for business:
195
@DavidVALLAT
cám ơn
196

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Economic intelligence and knowledge management

  • 1. Economic Intelligence and Knowledge Management Competitiveness is based on knowledge. The way companies acquire knowledge from their environment and apply it, will determine their ability to survive into the 21st century volatile, complexe and uncertain world. david.vallat@univ-lyon1.fr @DavidVALLAT https://www.researchgate.net/profile/David_Vallat https://univ-lyon1.academia.edu/DVALLAT
  • 3. Competitive Intelligence: what for? @DavidVALLAT 3
  • 5. So, is this Competitive Intelligence? @DavidVALLAT 5
  • 6. Competitive Intelligence, a definition « Competitive intelligence is the action of defining, gathering, analyzing, and distributing intelligence about products, customers, competitors, and any aspect of the environment needed to support executives and managers making strategic decisions for an organization »http://en.wikipedia.org/ wiki/Competitive_intelligence @DavidVALLAT 6
  • 7. To sum up Competitive Intelligence It’s about understanding the context… @DavidVALLAT 7
  • 9. Why Competitive Intelligence? Creating knowledge Understanding the context Making decisions Organizing this = Knowledge Management SURVIVAL @DavidVALLAT 9
  • 10. Why Competitive Intelligence? Creating knowledge Understanding the context Making decisions Organizing this = Knowledge Management SURVIVAL @DavidVALLAT 10
  • 14. Some species evolved to perfectly match their environment… @DavidVALLAT 14
  • 15. We learn to adapt. Trial & Error (Tim HARFORD): https://www.youtube.com/watch?v=K5wCfYujRdE @DavidVALLAT 15
  • 17. For adapting ourselves, we first need to accept the idea of change. A video of the book: https://www.youtube.com/wa tch?v=16hxCB1Dvd4 @DavidVALLAT 17
  • 18. How to conduct change? https://en.wikipedia.org/wiki/John_Kotter @DavidVALLAT 18
  • 19. Why Competitive Intelligence? Creating knowledge Understanding the context Making decisions Organizing this = Knowledge Management SURVIVAL @DavidVALLAT 19
  • 21. WHAT CONTEXT? Understanding the context @DavidVALLAT 21
  • 22. We live in a hyperconnected world… Hyperconnected world:http://www3.weforum.org/docs/Global_IT_Report_ 2012.pdf Knowledge IS a competitive advantage: - http://www3.weforum.org/docs/WEF_GCR_Report_201 1-12.pdf - http://reports.weforum.org/global-competitiveness- report-2012-2013/ @DavidVALLAT 22
  • 24. The Network Society  « Our societies are increasingly structured around the bipolar opposition of the Net and the Self » Castells, M. (1996, second edition, 2000). The Rise of the Network Society, The Information Age: Economy, Society and Culture Vol. I. Cambridge, MA; Oxford, UK: Blackwell, p. 3.  « The promise of the Information Age is the unleashing of unprecedented productive capacity by the power of the mind ». (ibid. p. 390) To go further: http://globetrotter.be rkeley.edu/people/Cas tells/castells- con4.html @DavidVALLAT 24
  • 25. Digital World « Thus, in the historical record, networks were the domain of the private life, while the world of production, power, and war was occupied by large, vertical organizations, such as states, churches, armies, and corporations that could marshall vast pools of resources around the purpose defined by a central authority. Digital networking technologies enable networks to overcome their historical limits » Castells, Manuel and Cardoso, Gustavo, eds., The Network Society: From Knowledge to Policy. Washington, DC: Johns Hopkins Center for Transatlantic Relations, 2005, p. 4) @DavidVALLAT 25
  • 26. Knowledge Economy « Researchers have found that productivity growth in this period has been largely associated to three processes, all of which are necessary conditions for productivity growth to take place: generation and diffusion of new microlectronics/digital technologies of information and communication, on the basis of scientific research and technological innovation; transformation of labor, with the growth of highly educated, autonomous labor that is able to innovate and adapt to a constantly changing global and local economy; diffusion of a new form of organization around networking. » Castells, M. and Cardoso, G., eds., The Network Society: From Knowledge to Policy. Washington, DC: Johns Hopkins Center for Transatlantic Relations, 2005, p. 8) @DavidVALLAT 26
  • 29. Knowledge Worker « Knowledge work can be differentiated from other forms of work by its emphasis on "non-routine" problem solving that requires a combination of convergent, divergent, and creative thinking. But despite the amount of research and literature on knowledge work, there is no succinct definition of the term » (Wikipedia, Knowledge Worker). « Knowledge workers have high degrees of expertise, education, or experience, and the primary purpose of their jobs involves the creation, distribution or application of knowledge » (Thomas Davenport, Thinking for a Living, 2005). « To make knowledge work productive will be the great management task of this century, just as to make manual work productive was the great management task of the last century » (Peter Drucker, Age of Discontinuity, 1969). @DavidVALLAT 29
  • 30. CONTEXT IS MOVING Understanding the context @DavidVALLAT 30
  • 33. A V.U.C.A. WORLD Understanding the context @DavidVALLAT 33
  • 35. It’s a V.U.C.A. World  What is it? http://www.youtube.com/watch?v=72AzCY45fKU  An US Army concept http://www.carlisle.army.mil/usawc/dclm/slp2ndEd.pdf  Complex and systemic problems:  Example 1. http://youtu.be/zexit7Tk1GA  Example 2. http://www.youtube.com/watch?v=9hXmyD9a4zg @DavidVALLAT 35
  • 38. C.I. TOOLS TO GRASP THE CONTEXT Understanding the context @DavidVALLAT 38
  • 39. A reminder about C.I.  The basic starting point for competitive intelligence is to define the problem.  Competitive intelligence should be a value-added service to managers who are facing critical strategic decisions.  What are the Key Intelligence Topics? @DavidVALLAT 39
  • 40. How to grasp the context?  More People/Method than Tools…  SWOT Analysis => to understand your own competitive advantages in relation to the marketplace  PESTEL analysis => to examine the external macro-environment  Porter’s Five Forces Model => industry analysis  Porter’s Four Corners Analysis => to understand the position of a competitor  System thinking! & Key Intelligence Topics @DavidVALLAT 40
  • 41. SWOT  A method used to evaluate the strengths, weaknesses, opportunities, and threats involved in a project or in a business venture.  http://en.wikipedia.org/wiki/SWOT_analysis  SWOT Online: http://i-swot.com @DavidVALLAT 41
  • 42. PESTEL Analysis  Identifying "Big Picture" Opportunities and Threats  Objective: developping an objective view of the environment  PESTEL & SWOT are often linked @DavidVALLAT 42
  • 43. PESTEL Analysis Examples  Identifying "Big Picture" Opportunities and Threats  Objectives  PESTEL & SWOT 43
  • 44. Porter’s 5 forces (1) Porter’s Five Forces analysis, developed by Michael E. Porter of Harvard Business School, is a framework for assessing and evaluating the competitive strength and position of a business organization. There are five forces which determine the competitive intensity and attractiveness of a market: supplier power, buyer power, competitive rivalry, threat of substitute products/technology change, and threat of new market entrants. @DavidVALLAT 44
  • 45. Porter’s 5 forces (2)  Threat of New Entrants: an industry with low barriers of entry will have intense competition as opposed to an industry with major barriers of entry.  Suppliers tend to have strong influence within an industry when they are few/acting together.  Power of Buyers: customers often dictate pricing and they demand certain levels of quality.  Substitute Products: new or emerging substitutes for a product will change competitive forces  Rivalry: this competitive rivalry may decline when times are good and everyone can grow. @DavidVALLAT 45
  • 46. Porter’s 5 forces (3) http://www.cosxo.com/analysis/ @DavidVALLAT 46
  • 47. Porter's four corners model (1)  « Porter’s four corners model is a predictive tool designed by Michael Porter that helps in determining a competitor’s course of action. Unlike other predictive models which predominantly rely on a firm’s current strategy and capabilities to determine future strategy, Porter’s model additionally calls for an understanding of what motivates the competitor. This added dimension of understanding a competitor's internal culture, value system, mindset, and assumptions helps in determining a much more accurate and realistic reading of a competitor’s possible reactions in a given situation » http://en.wikipedia.org/wiki/Porter's_four_corners_mo del @DavidVALLAT 47
  • 48. Porter's four corners model (2) http://www.cosxo.com/analysis/ @DavidVALLAT 48
  • 49. Key Intelligence Topics  What are the Key Intelligence Topics (KIT)?  What impact will bitechnology / internet have on our high volume product line?  How is our competitor able to retain major government contracts year after year  When these contracts come open for bid?  What is the timeline for when our competitor will launch their new US service?  Should we expand our Saigon facility or build a new facility in Hanoi?  Who are the key customers of our competitor?  How does this new regulation impact our business?  How well does this supplier perform with other companies? @DavidVALLAT 49
  • 50. Wargaming: a fun way to implement these tools… @DavidVALLAT 50
  • 51. Wargaming: what is it?  Human-based simulations. These are intelligence-driven, analytically and behaviorally modeled role-playing exercises http://www.bengilad.com  Simple - over-sophisticated, long and large scale games cost a lot more but do not produce better results.  Transparent - if you don't understand the exotic algorithm, how likely are you to trust the strategy?  Empowering - computer games don't understand internal politics, but you have to.  Fun - teams that learn how to role-play competitors with real market intelligence and character-building techniques maintain enthusiastic external focus for years.  Inexpensive - there is no good reason for games to cost hundred of thousands or even millions of dollars. If you know a good reason, write us.  Accessible - to truly improve the bottom line, managers at all levels of the organization should be able to use this amazing tool, not just few senior execs at the top.  Realistic - intelligence-based, human games are magnitudes more realistic than even the most sophisticated mathematical modeling. @DavidVALLAT 51
  • 52. Wargaming: an example  http://www.mckinsey.com/insights/strategy/playing_war_ga mes_to_win  « As the global downturn kicked in, a high-tech company’s senior executives decided to run a war game to prepare themselves for the uncertainties of the post-crisis landscape. After two days of simulations—when teams representing competitors and stakeholders role-played against a “company” team—the executives understood that a strong competitor on the sidelines was likely to enter the market aggressively. The executives also realized that the low end of the product range would face more price pressure than they had been anticipating. Moreover, while there would probably be industry mergers and acquisitions, as the company had expected, the deals were unlikely to kick off a wave of M&A or to have a material impact on the company’s share of any market. » @DavidVALLAT 52
  • 53. Wargaming: further readings  http://www.mckinsey.com/insights/innovation/battle- test_your_innovation_strategy  http://www.mckinsey.com/insights/strategy/playing_w ar_games_to_win  Ben Gilad’s book: http://www.amazon.com/Business- War-Games-Outmaneuver-Competition  http://www.bengilad.com @DavidVALLAT 53
  • 54. What you don’t need in a VUCA World (1)  A « God Complex » http://www.ted.com/talks/tim_harford.html  Scientific managementhttp://en.wikipedia.org/wiki/Frederick_Wi nslow_Taylor 54
  • 55. What you don’t need in a VUCA World (2) AND WHAT WE NEED?  We need trial and error (and humility) => simulations  We need to share, discuss, collaborate  We need to manage Knowledge http://www.ibicity.fr/blog/public/Leadership_Agility_-- _HRPS_Reprint_Permission__revised_.pdf 55
  • 56. Why Competitive Intelligence? Creating knowledge Understanding the context Making decisions Organizing this = Knowledge Management SURVIVAL @DavidVALLAT 56
  • 58. Why Knowledge Creation?  Knowledge is the basis for innovation  Innovation is the driving force behind long term competitive advantage  Competitive advantage ensures corporate longevity @DavidVALLAT 58
  • 60. Data/Information/Knowledge (1)  DATA is a set of objective facts about events  Data as an abstract concept can be viewed as the lowest level of abstraction, from which information and then knowledge are derived.  INFORMATION is a message  As with any message, it has a sender and a receiver. Information is meant to change the way the receiver perceives something, to have an impact on his judgment and behavior. It is data that makes a difference. 60
  • 61. Data/Information/Knowledge (2)  Information becomes knowledge, through:  Comparison  Consequences  Connections  Conversation  Knowledge is meant for action  A strong link between knowledge and experience 61
  • 66. But what Knowledge really is…? (1) • Knowledge is what you see/feel? • Knowledge is what you believe? • Knowledge is what is true? @DavidVALLAT 66
  • 67. But what Knowledge really is…? (2) • « Justified true belief » (notion derived from Plato’s dialogue Theaetetus – IVth century BC ). • « belief » = doxa = acceptance • « true »: a false belief is not considered to be knowledge (e.g. flat earth theory) • « justified »: justification for believing it is true The relationship between belief and knowledge is that a belief is knowledge if the belief is true, and if the believer has a justification (reasonable and necessarily plausible assertions/evidence) for believing it is true. @DavidVALLAT 67
  • 68. But what Knowledge really is…? (3) • The primary problem in epistemology (study of knowledge) is to understand exactly what is needed in order for us to have knowledge. • We need knowledge to take action… @DavidVALLAT 68
  • 69. But what Knowledge really is…? (4) • Karl POPPER (1902-1994) took falsifiability as his criterion of demarcation between what is, and is not, genuinely scientific (The Logic of Scientific Discovery, 1934). => « justified » • So, science/knowledge is open to discussion. • « justified »: with proofs that can be discussed (falsifiability) • « true »: reproducibility @DavidVALLAT 69
  • 70. How to gather knowledge? • a method of inquiry must be based on gathering observable and measurable evidence subject to specific principles of reasoning and experimentation. The scientific method consists of the collection of data through observation and experimentation, and the formulation and testing of hypotheses (Wikipedia, Knowledge) @DavidVALLAT 70
  • 71. Knowledge Creation => By trial and error and collaboration MOON CRASH… @DavidVALLAT 71
  • 72. Moon Crash: Lesson Learned Workshop (1)  LLW: a simple method to discuss and transfer experience  What did we learn?  In order to create real knowledge (Justified true belief), we have to answer the question with a scientific method:  gathering observable and measurable evidences  formulation and testing of hypotheses (+ reproducibility)  All this is open to discussion (falsifiability) 72
  • 73. Moon Crash: Lesson Learned Workshop (2)  (Normally) a group creativity is more than the added creativity of each member.  Discussion and sometimes conflicts foster creativity  What is the starting point of the decision-making process? (KIT)  What was your decision-making process (consensus, vote)? 73
  • 74. The power of discussion (in KM)  Don’t try to impose your opinion. Expose your point of view as logically as possible (with evidences when possible). Listen carefully to the responses of other participants (they may be right!) ≠ God complex  If the discussion is in a dead end don’t try to adopt majority’s point of view. Try to find the most acceptable solution for all participants. = motivation  Beware of superficial agreements reached too quickly and too easily. Take your time to reach a consensus.  Differences of opinion are normal and inevitable. They often are a guarantee of success for the final decision. 74
  • 75. TACIT & EXPLICIT KNOWLEDGE Creating Knowledge @DavidVALLAT 75
  • 76. Types of Knowledge: Tacit vs Explicit (1) Michael POLANYI, The Tacit Dimension, University of Chicago Press, 1966. “we can know more than we can tell.” Tacit knowledge can be distinguished from explicit knowledge in three major areas  Transferring knowledge  Methods for acquisition  Potential of aggregation and modes of appropriation @DavidVALLAT 76
  • 77. Types of Knowledge: Tacit vs Explicit (2)  Ikujiro NONAKA (1991): The Knowledge Creating Company, Harvard Business Review http://hbr.org/2007/07/the- knowledge-creating-company/es http://en.wikipedia.org/wiki/Tacit_kn owledge His research suggested that a successful KM effort needs to convert internalized tacit knowledge into explicit knowledge to share it. @DavidVALLAT 77
  • 78. The SECI Model @DavidVALLAT 78 meetings brainstorming quality circles CoP LLW training programs training manual consolidated annual financial performance report
  • 79. Ikujiro NONAKA (1991), ’’The Knowledge Creating Company’’, Harvard Business Review  First read the article (explicit knowledge) from I. Nonaka: http://hbr.org/2007/07/the-knowledge-creating-company/es  2) Try to sum up / sort out the main ideas (explicit => tacit = internalization)  3) Try to use the SECI model to analyse your organization (tacit knowledge creation)  A) For each stage of the SECI model try to find precise examples in your organization => write them (to learn you have to act)  B) Then try to organize your ideas, try to prioritize questions to build proposals to help knowledge creation in your organization (tacit => explicit = externalization) => write individually your proposals  4) When you have finished share your ideas in a team of 3 to 5 (tacit=>tacit = socialization) => each in turn explains what he has done (Community of Practice) @DavidVALLAT 79
  • 80. ’’The Knowledge Creating Company’’ (1)  P.2« In an economy where the only certainty is uncertainty,the one sure source of lasting competitive advantage is knowledge. »  P.3 Westernway≠Eastern way of thinking about knowledge (epistmology)  P.3 Successful japenese companies => «These companies have become famous for their ability to respond quickly to customers, create new markets, rapidly develop new products, and dominate emergent technologies. »  P.3 The success comes from «their unique approach to managing the creation of new knowledge. »  P.3 How? => by «managing that serendipity to the benefit of the company, its employees, and its customers. » (creativity)  P3 « A company is not a machine but a living organism ». (learning organization) @DavidVALLAT 80
  • 81.  P.3 « The centerpiece of the Japanese approach is the recognition that creating new knowledge is not simply a matter of “processing” objective information. Rather, it depends on tapping the tacit and often highly subjective insights, intuitions, and hunches of individual employees and making those insights available for testing and use by the company as a whole. »  P.3 It’s possible with a shared vision => «The key to this process is personal commitment, the employees’ sense of identity with the enterprise and its mission. » ; « a shared understanding of what the company stand for, where it is going, what kind of world it wants to live in, and, most important, how to make that world a reality.» (pragmatism) @DavidVALLAT ’’The Knowledge Creating Company’’ (2) 81
  • 82.  P.4 « New knowledge always begins with the individual. A brilliant researcher has an insight that leads to a new patent. A middle manager’s intuitive sense of market trends becomes the catalyst for an important new product concept. A shop-floor worker draws on years of experience to come up with a new process innovation. In each case, an individual’s personal knowledge is transformed into organizational knowledge valuable to the company as a whole. »  P.4 and « Making personal knowledge available to others is the central activity of the knowledge- creating company. »  P.4/5 How to use the SECI Model  P.6 Why it’s easy for japanese people to convert tacit knowledge into explicit knowledge? Because they are able to use «figurative language and symbolism that managers can draw from to articulate their intuitions and insights.» @DavidVALLAT ’’The Knowledge Creating Company’’ (3) 82
  • 83.  P.6 Use of metaphor: « Through metaphors, people put together what they know in new ways and begin to express what they know but cannot yet say. »  P.7 « Often, metaphoric images have multiple meanings and appear logically contradictory or even irrational. But far from being a weakness, this is in fact an enormous strength. For it is the very conflict that metaphors embody that jump-starts the creative process. »  P.7 « But while metaphor triggers the knowledge-creation process, it alone is not enough to complete it. The next step is analogy. »  P.7 Last step: TRIAL (and error) «Finally, the last step in the knowledge-creation process is to create an actual model. » @DavidVALLAT ’’The Knowledge Creating Company’’ (4) 83
  • 84.  a Metaphor is a figure of speech which makes an implicit, implied or hidden comparison between two things that are unrelated but share some common characteristics. In other words, a resemblance of two contradictory or different objects is made based on a single or some common characteristics. Two ideas in one expression ; a connection between two things distantly related: THEORY OF AUTOMOBILE EVOLUTION  Metaphor triggers the knowledge creation process because it spurs creativity.  Analogy: it’s more strutured than metaphor. A comparison between two things, typically on the basis of their structure and for the purpose of explanation or clarification. (computer and brain ; aluminium beer can / aluminium copier drum). @DavidVALLAT Metaphor & Analogy 84
  • 85.  P.7 Converting tacit knowldege into explicit: « first, by linking contradictory things and ideas through metaphor; then, by resolving these contradictions through analogy; and, finally, by crystallizing the created concepts and embodying them in a model, which makes the knowledge available to the rest of the company. »  P.7 Redundancy (to foster agility): « The fundamental principle of organizational design at the Japanese companies I have studied is redundancy—the conscious overlapping of company information, business activities, and managerial responsibilities. »  P.8 With Redundancy you have dialogue. « This helps create a “common cognitive ground” among employees and thus facilitates the transfer of tacit knowledge. » @DavidVALLAT ’’The Knowledge Creating Company’’ (5) 85
  • 86.  P.8 « The organizational logic of redundancy helps explain why Japanese companies manage product development as an overlapping process where different functional divisions work together in a shared division of labor. »  P.8 This is a collaborative organization (which needs transparency): « Free access to company information also helps build redundancy. When information differentials exist, members of an organization can no longer interact on equal terms, which hinders the search for different interpretations of new knowledge. » @DavidVALLAT ’’The Knowledge Creating Company’’ (6) 86
  • 87.  P.9 In a VUCA world « Senior managers give voice to a company’s future by articulating metaphors, symbols, and concepts that orient the knowledge-creating activities of employees. They do this by asking the questions, What are we trying to learn? What do we need to know? Where should we be going? Who are we? If the job of frontline employees is to know “what is,” then the job of senior executives is to know “what ought to be.” »  P.10 Managers give a vision:«Umbrella concepts and qualitative criteria for justification are crucial to giving a company’s knowledge-creating activities a sense of direction. »  P.11 To end as we started:«middlemanagers synthesized the tacit knowledge of both frontline employees and senior executives, made it explicit, and incorporated it into new technologies and products. In this respect, they are the true “knowledge engineers” of the knowledge-creating company. » (middle-up- down management: https://ai.wu.ac.at/~kaiser/birgit/Nonaka- Papers/Toward-middle-up-down-mgmt-1988.pdf ) @DavidVALLAT ’’The Knowledge Creating Company’’ (7) 87
  • 88. To Sum up Nonaka’s approach  « In an economy where the only certainty is uncertainty,the one sure source of lasting competitive advantage is knowledge. »  > «These companies have become famous for their ability to respond quickly to customers, create new markets, rapidly develop new products, and dominate emergent technologies. »  HOW:  « …by giving a company’s knowledge-creating activities a sense of direction »  « Making personal knowledge available to others is the central activity of the knowledge- creating company. » (SECI process)  «middlemanagers synthesized the tacit knowledge of both frontline employees and senior executives, made it explicit, and incorporated it into new technologies and products. In this respect, they are the true “knowledge engineers” of the knowledge-creating company. » 88 @DavidVALLAT
  • 90. Experimentation of the SECI Model 90 3) Try to use the SECI model to analyse your organization (tacit knowledge creation) A) For each stage of the SECI model try to find precise examples in your organization => write them (to learn you have to act) B) Then try to organize your ideas, try to prioritize questions to build proposals to help knowledge creation in your organization (tacit => explicit = externalization) => write individually your proposals 4) When you have finished share your ideas in a team of 3 to 5 (tacit=>tacit = socialization) => each in turn explains what he has done (Community of Practice) 5) Share with me…
  • 92. Classical Knowledge Creation Tools (= creativity)  Outsourcing Knowledge Creation…  Other methods to spur creativity:  Brainstorming  Mind Mapping http://www.mindomo.com  6-3-5 Method (Brainwriting)  6 participants. Each participant thinks up 3 ideas every 5 minutes. The ideas are written down on a worksheet and passed on to the next participant. The participant reads the ideas and uses them as inspiration for more ideas… After 6 rounds in 30 minutes the group has thought up a total of 108 ideas. 92 @DavidVALLAT
  • 95. Creative Environment (1) 95  To be creative, it helps to live in a creative environment.  What is a creative environment? @DavidVALLAT
  • 96. 96
  • 97. 97
  • 98. Creative Environment (2) 98 A pleaseant physical environment (calm, furnishings, light) is not enough…  No distraction (telephone, mail, other interruptions)  Sufficient time  Technical equipment (flipchart, projector, paper, sticky notes, games, etc.)  Creative skills  Constructive communication culture  Top management supports ceativity @DavidVALLAT LEADERSHIP
  • 99. Less classical Tools In a creative environment you can experience less classical tools:  Metaphor/Analogy/Symbol (Nonaka)  Storytelling (in business): https://en.wikipedia.org/wiki/Storytelling  Wargaming  Gamestorming: http://www.youtube.com/watch?v=3mrtu4MmthE http://en.wikipedia.org/wiki/Gamestorming 99 @DavidVALLAT
  • 100. 100 Transfer of Experience (1)  The transfer of experience is a special form of knowledge transfer.  This type of transfer should serve to broaden the spectrum of decision-making possibilities open to employees and avoid unnecessary repeated learning through trial and error.  The transfer of experience can be through INTERNALIZATION (tacit=>explicit) or SOCIALIZATION (tacit=>tacit)  INTERNALIZATION = LLW and CoP  SOCIALIZATION = meetings (and ‘BA’) @DavidVALLAT
  • 101. 101 Transfer of Experience (2) Transfer of Experience through : Personalization Codification Organisational level Human Network (expert database, social network) Repository and distribution source for documented learning experiences (Intranet) Team level Support: Communities of Practice Support: Lessons Learned Workshops Individual level Transfer of experience through processes of communication and mutual observation Transfer of experience through information and documentation @DavidVALLAT
  • 102. 102 Transfer of Experience (3) Advantages and disadvantages of a Codification strategy (Externalization) + + knowledge is always available + particularly suitable for frequent re-use + can be passed on quickly and easily; high degree of distribution - - codification is complex and time-consuming - documented knowledge can quickly become obsolete - complicated wording or terminology makes knowledge difficult to absorb - context cannot be fully described/provided - some knowledge cannot be made explicit - different "mental models" prevent direct use of documented knowledge @DavidVALLAT
  • 103. 103 Transfer of Experience (4) Advantages and disadvantages of a Personalization strategy (Socialization) + + knowledge is always up-to-date + complexity of knowledge transfer can be adapted to the situation + creative innovation possible during transfer - - complicated search for the right person - the right person is not available - personal aversion @DavidVALLAT
  • 104. 104 Tools for Transfering Experience (Internalization)  Community of Practice (Personalization / Team level) ≠ project  Lessons Learned Workshop (Codification / Team level) => project @DavidVALLAT
  • 105. 105 Community of Practice (1) « A community of practice (CoP) is a group of people who share a craft and/or a profession. The group can evolve naturally because of the members' common interest in a particular domain or area, or it can be created specifically with the goal of gaining knowledge related to their field. It is through the process of sharing information and experiences with the group that the members learn from each other, and have an opportunity to develop themselves personally and professionally » (Wikipedia) @DavidVALLAT
  • 106. 106 Community of Practice (2)  Real / Virtual / Mobile CoP  Origin: LAVE, Jean; WENGER, Etienne (1991). Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press  Example: Xerox customer service representatives (Eureka database)http://www.kmworld.com/Articles/Edito rial/Features/Best-Practices-Eureka!-Xerox- discovers-way-to-grow-community-knowledge.-.- And-customer-satisfaction-9140.aspx  CoP ≠ Project team @DavidVALLAT
  • 107. 107 Community of Practice (3)  CoP and KM => how to transfer tacit knowledge?  CoPs bridge the gap between knowing what and knowing how (sensemaking): while organizations tend to provide manuals to meet the training needs of their employees, CoPs help foster the process of storytelling among colleagues which, in turn, helps them strengthen their skills on the job.  Motivation to share knowledge is critical to success in communities of practice. Studies show that members are motivated to become active participants in a CoP when they view knowledge as meant for the public good, a moral obligation and/or as a community interest. @DavidVALLAT
  • 108. 108 Community of Practice (4) Cultivating CoP by:  Design the community to evolve naturally  Create opportunities for open dialog within and outside  Allow different levels of participation  Develop both public and private exchanges  CoPs should create opportunities for participants to explicitly discuss the value and productivity of their participation in the group  Combine familiarity and novelty  Find a regular rhythm for the community @DavidVALLAT
  • 109. Lessons Learned Workshop (1) • Why closing a project with a LLW? • A simple method to discuss and transfer experience: • What was done well in the project? • What could have been improved? • What would be the ideal situation for points that could have been improved? • What would I personally do differently in the next project? • What should the organisation do differently in the next project? @DavidVALLAT
  • 110. Lessons Learned Workshop (2) Defining the relevant issues Lessons Learned Workshop Processing and applying the results @DavidVALLAT
  • 111. • How to manage a Lessons Learned Workshop? • Background (detailed presentations of the project - from start to finish) • Cluster building (brainstorming) • Lessons learned (these are summarised to produce a list of recommendations for the organisation) • After the workshop (initiate organisational learning to implement changes). david.vallat@univ-lyon1.fr Lessons Learned Workshop (3) @DavidVALLAT
  • 112. Socialization: the ‘BA’ concept  You have meetings…  Knowledge is relational (SECI) ≠ Western epistemology has traditionally viewed knowledge as explicit.  Knowledge needs a context to be created.  The context is a time and place (physical, virtual, mental) = ‘BA’ (Nonaka)  TIME: when it’s the moment…  PLACE: - Physical = an office, - Virtual = a social network - Mental = shared culture and objectives  It’s where/when people can interact to create situated knowlegde (like a CoP with an objective). 112 @DavidVALLAT
  • 113. Why Competitive Intelligence? Creating knowledge Understanding the context Making decisions Organizing this = Knowledge Management SURVIVAL @DavidVALLAT 113
  • 115. HOW TO MAKE GOOD DECISIONS? Making Decisions @DavidVALLAT 115
  • 116. Decision-making and organization  The decision-making process is an organizational process. 116 @DavidVALLAT
  • 117. A little game…  Group of 4 or 5 people  Try to solve the puzzle as fast as possible  How do you learned to solve the problem? 117
  • 118. HOW TO MAKE GOOD DECISIONS? 1. ROUTINES Making Decisions @DavidVALLAT 118
  • 119. Organizational Routines  What is a routine?  a sequence of actions regularly followed; a fixed program.  organisational routines are described as the relatively mindless repetition of actions that have been well-established via evolution or voluntary design 119 @DavidVALLAT  Why a routine?  The right way to do things… An organizational memory.  A routine may be a trap…
  • 120. Organizational Traps  Competency Trap: The Innovator’s Dilemma (C. Christensen) http://www.forbes.com/sites/stevedenning/2012/ 04/05/clayton-christensen-and-the-innovators- smackdown/ http://www.youtube.com/watch?v=35z03U3wugs  Surpersticious Learning http://blogs.hbr.org/2011/07/superstitious-learning/  A little God in his quiet realm= GOD COMPLEXhttp://www.youtube.com/watch?v=K5wCfYujR dE 120 @DavidVALLAT
  • 121. The Innovator’s Dilemma (C. Christensen) - 1  The Innovator’s Dilemma (C. Christensen, 1997) http://www.forbes.com/sites/stevedenning/2012/04/ 05/clayton-christensen-and-the-innovators- smackdown/  “That book documents how market-leading companies have missed game-changing transformations in industry after industry—computers (mainframes to PCs), telephony (landline to mobile), photography (film to digital), stock markets (floor to online)—not because of ‘bad’ management, but because they followed the dictates of ‘good’ management. They listened closely to their customers. They carefully studied market trends. They allocated capital to the innovations that promised the largest returns. And in the process, they missed disruptive innovations that opened up new customers and markets for lower-margin, blockbuster products.” david.vallat@univ-lyon1.fr @DavidVALLAT
  • 122. The Innovator’s Dilemma (C. Christensen) - 2  Examples:  Example: “When Toyota was making rusty little subcompacts, it made no sense for General Motors to go after the subcompact market, when the profits they could get on bigger SUVs and pickup trucks made all the sense in the world. Toyota just made their products better and better, until eventually customers who used to bigger General Motors cars could now buy cheaper ones. Now Toyota is making the best in the world, while at the bottom, the Koreans, Kia and Hyundai, have stolen the low end of the market. It’s not because Toyota is asleep at the switch. They have to decide, ‘Should we go down and compete against Kia? Or should we go up and compete against Mercedes?’” david.vallat@univ-lyon1.fr @DavidVALLAT
  • 123. Surpersticious Learning  Surpersticious Learning http://blogs.hbr.org/2011/07/superstitious-learning/  « Superstitious learning takes place when the connection between the cause of an action and the outcomes experienced aren’t clear, or are misattributed. »  « For instance, a major retailer prided itself on the steady, profitable growth of its music CD business over a long period of time. […] The real story was not one of success. Rather, it was one of grabbing share from a market that was in deep decline. » @DavidVALLAT
  • 124. Avoiding Organizational Traps (routines)  A lot of traps…  How to avoid them?  Meet Chris ARGYRIS http://en.wikipedia.org/wiki/Chris_Argyris  Organizations need to learn to adapt  Argyris, C., & Schön, D. (1974) Theory in practice: Increasing professional effectiveness. San Francisco: Jossey Bass.  Espoused theory and Theory-in-use @DavidVALLAT
  • 125. Espoused theory and Theory-in-use  Espoused theory: values people believe their behaviour is based on - what individuals believe is how they would behave in a particular circumstance.  Theory-in-use: values implied by their behaviour, or the maps they use to take action - how individuals actually behave in that circumstance. david.vallat@univ-lyon1.fr When someone is asked how he would behave under certain circumstances, the answer he usually gives is his espoused theory of action for that situation. This is the theory of action to which he gives allegiance and which, upon request, he communicates to others. However, the theory that actually governs his actions is his theory-in-use; furthermore, the individual may or may not be aware of the incompatibility of the two theories (Argyris and Schön, Theory in Practice, Jossey-Bass, 1974, p 11.)
  • 126. A Loop Story…(i)  Organizational learning is about detecting and correcting error Source: http://www.afs.org/blog/icl/?p=2653 david.vallat@univ-lyon1.fr
  • 127. A Loop Story…(ii)  C. Argyris, “Double-Loop Learning in Organisations“, Harvard Business Review Vol 55, No 5, 1977, pp 115–125.  C. Argyris & D. Schön, Organizational Learning: A Theory of Action Perspective, Addison-Wesley, 1978.  Single-Loop learning => Model I (Theory-in- use)  Double-Loop learning => Model II (Espoused theory) david.vallat@univ-lyon1.fr
  • 128. Model I (i)  The governing Values of Model I are:  Achieve the purpose as the actor defines it  Win, do not lose  Suppress negative feelings  Emphasise rationality  Primary Strategies are:  Control environment and task unilaterally  Protect self and others unilaterally david.vallat@univ-lyon1.fr
  • 129. Model I (ii)  Usually operationalised by:  Unillustrated attributions and evaluations eg. "You seem unmotivated"  Advocating courses of action which discourage inquiry eg. "Lets not talk about the past, that's over."  Treating ones' own views as obviously correct (God complex)  Making covert attributions and evaluations ("he has no strategic vision »)  Face-saving moves such as leaving potentially embarrassing facts unstated  Consequences include:  Defensive relationships  Low freedom of choice  Reduced production of valid information  Little public testing of ideas david.vallat@univ-lyon1.fr
  • 131. Model I (iv)  « Skilled Incompetence »  Organizational Defensive Routines (ODR)  Organizational Defensive Pattern (ODP) Defensive Reasoning ≠ Productive Reasoning david.vallat@univ-lyon1.fr
  • 132. Model II (i)  The governing values of Model II include:  Valid information  Free and informed choice  Internal commitment  Strategies include:  Sharing control  Participation in design and implementation of action david.vallat@univ-lyon1.fr
  • 133. Model II (ii)  Operationalised by:  Attribution and evaluation illustrated with relatively directly observable data  Conflicting views allowed  Encouraging public testing of evaluations  Consequences should include:  Minimally defensive relationships  High freedom of choice  Increased likelihood of double-loop learning david.vallat@univ-lyon1.fr
  • 135. Model I Observed  C. Argyris, “Teaching Smart People How to Learn“, Harvard Business Review, 1991.  Learning behaviours in US consultancies  Inability to learn from failure (because of the God complex) david.vallat@univ-lyon1.fr
  • 136. Does Organizational Development is Possible?  From Organizational I (O-I) learning systems to Organizational II (O-II) learning system  Intervention strategy in 6 phases  Phase 1 Mapping the problem as clients see it  Phase 2 Internalization of the map by clients  Phase 3 Test the model  Phase 4 Invent solutions  Phase 5 Produce the intervention  Phase 6 Study the impact david.vallat@univ-lyon1.fr
  • 138. Summary (2)  Organizational learning is about detecting and correcting error Source: http://www.afs.org/blog/icl/?p=2653 david.vallat@univ-lyon1.fr
  • 139. An exercise  Try to identify and describe a case of single-loop learning in your company. Why people are acting like this?  Try to identify and describe a case of double-loop learning in your company. What are the levers for learning in this environment?  Share with others in your group. 139
  • 140. An exercise: Left hand column  Think of a work situation you are concerned about  Divide a piece of paper into two columns  Ladder of inference david.vallat@univ-lyon1.fr
  • 142. HOW TO MAKE GOOD DECISIONS? 2. WE ARE BLIND Making Decisions @DavidVALLAT 142
  • 143. A triple blindness  1) Because we don’t understand probabilities  Black Swan  Two brains  2) We don’t see weak signals  3) We are not aware of consequences (system thinking) 143
  • 144. Black Swan Theory 144  Rare and improbable events do occur much more than we dare to think: these events are black swans.
  • 145. Why Black Swans?  Because of the Ludic Fallacy (too much faith in statistics)  statistics is applicable only in some domains, for instance Casinos.  It is impossible to be in possession of the entirety of available information.  Small unknown variations in the data could have a huge impact.  Because of the Narrative Fallacy  the narrative fallacy addresses our limited ability to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship upon them. We like to find stories… 145
  • 146. We don’t understand statistics… 146 Two brains: ONE FAST (system 1) to take every day decisions but also quick decisions => fast, instinctive and emotional ONE SLOW (system 2) to solve difficult problems => Slow, effortful, infrequent, logical, calculating, conscious.  Selective attention test https://www.youtube.com/watch?v=vJG698U2Mvo ‘halo effect’ https://en.wiki pedia.org/wiki /Thinking,_Fast _and_Slow
  • 147. Don’t forget weak signals david.vallat@univ-lyon1.fr
  • 148. Weak signals - Definition  Weak Signals are past or current developments/issues with ambiguous interpretations of their origin, meaning and/or implications. They are unclear observables warning us about the probability of future events. david.vallat@univ-lyon1.fr
  • 149. Some weak signals…  New unmet consumer or customer needs  The entry of new competitors and new suppliers  The advent of new breakthrough technologies  Changes in your organization’s core performance metrics  Unfulfilled business and other potential opportunities  Broad disruptive events  Premonitions, anxieties, and/or intuitions http://www.forbes.com/sites/martinzwilling/2013/12/14/how-good-is-your-business-at-reading-weak-s david.vallat@univ-lyon1.fr
  • 150. Bad ideas for sorting out weak signals  Remember the God complex?  Relying (only) on Tools (SWOT Analysis, etc.)  Denial (=> Kodak) david.vallat@univ-lyon1.fr
  • 151. What to do then?  People + Tools  Understand the context (VUCA)  SWOT Analysis => to understand your own competitive advantages in relation to the marketplace.  Porter’s Five Forces Model => industry analysis  Porter’s Four Corners Analysis => to understand the position of a competitor.  Key Intelligence Topics  Wargame  KNOWLEDGE CREATION  System thinking! david.vallat@univ-lyon1.fr
  • 153. From O.L. to the L.O.  Peter SENGE and the concept of the ‘learning organization’ in The Fifth Discipline (1990)  An ‘idealistic pragmatist’:  He wants to transform the workplace, bringing human values in it.  He wants to decentralize the role of leadership in organizations (to enhance the capacity of all people to work productively toward common goals)  Society for Organizational Learning (SoL)http://www.solonline.org  System thinking: http://www.youtube.com/watch?v=iLFCrv7- XlIhttps://www.youtube.com/watch?v=rDxOyJxgJeA david.vallat@univ-lyon1.fr
  • 154. Toward the LO (1)  What is a LO?  « …organizations where people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free, and where people are continually learning to see the whole together. » (P. Senge, The Fifth Discipline: The art and practice of the learning organization, London: Random House. 424 + viii pages, 1990, p.3).  Learning organizations are possible because we are all learners:http://www.ted.com/talks/sugata_mitra_shows_how_kids _teach_themselves.html  J. Medina, Brain Rules: http://brainrules.net
  • 155. Toward the LO (2)  Benefits of a LO: - Maintaining levels of innovation and remaining competitive - Being better placed to respond to external pressures - Having the knowledge to better link resources to customer needs - Improving quality of outputs at all levels - Improving Corporate image by becoming more people oriented - Increasing the pace of change within the organization david.vallat@univ-lyon1.fr
  • 156. Five Disciplines david.vallat@univ-lyon1.fr A shift of mind from seeing parts to seeing wholes
  • 157. The Fifth Discipline  Systems thinking – the cornerstone of the learning organization An famous example of system thinking: M. Porter’s 5 forces http://www.youtube.com/watch?v=mY F2_FBCvXw interview with P. Senge: http://www.mutualresponsib ility.org/science/what-is- systems-thinking-peter- senge-explains-systems- thinking-approach-and- principles david.vallat@univ-lyon1.fr
  • 158. These are not systems…  Systems are complexe ≠ complicated  This is complicated:  Dominos http://www.youtube.com/watch?v=vDy2xWpZWVc  Chain Reaction http://www.youtube.com/watch?v=qybUFnY7Y8w david.vallat@univ-lyon1.fr
  • 159. Systems thinking (1)  What Is Systems Thinking?  « Whenever I’m trying to help people understand what this word ‘system’ means, I usually start by asking: ‘Are you a part of a family?’ Everybody is a part of a family. ‘Have you ever seen in a family, people producing consequences in the family, how people act, how people feel, that aren’t what anybody intends?’ Yes. ‘How does that happen?’ Well… then people tell their stories and think about it. But that then grounds people in not the jargon of ‘system’ or ‘systems thinking’ but the reality – that we live in webs of interdependence.” (=> VUCA) david.vallat@univ-lyon1.fr http://www.mutualresponsibility.org/science/what-is-systems-thinking-peter-senge- explains-systems-thinking-approach-and-principles
  • 160. Systems thinking (2)  3 Characteristics Of A Systems Thinking Approach  ”A very deep and persistent commitment to ‘real learning.’  I have to be prepared to be wrong. If it was pretty obvious what we ought to be doing, then we’d be already doing it. So I’m part of the problem, my own way of seeing things, my own sense of where there’s leverage, is probably part of the problem. This is the domain we’ve always called ‘mental models.’ If I’m not prepared to challenge my own mental models, then the likelihood of finding non-obvious areas of leverage are very low.  The need to triangulate. You need to get different people, from different points of view, who are seeing different parts of the system to come together and collectively start to see something that individually none of them see.” david.vallat@univ-lyon1.fr http://www.mutualresponsibility.org/science/what-is-systems-thinking-peter-senge- explains-systems-thinking-approach-and-principles
  • 161. Systems thinking (3)  A Fundamental Principle Of Systems Thinking: Smart Individuals Are No Longer Needed, Collective Intelligence Is  « We all have probably spent too much time thinking about ‘smart individuals.’ That’s one of the problems with schools. They are very individualistic, very much about ‘the smart kids and the dumb kids.’ That’s not the kind of smartness we need.  The smartness we need is collective. We need cities that work differently. We need industrial sectors that work differently. We need value change and supply change that are managed from the beginning until the end to purely produce social, ecological and economic well-being. That is the concept of intelligence we need, and it will never be achieved by a handful of smart individuals.  It’s not about ‘the smartest guys in the room.’ It’s about what we can do collectively. So the intelligence that matters is collective intelligence, and that’s the concept of ‘smart’ that I think will really tell the tale. » david.vallat@univ-lyon1.fr http://www.mutualresponsibility.org/science/what-is-systems-thinking-peter-senge- explains-systems-thinking-approach-and-principles
  • 162. Systems thinking (4)  In management, rather simplistic frameworks are applied to what are complex systems (scientific management)  Focus on the parts rather than seeing the whole (scientific management)  Fail to see organization as a dynamic process (=> knowledge creation)  Learning from experience? (=AMBIGUITY)  Delays and the decline in visibility  Short-term improvements often involve very significant long-term costs.  Emergence: From the mutual interaction of the parts of a system there arise characteristics which can not be found as characteristic of any of the individual parts.  Systems maps: diagrams that show the key elements of systems and how they connect david.vallat@univ-lyon1.fr
  • 164. How does it work? (1) david.vallat@univ-lyon1.fr Page 1 sur 4htm Figure 2: Subtract Relationship The alternative is that thing 1 can subtract from thing 2, as indicated by the "-" sign in Figure 2, thus decreasing thing 2. All this thingness may a bit difficult to connect with so let's consider a couple specific examples. Figure 3: Sales Increases Revenue Figure 3 indicates that sales adds to revenue. Even if sales decrease it will still add to revenue, just not quite as rapidly as before. On the other hand, if sales increases it will add even more readily to revenue. To practice system thinking: http://www.systems-thinking.org/intst/int.htm 07/ 03/ 14 04:27o Systems Thinking Figure 4: Product Sales and Inventory Figure 4 indicates that product sales subtracts from finished goods inventory. If product sales increase it will subtract even more from finished goods inventory. On the other hand, if product sales decrease it will still subtract from finished goods inventory, just not quite so much. Within systems diagrams there are often items that are held constant within the context of what is being considered. These 07/ 03/ 14 04Introduction to Systems Thinking Introduction to Systems Thinking The Way of Systems Figure 4: Product Sales and Inventory Figure 4 indicates that product sales subtracts from finished goods inventory. If product sales increase it will subtract even more from finished goods inventory. On the other hand, if product sales decrease it will still subtract from finished goods inventory, just not quite so much. Within systems diagrams there are often items that are held constant within the context of what is being considered. These items will have neither a "+" nor a "-" attached to them. Figure 5: Constant Contribution Figure 5 indicates that resources interact with productivity in
  • 165. How does it work? (2) david.vallat@univ-lyon1.fr To practice system thinking: http://www.systems-thinking.org/intst/int.htm Page 2 sur 4 omplete to form loops. There are only two types of loops, einforcing and balancing. Reinforcing Loop A reinforcing loop is one in which the interactions are such that ach action adds to the other. Any situation where action produces result which promotes more of the same action is representative f a reinforcing loop. Figure 6: Reinforcing Loop and adds to the interest. Note that interest rate is considere a constant in this example. Interest then adds to the princip This reinforcing action happens every so many months depe on the period over which the institution computes the intere snowball rolling down hill is your signal that the loop is a reinforcing loop. The small graph to the right of principle indicates that the growth of principal is exponential. Typical examples of reinforcing loops are population growt decline, uncontrolled nuclear reactions, snow balls rolling d hill of course, runs on banks, wall street market crashes, etc Balancing Loop A balancing loop is one in which action attempts to bring tw things to agreement. Any situation where one attempts to so problem or achieve a goal or objective is representative of a balancing loop. Figure 7: Balancing Loop
  • 166. How does it work? (3) david.vallat@univ-lyon1.fr To practice system thinking: http://www.systems-thinking.org/intst/int.htm Figure 6 re you let yourself become overwhelmed by the complexity of this ram you had best fasten your seat belt as we're only about half way there. rtime has this real nasty habit of costing more than regular time so there ome implications of increasing Overtime. Figure 7 ncrease in Overtime brings with it an increase in Overtime Cost. As rtime Cost increases there is an increased emphasis on cost which shows s Cost Pressure. The Cost Pressure is interpreted by the management of ect in such a way that it shows up as additional Schedule Pressure. This eased Schedule Pressure then leads to even more Overtime. Here we but one more viscous reinforcing loop in which actions influence the all effect to be just the opposite of what is desired. rtime and Overtime Cost have a couple more influences. Project Systems Figure 8 Prolonged Overtime has a tendency to lead to Burnout which means H
  • 167. How does it work? (4) david.vallat@univ-lyon1.fr To practice system thinking: http://www.systems-thinking.org/intst/int.htm07/ 03/ 14 04:50tems Figure 12 Schedule Pressure has a couple additional influences that should be
  • 168. When using system thinking?  The following are some of the signs that indicate a systems thinking approach is most likely warranted.  There are multiple perspectives on just what the situation is, and how to deal with it  A previously applied fix has created problems elsewhere  After a fix is applied the problem returns in time  The same fix is used repeatedly  Growth slows over time  Partners for growth become adversaries  Limitations experienced are believed to result from insufficient capacity  There is more than one limit to growth  Limited resources are shared by others  Growth leads to decline elsewhere david.vallat@univ-lyon1.fr
  • 169. The four other disciplines  The 5 core disciplines are :  System thinking  Personal mastery  Mental models  Building shared vision  Team learning david.vallat@univ-lyon1.fr
  • 170. Personal mastery  « Organizations learn only through individuals who learn. Individual learning does not guarantee organizational learning. But without it no organizational learning occurs » (Senge 1990: 139).  « People with a high level of personal mastery live in a continual learning mode. They never ‘arrive’. Sometimes, language, such as the term ‘personal mastery’ creates a misleading sense of definiteness, of black and white. But personal mastery is not something you possess. It is a process. It is a lifelong discipline. People with a high level of personal mastery are acutely aware of their ignorance, their incompetence, their growth areas. And they are deeply self- confident. Paradoxical? Only for those who do not see the ‘journey is the reward’» (Senge 1990: 142). david.vallat@univ-lyon1.fr
  • 171. Mental models  These are « deeply ingrained assumptions, generalizations, or even pictures and images that influence how we understand the world and how we take action » (Senge 1990: 8).  « The discipline of mental models starts with turning the mirror inward; learning to unearth our internal pictures of the world, to bring them to the surface and hold them rigorously to scrutiny. It also includes the ability to carry on ‘learningful’ conversations that balance inquiry and advocacy, where people expose their own thinking effectively and make that thinking open to the influence of others » (Senge 1990: 9). david.vallat@univ-lyon1.fr
  • 172. Building shared vision  « When there is a genuine vision (as opposed to the all-to- familiar ‘vision statement’), people excel and learn, not because they are told to, but because they want to. But many leaders have personal visions that never get translated into shared visions that galvanize an organization… What has been lacking is a discipline for translating vision into shared vision – not a ‘cookbook’ but a set of principles and guiding practices. The practice of shared vision involves the skills of unearthing shared ‘pictures of the future’ that foster genuine commitment and enrolment rather than compliance. In mastering this discipline, leaders learn the counter- productiveness of trying to dictate a vision, no matter how heartfelt » (Senge 1990: 9). david.vallat@univ-lyon1.fr
  • 173. Team learning  Such learning is viewed as « the process of aligning and developing the capacities of a team to create the results its members truly desire » (Senge 1990: 236).  « The discipline of team learning starts with ‘dialogue’, the capacity of members of a team to suspend assumptions and enter into a genuine ‘thinking together’. To the Greeks dia-logos meant a free-flowing if meaning through a group, allowing the group to discover insights not attainable individually…. [It] also involves learning how to recognize the patterns of interaction in teams that undermine learning » (Senge 1990: 10). (group as a commons=> E. Ostrom) david.vallat@univ-lyon1.fr
  • 174. Issues with  Companies’ priorities are overwhelmingly financial BUT: « Productivity and competitiveness are, by and large, a function of knowledge generation and information processing: firms and territories are organized in networks of production, management and distribution; the core economic activities are global – that is they have the capacity to work as a unit in real time, or chosen time, on a planetary scale » - Castells, M. (2001), « Information technology and global capitalism » in W. Hutton and A. Giddens (eds.) On the Edge. Living with global capitalism, London: Vintage, p. 52.  Problem of competencies: the approach entails significant effort on the part of the practitioner david.vallat@univ-lyon1.fr
  • 176. Leading the learning organization (1)  A new view of leadership…  Traditional leaders: set the direction, make key decisions and energize the troops  The traditional view of leadership, « is based on assumptions of people’s powerlessness, their lack of personal vision and inability to master the forces of change, deficits which can be remedied only by a few great leaders » (Senge 1990: 340). david.vallat@univ-lyon1.fr
  • 177. Leading the learning organization (2)  In a learning organization, leaders are designers, stewards and teachers.  Leader as designer: « the leader’s task is designing the learning processes whereby people throughout the organization can deal productively with the critical issues they face, and develop their mastery in the learning disciplines » (Senge 1990: 345).  Leader as steward: « the leader develops a unique relationship to his or her own personal vision. He or she becomes a steward of the vision » (Senge 1990: 346). (=> Nonaka)  Leader as teacher: « much of the leverage leaders can actually exert lies in helping people achieve more accurate, more insightful and more empowering views of reality » (Senge 1990: 353). david.vallat@univ-lyon1.fr
  • 178. Phronetic leaders (Nonaka)  Phronetic leaders : https://hbr.org/2011/05/the-big-idea-the-wise-leader  “Phronesis” is a capability of finding the “right answer” for the overall good (common good) in an individual specific context, and a phronetic leader is a leader who has this capability. The capability of a phronetic leader has six factors:  1) Ability to make a judgment on “goodness” (ethics)  2) Ability to share contexts with others to create the Ba (and shared sense in a timely manner)  3) Ability to grasp the essence of particular situations/things (context)  4) Ability to reconstruct the particulars into universals using language/concepts/narratives (system thinking)  5) Ability to use any necessary political means well to realize concepts for the common good  6) Ability to foster practical wisdom in others to build a resilient organization 178
  • 179. The leader, a person and a method (1)  1. Wise Leaders Can Judge Goodness. Phronetic leaders practice moral discernment about what’s good and act on it in every situation.  VISION (≠VOLATILITY), BENEVOLENCE (CULTURE of creativity)  2. Wise Leaders Can Grasp the Essence. Before making judgment calls, wise leaders quickly sense what lies behind a situation, project a vision of the future or the consequences, and decide on the action needed to realize that vision.  CLARITY, SYSTEM THINKING (≠COMPLEXITY), AGILITY (≠ROUTINE, AMBIGUITY) 179
  • 180. The leader, a person and a method (2)  3. Wise Leaders Create Shared Contexts. Phronetic leaders constantly create opportunities for senior executives and employees to learn from one another. In Japan a ba (place, space, or field) refers to the context in which relationships are forged and interactions occur.  KNOWLEDGE CREATION (INNOVATION) => UNDERSTANDING (≠UNCERTAINTY)  4. Wise Leaders Communicate the Essence. Phronetic leaders must be able to communicate in a way that everyone can understand. The essence of a situation is often hard to express, so they must use stories, metaphors, and other figurative language.  KEY INTELLIGENCE TOPICS, SENSEMAKING, STORYTELLING, SYSTEM THINKING => VISION (≠VOLATILITY) 180
  • 181.  5. Wise Leaders Exercise Political Power. It isn’t enough to identify the essence or communicate it; phronetic leaders must bring people together and spur them to act, combining and synthesizing everyone’s knowledge and efforts in the single-minded pursuit of their goals.  CREATIVE CULTURE, BENEVOLENCE => UNDERSTANDING (≠UNCERTAINTY)  6. Wise Leaders Foster Practical Wisdom in Others. Practical wisdom should never be treated as if it were the preserve of the company’s chief executive or top management team. It must be distributed as much as possible through the organization, and employees at all levels can be trained in its use.  CREATIVE CULTURE, BENEVOLENCE => UNDERSTANDING (≠UNCERTAINTY) 181 The leader, a person and a method (3)
  • 182. Benevolence and Business Agility  All about people…  Theory X and Y (D. McGregor): http://en.wikipedia.org/wiki/Theor y_X_and_Theory_Y  Freedom Inc (Getz & Carney). http://www.amazon.com/Freedom- Inc-Employees-Business- Productivity/dp/0307409384  SEMCO: http://en.wikipedia.org/wiki/Maveric k_(book)  GORE: http://en.wikipedia.org/wiki/W._L._ Gore_and_Associates  IDEO: http://en.wikipedia.org/wiki/IDEO david.vallat@univ-lyon1.fr
  • 183. Motivation  Strong link between knowledge worker motivation and benevolence in management (≠ scientific management) 183 The book in a video: https://www.youtube.com/watch?v=u6XAPnuFjJc The book in a TED conference: http://www.ted.com/talks/dan_pink_on_motivatio n?language=en We are motivated when we can be creative…
  • 184. Business Agility (vucA)  An imperative for survival in a VUCA world.  Business agility is the ability of a business to adapt rapidly and cost efficiently in response to changes in the business environment. => LO  History: http://agilemanifesto.org david.vallat@univ-lyon1.fr
  • 185. Business Agility (definition)  Business agility is the ability of a business to adapt rapidly and cost efficiently in response to changes in the business environment. Business agility can be maintained by maintaining and adapting goods and services to meet customer demands, adjusting to the changes in a business environment and taking advantage of human resources.  Agility is a concept that incorporates the ideas of flexibility, balance, adaptability, and coordination under one umbrella. In a business context, agility typically refers to the ability of an organization to rapidly adapt to market and environmental changes in productive and cost-effective ways.  http://www.cise.ufl.edu/~manuel/Agile-for-Dummies 185
  • 187. Why Competitive Intelligence? Creating knowledge Understanding the context Making decisions Organizing this = Knowledge Management SURVIVAL (Innovation) @DavidVALLAT 187
  • 188. Why Competitive Intelligence? @DavidVALLAT 188 SURVIVAL (Innovation) V.U.C.A. C.I. Tools (swot, etc.) Knowledge Creation
  • 189. Why Competitive Intelligence? @DavidVALLAT 189 Knowledge Creation PEOPLE (collaboration) Tacit & Explicit Knowledge (SECI Model) Knowledge Creation Tools (LLW, CoP, Ba)
  • 190. Why Competitive Intelligence? @DavidVALLAT 190 Knowledge Creation to make decisions Struggle against routines and blindness… … and finally adopt system thinking in order to foster a learning organization
  • 191. Why Competitive Intelligence? @DavidVALLAT 191 A learning organization... … relies upon a phronetic leader... … that everyone can be PEOPLE (collaboration = motivation)
  • 192. What to do next?  Drivers/Vision/Sensemaking for yourself  Learning and continuous improvement (MOOC, TED, etc.)  Implementation of knowledge creation (Ba, LLW, CoP)  Train to be a phronetic leader  Train others  Measure results (BSC) => feebacks 192 @DavidVALLAT
  • 193. Recommended Readings (1)  Fun and useful for business:  S. Johnson et al., The One Minute Manager (in the Google doc files)  S. Johnson, Where is my cheese? (in the Google doc files) 193 @DavidVALLAT
  • 194. Recommended Readings (2)  Less fun but very useful for business: 194 @DavidVALLAT
  • 195. Recommended Readings (3)  Less fun but very useful for business: 195 @DavidVALLAT

Editor's Notes

  1. Baseline Recipe (iiii à la fin)
  2. To reach a goal you have to set one. Take 5 minutes to write what do you want from this course… Now I’ll show you what I want from you ; in other words what are the goals of this course... To do so let’s have a look to the assessment
  3. Words have a lot of significations…
  4. I think it’s XXth century CI Let’s move on
  5. Take a sheet of paper Write the three most important words according to you : customer, environment, decision Replace intelligence with knowledge It’s about producing something How to priorize?
  6. The quote is not complete: country UNDERSTANDING THE CONTEXT => those are the most important words… Thinking out the box
  7. Decision making = hard choices
  8. To sum up and visualize a theorical process It’s a model It’s a simplification of reality (prendre une carte de Saigon) => the map is not the territory Do not mix up the map with the territory… It’s sometime what experts do... A part of reality is not the reality...
  9. On The Origin of Species (1859)
  10. Have a look at this video: Trial & Error (Tim HARFORD): https://www.youtube.com/watch?v=K5wCfYujRdE
  11. What is it to be OPEN TO CHANGE? We need to get comfortable with being uncomfortable… System thinking Open to learning (voir pink about profile...) : two kinds of people : Intelligence is the result of a process? Or intelligence is genetically in a limited supply, a fixed quantity
  12. Resistance to change… Watch this little movie tonight (15 minutes) and we will talk about it tomorrow.
  13. A quick reminder to how to conduct change
  14. Knowledge Workers: peter drucker management guru
  15. Intelligence is the fruit of a process… We all need to skill up : countries, companies and people... Who in this class has already taken a MOOcourse? Could you speak about your experience? why a mooc? Successful ?
  16. MOTIVATION !!!!!!!!!!!!!!!!!!! What is a knowledge worker?
  17. Do you think you are Knowledge Workers? HOW TO MANAGE KW????????? Millenials Y generation
  18. So we need to adapt, we need to embrace change
  19. So we need to adapt, we need to embrace change
  20. North korea Complexity is based on human relation
  21. A basis of a new way to understand the organization / a new way to manage it. Why organizations: to produce knowledge… L’incertitude se combat par la compréhension. Comprendre son environnement suppose d’écouter toutes les parties prenantes (et donc d’avoir les instances permettant de pratiquer cette écoute, de capitaliser l’information et de développer les actions afférentes). SHAREHOLDERS La complexité s’apprivoise par l’expérimentation, la simulation. La volatilité peut être contrebalancée par une vision de long terme, c’est-à-dire une orientation stratégique forte assumée et communiquée afin de rassurer les parties prenantes. L’ambiguïté, source d’erreurs, demande à ce que les ajustements soient rapides, c’est le propre des organisations agiles.
  22. Understanding the context is a way of being (a vuca way of being) But it’s also tools like vuca
  23. KIT = good questions you have to ask yourself…
  24. These models are fine but not very dynamic / not very systemic I’m not sure they are appropriate for a VUCA world… These models don’t talk a lot about the consumers...
  25. THINK OF WHAT THIS MODEL LEAVES OUT… (video of Tim Harford)
  26. PEST analysis examines the external macro-environment in which a company exists: political factors, economic factors, social factors and technological factors. It can also be used for evaluating market growth or decline, and a company’s position, potential and direction for a business. OBJECTIVES: PEST Analysis is useful for four main reasons: It helps you to spot business or personal opportunities, and it gives you advanced warning of significant threats. It reveals the direction of change within your business environment. This helps you shape what you're doing, so that you work with change, rather than against it. It helps you avoid starting projects that are likely to fail, for reasons beyond your control. It can help you break free of unconscious assumptions when you enter a new country, region, or market; because it helps you develop an objective view of this new environment. Note: PEST Analysis is often linked with SWOT Analysis  , however, the two tools have different areas of focus. PEST Analysis looks at "big picture" factors that might influence a decision, a market, or a potential new business. SWOT Analysis explores these factors at a business, product-line or product level. These tools complement one another and are often used together. This framework is used in the early phases of strategy development to describe the landscape and environment in which a firm operates ( PEST stands for Political, Economic, Social and Technological). Note: It is sometimes transformed into SLEPT (Social, Legal, Economic, Political, Technological), PESTEL (Political, Economic, Social, Technological, Environmental/Ecological, Legal), STEEPLE (Social, Technological, Economic, Environmental, Legal, Ethical), etc. Changes in your business environment can create great opportunities for your organization – and cause significant threats. For example, opportunities can come from new technologies that help you reach new customers, from new funding streams that allow you to invest in better equipment, and from changed government policies that open up new markets. Threats can include deregulation that exposes you to intensified competition; a shrinking market; or increases to interest rates, which can cause problems if your company is burdened by debt. PEST Analysis is a simple and widely used tool that helps you analyze the Political, Economic, Socio-Cultural, and Technological changes in your business environment. This helps you understand the "big picture" forces of change that you're exposed to, and, from this, take advantage of the opportunities that they present. In this article, we'll look at how you can use PEST Analysis to understand and adapt to your future business environment. About the Tool Harvard professor Francis Aguilar is thought to be the creator of PEST Analysis. He included a scanning tool called ETPS in his 1967 book "Scanning the Business Environment." The name was later tweaked to create the current acronym. OBJECTIVES: PEST Analysis is useful for four main reasons: It helps you to spot business or personal opportunities, and it gives you advanced warning of significant threats. It reveals the direction of change within your business environment. This helps you shape what you're doing, so that you work with change, rather than against it. It helps you avoid starting projects that are likely to fail, for reasons beyond your control. It can help you break free of unconscious assumptions when you enter a new country, region, or market; because it helps you develop an objective view of this new environment. Note: PEST Analysis is often linked with SWOT Analysis  , however, the two tools have different areas of focus. PEST Analysis looks at "big picture" factors that might influence a decision, a market, or a potential new business. SWOT Analysis explores these factors at a business, product-line or product level. These tools complement one another and are often used together. How to Use the Tool Follow these steps to analyze your business environment, and the opportunities and threats that it presents. Use PEST to brainstorm the changes happening around you. Use the prompts below to guide your questioning, and tailor the questions to suit the specific needs of your business Brainstorm opportunities arising from each of these changes. Brainstorm threats or issues that could be caused by them. Take appropriate action. Our worksheet guides you through these steps Step 1: Brainstorm Factors Political Factors to Consider When is the country's next local, state, or national election? How could this change government or regional policy? Who are the most likely contenders for power? What are their views on business policy, and on other policies that affect your organization? Depending on the country, how well developed are property rights and the rule of law, and how widespread are corruption and organized crime? How are these situations likely to change, and how is this likely to affect you? Could any pending legislation or taxation changes affect your business, either positively or negatively? How will business regulation, along with any planned changes to it, affect your business? And is there a trend towards regulation or deregulation? How does government approach corporate policy, corporate social responsibility, environmental issues, and customer protection legislation? What impact does this have, and is it likely to change? What is the likely timescale of proposed legislative changes? Are there any other political factors that are likely to change? Economic Factors to Consider How stable is the current economy? Is it growing, stagnating, or declining? Are key exchange rates stable, or do they tend to vary significantly? Are customers' levels of disposable income rising or falling? How is this likely to change in the next few years? What is the unemployment rate? Will it be easy to build a skilled workforce? Or will it be expensive to hire skilled labor? Do consumers and businesses have easy access to credit? If not, how will this affect your organization? How is globalization affecting the economic environment? Are there any other economic factors that you should consider? Tip: Use Porter's Diamond   to align your strategy with your country's business conditions. Socio-Cultural Factors to Consider What is the population's growth rate and age profile? How is this likely to change? Are generational shifts in attitude likely to affect what you're doing? What are your society's levels of health, education, and social mobility? How are these changing, and what impact does this have? What employment patterns, job market trends, and attitudes toward work can you observe? Are these different for different age groups? What social attitudes and social taboos could affect your business? Have there been recent socio-cultural changes that might affect this? How do religious beliefs and lifestyle choices affect the population? Are any other socio-cultural factors likely to drive change for your business? Tip: Values take a central role in any society. Use the Competing Values Framework   to identify your organization's values, and Hofstede's Cultural Dimensions   to explore the values of your customers. Technological Factors to Consider Are there any new technologies that you could be using? Are there any new technologies on the horizon that could radically affect your work or your industry? Do any of your competitors have access to new technologies that could redefine their products? In which areas do governments and educational institutions focus their research? Is there anything you can do to take advantage of this? How have infrastructure changes affected work patterns (for example, levels of remote working)? Are there existing technological hubs that you could work with or learn from? Are there any other technological factors that you should consider? Note: There are variations of PEST Analysis that bring other factors into consideration. These include: PESTLE/PESTEL: Political, Economic, Socio-Cultural, Technological, Legal, Environmental. PESTLIED: Political, Economic, Socio-Cultural, Technological, Legal, International, Environmental, Demographic. STEEPLE: Social/Demographic, Technological, Economic, Environmental, Political, Legal, Ethical. SLEPT: Socio-Cultural, Legal, Economic, Political, Technological. LONGPESTLE: Local, National, and Global versions of PESTLE. (These are best used for understanding change in multinational organizations.) Choose the version that best suits your situation. Step 2: Brainstorm Opportunities Once you've identified the changes that are taking place in your business environment, it's time to look at each change, and brainstorm the opportunities that this could open up for you. For example, could it help you develop new products, open up new markets, or help you make processes more efficient? Step 3: Brainstorm Threats It's also important to think about how these changes could undermine your business. If you understand this early enough, you may be able to avoid these problems, or minimize their impact. For example, if a core part of your market is in demographic decline, could you open up other areas of the market? Or if technology is threatening a key product, can you master that technology and improve the product? (Risk Analysis   can help you to assess these threats and devise strategies to manage them.) Step 4: Take Action Where you have identified significant opportunities, build the actions you'll take to exploit them into your Business Plan  . Where you've identified significant risks, take appropriate action to manage or eliminate them. Key Points PEST Analysis helps you understand the Political, Economic, Social, and Technological changes that will shape your business environment. You can use these headings to brainstorm the "big picture" characteristics of a business environment (this could be a country, a region, or a new or existing market), and, from this, draw conclusions about the significant forces of change operating within it. This provides a context for more detailed planning, within which you will be able to minimize risk and take full advantage of the opportunities that present themselves. -------------- One of the concepts discussed in Part 1 of this short course was environmental mapping. We need to understand the complete competitive landscape – things like economic trends, technology and other factors impacting our organization. One of the more popular analytical models for environmental assessment is PEST: Political – Understanding the political environment. For example, politicians can create new issues for a company, such as new reporting requirements for publicly traded companies per passage of the Sarbanes-Oxley Act. Economic – Changes in the economy will impact a company, such as lower investment rates, higher interest rates, slower economic growth, and changes in consumer spending. Social – Trends in demographics, population shifts, lifestyles, and other changes in society can influence an organization. Technology – Sudden changes can occur with new technologies, especially for those companies that depend upon technology for producing and distributing products and services. For some organizations, the natural environment or ecology could be important, such as those companies that use or impact the physical environment. Therefore, we can add another letter to our PEST Model (E for Ecology), rearrange the letters and come up with STEEP (Social, Technology, Economic, Ecology, Political). However, the important point is to create your own unique model that effectively monitors the external environment that you operate in, recognizing that many elements influence one another. Additionally, you want to relate the trends into KIT’s where possible, giving you the baseline you need for understanding the implications on your organization. Most companies need a framework for evaluating external forces and PEST or STEEP are good places to start.
  27. PEST analysis examines the external macro-environment in which a company exists: political factors, economic factors, social factors and technological factors. It can also be used for evaluating market growth or decline, and a company’s position, potential and direction for a business. OBJECTIVES: PEST Analysis is useful for four main reasons: It helps you to spot business or personal opportunities, and it gives you advanced warning of significant threats. It reveals the direction of change within your business environment. This helps you shape what you're doing, so that you work with change, rather than against it. It helps you avoid starting projects that are likely to fail, for reasons beyond your control. It can help you break free of unconscious assumptions when you enter a new country, region, or market; because it helps you develop an objective view of this new environment. Note: PEST Analysis is often linked with SWOT Analysis  , however, the two tools have different areas of focus. PEST Analysis looks at "big picture" factors that might influence a decision, a market, or a potential new business. SWOT Analysis explores these factors at a business, product-line or product level. These tools complement one another and are often used together. This framework is used in the early phases of strategy development to describe the landscape and environment in which a firm operates ( PEST stands for Political, Economic, Social and Technological). Note: It is sometimes transformed into SLEPT (Social, Legal, Economic, Political, Technological), PESTEL (Political, Economic, Social, Technological, Environmental/Ecological, Legal), STEEPLE (Social, Technological, Economic, Environmental, Legal, Ethical), etc. Changes in your business environment can create great opportunities for your organization – and cause significant threats. For example, opportunities can come from new technologies that help you reach new customers, from new funding streams that allow you to invest in better equipment, and from changed government policies that open up new markets. Threats can include deregulation that exposes you to intensified competition; a shrinking market; or increases to interest rates, which can cause problems if your company is burdened by debt. PEST Analysis is a simple and widely used tool that helps you analyze the Political, Economic, Socio-Cultural, and Technological changes in your business environment. This helps you understand the "big picture" forces of change that you're exposed to, and, from this, take advantage of the opportunities that they present. In this article, we'll look at how you can use PEST Analysis to understand and adapt to your future business environment. About the Tool Harvard professor Francis Aguilar is thought to be the creator of PEST Analysis. He included a scanning tool called ETPS in his 1967 book "Scanning the Business Environment." The name was later tweaked to create the current acronym. OBJECTIVES: PEST Analysis is useful for four main reasons: It helps you to spot business or personal opportunities, and it gives you advanced warning of significant threats. It reveals the direction of change within your business environment. This helps you shape what you're doing, so that you work with change, rather than against it. It helps you avoid starting projects that are likely to fail, for reasons beyond your control. It can help you break free of unconscious assumptions when you enter a new country, region, or market; because it helps you develop an objective view of this new environment. Note: PEST Analysis is often linked with SWOT Analysis  , however, the two tools have different areas of focus. PEST Analysis looks at "big picture" factors that might influence a decision, a market, or a potential new business. SWOT Analysis explores these factors at a business, product-line or product level. These tools complement one another and are often used together. How to Use the Tool Follow these steps to analyze your business environment, and the opportunities and threats that it presents. Use PEST to brainstorm the changes happening around you. Use the prompts below to guide your questioning, and tailor the questions to suit the specific needs of your business Brainstorm opportunities arising from each of these changes. Brainstorm threats or issues that could be caused by them. Take appropriate action. Our worksheet guides you through these steps Step 1: Brainstorm Factors Political Factors to Consider When is the country's next local, state, or national election? How could this change government or regional policy? Who are the most likely contenders for power? What are their views on business policy, and on other policies that affect your organization? Depending on the country, how well developed are property rights and the rule of law, and how widespread are corruption and organized crime? How are these situations likely to change, and how is this likely to affect you? Could any pending legislation or taxation changes affect your business, either positively or negatively? How will business regulation, along with any planned changes to it, affect your business? And is there a trend towards regulation or deregulation? How does government approach corporate policy, corporate social responsibility, environmental issues, and customer protection legislation? What impact does this have, and is it likely to change? What is the likely timescale of proposed legislative changes? Are there any other political factors that are likely to change? Economic Factors to Consider How stable is the current economy? Is it growing, stagnating, or declining? Are key exchange rates stable, or do they tend to vary significantly? Are customers' levels of disposable income rising or falling? How is this likely to change in the next few years? What is the unemployment rate? Will it be easy to build a skilled workforce? Or will it be expensive to hire skilled labor? Do consumers and businesses have easy access to credit? If not, how will this affect your organization? How is globalization affecting the economic environment? Are there any other economic factors that you should consider? Tip: Use Porter's Diamond   to align your strategy with your country's business conditions. Socio-Cultural Factors to Consider What is the population's growth rate and age profile? How is this likely to change? Are generational shifts in attitude likely to affect what you're doing? What are your society's levels of health, education, and social mobility? How are these changing, and what impact does this have? What employment patterns, job market trends, and attitudes toward work can you observe? Are these different for different age groups? What social attitudes and social taboos could affect your business? Have there been recent socio-cultural changes that might affect this? How do religious beliefs and lifestyle choices affect the population? Are any other socio-cultural factors likely to drive change for your business? Tip: Values take a central role in any society. Use the Competing Values Framework   to identify your organization's values, and Hofstede's Cultural Dimensions   to explore the values of your customers. Technological Factors to Consider Are there any new technologies that you could be using? Are there any new technologies on the horizon that could radically affect your work or your industry? Do any of your competitors have access to new technologies that could redefine their products? In which areas do governments and educational institutions focus their research? Is there anything you can do to take advantage of this? How have infrastructure changes affected work patterns (for example, levels of remote working)? Are there existing technological hubs that you could work with or learn from? Are there any other technological factors that you should consider? Note: There are variations of PEST Analysis that bring other factors into consideration. These include: PESTLE/PESTEL: Political, Economic, Socio-Cultural, Technological, Legal, Environmental. PESTLIED: Political, Economic, Socio-Cultural, Technological, Legal, International, Environmental, Demographic. STEEPLE: Social/Demographic, Technological, Economic, Environmental, Political, Legal, Ethical. SLEPT: Socio-Cultural, Legal, Economic, Political, Technological. LONGPESTLE: Local, National, and Global versions of PESTLE. (These are best used for understanding change in multinational organizations.) Choose the version that best suits your situation. Step 2: Brainstorm Opportunities Once you've identified the changes that are taking place in your business environment, it's time to look at each change, and brainstorm the opportunities that this could open up for you. For example, could it help you develop new products, open up new markets, or help you make processes more efficient? Step 3: Brainstorm Threats It's also important to think about how these changes could undermine your business. If you understand this early enough, you may be able to avoid these problems, or minimize their impact. For example, if a core part of your market is in demographic decline, could you open up other areas of the market? Or if technology is threatening a key product, can you master that technology and improve the product? (Risk Analysis   can help you to assess these threats and devise strategies to manage them.) Step 4: Take Action Where you have identified significant opportunities, build the actions you'll take to exploit them into your Business Plan  . Where you've identified significant risks, take appropriate action to manage or eliminate them. Key Points PEST Analysis helps you understand the Political, Economic, Social, and Technological changes that will shape your business environment. You can use these headings to brainstorm the "big picture" characteristics of a business environment (this could be a country, a region, or a new or existing market), and, from this, draw conclusions about the significant forces of change operating within it. This provides a context for more detailed planning, within which you will be able to minimize risk and take full advantage of the opportunities that present themselves. -------------- One of the concepts discussed in Part 1 of this short course was environmental mapping. We need to understand the complete competitive landscape – things like economic trends, technology and other factors impacting our organization. One of the more popular analytical models for environmental assessment is PEST: Political – Understanding the political environment. For example, politicians can create new issues for a company, such as new reporting requirements for publicly traded companies per passage of the Sarbanes-Oxley Act. Economic – Changes in the economy will impact a company, such as lower investment rates, higher interest rates, slower economic growth, and changes in consumer spending. Social – Trends in demographics, population shifts, lifestyles, and other changes in society can influence an organization. Technology – Sudden changes can occur with new technologies, especially for those companies that depend upon technology for producing and distributing products and services. For some organizations, the natural environment or ecology could be important, such as those companies that use or impact the physical environment. Therefore, we can add another letter to our PEST Model (E for Ecology), rearrange the letters and come up with STEEP (Social, Technology, Economic, Ecology, Political). However, the important point is to create your own unique model that effectively monitors the external environment that you operate in, recognizing that many elements influence one another. Additionally, you want to relate the trends into KIT’s where possible, giving you the baseline you need for understanding the implications on your organization. Most companies need a framework for evaluating external forces and PEST or STEEP are good places to start.
  28. Porter’s Five Forces analysis, developed by Michael E. Porter of Harvard Business School, is a framework for assessing and evaluating the competitive strength and position of a business organization. Porter’s theory is based on the concept that there are five forces which determine the competitive intensity and attractiveness of a market: supplier power, buyer power, competitive rivalry, threat of substitute products/technology change, and threat of new market entrants. Porter’s framework provides a checklist to analyze the competitiveness level of an industry based on the balance of power. When using it, do not forget it is only the start of your analysis. The next step includes defining which strategy would augment chances of success: cost structure strategy, differentiation strategy or integration strategy. ------------- When it comes to understanding an industry, Porter’s Five Forces Model is widely regarded as the best analytical model. Part 1 of this short course touched on the basics, but since this is such a popular model, it warrants more attention. As noted in Part 1 of this short course, an industry consists of five competitive forces: 1. Threat of New Entrants – An industry with low barriers of entry will invariably have intense competition as opposed to an industry with major barriers of entry. For example, professional consulting is an industry with few barriers of entry. This leads to very serious competition, which in turn puts pressure on lower pricing and higher quality. Starting a pharmaceutical company is not so easy and he players are well-defined. Profit margins tend to be higher for an industry with high barriers of entry. Barriers of entry can include: High capital investments, such as a micro-processing manufacturing facility. Deep Rooted Brand Appeal, such as Coke Cola. Strong Government Regulation, such as nuclear energy. Switching Costs, such as scraping a major defense program for a new program. Power of Suppliers – Basic inputs for a product or service are subject to control by suppliers, such as control over prices or availability. Suppliers tend to have strong influence within an industry when: Few Suppliers – Only a small number of suppliers service the industry and there are no real substitutes for what they provide. Acting Together – Suppliers sometimes act as one large monopoly, setting prices, quality, and supply. For example, OPEC governs the supply and pricing of crude oil. Socialism – In certain countries, prices and supply may be under serious government control. Power of Buyers – Customers (including distributors and other types of buyers) often influence what happens within an industry. For example, customers often dictate pricing and they demand certain levels of quality. The power of buyers or customers depends on several factors: Product Uniqueness – A unique product or fad usually negates the power of customers since they are willing to pay high prices to just to obtain the product. On the other hand, a common product, such as toilet paper, is not very unique. Customers will tend to have a lot more influence. Few Customers – If you service a few customers or one customer accounts for most of your business, then this customer will have a lot of influence. Informed Buyer – Comparative information that is readily available will tend to empower buyers and give them more influence. The absence of information about the industry’s products and services will reduce the buyer’s influence. Easy Crossover – More choices will increase the power of buyers whereas few options will limit a buyer’s influence. Substitute Products – New or emerging substitutes for a product will change competitive forces. This can be influenced by things such as the costs and profitability of the substitute product, how easy it is to crossover to the substitute product, and how well does the substitute product perform relative to the existing product. Rivalry and Intensity – Companies will jockey and maneuver to gain a competitive foothold within an industry. For example, airline companies may try to undercut their competition through lower airfares. This competitive rivalry may decline when times are good and everyone can grow. Competitive rivalry usually remains high for common products where switching takes place. It’s worth noting that as one of the five forces change, it will impact the other forces. So understanding the relationship of the five forces is as important as understanding the force itself. One way to simplify this is to assign weights to each force. Higher weights are assigned to those forces that have more influence. The key to five forces industry analysis is to gain an understanding of how profitable the industry will be going forward. And how can we change our current strategy to improve our competitive position? At the center of this analysis is a clear understanding of what forces will impact a company’s profitability and how do we protect ourselves from profit erosion. Finally, Five Forces is not without its drawbacks. Five Forces Analysis works best for industries that are well defined with relative stability. Some industries are a blur with overlapping players. For example, a telephone company may provide internet services or a bank may provide business consulting services. And given today’s rate of change, few industries can be considered relatively stable. A third dilemma with Five Forces is the failure to recognize indirect forces that impact an industry. This can include regulatory, social, economic, and technology. The most prudent approach is to pull from several analytical models for a complete picture.
  29. Porter’s Five Forces analysis, developed by Michael E. Porter of Harvard Business School, is a framework for assessing and evaluating the competitive strength and position of a business organization. Porter’s theory is based on the concept that there are five forces which determine the competitive intensity and attractiveness of a market: supplier power, buyer power, competitive rivalry, threat of substitute products/technology change, and threat of new market entrants. Porter’s framework provides a checklist to analyze the competitiveness level of an industry based on the balance of power. When using it, do not forget it is only the start of your analysis. The next step includes defining which strategy would augment chances of success: cost structure strategy, differentiation strategy or integration strategy. ------------- When it comes to understanding an industry, Porter’s Five Forces Model is widely regarded as the best analytical model. Part 1 of this short course touched on the basics, but since this is such a popular model, it warrants more attention. As noted in Part 1 of this short course, an industry consists of five competitive forces: 1. Threat of New Entrants – An industry with low barriers of entry will invariably have intense competition as opposed to an industry with major barriers of entry. For example, professional consulting is an industry with few barriers of entry. This leads to very serious competition, which in turn puts pressure on lower pricing and higher quality. Starting a pharmaceutical company is not so easy and he players are well-defined. Profit margins tend to be higher for an industry with high barriers of entry. Barriers of entry can include: High capital investments, such as a micro-processing manufacturing facility. Deep Rooted Brand Appeal, such as Coke Cola. Strong Government Regulation, such as nuclear energy. Switching Costs, such as scraping a major defense program for a new program. Power of Suppliers – Basic inputs for a product or service are subject to control by suppliers, such as control over prices or availability. Suppliers tend to have strong influence within an industry when: Few Suppliers – Only a small number of suppliers service the industry and there are no real substitutes for what they provide. Acting Together – Suppliers sometimes act as one large monopoly, setting prices, quality, and supply. For example, OPEC governs the supply and pricing of crude oil. Socialism – In certain countries, prices and supply may be under serious government control. Power of Buyers – Customers (including distributors and other types of buyers) often influence what happens within an industry. For example, customers often dictate pricing and they demand certain levels of quality. The power of buyers or customers depends on several factors: Product Uniqueness – A unique product or fad usually negates the power of customers since they are willing to pay high prices to just to obtain the product. On the other hand, a common product, such as toilet paper, is not very unique. Customers will tend to have a lot more influence. Few Customers – If you service a few customers or one customer accounts for most of your business, then this customer will have a lot of influence. Informed Buyer – Comparative information that is readily available will tend to empower buyers and give them more influence. The absence of information about the industry’s products and services will reduce the buyer’s influence. Easy Crossover – More choices will increase the power of buyers whereas few options will limit a buyer’s influence. Substitute Products – New or emerging substitutes for a product will change competitive forces. This can be influenced by things such as the costs and profitability of the substitute product, how easy it is to crossover to the substitute product, and how well does the substitute product perform relative to the existing product. Rivalry and Intensity – Companies will jockey and maneuver to gain a competitive foothold within an industry. For example, airline companies may try to undercut their competition through lower airfares. This competitive rivalry may decline when times are good and everyone can grow. Competitive rivalry usually remains high for common products where switching takes place. It’s worth noting that as one of the five forces change, it will impact the other forces. So understanding the relationship of the five forces is as important as understanding the force itself. One way to simplify this is to assign weights to each force. Higher weights are assigned to those forces that have more influence. The key to five forces industry analysis is to gain an understanding of how profitable the industry will be going forward. And how can we change our current strategy to improve our competitive position? At the center of this analysis is a clear understanding of what forces will impact a company’s profitability and how do we protect ourselves from profit erosion. Finally, Five Forces is not without its drawbacks. Five Forces Analysis works best for industries that are well defined with relative stability. Some industries are a blur with overlapping players. For example, a telephone company may provide internet services or a bank may provide business consulting services. And given today’s rate of change, few industries can be considered relatively stable. A third dilemma with Five Forces is the failure to recognize indirect forces that impact an industry. This can include regulatory, social, economic, and technology. The most prudent approach is to pull from several analytical models for a complete picture.
  30. diagram
  31. It’s like trying to think in the head of competitors… It’s not a crystal ball: the thinking process is more relevant than the result... It’s a simulation => it helps to deal with complexity
  32. These questions are more specific/contextual. Good questions to ask in order to develop your business…
  33. Reed about this and tell me tommorow what do you think about it…
  34. Reed about this and tell me tommorow what do you think about it… Big consultancy company McKinsey
  35. Reed about this and tell me tommorow what do you think about it…
  36. Effective : successful in producing a desired or intended result. Efficient : (especially of a system or machine) achieving maximum productivity with minimum wasted effort or expense. Scientific management requires a high level of managerial control over employee work practices and entails a higher ratio of managerial workers to laborers than previous management methods. Such detail-oriented management may cause friction between workers and managers. Taylor's four principles are as follows: Replace working by "rule of thumb," or simple habit and common sense, and instead use the scientific method to study work and determine the most efficient way to perform specific tasks. Rather than simply assign workers to just any job, match workers to their jobs based on capability and motivation, and train them to work at maximum efficiency. Monitor worker performance, and provide instructions and supervision to ensure that they're using the most efficient ways of working. Allocate the work between managers and workers so that the managers spend their time planning and training, allowing the workers to perform their tasks efficiently.
  37. Effective : successful in producing a desired or intended result. Efficient : (especially of a system or machine) achieving maximum productivity with minimum wasted effort or expense. Scientific management requires a high level of managerial control over employee work practices and entails a higher ratio of managerial workers to laborers than previous management methods. Such detail-oriented management may cause friction between workers and managers. Taylor's four principles are as follows: Replace working by "rule of thumb," or simple habit and common sense, and instead use the scientific method to study work and determine the most efficient way to perform specific tasks. Rather than simply assign workers to just any job, match workers to their jobs based on capability and motivation, and train them to work at maximum efficiency. Monitor worker performance, and provide instructions and supervision to ensure that they're using the most efficient ways of working. Allocate the work between managers and workers so that the managers spend their time planning and training, allowing the workers to perform their tasks efficiently.
  38. To sum up and visualize a theorical process It’s a model It’s a simplification of reality (prendre une carte de Saigon) => the map is not the territory
  39. Chief km officer
  40. => People gather data because it is factual and therefore creates an illusion of scientific accuracy. They think that if enough data is available, objectively correct decisions will become easy to make. This is false on two counts. - First, too much data can make it harder to identify and make sense of a situation. - Second, there is no inherent meaning in data. Data provides no judgment or interpretation. Data, by itself cannot tell us what to do. Data says nothing about its own importance or relevance. But all the same, data is im­portant to organizations, because it is what gives rise to information. We transform data into information by adding value in various ways. . Contextualizing: To know for what purpose the data was gathered (GDP => measure wealth in a country) . Categorizing: To know the units of analysis or key components of the data (GDP => sum of gross value added) . Calculating: To analyse the data mathematically or statistically . Correcting: To remove errors from the data . Condensing: To make the data available in a more concise, user friendly form (diagram)
  41. Knowledge is broader, deeper, and richer than data or information. Information becomes knowledge, through:   . Comparison: How does information about this situation compare to other situations? . Consequences: What implications does the information have for decisions and actions? . Connections: How does this bit of knowledge relate to others? . Conversation: What do other people think about this information? One of the reasons that we find knowledge valuable is that it is closer than data or information to action. Knowledge must be evaluated by the decisions or actions to which it leads. Better knowledge must lead to improved productivity or lower cost and must facilitate wiser decisions. Knowledge develops over time, through experience, which provides a historical perspective from which to view and understand new situations and events. Knowledge born of experience recognizes familiar patterns and can make connections between what is happening now and what happened in the past. Knowledge through experience is effective By helping us deal with complexity, knowledge provides value.
  42. Faith / science Let me ask you a question: what is knowledge? What are the caracteristics of knowledge?
  43. How to acquire knowledge? Question of memory. Experiential knowledge ; a priori knowledge (before doing / after having done) In philosophy, the study of knowledge is called epistemology; t Episteme = personification of knowledge
  44. Let me ask you a question: what is knowledge? What are the caracteristics of knowledge? How to acquire knowledge? Question of memory. Experiential knowledge ; a priori knowledge (before doing / after having done) In philosophy, the study of knowledge is called epistemology; t Episteme = personification of knowledge
  45. Austrian-British philosopher We can oppose science with ideology/religion. Religion doesn’t accept to be questioned… it suffices of one couterexample for dropping the law. How to acquire knowledge? Question of memory. Experiential knowledge ; a priori knowledge (before doing / after having done) In philosophy, the study of knowledge is called epistemology; t Episteme = personification of knowledge
  46. Let me ask you a question: what is knowledge? What are the caracteristics of knowledge? How to acquire knowledge? Question of memory. Experiential knowledge ; a priori knowledge (before doing / after having done) In philosophy, the study of knowledge is called epistemology; t Episteme = personification of knowledge
  47. Clarity in defining objectives Prioritize objectives Which is the more effective = individual or collaborative decison making? WHY? Moyenne des résultats individuels= Average individual results Meilleur résultat individuel= Best individual result Résultat du groupe après discussion= after discussion group result
  48. Two Key intelligence topics - Staying alive Going to the spaceship PRIORITIZE OBJECTIVES You sort out the items with these two objectives in mind
  49. We need to share a common goal…
  50. In this model, knowledge follows a cycle in which implicit knowledge is 'extracted' to become explicit knowledge, and explicit knowledge is 're-internalized' into implicit knowledge 4 stages in the process Tacit to Tacit (Socialization) This process focuses on tacit to tacit knowledge linking. New knowledge is created by using the process of interactions, observing, discussing, analyzing, spending time together or living in same environment. Traditional apprenticeship, where apprentices learn the tacit knowledge needed in their craft through hands-on experience, rather than from written manuals or textbooks Organizations gain new knowledge from outside its boundary also like interacting with customers, suppliers and stake holders. The socialization is also known as converting new knowledge through shared experiences. For example, meetings and brainstorm can support this kind of interaction. Externalization This process focuses on tacit to explicit knowledge linking. It helps in creating new knowledge as tacit knowledge became collective group knowledge. This process we can say that knowledge is crystallized. The process of externalization is often driven by metaphor analogy and models (=> simulation & game). E.G. Nonaka… Quality circles are formed in manufacturing sectors where workman put their learning and experience they have to improve or solve the process related problems. LLW AAR Writing things When tacit knowledge is made explicit, knowledge is crystallized, thus allowing it to be shared by others, and it becomes the basis of new knowledge. Concept creation in new product development is an example of this conversion process   Combination => Explicit to Explicit Combination is a process where knowledge transforms from explicit knowledge to explicit knowledge. The finance department collects all financial reports from each departments and makes a consolidated annual financial performance report. Creative use of database to get business report, sorting, adding , categorizing are some examples of combination process. Explicit knowledge is collected from inside or outside the organisation and then combined, edited or processed to form new knowledge. The new explicit knowledge is then disseminated among the members of the organization Internalization => Explicit to tacit By internalization explicit knowledge is shared across the organization. When this explicit knowledge is read or practiced by individuals then it becomes tacit. Organizations provide training programs for its employees at different stages of their working with the company. By reading these training manuals and documents employees internalize the tacit knowledge and try to create new knowledge after the internalization process. Explicit=>(training) tacit=>tacit=>explicit NOW a little exercise to LEARN BY EXPERIENCE First read this article from HBR (explicit K) Try to sum up it / sort the main ideas (explicit => tacit / internalize) Try to use the SECI model to analyse your organization (tacit knowledge creation) For each stage of the SECI model try to find precise examples in your organization => write them (to learn you have to act) When you have finished share your ideas in your team of 3 or 4 (socialization / tacit=>tacit) => each in turn explains what he has done Then try to organize your ideas, try to prioritize questions to build proposals to help knowledge creation in your organization (externalization) => write individually your proposals If you have made mistakes, if you want to complete your writings do it => write all you want ; it’ll be material you’ll use in the final assessment
  51. Exercise to train
  52. Metaphor is a figure of speech which makes an implicit, implied or hidden comparison between two things that are unrelated but share some common characteristics. In other words, a resemblance of two contradictory or different objects is made based on a single or some common characteristics. “He is the black sheep of the family” is a metaphor because he is not a sheep and is not even black. You can compare a beautiful girl to a flower Nonaka: two ideas in one expression, a connection between two thingsdistantly related: THEORY OF AUTOMOBILE EVOLUTION A SMILING COMPUTER (Macintosh) Metaphor triggers the knowledge creation process because it spurs creativity Analogy: it’s more strutured than metaphor a comparison between two things, typically on the basis of their structure and for the purpose of explanation or clarification. drawing a comparison in order to show a similarity in some respect (computer and brain) an inference that if things agree in some respects they probably agree in others Just as a sword is the weapon of a warrior, a pen is the weapon of a writer. How a doctor diagnoses diseases is like how a detective investigates crimes. Life is like a box of chocolates. (Forest Gump) Canon needed disposable copier drum for its minicopier: Aluminium beer can (cost) / alumiium copier drum A symbol is a person or a concept that represents, stands for or suggests another idea, visual image, belief, action or material entity. Symbols take the form of words, sounds, gestures, ideas or visual images and are used to convey other ideas and beliefs. For example, a red octagon may be a symbol for "STOP". On a map, a blue line might represent a river. Numerals are symbols for numbers. Alphabetic letters may be symbols for sounds. Personal names are symbols representing individuals. A red rose may symbolize love and compassion. The variable x in a mathematical equation may symbolize the position of a particle in space.
  53. Metaphor is a figure of speech which makes an implicit, implied or hidden comparison between two things that are unrelated but share some common characteristics. In other words, a resemblance of two contradictory or different objects is made based on a single or some common characteristics. “He is the black sheep of the family” is a metaphor because he is not a sheep and is not even black. You can compare a beautiful girl to a flower Nonaka: two ideas in one expression, a connection between two things distantly related: THEORY OF AUTOMOBILE EVOLUTION A SMILING COMPUTER (Macintosh) Metaphor triggers the knowledge creation process because it spurs creativity Analogy: it’s more strutured than metaphor a comparison between two things, typically on the basis of their structure and for the purpose of explanation or clarification. drawing a comparison in order to show a similarity in some respect (computer and brain) an inference that if things agree in some respects they probably agree in others Just as a sword is the weapon of a warrior, a pen is the weapon of a writer. How a doctor diagnoses diseases is like how a detective investigates crimes. Life is like a box of chocolates. (Forest Gump) Canon needed disposable copier drum for its minicopier: Aluminium beer can (cost) / alumiium copier drum A symbol is a person or a concept that represents, stands for or suggests another idea, visual image, belief, action or material entity. Symbols take the form of words, sounds, gestures, ideas or visual images and are used to convey other ideas and beliefs. For example, a red octagon may be a symbol for "STOP". On a map, a blue line might represent a river. Numerals are symbols for numbers. Alphabetic letters may be symbols for sounds. Personal names are symbols representing individuals. A red rose may symbolize love and compassion. The variable x in a mathematical equation may symbolize the position of a particle in space.
  54. In this model, knowledge follows a cycle in which implicit knowledge is 'extracted' to become explicit knowledge, and explicit knowledge is 're-internalized' into implicit knowledge 4 stages in the process Tacit to Tacit (Socialization) This process focuses on tacit to tacit knowledge linking. New knowledge is created by using the process of interactions, observing, discussing, analyzing, spending time together or living in same environment. Traditional apprenticeship, where apprentices learn the tacit knowledge needed in their craft through hands-on experience, rather than from written manuals or textbooks Organizations gain new knowledge from outside its boundary also like interacting with customers, suppliers and stake holders. The socialization is also known as converting new knowledge through shared experiences. For example, meetings and brainstorm can support this kind of interaction. Externalization This process focuses on tacit to explicit knowledge linking. It helps in creating new knowledge as tacit knowledge became collective group knowledge. This process we can say that knowledge is crystallized. The process of externalization is often driven by metaphor analogy and models (=> simulation & game). E.G. Nonaka… Quality circles are formed in manufacturing sectors where workman put their learning and experience they have to improve or solve the process related problems. LLW AAR Writing things When tacit knowledge is made explicit, knowledge is crystallized, thus allowing it to be shared by others, and it becomes the basis of new knowledge. Concept creation in new product development is an example of this conversion process   Combination => Explicit to Explicit Combination is a process where knowledge transforms from explicit knowledge to explicit knowledge. The finance department collects all financial reports from each departments and makes a consolidated annual financial performance report. Creative use of database to get business report, sorting, adding , categorizing are some examples of combination process. Explicit knowledge is collected from inside or outside the organisation and then combined, edited or processed to form new knowledge. The new explicit knowledge is then disseminated among the members of the organization Internalization => Explicit to tacit By internalization explicit knowledge is shared across the organization. When this explicit knowledge is read or practiced by individuals then it becomes tacit. Organizations provide training programs for its employees at different stages of their working with the company. By reading these training manuals and documents employees internalize the tacit knowledge and try to create new knowledge after the internalization process. Explicit=>(training) tacit=>tacit=>explicit NOW a little exercise to LEARN BY EXPERIENCE First read this article from HBR (explicit K) Try to sum up it / sort the main ideas (explicit => tacit / internalize) Try to use the SECI model to analyse your organization (tacit knowledge creation) For each stage of the SECI model try to find precise examples in your organization => write them (to learn you have to act) When you have finished share your ideas in your team of 3 or 4 (socialization / tacit=>tacit) => each in turn explains what he has done Then try to organize your ideas, try to prioritize questions to build proposals to help knowledge creation in your organization (externalization) => write individually your proposals If you have made mistakes, if you want to complete your writings do it => write all you want ; it’ll be material you’ll use in the final assessment
  55. OUTSOURCING KNOWLEDGE CREATION There are a number of reasons for including external knowledge sources in internal innovation processes, including: • Economic/time restraints mean no internal resources are available to cover the knowledge domain • It does not make strategic sense to develop the knowledge internally. The knowledge base can be expanded externally through outsourcing. This involves buying in specific services, skills and expertise outwith the company’s core knowledge domain(s), and can include both routine tasks and specific tasks that can only be accomplished by appropriate experts or knowledge holders. It also involves enlisting the support of external partners to establish and/or develop knowledge domains relevant to the company. First you have to ask yourself : does this knowledge already exist in the organization? Examples… Consulting firm in management, in creativity, in marketing => but very often the knwoledge is inside The company thinks very often that knowledge is elsewhere while it’s within people of the company but it’s tacit… One need to ask 635 The technique involves 6 participants who sit in a group and are supervised by a moderator. Each participant thinks up 3 ideas every 5 minutes. The ideas are written down on a worksheet and passed on to the next participant. The participant reads the ideas and uses them as inspiration for more ideas. Participants are encouraged to draw on others' ideas for inspiration, thus stimulating the creative process. After 6 rounds in 30 minutes the group has thought up a total of 108 ideas.
  56. People take the time You ask a question : how to improve sales and eveybody write an idea on a sticky note You put the note on the board and you sort it Sort of the ideas Sticky notes
  57. INTERNET: MINDOMO…
  58. This is not simply a matter of pleasant place…
  59. Storytelling TED conference the start of tim harford conference about WW2 Nonaka’s article telling stories… Using narrative in the reasoning process Storytelling plays an important role in reasoning processes and in convincing others. In meetings, the managers preferred stories to abstract arguments or statistical measures. When situations are complex, narrative allows the managers to involve more context. Using narrative to build a shared vision… Steve Jobs Macintosh (a computer which smiles at you...) Metaphor is a figure of speech which makes an implicit, implied or hidden comparison between two things that are unrelated but share some common characteristics. In other words, a resemblance of two contradictory or different objects is made based on a single or some common characteristics. “He is the black sheep of the family” is a metaphor because he is not a sheep and is not even black. You can compare a beautiful girl to a flower Nonaka: two ideas in one expression, a connection between two thingsdistantly related: THEORY OF AUTOMOBILE EVOLUTION A SMILING COMPUTER (Macintosh) Metaphor triggers the knowledge creation process because it spurs creativity Analogy: it’s more strutured than metaphor a comparison between two things, typically on the basis of their structure and for the purpose of explanation or clarification. drawing a comparison in order to show a similarity in some respect (computer and brain) an inference that if things agree in some respects they probably agree in others Just as a sword is the weapon of a warrior, a pen is the weapon of a writer. How a doctor diagnoses diseases is like how a detective investigates crimes. Life is like a box of chocolates. (Forest Gump) Canon needed disposable copier drum for its minicopier: Aluminium beer can (cost) / alumiium copier drum A symbol is a person or a concept that represents, stands for or suggests another idea, visual image, belief, action or material entity. Symbols take the form of words, sounds, gestures, ideas or visual images and are used to convey other ideas and beliefs. For example, a red octagon may be a symbol for "STOP". On a map, a blue line might represent a river. Numerals are symbols for numbers. Alphabetic letters may be symbols for sounds. Personal names are symbols representing individuals. A red rose may symbolize love and compassion. The variable x in a mathematical equation may symbolize the position of a particle in space. A figure of speech is a word or phrase that has a meaning something different than its literal meaning. It can be a metaphor or simile that is designed to further explain a concept.
  60. It is not possible to transfer experience through communication and/or documentation and information processes, all that can be transferred is a description of what was experienced and any insights gained. Experiential knowledge can only be created through the process of experiential learning and not through transfer processes. The transfer of experience is a special form of knowledge transfer and, as part of a corporate knowledge management strategy, has two basic aims: Firstly, the transfer of experience should provide individual employees with a broader spectrum of decision-making options and possible courses of action in business situations. This avoids unnecessary effort and repeated learning through "trial and error". Secondly, the transfer of experience supports individual and organisational learning processes and helps to build up individual expertise and develop the company’s capacity to learn. Two basic strategies play a role in the transfer of experience: A codification strategy (EXPLICIT) attempts to document the parts of experiential knowledge that can be made explicit (i.e. can be written down), thus detaching it from the individual employee and making it available to others in a codified form (Fig.22). Other employees who encounter similar situations can refer to and apply these documented learning experiences (e.g. Lessons Learned Reports) whenever appropriate without direct contact to the expert. A personalisation strategy, on the other hand, focuses on transferring experience through direct contact (Fig. 22). The intention here is to encourage additional tacit knowledge transfer through processes of communication and mutual observation. To ensure that these contacts occur systematically, and are not just left to chance, a company must know what expertise its employees have. E-mails, project documents, minutes, reports, interviews, etc. contain good indications of what could be included in expert profiles. The three levels indicated in Figure 21 serve as the basis for the analysis, design and development of the transfer of experience in a company. Transfer of experience will always begin and end at the individual level. In codification strategies, the organisational level represents the repository and distribution source for documented learning experiences, whereas in personalisation strategies it provides the necessary tools (e.g. expert profiles) for identifying colleagues and/or experts with the experience sought. The team level not only delivers the required context for the transfer of experience (e.g. projects), it also acts as an important link between the individual and organisational levels (e.g. Communities of Practice or Lessons Learned Workshops).
  61. Need of a computer based social network SKILL DIRECTORY
  62. CoPs exist in real life, such as in a lunch room at work, in a field setting, on a factory floor, or elsewhere in the environment, but members of CoPs do not have to be co-located. ------------ YOU ARE A COP => GOOGLE+ it’s now mandatory to join… since you wille xperiment what it is (you have to be active) You can create cop in your enterprise to share ideas/informations… You can start it like a brainstorming exercise… : how to improve sales, conquer new markets…
  63. They form a “virtual community of practice” (VCoP) when they collaborate online, such as within discussion boards and newsgroups, or a ‘‘mobile community of practice’’ (MCoP) when members communicate with one another via mobile phones and participate in community work on the go. => TWITTER inside the company with a simple hashtag Communities of practice are not new phenomena: this type of learning practice has existed for as long as people have been learning and sharing their experiences through storytelling. ORIGIN Since the publication of "Situated Learning: Legitimate Peripheral Participation" (Lave & Wenger 1991), communities of practice have been the focus of attention, first as a theory of learning and later as part of the field of knowledge management. Lave, Jean; Wenger, Etienne (1991). Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press EXAMPLE A famous example of a community of practice within an organization is that which developed around the Xerox customer service representatives who repaired the machines in the field (Brown & Duguid 2000). The Xerox reps began exchanging tips and tricks over informal meetings over breakfast or lunch and eventually Xerox saw the value of these interactions and created the Eureka project to allow these interactions to be shared across the global network of representatives. The Eureka database has been estimated to have saved the corporation $100 million. Xerox came up with Eureka, an online knowledge-sharing system designed to help its service engineers with time-consuming and tough-to-tackle repair problems. Communities of practice compared to functional or project teams Collaboration constellations differ in various ways. Some are under organizational control (e.g., teams, see below) others, like CoPs, are self-organized or under the control of individuals. No control For examples of how these and other collaboration types vary in terms of their temporal or boundary focus and the basis of their members’ relationships, see Kietzmann et al. (Kietzmann et al. 2013). A project team differs from a community of practice in several significant ways (McDermott, 1999). A project team is driven by deliverables with shared goals, milestones and results. A project team meets to share and exchange information and experiences just as the community of practice does, but team membership is defined by task. A project team typically has designated members who remain consistent in their roles during the project. A project team is dissolved once its mission is accomplished. By contrast, A community of practice is often organically created, with as many objectives as members of that community. Community membership is defined by the knowledge of the members. CoP membership changes and members may take on new roles within the community as interests and needs arise. A community of practice can exist as long as the members believe they have something to contribute to it, or gain from it. EUREKA Eureka's story begins in France in the mid-1990s, when Xerox customers there were reporting some of the lowest satisfaction rates on the planet. PARC scientists spent six months riding around with service engineers, observing how they worked, what their frustrations were, and what type of information they needed. The scientists also learned that the engineers needed desperately to share their knowledge. "Service engineers love to talk about how they figured out really nasty problems," says Kiki France-Parry, Xerox's manager of Global Service Net, the business unit responsible for Eureka's ongoing development. "Eureka has provided a very public and useful forum for that." Since piloting the system in France in 1996, Xerox has launched Eureka in 71 countries and has made it available to the company's entire corps of service engineers. The results have beat expectations. The system currently stores about 50,000 product fixes. Last year alone, it helped solve 350,000 service problems and saved Xerox approximately $15 million in parts and labor.
  64. Communities of practice and knowledge management[edit] Wasko and Faraj (2000) describe three kinds of knowledge: "knowledge as object", "knowledge embedded within individuals", and "knowledge embedded in a community". Communities of Practice have become associated with finding, sharing, transferring, and archiving knowledge, as well as making explicit "expertise", or tacit knowledge. Tacit knowledge is considered to be those valuable context-based experiences that cannot easily be captured, codified and stored (Davenport & Prusak 2000). Becauseknowledge management is seen "primarily as a problem of capturing, organizing, and retrieving information, evoking notions of databases, documents, query languages, and data mining" (Thomas, Kellogg & Erickson 2001), the community of practice, collectively and individually, is considered a rich potential source of helpful information in the form of actual experiences; in other words, best practices. Thus, for knowledge management, a community of practice is one source of content and context that if codified, documented and archived can be accessed for later use. WHY / FORCTOR OF SUCCESS Members of communities of practice are thought to be more efficient and effective conduits of information and experiences. While organizations tend to provide manuals to meet the training needs of their employees, CoPs help foster the process of storytelling among colleagues which, in turn, helps them strengthen their skills on the job. (Brown & Duguid 1991) Studies have shown that workers spend a third of their time looking for information and are five times more likely to turn to a co-worker rather than an explicit source of information (book, manual, or database) (Davenport & Prusak 2000). Time is saved by conferring with members of a CoP. Members of the community have tacit knowledge which can be difficult to store and retrieve outside. For example, one person can share the best way to handle a situation based on his experiences, which may enable the other person to avoid mistakes and shorten the learning curve. In a CoP, members can openly discuss and brainstorm about a project, which can lead to new capabilities. The type of information that is shared and learned in a CoP is boundless (Dalkir 2005). Duguid (2005) clarifies the difference between tacit knowledge, or knowing how, and explicit knowledge, or knowing what. Performing optimally in a job requires being able to convert theory into practice. Communities of practice help the individual bridge the gap between knowing what and knowing how. (Duguid 2005) As members of communities of practice, individuals report increased communication with people (professionals, interested parties, hobbyists), less dependence on geographic proximity, and the generation of new knowledge. (Ardichvilli, Page & Wentling 2003) Motivation[edit] Motivation to share knowledge is critical to success in communities of practice. Studies show that members are motivated to become active participants in a CoP when they view knowledge as meant for the public good, a moral obligation and/or as a community interest (Ardichvilli, Page & Wentling 2003). Members of a community of practice can also be motivated to participate by using methods such as tangible returns (promotion, raises or bonuses), intangible returns (reputation, self-esteem) and community interest (exchange of practice related knowledge, interaction).
  65. What makes a community of practice succeed depends on the purpose and objective of the community as well as the interests and resources of the members of that community. Wenger identified seven actions that could be taken in order to cultivate communities of practice: 1) Design the community to evolve naturally - Because the nature of a Community of Practice is dynamic, in that the interests, goals, and members are subject to change, CoP forums should be designed to support shifts in focus. 2) Create opportunities for open dialog within and with outside perspectives - While the members and their knowledge are the CoP's most valuable resource, it is also beneficial to look outside of the CoP to understand the different possibilities for achieving their learning goals. 3) Welcome and allow different levels of participation - Wenger identifies 3 main levels of participation. 1) The core group who participate intensely in the community through discussions and projects. This group typically takes on leadership roles in guiding the group 2) The active group who attend and participate regularly, but not to the level of the leaders. 3) The peripheral group who, while they are passive participants in the community, still learn from their level of involvement. Wenger notes the third group typically represents the majority of the community. 4) Develop both public and private community spaces - While CoPs typically operate in public spaces where all members share, discuss and explore ideas, they should also offer private exchanges. Different members of the CoP could coordinate relationships among members and resources in an individualized approach based on specific needs. 5) Focus on the value of the community - CoPs should create opportunities for participants to explicitly discuss the value and productivity of their participation in the group. 6) Combine familiarity and excitement - CoPs should offer the expected learning opportunities as part of their structure, and opportunities for members to shape their learning experience together by brainstorming and examining the conventional and radical wisdom related to their topic. 7) Find and nurture a regular rhythm for the community - CoPs should coordinate a thriving cycle of activities and events that allow for the members to regularly meet, reflect, and evolve. The rhythm, or pace, should maintain an anticipated level of engagement to sustain the vibrancy of the community, yet not be so fast-paced that it becomes unwieldy and overwhelming in its intensity. (Wenger, McDermott & Snyder 2002)
  66. A Lessons Learned Workshop gives team members an opportunity to present and discuss their individual points of view. It also encourages individual learning (personal measures) and organisational development (recommendations). The method described below is a useful way of discussing and transferring experiences with a group of around 30 participants. The aim is to enable effective and efficient transfer of experience in one day. Insight should be gained into the following issues: What was done well in the project? What could have been improved? What would be the ideal situation for points that could have been improved? What would I personally do differently in the next project? What should the organisation do differently in the next project? The most important stages in this procedure are: • Defining the relevant issues (Fig.23) • The Lessons Learned Workshop (Fig.24) • Processing and applying the results If a one-day workshop is planned, it makes good sense to define the relevant issues in advance in a smaller group (e.g. project managers, sub- project managers, quality managers, ...). Examples of possible issues are given in Fig. 23. Defining the issues in advance will steer the workshop strongly in a particular direction. This restriction will prevent other issues identified by the participants during the workshop from being discussed. If such issues are to be included, then it makes sense not to define the issues in advance, but rather to do so with the whole group at the beginning of the workshop. This will double the time required for the workshop. This shows the importance of including experienced project team members in the definition of issues.
  67. The most important stages in this procedure are: • Defining the relevant issues (Fig.23) • The Lessons Learned Workshop (Fig.24) • Processing and applying the results If a one-day workshop is planned, it makes good sense to define the relevant issues in advance in a smaller group (e.g. project managers, sub- project managers, quality managers, ...). Examples of possible issues are given in Fig. 23. Defining the issues in advance will steer the workshop strongly in a particular direction. This restriction will prevent other issues identified by the participants during the workshop from being discussed. If such issues are to be included, then it makes sense not to define the issues in advance, but rather to do so with the whole group at the beginning of the workshop. This will double the time required for the workshop. This shows the importance of including experienced project team members in the definition of issues.
  68. The most important stages in a workshop of this kind are: Background: The introductory session should include clear and detailed presentations of the project (from start to finish). In this way, participants will be reminded of what actually went on during the project. Emphasis should be placed on early events, since these are more likely to have been forgotten in the meantime. Cluster building: The input from the brainstorming sessions is collected and sorted into subject areas. A key term is defined for each subject area (cluster) that best describes its content. This abstraction simplifies subsequent work with the individual clusters. Lessons learned: An ideal target situation is defined for each issue where improvement was considered necessary. Each participant then notes what he or she could do in his or her individual project roles to ensure this ideal target situation is achieved. These are summarised to produce a list of recommendations for the organisation. Although one of the goals is obviously individual learning on the part of the workshop participants, other colleagues not directly involved in the workshop or project should also be able to profit from any lessons learned. After the workshop, it is vital that any insights and proposed measures are implemented appropriately. For this to happen, the results and knowledge must be passed on in a suitable form to the appropriate places or bodies to initiate organisational learning. The insights gained in a Lessons Learned Workshop can have long-term effects on the organisation, for example, through: EXPLICIT K • Introduction of new training measures/ programmes • Corrections/additions to project and quality handbooks • Presentation of results to the Board and management • Publication in the Intranet. ----- diapo suivante / next slide is a more precise time schedule for a Lessons Learned Workshop This method of transferring experience includes elements of both codification and personalisation strategies, whereby the focus is on codification. Consequently, it strives to ensure that lessons learned are transferred through information and documentation processes between experts and problem solvers. It is also advantageous to include selected (inexperienced) employees as participants in the workshop, since they will learn from direct (face- to-face) communication with experts (personalisation strategy).
  69. Place: Physical = an office, Virtual = a social network Mental = shared culture and objectives
  70. To sum up and visualize a theorical process It’s a model It’s a simplification of reality (prendre une carte de Saigon) => the map is not the territory Do not mix up the map with the territory… It’s sometime what experts do... A part of reality is not the reality...
  71. Knowledge starts with the individual… Learning process by sharing knowledge
  72. Anyone who has spent time in an organization knows that dysfunctional behavior abounds. => everybody knows it but nothing change Conflict is frequently avoided or pushed underground rather than dealt with openly. At the same time, the same arguments often burst out again and again, almost verbatim. People nod their heads in agreement in meetings, and then rush out of the room to voice complaints to sympathetic ears in private. Worst of all, when people are asked if things will ever change, they throw up their hands in despair. They feel like victims trapped in an asylum. And people often are trapped. But they are not trapped by some oppressive regime or organizational structure that has been imposed on them. They are not victims. In fact, people themselves are responsible for making the status quo so resistant to change. We are trapped by our own behavior. Researchers and practitioners have often reflected on these things, but there is a puzzle. On the one hand, there is substantial agreement that these traps are counterproductive to effective performance. On the other hand, there is almost no focus on how organizational traps can be prevented or reduced. How to ? => Meet Chris Argyris Chris Argyris (July 16, 1923 – November 16, 2013[1]) was an American business theorist AND practionner, Professor Emeritus at Harvard Business School, Organizations need to learn to adapt To do so people need to learn how they behave How do people behave? Chris Argyris and Donald Schön are regarded by many as the seminal thinkers on the formation of the learning organisation. Argyris and Schon's work over the past twenty years has been concerned with examining conscious and unconscious reasoning processes. ---------------------- It is based on the belief that people are designers of action.  They design action in order to achieve intended consequences and monitor to learn if their actions are effective. In other words, Argyris and Schon (1974) assert that people hold maps in their heads about how to plan, implement and review their actions.  They further assert that few people are aware that the maps they use to take action are not the theories they explicitly espouse.  Also, even fewer people are aware of the maps or theories they do use (Argyris, 1980). To clarify, this is not merely the difference between what people say and do.  Argyris and Schon suggest that there is a theory consistent with what people say and a theory consistent with what they do.  Therefore the distinction is not between "theory and action but between two different "theories of action" (Argyris, Putnam & McLain Smith, 1985, p.82).  Hence the concepts Espoused theory and Theory-in-use:
  73. Argyris and Schön (1996) observed that within an organisational context individuals tend to promote one set of behaviours, and use another set. In explaining this disparity, Argyris and Schön  defined two kinds of theory of action: espoused theories and theories-in-use. values we express / values we use « Theories » because there is thought behind An EXAMPLE from Argyris' (1987, p93) research may serve to clarify this distinction.  When asked about how he would deal with a disagreement with a client, a management consultant responded that he would First, discussing to try to understand the disagreement, then negotiate with the client to resolve the disagreement, This represents his espoused theory (or the theory behind what he says) which is of joint control of the problem.  A tape recording of the consultant in such a situation however, revealed that he actually advocated his own point of view and dismissed the client's.  This indicated his theory-in-use (or the theory behind what he did), which more closely approximates his unilateral control of the problem and a rejection of valid information exchange. EXERCISE What values are driving us/YOU? Take a sheet of paper and write your values, your espoused theory Loyalty Transparency Openness open-mindedness Able to listen Friendly Commited Courageous And now be very very very honest: is your theory in use / the way you do things reflects these values? / it’s for your eyes only… write it YES/NO If you are saying yes, you propably are lying to yourselves… because sometimes we are not aware of how we act… we don’t think about value but to put it simply we only want to do our work quickly… This raises the question, if people are unaware of the theories that drive their action (Theories-in-use), then how can they effectively manage their behaviour?  Argyris (1980) suggests that effectiveness results from developing congruence between Theory-in-use and Espoused theory. The models and conceptualisations developed by Argyris and Schon are for the purpose of helping people to be able to make more informed choices about the action they design and implement.  To this end they have developed models which seek to explain the processes which create and maintain people's theory-in-use. To sum up the point: a quote from A&S
  74. Argyris & Donald Schön, Organizational Learning: A Theory of Action Perspective (Addison-Wesley, 1978) The theory’s foundation is that all organisational learning involves detecting and correcting error. When an error is detected and corrected and the organisation is then able to carry on where it had left off, or go on to achieve its original goals, that ‘error-detection-and-correction process’ is termed single-loop learning.  Single-loop learning, then, focuses principally on accomplishing existing goals, and solving familiar problems. It works very well when errors can be corrected whilst keeping things in the organisation largely constant. Argyris and Schön liken it to a thermostat that turns the heat on or off according to a predictable and familiar variable; the room temperature.  By contrast, double-loop learning involves error correction where things are not so predictable, namely ‘the modification of an organization’s underlying norms, policies and objectives’. Whilst single-loop learning is dealt with regularly and efficiently by most organisations, double-loop learning is far harder to adopt. To illustrate the concept, Argyris and Schön describe a hypothetical industrial firm which, in order to remain competitive, has set up a new research and development department and encouraged it to generate new consumer products which the firm will manufacture in place of the intermediate products upon which it has relied for many years. The consequent shifts in production processes, marketing, advertising and distribution, as well as in the entire image of the firm to staff and general public alike, are immense. All this conflicts strongly with the ‘corporate norm’ firmly established in the company; that represented by stability and predictability (ROUTINES). In this example, the establishment of the R&D department is the ‘error’ which must be fixed. Single-loop processes are useless, as nothing here is familiar or normal or predictable. For double-loop learning to work in such a situation, Argyris and Schön explain that the first step is to recognise the conflict between corporate norm and radical change. The next step is to examine this conflict in order to realise that the error will not be corrected ‘by doing better what they already know’. Chris Argyris looks to move people from a Model I to a Model II orientation and practice – one that fosters double-loop learning. He suggests that most people, when asked, will espouse Model II.
  75. Argyris & Donald Schön, Organizational Learning: A Theory of Action Perspective (Addison-Wesley, 1978) The theory’s foundation is that all organisational learning involves detecting and correcting error. Not very original (model 1 & 2) When an error is detected and corrected and the organisation is then able to carry on where it had left off, or go on to achieve its original goals, that ‘error-detection-and-correction process’ is termed single-loop learning. Single-loop learning, then, focuses principally on accomplishing existing goals, and solving familiar problems. It works very well when errors can be corrected whilst keeping things in the organisation largely constant. Argyris and Schön liken it to a thermostat that turns the heat on or off according to a predictable and familiar variable; the room temperature. By contrast, double-loop learning involves error correction where things are not so predictable, namely ‘the modification of an organization’s underlying norms, policies and objectives’.[3] Whilst single-loop learning is dealt with regularly and efficiently by most organisations, double-loop learning is far harder to adopt. To illustrate the concept, Argyris and Schön describe a hypothetical industrial firm which, in order to remain competitive, has set up a new research and development department and encouraged it to generate new consumer products which the firm will manufacture in place of the intermediate products upon which it has relied for many years. The consequent shifts in production processes, marketing, advertising and distribution, as well as in the entire image of the firm to staff and general public alike, are immense. All this conflicts strongly with the ‘corporate norm’ firmly established in the company; that represented by stability and predictability (ROUTINES). In this example, the establishment of the R&D department is the ‘error’ which must be fixed. Single-loop processes are useless, as nothing here is familiar or normal or predictable. For double-loop learning to work in such a situation, Argyris and Schön explain that the first step is to recognise the conflict between corporate norm and radical change. The next step is to examine this conflict in order to realise that the error will not be corrected ‘by doing better what they already know’. Chris Argyris looks to move people from a Model I to a Model II orientation and practice – one that fosters double-loop learning. He suggests that most people, when asked, will espouse Model II.
  76. Almost everyone participating in Argyris and Schön’s original research, when at risk of embarrassment or threat (endangered), could be seen as having adopted a theory-in-use that Argyris and Schön term Model I. This is a form of behaviours learnt early on in life and which is supported by a set of virtues widely held within society and within organisations. But Model I isn’t bad… For example virtues associated to model I These virtues include: caring, help and support: give people approval and praise, tell people what you think will make them feel good about themselves, reduce their feelings of hurt – by saying how much you care, and if possible agreeing with them that other people have behaved improperly respect for others: defer to others when they are talking and do not confront their reasoning honesty: tell no lies, and/or tell others all you think and feel strength: advocate your own position and hold it in the face of attack from others. Feeling vulnerable is a sign of weakness. integrity: stick to your principles, values and beliefs. Behaviours associated with Model I include: The governing Values of Model I are: / Primary Strategies are: Argyris (1980) suggests that (as mentioned previously) the primary action strategy of Model I is: unilateral control of the environment and task, and unilateral protection of self and others.  The underlying strategy is control over others.  (taylorism) Such control inhibits communication and can produce defensiveness.  Defensiveness is a mechanism used in order to protect the individual.  Model I theory-in-use informs individuals how to design and use defences unilaterally, whether to protect themselves or others, eg.  "I couldn't tell him the truth, it would hurt him too much". « I could tell that this meeting is useless because it was not prepared » The assertion that Model I is predominantly defensive has another ramification.  Acting defensively can be viewed as moving away from something, usually some truth about ourselves. In order to protect themselves individuals must distort reality.  Such distortion is usually coupled with defences which are designed to keep themselves and others unaware of their defensive reaction (Argyris, 1980).  The more people expose their thoughts and feelings the more vulnerable they become to the reactions of others.  This is particularly true if these others are programmed with Model I theory-in-use and are seeking to maximise winning. The assertion that Model I is predominantly defensive has another ramification.  Acting defensively can be viewed as moving away from something, usually some truth about ourselves.  If our actions are driven by moving away from something then our actions are controlled and defined by whatever it is we are moving away from, not by us and what we would like to be moving towards.  Therefore our potential for growth and learning is seriously impaired.  If my behaviour is driven by my not wanting to be seen as incompetent, this may lead me to hide things from myself and others, in order to avoid feelings of incompetence.  For example, if my behaviour is driven by wanting to be competent, honest evaluation of my behaviour by myself and others would be welcome and useful. In summary, Model I has been identified as a grouping of characteristics which inhibit double-loop learning.  Model I is seen as being predominantly defensive and competitive, and therefore unlikely to allow an honest evaluation of the actor's motives and strategies, and less likely to lead to growth.  Defensiveness protects individuals from discovering embarrassing truths about their incongruent or less-than-perfect behaviour and intentions.  The actor further protects herself by reinforcing conditions such as ambiguity and inconsistency which help to further mask their incongruence from themselves and others.  Becoming aware of this incongruence is difficult, as is doing something about it.  According to Argyris and Schon (1974) this is due to the strength of the socialisation to Model I, and the fact that the prevailing culture in most systems is Model I.  An added complication is that anyone trying to inform them of the incongruence is likely to use Model I behaviour to do so, and therefore trigger a defensive reaction (Dick and Dalmau, 1990). Therefore, Model I theories-in-use are likely to inhibit double-loop learning for the following reasons.  Model I is characterised by unilateral control and protection, and maximising winning.  In order to maintain these, the actor is often involved in distortion of the facts, attributions and evaluations, and face-saving.  Doing such things is not something we would readily admit we involve ourselves in.  Therefore, in order to live with ourselves we put in place defences which hamper our discovery of the truth about ourselves.  If we are unwilling to admit to our motives and intentions we are hardly in a position to evaluate them.  As evaluating our governing values (which may be equated with intentions) is what characterises double-loop learning, Model I theories-in-use may be seen as inhibiting this process. Despite all the evidence which suggests that peoples' theory-in-use is consistent with Model I, Argyris has found that most people hold espoused theories which are inconsistent with Model I.  Most people in fact, espouse Model II, according to Argyris.  The defining characteristics of Model II are summarised in Table 2.
  77. Covert attribution : eg « he is a career-minded person » ; « he has no strategic vision » ; « he’s not motivated »
  78. To sum up Model I
  79. We apply Model I automatically because we become skilled at it from an early age. Because we are skilled at it, and the better at it we become the more averse to learning we are, Argyris and Schön call this skilled incompetence. If we are operating in Model I and are asked why we behaved in such-and-such a way, we tend to justify our actions by referring to our good intentions: the desire not to hurt other people’s feelings, the wish to advocate a position in accord with our values, and so on. If probed more deeply we will blame the situation we are in on other people, attributing to them negative attributes and motives, for example, their inability to handle the truth or readiness to play political games. Although hidden from us, the disparity between our theories-in-use and our theories of action tend to be apparent to those we interact with. Do they draw our attention to this? Generally speaking, no. This is because they too have adopted a Model I theory-in-use: they too wish to avoid hurting our feelings and want us to save face. They in turn attribute to us an inability to handle honest feedback or a lack of willingness to work cooperatively with them. In this situation both participants engage in what Argyris and Schön call bypass and cover up. Moreover, they make the bypass undiscussable, and they make that undiscussability itself undiscussable. This set of activities is known as an organisational defensive routine (ODR). Because ODRs are pervasive, individuals tend either not to notice them or to feel powerless to change them. They can see that they inhibit organisational effectiveness, yet challenging them requires the courage to risk making the situation more uncomfortable. Unchallenged ODRs lead to further fancy footwork, as Argyris and Schön call it, as people get to know the ‘way we do things round here’ and find ways around this. This in turn leads to what they call a state of organisational malaise whose general symptoms include hopelessness, cynicism, distancing and blaming others. Specific symptoms are: - seeking and finding fault with the organisation, without accepting responsibility for correcting it - accentuating the negative and de-emphasising the positive - espousing values that everyone knows are not implementable but acting as if they are. The following overall sequence: skilled incompetence leads to ODRs of bypass and cover up, fancy footwork, organisational malaise, mediocre performance is called an organisational defensive pattern (ODP), and the reasoning at its heart is known as defensive reasoning. Argyris and Schön contrast this with productive reasoning, a way of thinking and talking which enables us to test the validity of our own and others’ theories. To engage in productive reasoning we need to adopt a new theory-in-use, called Model II.
  80. Model II is not the OPPOSITE of Model I, since we still need to be able to draw on the behaviours and virtues of Model I. We simply need to choose more judiciously and awarely when to use or be guided by them. As with Model I, there is a set of corresponding virtues that support Model II behaviours: help and support: increase others’ capacity to confront their own ideas, to face their unsurfaced assumptions, biases and fears, by acting in this way towards them. respect for others: attribute to other people a high capacity for self reflection and self examination – without becoming so upset they lose their effectiveness and sense of self respect and choice.  strength: combine advocacy with inquiry and self-reflection. Feeling vulnerable during inquiry is a sign of strength. honesty: encourage self and others to say what they know ( having tested assumptions and attributions) and yet fear to say. integrity: advocate principles, values and beliefs in a way that invites inquiry into them and encourages others to do the same. No reason is offered for why most people espouse Model II, however it seems reasonable to assume that this is because Model II values are the more palatable in terms of the way we like to see our (Western) society.  Freedom of Information Acts, the Constitution, America's bill of Rights, all seem to be drawing heavily from Model II values.  Dick and Dalmau (1990) suggest that people often show a mix of Model I and Model II espoused theories.  This seems probable, as most people will readily admit to being driven to win at least in some situations.  Some professions in fact, are based almost entirely around the concept of winning and not losing, such as Law, sport and sales. The behaviour required to satisfy the governing values of Model II though, are not opposite to that of Model I.  For instance, the opposite of being highly controlling would be to relinquish control altogether.  This is not Model II behaviour because Model II suggest bilateral control.  Relinquishing control is still unilateral, but in the other direction.  Model II combines articulateness about one's goals and advocacy of one's own position, with an invitation to others to confront one's views.  It therefore produces an outcome which is based on the most complete and valid information possible.  Therefore, "Every significant Model II action is evaluated in terms of the degree to which it helps the individuals involved generate valid and useful information (including relevant feelings), solve the problem in a way that it remains solved, and do so without reducing the present level of problem solving effectiveness." (Argyris, 1976, p21-22) If we go back to the information chain model put forward by Dick and Dalmau (Figure 2), valid information has to do with expressing our beliefs, feelings, and intentions (the highlighted area in Figure 2). Given the above considerations, the consequences for learning should be an emphasis on double-loop learning, in which the basic assumptions behind views are confronted, hypotheses are tested publicly, and processes are disconfirmable, not self-sealing.  The end result should be increased effectiveness.
  81. To sum up: productive reasoning To be able to implement Model II we usually need to slow down our reasoning and increase our capacity for analysis and reflection, otherwise we unwittingly revert to Model I.
  82. Later research by Argyris[7] studied learning behaviours in US consultancies over a period of time and found that even the most experienced professionals did not learn as effectively as possible and that many suffered from ‘blockages’ in the learning process. Argyris deduced that removing these would improve the ability to learn both of these individuals, and subsequently of the entire organisation. The principal block on the consultants’ learning abilities is connected with their inability to learn from failure. Double-loop learning can involve making mistakes and examining why they happen. Yet most of the consultants studied were successful, motivated people who rarely made significant errors. Their highly competitive working environment meant however that many of the consultants became defensive when their mistakes were pointed out to them. Argyris notes many examples of consultants shifting blame away from themselves to either the client or the organisational set-up to avoid taking responsibility for their actions. This instinctive ‘defensive reasoning’ meant that few consultants actually took any time to look at the broader implications of the mistakes, which meant that many responded with single-loop, rather than double-loop learning. C Argyris, ‘Teaching Smart People How to Learn’, Harvard Business Review, (May–June 1991), p 100.
  83. The next step is to argue that individuals using Model I create Organizational I (O-I) learning systems. These are characterized by ‘defensiveness, self-fulfilling prophecies, self-fuelling processes, and escalating error’ (Argyris 1982: 8). O-I systems involve a web of feedback loops that ‘make organizational assumptions and behavioural routines self-reinforcing – inhibiting “detection and correction of error” and giving rise to mistrust, defensiveness and self-fulfilling prophecy’ (Edmondson and Moingeon 1999:161). In other words, if individuals in an organization make use of Model I learning the organization itself can begin to function in ways that act against its long-term interests. Indeed, in a very real sense systems can begin to malfunction. As Argyris and Schön (1996: 28) put it, ‘The actions we take to promote productive organizational learning actually inhibit deeper learning’. The challenge is, then, to create a rare phenomenon – an Organizational II (O-II) learning system. Here we come to the focus of organizational effort – the formulation and implementation of an intervention strategy. This, according to Argyris and Schön (1978: 220-1) involves the ‘interventionist’ in moving through six phases of work: Phase 1 Mapping the problem as clients see it. This includes the factors and relationships that define the problem, and the relationship with the living systems of the organization. Phase 2 The internalization of the map by clients. Through inquiry and confrontation the interventionists work with clients to develop a map for which clients can accept responsibility. However, it also needs to be comprehensive. Phase 3 Test the model. This involves looking at what ‘testable predictions’ can be derived from the map – and looking to practice and history to see if the predictions stand up. If they do not, the map has to be modified. Phase 4 Invent solutions to the problem and simulate them to explore their possible impact. Phase 5 Produce the intervention. Phase 6 Study the impact. This allows for the correction of errors as well as generating knowledge for future designs. If things work well under the conditions specified by the model, then the map is not disconfirmed.   By running through this sequence and attending to key criteria suggested by Model II, it is argued, organizational development is possible. The process entails looking for the maximum participation of clients, minimizing the risks of candid participation, starting where people want to begin (often with instrumental problems), and designing methods so that they value rationality and honesty. How are we to evaluate these models and line of argument? Third, and this might be my prejudice, I think we need to be distrustful of bipolar models like Model I and Model II. They tend to set up an ‘either-or’ orientation. They are useful as teaching or sensitizing devices, alerting us to different and important aspects of organizational life, but the area between the models (and beyond them) might well yield interesting alternatives. Fourth, the interventionist strategy is staged or phased – and this does bring with it some problems. Why should things operate in this order. Significantly, this does highlight a tension between Argyris’s orientation and that of Schön (1983). Schön in his later work on reflection-in-action draws on his pragmatist heritage (and especially the work of Dewey) and presents the making of theory-in-action and the expression of professional artistry in a far less linear fashion. Rather than there being phases, we could argue that intervention of this kind involves a number of elements or dimensions working at once. This said, the theorizing of theory-in-action, the educative power of the models, and the conceptualization of organizational learning have been, and continue to be, significant contributions to our appreciation of processes in organizations. The notion of ‘double-loop learning’ does help us to approach some of the more taken-for-granted aspects of organizations and experiences. It provides us with a way of naming a phenomenon (and problem), and a possible way of ‘learning our way out’ (Finger and Asún 2000). Argyris and Schön have made a significant contribution to pragmatic learning theory (following in the line of Dewey 1933; Lewin 1948, 1951; and Kolb 1984). First, by introducing the term ‘theory’ or ‘theory in action’, ‘they provide the function of abstract conceptualization (see experiential learning) ‘more structure and more coherence’ (Finger and Asún 2000: 45). Abstract conceptualization ‘becomes something one can analyze and work from’ (op. cit.). Second, through the notion of ‘learning-in-action’ Argyris and Schön rework the experiential learning cycle. Argyris argues that most advice from academic researchers, management consultants and executive development programmes, including those advising on Learning Organisations reinforces ODRs, and indeed that these advisors are often guilty of defensive routines themselves. In order to minimise the risk of advisors exacerbating the situation he suggests that if advice is to be implementable it must have three essential parts: - A causal theory (if you do x, then y will happen) - It must illustrate x at two levels: the action strategy – for example,  ‘combine advocacy with inquiry’ – and actual examples that illustrate the saying and doing - It should articulate the values that govern the suggestion – for example, if the governing value is ‘to win’ this should be expressed. If these governing values are made explicit then the advice can be awarely accepted or rejected by client organisations.
  84. Argyris and Schön (1974) present two models that describe different theories-in-use. Model I describes the behaviour of a group of professionals that they studied. It is based on the values of unilateral control of the situation, “winning” (proving oneself right), and suppression of any data that does not fit the actor’s assumptions. Such control can produce defensiveness that inhibits communication. Argyris and Schön believe that Model I describes features of a theory-in-use commonly employed by people in difficult situations. They go on to present Model II, “a model of theories-in-use that is free of the dysfunctionalities of model I” (page 85). The following summary draws on a presentation by Absolum (2006), based on the original models proposed by Argyris and Schön. Model II represents a consultative approach in which the participants in learning have “bilateral” control of the process, where winning is not being “right” but rather making better sense of the evidence, and where no dialogue is suppressed, even if it is painful. It requires people to pay close attention to their own behaviour and to the way they interact with others. Argyris and Schön suggest that “In general, Model-II learning tends to facilitate others’ learning, which in turn facilitates one’s own learning” (page 92). They say that in a Model II world, “research activities and learning activities would reinforce each other” (page 93).
  85. Argyris & Donald Schön, Organizational Learning: A Theory of Action Perspective (Addison-Wesley, 1978) The theory’s foundation is that all organisational learning involves detecting and correcting error. When an error is detected and corrected and the organisation is then able to carry on where it had left off, or go on to achieve its original goals, that ‘error-detection-and-correction process’ is termed single-loop learning.  Single-loop learning, then, focuses principally on accomplishing existing goals, and solving familiar problems. It works very well when errors can be corrected whilst keeping things in the organisation largely constant. Argyris and Schön liken it to a thermostat that turns the heat on or off according to a predictable and familiar variable; the room temperature.  By contrast, double-loop learning involves error correction where things are not so predictable, namely ‘the modification of an organization’s underlying norms, policies and objectives’. Whilst single-loop learning is dealt with regularly and efficiently by most organisations, double-loop learning is far harder to adopt. To illustrate the concept, Argyris and Schön describe a hypothetical industrial firm which, in order to remain competitive, has set up a new research and development department and encouraged it to generate new consumer products which the firm will manufacture in place of the intermediate products upon which it has relied for many years. The consequent shifts in production processes, marketing, advertising and distribution, as well as in the entire image of the firm to staff and general public alike, are immense. All this conflicts strongly with the ‘corporate norm’ firmly established in the company; that represented by stability and predictability (ROUTINES). In this example, the establishment of the R&D department is the ‘error’ which must be fixed. Single-loop processes are useless, as nothing here is familiar or normal or predictable. For double-loop learning to work in such a situation, Argyris and Schön explain that the first step is to recognise the conflict between corporate norm and radical change. The next step is to examine this conflict in order to realise that the error will not be corrected ‘by doing better what they already know’. Chris Argyris looks to move people from a Model I to a Model II orientation and practice – one that fosters double-loop learning. He suggests that most people, when asked, will espouse Model II.
  86. To be able to implement Model II we usually need to slow down our reasoning and increase our capacity for analysis and reflection, otherwise we unwittingly revert to Model I. One way of doing this is to use the approach introduced by Argyris and Schön, known as the Left hand column. Think of a work situation you are concerned about. Think of a conversation you either have had, or would like to have, with a colleague or someone else involved in that situation – someone you perceive as contributing to the problem. Divide a piece of paper into two columns. In the right hand column write down what you actually said or did  (or would like to say and do). In the left hand column write all the things you would be thinking in response to what the other person was (or would be) saying. Review the left hand column entries to see how often you fell into Model I thinking. For example, consider asking yourself the following questions: - How often did I attribute negative motives or evaluations to the other person’s performance and yet not want to tell them? - How confident am I that I attributed those negative motives etc correctly? If I use the ladder of inference can I see that I have used data very selectively and added other beliefs that are not necessarily appropriate? - Did I advocate my own position firmly to the exclusion of the other person’s?
- Did I tell the other person that I care about his or her views while not truly being open to these? - Did I find a third party to blame for the overall situation, e.g. budget, the Government, and so on? Model II leads us to be able to reason productively rather than defensively and to: - strive to make premises and inferences explicit and clear - develop conclusions that are publicly testable - test them in ways that are independent of the logic used by the actor involved - while taking action, reflect and be aware of own thoughts and feelings - be clear about the position we are advocating and about any evaluations or attributions we make of others - check constantly for unrecognised gaps or inconsistencies and encourage others to do the same combine taking the initiative with being open to any constructive confrontation of own views, evaluations and attributions. A tool can be useful to think about how each of us assign meanings
  87. This is a model of how people process information and assign meaning. In other words: ‘how we make sense’. What the concept implies is that we begin with real data and experience. We then choose a set of selected data and experience that we pay attention to. To this selected data and experience we attach meaning, develop assumptions, come to conclusions, and finally develop beliefs. Beliefs then form the basis of our actions which create additional real data & experience.
  88. To much faith in models ; in probalilities
  89. IT’s COMFORTING We concentrate only on routine We don’t want to be aware of the unknown unknown Weather forecast You think the life/world is as controlled as the statistics in a casino. LUDIC FALLACY => economists One example given in the book is the following thought experiment. Two people are involved Dr. John who is regarded as a man of science and logical thinking Fat Tony who is regarded as a man who lives by his wits A third party asks them to "assume a fair coin is flipped 99 times, and each time it comes up heads. What are the odds that the 100th flip would also come up heads?" Dr. John says that the odds are not affected by the previous outcomes so the odds must still be 50:50. Fat Tony says that the odds of the coin coming up heads 99 times in a row are so low that the initial assumption that the coin had a 50:50 chance of coming up heads is most likely incorrect. "The coin gotta be loaded. It can't be a fair game." The ludic fallacy here is to assume that in real life the rules from the purely hypothetical model (where Dr. John is correct) apply. Would a reasonable person bet on black on a roulette table that has come up red 99 times in a row (especially as the reward for a correct guess is so low when compared with the probable odds that the game is fixed)?
  90. Kahneman uses heuristics to assert that System 1 thinking involves associating new information with existing patterns, or thoughts, rather than creating new patterns for each new experience. 23 + 44 + 67 Bias partiality prejudice = préjugé Sometime, very often actually system 1 takes the lead
  91. Weak signal : slow change Imperceptible changes No warning signals Agility…
  92. Remember VUCA World / system thinking Need to find the context and see… Being able to stand outside their own culture Competitive intelligence—analyzed information that gives you insight and competitive advantage—is a discipline that can be taught. This isn’t to say that the discipline is simple and easy to learn. The biggest challenge most managers face is that they are surrounded by smoke screens, rumors, and competitive distortions. Competitors create smoke screens all the time—and the marketplace helps them out with a glut of information and misinformation. Ru- mors (sometimes intentionally, sometimes unintentionally placed) course through markets, prompting managers to react inappropri- ately or to ignore danger signs altogether. Sometimes the artist’s impression can appear in a minute; other times, it can take weeks or months of intense data collection. Just recently, for example, the CEO of an old-line U.S. textile com- pany was concerned about an Asian competitor that was threaten- ing to produce low-cost knockoff products out of a plant it announced it would operate in Indonesia. None of the dozen in- dustry experts I spoke with could verify when the rival’s plant would begin operation. However, an analyst from my firm visited the proposed location a couple of weeks later and sent us back a picture of a goat grazing in a field. Thinking he sent this in error, we asked him if he had made a mistake. “No,” he responded, “this is the plant location. Based on what you see here, the company has not even begun to lay the foundation, let alone consider whether to begin production.” This one picture, this solid piece of data, the image of a goat grazing, led us to ask more precise questions, such as why the rival did not commission a contractor to build the plant. Was it short on funds? Did it run into a raft of government regulations? Or did a business shortfall delay the plant’s construction? The goat image was a doorway through which we began to explore other intelli- gence options.
  93. When the economy tanks as it did in the recent recession, that’s a strong signal that things have to change, and it’s hard to miss. But most of us in business have to deal most of the time with weak signals, or change that is happening in a far more subtle way. These changes can be cultural, like the increasing need to be social, spawning Facebook and a hundred others, or technological, like the explosion of mobile devices around the world. TOOL TO ANALYZE -SYSTEM THINKING -PORTER 5 FORCES the following triggers were outlined as weak signals which should not be overlooked in your efforts to think outside the box, or think in a new box: A changing value proposition. For example, if it’s getting harder to charge a price premium for the product you’re marketing, or others are offering your subscription service for free, it may be time to start thinking in a new box. Another example is seeing substitute versions of a product, like eBooks, for a low price displacing hardcover books. New unmet consumer or customer needs. Perhaps you own a consumer products store and see that following the introduction of the new iPad, there are no attractive protective cases for them yet available. Or you notice that people are getting overnight delivery from Amazon, but your retail store offers no home delivery options. The entry of new competitors and new suppliers. You are selling several successful computer video games, but notice more and more new ones popping up on smartphones. Or you notice that your line of high quality tools is being undercut by cheap knockoffs manufactured in other countries. The advent of new breakthrough technologies. You are still providing conventional digital wristwatches while a crowd-sourced new company is offering a high-tech new version that syncs with your smartphone. Or you are still delivering coupons via the local newspaper, while new entrants are loading them onto your loyalty card or smartphone. CELL PHONE/SMART PHONE Changes in your organization’s core performance metrics. For example, quarterly sales on one of your most important products suddenly decreases, or your inventory across a whole category has surged. If one metric changes, it may not be significant, but someone needs to monitor whole categories for fluctuations that may be a weak signal. Unfulfilled business and other potential opportunities. Sometimes you might be astonished to notice something that has not yet occurred, and therefore signals to you an opportunity, like new transportation alternatives. Taxi or bus companies are often slow to recognize a new popular travel location based on population shifts or resort communities. Broad disruptive events. Everyone notes macro changes, but the weak or secondary implications are often overlooked. Look hard for unanticipated consequences of events like new government regulations on financial processes, changes in environmental patterns, or sociological changes in other countries. Premonitions, anxieties, and/or intuitions. Weak signals may be even more subtle or insidious. Perhaps your assistant mentions that your phone has been ringing much less lately. Or you sense that some of your best people are getting bored. Such inklings and realizations can be valuable warnings of significant impending change. Higher rate of turnover or burnout in the company First responders are the winners. All weak signals need to be treated with a continuous innovation mindset and urgency, to stay competitive and current. Here is the recommended five-step approach to thinking in new boxes: Doubting everything you think you know. Probing the possible issues to fully understand what is happening. Divergent thinking to create many new boxes, concepts, and hypotheses. Convergence through testing and validating back to a small number of viable changes. Re-evaluating relentlessly for the agility to survive. New entrepreneurs are notoriously great at capitalizing on new opportunities, both weak and strong. But nurturing this ability after the first burst of creativity, to accomplish the necessary pivots, and keep from getting seduced by their own initial success, is a more rare commodity, even in the startup community. If you aren’t reacting to weak signals almost every day in this era of fast-paced change, then you are missing opportunities and falling behind. What new boxes are you implementing these days?
  94. Groupthink strangles good intelligence. It is the term used by large organizations to describe the process of drawing conclusions based on what everyone has grown to believe is true but may or may not be accurate. => MODEL I mental model A recent vivid example of groupthink and its damage to intel- ligence assessment came from the U.S. government’s decision to attack Iraq in early 2003. In July 2004, the Report on the U.S. Intel- ligence Community’s Prewar Intelligence Assessments on Iraq2 de- tailed a story of intelligence breakdowns that in many ways mirror the psychological stumbling blocks I have seen in companies over the last twenty-five years. The Senate’s Select Committee on Intel- ligence found a long list of causes of intelligence failure, including these: • “THE ‘GROUPTHINK’ DYNAMIC LED THE INTELLIGENCE COMMU- NITY . . . TO BOTH INTERPRET AMBIGUOUS EVIDENCE AS CONCLU- SIVELY INDICATIVE OF A WMD (WEAPONS OF MASS DESTRUCTION) PROGRAM AS WELL AS IGNORE OR MINIMIZE EVIDENCE THAT IRAQ DID NOT HAVE ACTIVE AND EXPANDING WEAPONS OF MASS DE- STRUCTION PROGRAM.” DENIAL Another mind-related intelligence barrier is denial. People tend to see what they wish to see. Denial and rationalization can turn clarity into a blurred vision of the real world. Often, manage- ment would rather believe in the blurred but comforting view of the competition they think exists rather than in the real image. For nearly a decade, Kodak, consumer photography’s standard bearer, failed to acknowledge that digital cameras were a real threat to its business. It had lost sales to a number of new digital entrants in the photography business, companies such as Hewlett- Packard, Epson, and Fuji. After nearly a decade of dragging its feet, management could deny no longer. In late 2003, the company ad- mitted it was not terrorism, a recession, or a decline in the travel business (all excuses presented to stock analysts in previous years) that put a severe crimp into film sales, but rather consumers’ rapid conversion to digital cameras. Denial definitely had a strong grip on Kodak. In January 2012, Kodak filed for Chapter 11 bankruptcy protection in the United States District Court for the Southern District of New York.[10][11][12] In February 2012, Kodak announced that it would cease making digital cameras, pocket video cameras and digital picture frames and focus on the corporate digital imaging market Denial definitely had a strong grip on Kodak. Contrast Kodak’s denial with Visa International’s willingness to explore the future and adjust its strategy to meet threatening changes brought on by the Internet, and you will see a stark differ- ence between Visa’s use of intelligence to shape strategy and tactics and sustain its brand and Kodak’s deer-in-the-headlights inaction. Visa International, like Kodak, had placed a large bet on a single product. With Kodak it was chemical-based film; with Visa it was its traditional plastic credit cards. Faced with a problem, Kodak chose to sit tight and wait, despite mounting evidence of digital photography’s very real threat. Visa’s management felt it could not sit still. It needed to know more about alternative Internet pay- ment systems that threatened its traditional credit card business and developed an early warning approach to track the threat if in- deed it became real. Visa used intelligence to realistically examine its potential futures. For each future, Visa developed a successful counterstrategy.
  95. Analytical Models The tools of the trade for competitive intelligence are analytical models. As a minimum, a good CI Professional should be proficient in at least eight to ten analytical models to cover the competitive intelligence universe. Additionally, we need to recognize that each issue or KIT (Key Intelligence Topic) will require a different set of analytical models. Therefore, you must have a broad range of analytical approaches at your disposal if you expect to be effective as a CI Professional. Once we match up the KIT to the appropriate analytical model, we can then collect information to feed our analysis. If you start collecting information before knowing which analytical model to use, you tend to waste time collecting the wrong types of information for your analysis. So make sure you understand your approach (use of analytical models) before collecting information. “But managing change also means anticipating it. By anticipation, we mean gaining insight into what is likely to occur and then positioning for that future. Anticipation means looking ahead to the needs of the global market and then lining up ahead of time the right resources, such as venture partners, cross-cultural employees, and sophisticated currency trading skills. Or it could mean forseeing the emergence of a new customer segment and developing the market channels to compete in it. Like reaction, anticipation is still defensive in that forces from outside of the firm, such as customers and competitors, are calling the shots. Anticipation, however, creates new opportunities and so is a better way to change.” – Competing on the Edge: Strategy as Structured Chaos by Shona L. Brown and Kathleen M. Eisenhardt If I had to point to one analytical model that is the most popular, it would be SWOT or Strengths, Weaknesses, Opportunities, and Threats. However, therein lies the problem – we should not always reach for the SWOT Model each time we have a Key Intelligence Topic (KIT). SWOT Analysis is useful when you need to understand your own competitive advantages in relation to the marketplace. However, if the KIT is related to your industry, then Porter’s Five Forces Model may be better. Or perhaps you need to understand the position of a competitor. In this case, Porter’s Four Corners Analysis may be more appropriate. If we look at evolutionary issues in the marketplace, product life cycle analysis would be appropriate. If you need to profile the competitor’s management, then psychological profiling may work. Therefore, it is very important to understand which analytical models are appropriate for different KIT’s. So don’t get addicted to SWOT every time you are confronted with a KIT.
  96. Peter M. Senge (1947- ) was named a ‘Strategist of the Century’ by the Journal of Business Strategy, one of 24 men and women who have ‘had the greatest impact on the way we conduct business today’ (September/October 1999). While he has studied how firms and organizations develop adaptive capabilities for many years at MIT (Massachusetts Institute of Technology), it was Peter Senge’s 1990 book The Fifth Discipline that brought him firmly into the limelight and popularized the concept of the ‘learning organization’. Since its publication, more than a million copies have been sold and in 1997, Harvard Business Review identified it as one of the seminal management books of the past 75 years. One aspect of this is Senge’s involvement in the Society for Organizational Learning (SoL), a Cambridge-based, non-profit membership organization. Peter Senge is its chair and co-founder. SoL is part of a ‘global community of corporations, researchers, and consultants’ dedicated to discovering, integrating, and implementing ‘theories and practices for the interdependent development of people and their institutions’. One of the interesting aspects of the Center (and linked to the theme of idealistic pragmatism) has been its ability to attract corporate sponsorship to fund pilot programmes that carry within them relatively idealistic concerns.
  97. Perhaps the most widely known of the books on Learning Organisations is Peter Senge’s The Fifth Discipline (1990) We are all learners: Kids: (First experiment was by chance: serendipity) he has given kids in a very poor village in india a computer with a wifi connexion. Kids (6-12) didn’t know english. One or two months laters he comes back and see that kids have learned english and learned to use internet!!! Neurobilogist / Brain: our brain is a learning machine made to be adaptative (and survive)
  98. VUCA => only those that are flexible, adaptive and productive will excel. For this to happen, it is argued, organizations need to ‘discover how to tap people’s commitment and capacity to learn at all levels’ (ibid.: 4). While all people have the capacity to learn, the structures in which they have to function are often not conducive to reflection and engagement. Furthermore, people may lack the tools and guiding ideas to make sense of the situations they face. Organizations that are continually expanding their capacity to create their future require a fundamental shift of mind among their members.
  99. The dimension that distinguishes learning from more traditional organizations is the mastery of certain basic disciplines or ‘component technologies’. The five that Peter Senge identifies are said to be converging to innovate learning organizations. They are: Systems thinking Personal mastery Mental models Building shared vision Team learning/DIALOGUE He adds to this recognition that people are agents, able to act upon the structures and systems of which they are a part. All the disciplines are, in this way, ‘concerned with a shift of mind from seeing parts to seeing wholes, from seeing people as helpless reactors to seeing them as active participants in shaping their reality, from reacting to the present to creating the future’ (Senge 1990: 69). It is to the disciplines that we will now turn.
  100. He adds to this recognition that people are agents, able to act upon the structures and systems of which they are a part. All the disciplines are, in this way, ‘concerned with a shift of mind from seeing parts to seeing wholes, from seeing people as helpless reactors to seeing them as active participants in shaping their reality, from reacting to the present to creating the future’ (Senge 1990: 69). It is to the disciplines that we will now turn. Systems thinking – the cornerstone of the learning organization A great virtue of Peter Senge’s work is the way in which he puts systems theory to work. The Fifth Discipline provides a good introduction to the basics and uses of such theory – and the way in which it can be brought together with other theoretical devices in order to make sense of organizational questions and issues. Systemic thinking is the conceptual cornerstone (‘The Fifth Discipline’) of his approach. It is the discipline that integrates the others, fusing them into a coherent body of theory and practice (ibid.: 12). Systems theory’s ability to comprehend and address the whole, and to examine the interrelationship between the parts provides, for Peter Senge, both the incentive and the means to integrate the disciplines. However, it is necessary to highlight one or two elements of his argument. First, while the basic tools of systems theory are fairly straightforward they can build into sophisticated models. Peter Senge argues that one of the key problems with much that is written about, and done in the name of management, is that rather simplistic frameworks are applied to what are complex systems. We tend to focus on the parts rather than seeing the whole, and to fail to see organization as a dynamic process. Thus, the argument runs, a better appreciation of systems will lead to more appropriate action. ‘We learn best from our experience, but we never directly experience the consequences of many of our most important decisions’, Peter Senge (1990: 23) argues with regard to organizations. We tend to think that cause and effect will be relatively near to one another. Thus when faced with a problem, it is the ‘solutions’ that are close by that we focus upon. Classically we look to actions that produce improvements in a relatively short time span. However, when viewed in systems terms short-term improvements often involve very significant long-term costs. For example, cutting back on research and design can bring very quick cost savings, but can severely damage the long-term viability of anorganization. Part of the problem is the nature of the feedback we receive. Some of the feedback will be reinforcing (or amplifying) – with small changes building on themselves. ‘Whatever movement occurs is amplified, producing more movement in the same direction. A small action snowballs, with more and more and still more of the same, resembling compound interest’ (Senge 1990: 81). Thus, we may cut our advertising budgets, see the benefits in terms of cost savings, and in turn further trim spending in this area. In the short run there may be little impact on people’s demands for our goods and services, but longer term the decline in visibility may have severe penalties. An appreciation of systems will lead to recognition of the use of, and problems with, such reinforcing feedback, and also an understanding of the place of balancing (or stabilizing) feedback. (See, also Kurt Lewin on feedback). A further key aspect of systems is the extent to which they inevitably involve delays – ‘interruptions in the flow of influence which make the consequences of an action occur gradually’ (ibid.: 90). Peter Senge (1990: 92) concludes:The systems viewpoint is generally oriented toward the long-term view. That’s why delays and feedback loops are so important. In the short term, you can often ignore them; they’re inconsequential. They only come back to haunt you in the long term. Peter Senge advocates the use of ‘systems maps’ – diagrams that show the key elements of systems and how they connect. However, people often have a problem ‘seeing’ systems, and it takes work to acquire the basic building blocks of systems theory, and to apply them to your organization. On the other hand, failure to understand system dynamics can lead us into ‘cycles of blaming and self-defense: the enemy is always out there, and problems are always caused by someone else’ Bolam and Deal 1997: 27; see, also, Senge 1990: 231).
  101. Systemic thinking is the conceptual cornerstone (‘The Fifth Discipline’) of his approach. It is the discipline that integrates the others, fusing them into a coherent body of theory and practice (ibid.: 12). Systems theory’s ability to comprehend and address the whole, and to examine the interrelationship between the parts provides, for Peter Senge, both the incentive and the means to integrate the disciplines. However, it is necessary to highlight one or two elements of his argument. First, while the basic tools of systems theory are fairly straightforward they can build into sophisticated models. Peter Senge argues that one of the key problems with much that is written about, and done in the name of management, is that rather simplistic frameworks are applied to what are complex systems. We tend to focus on the parts rather than seeing the whole, and to fail to see organization as a dynamic process. Thus, the argument runs, a better appreciation of systems will lead to more appropriate action. ‘We learn best from our experience, but we never directly experience the consequences of many of our most important decisions’, Peter Senge (1990: 23) argues with regard to organizations. We tend to think that cause and effect will be relatively near to one another. Thus when faced with a problem, it is the ‘solutions’ that are close by that we focus upon. Classically we look to actions that produce improvements in a relatively short time span. However, when viewed in systems terms short-term improvements often involve very significant long-term costs. For example, cutting back on research and design can bring very quick cost savings, but can severely damage the long-term viability of anorganization. Part of the problem is the nature of the feedback we receive. Some of the feedback will be reinforcing (or amplifying) – with small changes building on themselves. ‘Whatever movement occurs is amplified, producing more movement in the same direction. A small action snowballs, with more and more and still more of the same, resembling compound interest’ (Senge 1990: 81). Thus, we may cut our advertising budgets, see the benefits in terms of cost savings, and in turn further trim spending in this area. In the short run there may be little impact on people’s demands for our goods and services, but longer term the decline in visibility may have severe penalties. An appreciation of systems will lead to recognition of the use of, and problems with, such reinforcing feedback, and also an understanding of the place of balancing (or stabilizing) feedback. (See, also Kurt Lewin on feedback). A further key aspect of systems is the extent to which they inevitably involve delays – ‘interruptions in the flow of influence which make the consequences of an action occur gradually’ (ibid.: 90). Peter Senge (1990: 92) concludes:The systems viewpoint is generally oriented toward the long-term view. That’s why delays and feedback loops are so important. In the short term, you can often ignore them; they’re inconsequential. They only come back to haunt you in the long term. Emergence Associated with the idea of system is a principle called emergence. From the mutual interaction of the parts of a system there arise characteristics which can not be found as characteristic of any of the individual parts. Peter Senge advocates the use of ‘systems maps’ – diagrams that show the key elements of systems and how they connect. However, people often have a problem ‘seeing’ systems, and it takes work to acquire the basic building blocks of systems theory, and to apply them to your organization. On the other hand, failure to understand system dynamics can lead us into ‘cycles of blaming and self-defense: the enemy is always out there, and problems are always caused by someone else’ Bolam and Deal 1997: 27; see, also, Senge 1990: 231).
  102. Systemic thinking is the conceptual cornerstone (‘The Fifth Discipline’) of his approach. It is the discipline that integrates the others, fusing them into a coherent body of theory and practice (ibid.: 12). Systems theory’s ability to comprehend and address the whole, and to examine the interrelationship between the parts provides, for Peter Senge, both the incentive and the means to integrate the disciplines. However, it is necessary to highlight one or two elements of his argument. First, while the basic tools of systems theory are fairly straightforward they can build into sophisticated models. Peter Senge argues that one of the key problems with much that is written about, and done in the name of management, is that rather simplistic frameworks are applied to what are complex systems. We tend to focus on the parts rather than seeing the whole, and to fail to see organization as a dynamic process. Thus, the argument runs, a better appreciation of systems will lead to more appropriate action. ‘We learn best from our experience, but we never directly experience the consequences of many of our most important decisions’, Peter Senge (1990: 23) argues with regard to organizations. We tend to think that cause and effect will be relatively near to one another. Thus when faced with a problem, it is the ‘solutions’ that are close by that we focus upon. Classically we look to actions that produce improvements in a relatively short time span. However, when viewed in systems terms short-term improvements often involve very significant long-term costs. For example, cutting back on research and design can bring very quick cost savings, but can severely damage the long-term viability of anorganization. Part of the problem is the nature of the feedback we receive. Some of the feedback will be reinforcing (or amplifying) – with small changes building on themselves. ‘Whatever movement occurs is amplified, producing more movement in the same direction. A small action snowballs, with more and more and still more of the same, resembling compound interest’ (Senge 1990: 81). Thus, we may cut our advertising budgets, see the benefits in terms of cost savings, and in turn further trim spending in this area. In the short run there may be little impact on people’s demands for our goods and services, but longer term the decline in visibility may have severe penalties. An appreciation of systems will lead to recognition of the use of, and problems with, such reinforcing feedback, and also an understanding of the place of balancing (or stabilizing) feedback. (See, also Kurt Lewin on feedback). A further key aspect of systems is the extent to which they inevitably involve delays – ‘interruptions in the flow of influence which make the consequences of an action occur gradually’ (ibid.: 90). Peter Senge (1990: 92) concludes:The systems viewpoint is generally oriented toward the long-term view. That’s why delays and feedback loops are so important. In the short term, you can often ignore them; they’re inconsequential. They only come back to haunt you in the long term. Emergence Associated with the idea of system is a principle called emergence. From the mutual interaction of the parts of a system there arise characteristics which can not be found as characteristic of any of the individual parts. Peter Senge advocates the use of ‘systems maps’ – diagrams that show the key elements of systems and how they connect. However, people often have a problem ‘seeing’ systems, and it takes work to acquire the basic building blocks of systems theory, and to apply them to your organization. On the other hand, failure to understand system dynamics can lead us into ‘cycles of blaming and self-defense: the enemy is always out there, and problems are always caused by someone else’ Bolam and Deal 1997: 27; see, also, Senge 1990: 231).
  103. Systemic thinking is the conceptual cornerstone (‘The Fifth Discipline’) of his approach. It is the discipline that integrates the others, fusing them into a coherent body of theory and practice (ibid.: 12). Systems theory’s ability to comprehend and address the whole, and to examine the interrelationship between the parts provides, for Peter Senge, both the incentive and the means to integrate the disciplines. However, it is necessary to highlight one or two elements of his argument. First, while the basic tools of systems theory are fairly straightforward they can build into sophisticated models. Peter Senge argues that one of the key problems with much that is written about, and done in the name of management, is that rather simplistic frameworks are applied to what are complex systems. We tend to focus on the parts rather than seeing the whole, and to fail to see organization as a dynamic process. Thus, the argument runs, a better appreciation of systems will lead to more appropriate action. ‘We learn best from our experience, but we never directly experience the consequences of many of our most important decisions’, Peter Senge (1990: 23) argues with regard to organizations. We tend to think that cause and effect will be relatively near to one another. Thus when faced with a problem, it is the ‘solutions’ that are close by that we focus upon. Classically we look to actions that produce improvements in a relatively short time span. However, when viewed in systems terms short-term improvements often involve very significant long-term costs. For example, cutting back on research and design can bring very quick cost savings, but can severely damage the long-term viability of anorganization. Part of the problem is the nature of the feedback we receive. Some of the feedback will be reinforcing (or amplifying) – with small changes building on themselves. ‘Whatever movement occurs is amplified, producing more movement in the same direction. A small action snowballs, with more and more and still more of the same, resembling compound interest’ (Senge 1990: 81). Thus, we may cut our advertising budgets, see the benefits in terms of cost savings, and in turn further trim spending in this area. In the short run there may be little impact on people’s demands for our goods and services, but longer term the decline in visibility may have severe penalties. An appreciation of systems will lead to recognition of the use of, and problems with, such reinforcing feedback, and also an understanding of the place of balancing (or stabilizing) feedback. (See, also Kurt Lewin on feedback). A further key aspect of systems is the extent to which they inevitably involve delays – ‘interruptions in the flow of influence which make the consequences of an action occur gradually’ (ibid.: 90). Peter Senge (1990: 92) concludes:The systems viewpoint is generally oriented toward the long-term view. That’s why delays and feedback loops are so important. In the short term, you can often ignore them; they’re inconsequential. They only come back to haunt you in the long term. Emergence Associated with the idea of system is a principle called emergence. From the mutual interaction of the parts of a system there arise characteristics which can not be found as characteristic of any of the individual parts. Peter Senge advocates the use of ‘systems maps’ – diagrams that show the key elements of systems and how they connect. However, people often have a problem ‘seeing’ systems, and it takes work to acquire the basic building blocks of systems theory, and to apply them to your organization. On the other hand, failure to understand system dynamics can lead us into ‘cycles of blaming and self-defense: the enemy is always out there, and problems are always caused by someone else’ Bolam and Deal 1997: 27; see, also, Senge 1990: 231).
  104. Systemic thinking is the conceptual cornerstone (‘The Fifth Discipline’) of his approach. It is the discipline that integrates the others, fusing them into a coherent body of theory and practice (ibid.: 12). Systems theory’s ability to comprehend and address the whole, and to examine the interrelationship between the parts provides, for Peter Senge, both the incentive and the means to integrate the disciplines. ‘We learn best from our experience, but we never directly experience the consequences of many of our most important decisions’, EG: Peter Senge (1990: 23) argues with regard to organizations. We tend to think that cause and effect will be relatively near to one another. Thus when faced with a problem, it is the ‘solutions’ that are close by that we focus upon. Classically we look to actions that produce improvements in a relatively short time span. However, when viewed in systems terms short-term improvements often involve very significant long-term costs. For example, cutting back on research and design can bring very quick cost savings, but can severely damage the long-term viability of anorganization. Part of the problem is the nature of the feedback we receive. Some of the feedback will be reinforcing (or amplifying) – with small changes building on themselves. ‘Whatever movement occurs is amplified, producing more movement in the same direction. A small action snowballs, with more and more and still more of the same, resembling compound interest’ (Senge 1990: 81). Thus, we may cut our advertising budgets, see the benefits in terms of cost savings, and in turn further trim spending in this area. In the short run there may be little impact on people’s demands for our goods and services, but longer term the decline in visibility may have severe penalties. An appreciation of systems will lead to recognition of the use of, and problems with, such reinforcing feedback, and also an understanding of the place of balancing (or stabilizing) feedback. (See, also Kurt Lewin on feedback). A further key aspect of systems is the extent to which they inevitably involve delays – ‘interruptions in the flow of influence which make the consequences of an action occur gradually’ (ibid.: 90). Peter Senge (1990: 92) concludes:The systems viewpoint is generally oriented toward the long-term view. That’s why delays and feedback loops are so important. In the short term, you can often ignore them; they’re inconsequential. They only come back to haunt you in the long term. Emergence => intelligence (in the body) ; creativity ; chaos (in nature : storm) ; Associated with the idea of system is a principle called emergence. From the mutual interaction of the parts of a system there arise characteristics which can not be found as characteristic of any of the individual parts. Peter Senge advocates the use of ‘systems maps’ – diagrams that show the key elements of systems and how they connect. However, people often have a problem ‘seeing’ systems, and it takes work to acquire the basic building blocks of systems theory, and to apply them to your organization. On the other hand, failure to understand system dynamics can lead us into ‘cycles of blaming and self-defense: the enemy is always out there, and problems are always caused by someone else’ Bolam and Deal 1997: 27; see, also, Senge 1990: 231).
  105. Systems Muscular Energy distribution Social An organization as a system You need to draw map to understand system in particular reinforcing loop and balancing loop Reinforcing loop Balancing loop 5 forces de porter pour systémique… Reportage vidéo
  106. 1 An increase in Overtime brings with it an increase in Overtime Cost. As Overtime Cost increases there is an increased emphasis on cost which shows up as Cost Pressure. The Cost Pressure is interpreted by the management of project in such a way that it shows up as additional Schedule Pressure. This increased Schedule Pressure then leads to even more Overtime. Here we have but one more viscous reinforcing loop in which actions influence the overall effect to be just the opposite of what is desired. 2 Prolonged Overtime has a tendency to lead to Burnout which means Hiring must occur to replace or augment resources. Yet Hiring only serves to increase Cost Pressure also, creating another viscous reinforcing loop. Also, in an attempt to minimize Overtime Costs additional resources are hired. And, because of the time delays involved, Hiring only serves to increase Cost Pressure. We there for have another viscous reinforcing loop driving Cost Pressure to increase Schedule Pressure leading to more Overtime. Does it sound like things are going down hill fast?
  107. The core disciplines Alongside systems thinking, there stand four other ‘component technologies’ or disciplines. A ‘discipline’ is viewed by Peter Senge as a series of principles and practices that we study, master and integrate into our lives. --------------- The five disciplines can be approached at one of three levels: Practices: what you do. Principles: guiding ideas and insights. Essences: the state of being those with high levels of mastery in the discipline (Senge 1990: 373). Each discipline provides a vital dimension. Each is necessary to the others if organizations are to ‘learn’.
  108. People with a high level of personal mastery live in a continual learning mode. => ED, MOOC, KHAN ACADEMY
  109. Remember Argyris… LADDER OF INFERENCE In other words it means fostering openness / OPEN MINDED
  110. VUCA We come back to nonaka Nonaka P.3 It’s possible with a shared vision => «The key to this process is personal commitment, the employees’ sense of identity with the enterprise and its mission. » ; «  a shared understanding of what the company stand for, where it is going, what kind of world it wants to live in, and, most important, how to make that world a reality. » P.9 In a VUCA world « Senior managers give voice to a company’s future by articulating metaphors, symbols, and concepts that orient the knowledge-creating activities of employees. They do this by asking the questions, What are we trying to learn? What do we need to know? Where should we be going? Who are we? If the job of frontline employees is to know “what is,” then the job of senior executives is to know “what ought to be.” » ------------------------ Peter Senge starts from the position that if any one idea about leadership has inspired organizations for thousands of years, ‘it’s the capacity to hold a share picture of the future we seek to create’ (1990: 9). Such a vision has the power to be uplifting – and to encourage experimentation and innovation. Crucially, it is argued, it can also foster a sense of the long-term, something that is fundamental to the ‘fifth discipline’. Visions spread because of a reinforcing process. Increased clarity, enthusiasm and commitment rub off on others in the organization. ‘As people talk, the vision grows clearer. As it gets clearer, enthusiasm for its benefits grow’ (ibid.: 227). There are ‘limits to growth’ in this respect, but developing the sorts of mental models outlined above can significantly improve matters. Where organizations can transcend linear and grasp system thinking, there is the possibility of bringing vision to fruition/achievement
  111. Lessons learned workshop CoP => Xerox representatives DISCUSSION => argyris (model II) Such learning is viewed as ‘the process of aligning and developing the capacities of a team to create the results its members truly desire’ (Senge 1990: 236). It builds on personal mastery and shared vision – but these are not enough. People need to be able to act together. When teams learn together, Peter Senge suggests, not only can there be good results for the organization, members will grow more rapidly than could have occurred otherwise. The discipline of team learning starts with ‘dialogue’, the capacity of members of a team to suspend assumptions and enter into a genuine ‘thinking together’. To the Greeks dia-logos meant a free-flowing if meaning through a group, allowing the group to discover insights not attainable individually…. [It] also involves learning how to recognize the patterns of interaction in teams that undermine learning. (Senge 1990: 10) The notion of dialogue that flows through The Fifth Discipline => the group ‘becomes open to the flow of a larger intelligence’, and thought is approached largely as collective phenomenon). When dialogue is joined with systems thinking, Senge argues, there is the possibility of creating a language more suited for dealing with complexity, and of focusing on deep-seated structural issues and forces rather than being diverted by questions of personality and leadership style. Indeed, such is the emphasis on dialogue in his work that it could almost be put alongside systems thinking as a central feature of his approach.
  112. Companies’ priorities are overwhelmingly financial We can find very few organizations that come close to the combination of characteristics that he identifies with the learning organization. Within a capitalist system his vision of companies and organizations turning wholehearted to the cultivation of the learning of their members can only come into fruition in a limited number of instances. While those in charge of organizations will usually look in some way to the long-term growth and sustainability of their enterprise, they may not focus on developing the human resources that the organization houses. The focus may well be on enhancing brand recognition and status (Klein 2001); developing intellectual capital and knowledge (Leadbeater 2000); delivering product innovation; and ensuring that production and distribution costs are kept down. What is more, ‘the targets for profit are too high and time horizons too short’ (1995: xi). Such conditions are hardly conducive to building the sort of organization that Peter Senge proposes. Here the case against Senge is that within capitalist organizations, where the bottom line is profit, a fundamental concern with the learning and development of employees and associates is simply too idealistic. Yet there are some currents running in Peter Senge’s favour. The need to focus on knowledge generation within an increasingly globalized economy does bring us back in some important respects to the people who have to create intellectual capital. Problem of competencies The issue here is that the people to whom it is addressed do not have the disposition or theoretical tools to follow it through. the approach entails significant effort on the part of the practitioner. It also entails developing quite complicated mental models, and being able to apply and adapt these to different situations – often on the hoof. Classically, the approach involves a shift from product to process (and back again). The question then becomes whether many people in organizations can handle this.
  113. Peter Senge argues that learning organizations require a new view of leadership. He sees the traditional view of leaders (as special people who set the direction, make key decisions and energize the troops as deriving from a deeply individualistic and non-systemic worldview (Senge 1990: 340). At its centre the traditional view of leadership, ‘is based on assumptions of people’s powerlessness, their lack of personal vision and inability to master the forces of change, deficits which can be remedied only by a few great leaders’ (op. cit.). Against this traditional view he sets a ‘new’ view of leadership that centres on ‘subtler and more important tasks’
  114. In a learning organization, leaders are designers, stewards and teachers. They are responsible for building organizations were people continually expand their capabilities to understand complexity, clarify vision, and improve shared mental models – that is they are responsible for learning…. Learning organizations will remain a ‘good idea’… until people take a stand for building such organizations. Taking this stand is the first leadership act, the start of inspiring (literally ‘to breathe life into’) the vision of the learning organization. (Senge 1990: 340) Many of the qualities that Peter Senge discusses with regard to leading the learning organization can be found in the shared leadershipmodel (discussed elsewhere on these pages). For example, what Senge approaches as inspiration, can be approached as animation. Here we will look at the three aspects of leadership that he identifies – and link his discussion with some other writers on leadership Leader as designer. The functions of design are rarely visible, Peter Senge argues, yet no one has a more sweeping influence than the designer (1990: 341). The organization’s policies, strategies and ‘systems’ are key area of design, but leadership goes beyond this. Integrating the five component technologies is fundamental. However, the first task entails designing the governing ideas – the purpose, vision and core values by which people should live. Building a shared vision is crucial early on as it ‘fosters a long-term orientation and an imperative for learning’ (ibid.: 344). Other disciplines also need to be attended to, but just how they are to be approached is dependent upon the situation faced. In essence, ‘the leaders’ task is designing the learning processes whereby people throughout the organization can deal productively with the critical issues they face, and develop their mastery in the learning disciplines’ (ibid.: 345). Leader as steward. While the notion of leader as steward is, perhaps, most commonly associated with writers such as Peter Block (1993), Peter Senge has some interesting insights on this strand. His starting point was the ‘purpose stories’ that the managers he interviewed told about their organization. He came to realize that the managers were doing more than telling stories, they were relating the story: ‘the overarching explanation of why they do what they do, how their organization needs to evolve, and how that evolution is part of something larger’ (Senge 1990: 346). => Such purpose stories provide a single set of integrating ideas that give meaning to all aspects of the leader’s work – and not unexpectedly ‘the leader develops a unique relationship to his or her own personal vision. He or she becomes a steward of the vision’ (op. cit.). One of the important things to grasp here is that stewardship involves a commitment to, and responsibility for the vision, but it does not mean that the leader owns it. It is not their possession. Leaders are stewards of the vision, their task is to manage it for the benefit of others (hence the subtitle of Block’s book – ‘Choosing service over self-interest’). Leaders learn to see their vision as part of something larger. Purpose stories evolve as they are being told, ‘in fact, they are as a result of being told’ (Senge 1990: 351). Leaders have to learn to listen to other people’s vision and to change their own where necessary. Telling the story in this way allows others to be involved and to help develop a vision that is both individual and shared. Leader as teacher. Peter Senge starts here with Max de Pree’s (1990) injunction that the first responsibility of a leader is to define reality. While leaders may draw inspiration and spiritual reserves from their sense of stewardship, ‘much of the leverage leaders can actually exert lies in helping people achieve more accurate, more insightful and more empowering views of reality (Senge 1990: 353). Building on an existing ‘hierarchy of explanation’ leaders, Peter Senge argues, can influence people’s view of reality at four levels: events, patterns of behaviour, systemic structures and the ‘purpose story’. By and large most managers and leaders tend to focus on the first two of these levels (and under their influence organizations do likewise). Leaders in learning organizations attend to all four, ‘but focus predominantly on purpose and systemic structure. Moreover they “teach” people throughout the organization to do likewise’ (Senge 1993: 353). This allows them to see ‘the big picture’ and to appreciate the structural forces that condition behaviour. By attending to purpose, leaders can cultivate an understanding of what the organization (and its members) are seeking to become. One of the issues here is that leaders often have strengths in one or two of the areas but are unable, for example, to develop systemic understanding. A key to success is being able to conceptualize insights so that they become public knowledge, ‘open to challenge and further improvement’ (ibid.: 356). “Leader as teacher” is not about “teaching” people how to achieve their vision. It is about fostering learning, for everyone. Such leaders help people throughout the organization develop systemic understandings. Accepting this responsibility is the antidote to one of the most common downfalls of otherwise gifted teachers – losing their commitment to the truth. (Senge 1990: 356) Leaders have to create and manage creative tension – especially around the gap between vision and reality. Mastery of such tension allows for a fundamental shift. It enables the leader to see the truth in changing situations.
  115. Phronesis  In Book 6 of the Nicomachean Ethics, Aristotle distinguishes between two intellectual virtues which are sometimes translated as "wisdom": sophia and phronesis. Sophia (sometimes translated as "theoretical wisdom") is a combination of nous, the ability to discern reality, and epistēmē, a type of knowledge which is logically built up, and teachable, and which is sometimes equated with science. Sophia, in other words, involves reasoning concerning universal truths. Phronesis also combines a capability of rational thinking, with a type of knowledge. On the one hand it requires the capability to rationally consider actions which can deliver desired effects. Aristotle says that phronesis is not simply a skill (technē), however, as it involves not only the ability to decide how to achieve a certain end, but also the ability to reflect upon and determine good ends consistent with the aim of living well overall. Aristotle points out that although sophia is higher and more serious than phronesis, the highest pursuit of wisdom and happiness requires both, because phronesis facilitates sophia. He also associates phronesis with political ability.
  116. Phronesis  In Book 6 of the Nicomachean Ethics, Aristotle distinguishes between two intellectual virtues which are sometimes translated as "wisdom": sophia and phronesis. Sophia (sometimes translated as "theoretical wisdom") is a combination of nous, the ability to discern reality, and epistēmē, a type of knowledge which is logically built up, and teachable, and which is sometimes equated with science. Sophia, in other words, involves reasoning concerning universal truths. Phronesis also combines a capability of rational thinking, with a type of knowledge. On the one hand it requires the capability to rationally consider actions which can deliver desired effects. Aristotle says that phronesis is not simply a skill (technē), however, as it involves not only the ability to decide how to achieve a certain end, but also the ability to reflect upon and determine good ends consistent with the aim of living well overall. Aristotle points out that although sophia is higher and more serious than phronesis, the highest pursuit of wisdom and happiness requires both, because phronesis facilitates sophia. He also associates phronesis with political ability.
  117. Phronesis  In Book 6 of the Nicomachean Ethics, Aristotle distinguishes between two intellectual virtues which are sometimes translated as "wisdom": sophia and phronesis. Sophia (sometimes translated as "theoretical wisdom") is a combination of nous, the ability to discern reality, and epistēmē, a type of knowledge which is logically built up, and teachable, and which is sometimes equated with science. Sophia, in other words, involves reasoning concerning universal truths. Phronesis also combines a capability of rational thinking, with a type of knowledge. On the one hand it requires the capability to rationally consider actions which can deliver desired effects. Aristotle says that phronesis is not simply a skill (technē), however, as it involves not only the ability to decide how to achieve a certain end, but also the ability to reflect upon and determine good ends consistent with the aim of living well overall. Aristotle points out that although sophia is higher and more serious than phronesis, the highest pursuit of wisdom and happiness requires both, because phronesis facilitates sophia. He also associates phronesis with political ability.
  118. http://agilityconsulting.com/the-agile-imperative/ THE AGILE IMPERATIVE The Age of Agility is upon us.  Those not recognizing this reality are at great risk of “accelerated obsolescence”.   We call this The Agile Imperative and it also defines the approach we take in helping our clients develop and build capability with their leaders, teams and overall organizations.  It begins with the adoption of a core belief system followed by a progressive process building clarity, speed and adaptability as an on-going competitive advantage. Agility Core Belief System Our world will continue to move faster and get more volatile, uncertain, complex and ambiguous in the future … a lot more! Agility is not just nice to do … it is an imperative for your survival in a VUCA world. Your customers and your people are the highest priority. The organizational mindset must be Focused, Fast and Flexible fueled by excellence in the 5 Drivers of The Agile Model®. The Agile Culture involves trust, respect, transparency, inclusiveness, collaboration, accountability, optimism and enthusiasm. Operating systems will be guided by principles of speed, simplicity, reliability, synchronicity, fluidity and interconnectedness. Business agility is the ability of a business to adapt rapidly and cost efficiently in response to changes in the business environment. Business agility can be maintained by maintaining and adapting goods and services to meet customer demands, adjusting to the changes in a business environment and taking advantage of human resources.[1] Agility is a concept that incorporates the ideas of flexibility, balance, adaptability, and coordination under one umbrella. In a business context, agility typically refers to the ability of an organization to rapidly adapt to market and environmental changes in productive and cost-effective ways. The agile enterprise is an extension of this concept, referring to an organization that utilizes key principles of complex adaptive systems and complexity science to achieve success.[2] One can say that business agility is the outcome of Organizational intelligence. Overview[edit] The agile enterprise strives to make change a routine part of organizational life to reduce or eliminate the organizational trauma that paralyzes many businesses attempting to adapt to new markets and environments.[3] Because change is perpetual, the agile enterprise is able to nimbly adjust to and take advantage of emerging opportunities. The agile enterprise views itself as an integral component of a larger system whose activities produce a ripple effect of change both within the enterprise itself and the broader system.[4] One type of enterprise architecture that supports agility is a non-hierarchical organization without a single point of control.[5] Individuals function autonomously, constantly interacting with each other to define the vision and aims, maintain a common understanding of requirements and monitor the work that needs to be done. Roles and responsibilities are not predetermined but rather emerge from individuals’ self-organizing activities and are constantly in flux. Similarly, projects are generated everywhere in the enterprise, sometimes even from outside affiliates. Key decisions are made collaboratively, on the spot, and on the fly. Because of this, knowledge, power, and intelligence are spread through the enterprise, making it uniquely capable of quickly recovering and adapting to the loss of any key enterprise component. In business, projects can be complex with uncertain outcomes and goals that can change over time. Traditionally these issues were dealt with by planning experts that would attempt to pre-determine every possible detail prior to implementation; however, in many situations, even the most carefully thought out projects will be impossibly difficult to manage. Agile techniques, originating from the software development community, represent an alternative approach to the classic prescriptive planning approaches to management. The main focus of agile methods is to address the issues of complexity, uncertainty, and dynamic goals, by making planning and execution work in parallel rather than in sequence to eliminate unnecessary planning activity, and the resulting unnecessary work. Agile methods integrate planning with execution allowing an organization to "search" for an optimal ordering of work tasks and to adjust to changing requirements. The major causes of chaos on a project include incomplete understanding of project components, incomplete understanding of component interactions and changing requirements. Sometimes requirements change as a greater understanding of the project components unfolds over time. Requirements also change due to changing needs and wants of the stakeholders. The agile approach allows a team or organization of collective trust, competence and motivation to implement successful projects quickly by only focusing on a small set of details in any change iteration. This is in contrast to non-agile in which all the details necessary for completion are generally taken to be foreseeable and have equal priority inside of one large iteration. History[edit] The concept of "agility" as an attribute of business organizations arose in response to the requirements of the modern business to operate in predictable ways even in the face of extreme complexity. In particular, software development organizations have developed a specific set of techniques known as Agile Methods to address the problems of changing requirements, uncertain outcomes due to technological complexity, and uncertain system dynamics due to overall system complexity. Some of the ideas that have shaped thinking in the agile community arose from the studies of Complexity science and the notion of complex adaptive systems (CAS). As with complex adaptive systems, the outcomes or products of agile organizations such as software teams are inherently unpredictable yet will eventually form an identifiable pattern. Despite their unpredictability, agile enterprises are thought to be best positioned to take advantage of hypercompetitive external environments. Agile enterprises exist in corporate (e.g. W. L. Gore & Associates and Oticon), non-profit (e.g., Alcoholics Anonymous), community (e.g., Wikipedia, the Burning Man festival) and even terrorist (e.g. Al Qaeda) environments. Key topics in agile enterprise studies[edit] Comparing agile enterprises to complex systems [6][edit] Interactions, self-organizing, co-evolution, and the edge of chaos are concepts borrowed from complexity science that can help define some of the processes that take place within an agile enterprise. Interactions are exchanges among individuals etc. holding a common vision and possessing the necessary resources, behaviors, competence and experience in aggregate. They are an important driving force for agile enterprises, because new ideas, products, services, and solutions emerge from the multiple exchanges happening over time. The interactions themselves, rather than individuals or the external environment, are significant drivers of innovation and change in an agile enterprise. Self-organizing describes the spontaneous, unchoreographed, feedback-driven exchanges that are often found within agile enterprises. Vital initiatives within the agile enterprise are not always managed by one single person—rather all parties involved collectively make decisions without guidance or management from an outside source. The creativity and innovation that arises from this self-organizing process gives the agile enterprise an edge in developing (and redeveloping) products, services, and solutions for a hypercompetitive marketplace. Co-evolution is a key process through which the enterprise learns from experience and adapts. The agile enterprise is constantly evolving in concert with (and in reaction to) external environmental factors. Products and services are in a constant state of change, because, once launched, they encounter competitors’ products, regulators, suppliers, and customer responses that force adaptations. In one sense, nothing is ever completely “finished,” although this does not mean that nothing is ever made, produced, or launched. The edge of chaos is a borderline region that lies between complete anarchy or randomness and a state of punctuated equilibrium. The agile enterprise ideally operates in this region, needing the tension between constant change and the constraints that weaken change efforts to keep the organization perturbed enough for innovation and success. In other words, the edge of chaos is the space in which self-organizing and co-evolution flourish. Agile enterprise versus bureaucracy[edit] There are several key distinctions between the agile enterprise and the traditional bureaucratic organization. The most notable is the agile enterprise’s use of fluid role definitions that allow for dynamic decision making structures. Unlike the rigid hierarchies characterizing traditional bureaucracies, organizational structures within agile enterprises are more likely to fluidly adapt to changing business conditions into structures that support the current direction and any emergent competitive advantage.[7] Similarly, agile enterprises do not adhere to the concept of sustained competitive advantage that typifies the bureaucratic organization. Operating in hypercompetitive, continuously changing markets, agile enterprises pursue a series of temporary competitive advantages—capitalizing for a time on the strength of an idea, product, or service then readily discarding it when no longer tenable.[8] Lastly, the agile enterprise is populated with individuals pursuing serial incompetence[9]—they work hard to obtain a certain level of proficiency in one area but are driven to move on to the next “new” area to develop expertise. There are no “subject-matter experts” specializing for years in one topical area, as found typically in a traditional bureaucracy. Operating at the edge of chaos[edit] Although agile enterprises by definition include numerous, constantly co-evolving and moving parts, they do require some structure. The enterprise must develop specific structures (also called system constraints) to serve as a counterbalance to randomness and anarchy, keeping the enterprise optimally functioning on the edge of chaos. These structures—including a shared purpose or vision, resource management aids, reward systems, and shared operating platforms—often emerge from three key organizational processes: strategizing, organizing, and mobilizing.[10] Strategizing is an experimental process for the agile enterprise, in which individuals repeatedly generate ideas (exploration), identify ways to capitalize on ideas (exploitation), nimbly respond to environmental feedback (adaptation), and move on to the next idea (exit). Organizing is an ongoing activity to develop structures and communication methods that promote serial execution. It often includes defining a shared vision, as well as systems and platforms, that ground the enterprise. Mobilizing involves managing resources, ensuring the fluid movement of people between projects, and finding ways to enhance internal and external interactions. Typically, enterprise values, personal accountability, and motivational and reward systems are a key output of this process.
  119. The concept of "agility" as an attribute of business organizations arose in response to the requirements of the modern business to operate in predictable ways even in the face of extreme complexity. http://agilityconsulting.com/the-agile-imperative/ THE AGILE IMPERATIVE / VUCA The Age of Agility is upon us.  Those not recognizing this reality are at great risk of “accelerated obsolescence”.   We call this The Agile Imperative and it also defines the approach we take in helping our clients develop and build capability with their leaders, teams and overall organizations.  It begins with the adoption of a core belief system followed by a progressive process building clarity, speed and adaptability as an on-going competitive advantage. Agility Core Belief System Our world will continue to move faster and get more volatile, uncertain, complex and ambiguous in the future … a lot more! Agility is not just nice to do … it is an imperative for your survival in a VUCA world. Your customers and your people are the highest priority. The organizational mindset must be Focused, Fast and Flexible fueled by excellence in the 5 Drivers of The Agile Model®. The Agile Culture involves trust, respect, transparency, inclusiveness, collaboration, accountability, optimism and enthusiasm. Operating systems will be guided by principles of speed, simplicity, reliability, synchronicity, fluidity and interconnectedness. Business agility is the ability of a business to adapt rapidly and cost efficiently in response to changes in the business environment. => LO Business agility can be maintained by maintaining and adapting goods and services to meet customer demands, adjusting to the changes in a business environment and taking advantage of human resources. Agility is a concept that incorporates the ideas of flexibility, balance, adaptability, and coordination under one umbrella. In a business context, agility typically refers to the ability of an organization to rapidly adapt to market and environmental changes in productive and cost-effective ways. The agile enterprise is an extension of this concept, referring to an organization that utilizes key principles of complex adaptive systems and complexity science to achieve success.[2] One can say that business agility is the outcome of Organizational intelligence. Overview[edit] The agile enterprise strives to make change a routine part of organizational life to reduce or eliminate the organizational trauma that paralyzes many businesses attempting to adapt to new markets and environments.[3] Because change is perpetual, the agile enterprise is able to nimbly adjust to and take advantage of emerging opportunities. The agile enterprise views itself as an integral component of a larger system whose activities produce a ripple effect of change both within the enterprise itself and the broader system.[4] One type of enterprise architecture that supports agility is a non-hierarchical organization without a single point of control.[5] Individuals function autonomously, constantly interacting with each other to define the vision and aims, maintain a common understanding of requirements and monitor the work that needs to be done. Roles and responsibilities are not predetermined but rather emerge from individuals’ self-organizing activities and are constantly in flux. Similarly, projects are generated everywhere in the enterprise, sometimes even from outside affiliates. Key decisions are made collaboratively, on the spot, and on the fly. Because of this, knowledge, power, and intelligence are spread through the enterprise, making it uniquely capable of quickly recovering and adapting to the loss of any key enterprise component. In business, projects can be complex with uncertain outcomes and goals that can change over time. Traditionally these issues were dealt with by planning experts that would attempt to pre-determine every possible detail prior to implementation; however, in many situations, even the most carefully thought out projects will be impossibly difficult to manage. Agile techniques, originating from the software development community, represent an alternative approach to the classic prescriptive planning approaches to management. The main focus of agile methods is to address the issues of complexity, uncertainty, and dynamic goals, by making planning and execution work in parallel rather than in sequence to eliminate unnecessary planning activity, and the resulting unnecessary work. Agile methods integrate planning with execution allowing an organization to "search" for an optimal ordering of work tasks and to adjust to changing requirements. The major causes of chaos on a project include incomplete understanding of project components, incomplete understanding of component interactions and changing requirements. Sometimes requirements change as a greater understanding of the project components unfolds over time. Requirements also change due to changing needs and wants of the stakeholders. The agile approach allows a team or organization of collective trust, competence and motivation to implement successful projects quickly by only focusing on a small set of details in any change iteration. This is in contrast to non-agile in which all the details necessary for completion are generally taken to be foreseeable and have equal priority inside of one large iteration. History The concept of "agility" as an attribute of business organizations arose in response to the requirements of the modern business to operate in predictable ways even in the face of extreme complexity. In particular, software development organizations have developed a specific set of techniques known as Agile Methods to address the problems of changing requirements, uncertain outcomes due to technological complexity, and uncertain system dynamics due to overall system complexity. Some of the ideas that have shaped thinking in the agile community arose from the studies of Complexity science and the notion of complex adaptive systems (CAS). As with complex adaptive systems, the outcomes or products of agile organizations such as software teams are inherently unpredictable yet will eventually form an identifiable pattern. Despite their unpredictability, agile enterprises are thought to be best positioned to take advantage of hypercompetitive external environments. Agile enterprises exist in corporate (e.gW. L. Gore & Associates and Oticon), non-profit (e.g., Alcoholics Anonymous), community (e.g. Wikipedia, the Burning Man festival) and even terrorist (e.g. Al Qaeda) environments Key topics in agile enterprise studies[edit] Comparing agile enterprises to complex systems [6][edit] Interactions, self-organizing, co-evolution, and the edge of chaos are concepts borrowed from complexity science that can help define some of the processes that take place within an agile enterprise. Interactions are exchanges among individuals etc. holding a common vision and possessing the necessary resources, behaviors, competence and experience in aggregate. They are an important driving force for agile enterprises, because new ideas, products, services, and solutions emerge from the multiple exchanges happening over time. The interactions themselves, rather than individuals or the external environment, are significant drivers of innovation and change in an agile enterprise. Self-organizing describes the spontaneous, unchoreographed, feedback-driven exchanges that are often found within agile enterprises. Vital initiatives within the agile enterprise are not always managed by one single person—rather all parties involved collectively make decisions without guidance or management from an outside source. The creativity and innovation that arises from this self-organizing process gives the agile enterprise an edge in developing (and redeveloping) products, services, and solutions for a hypercompetitive marketplace. Co-evolution is a key process through which the enterprise learns from experience and adapts. The agile enterprise is constantly evolving in concert with (and in reaction to) external environmental factors. Products and services are in a constant state of change, because, once launched, they encounter competitors’ products, regulators, suppliers, and customer responses that force adaptations. In one sense, nothing is ever completely “finished,” although this does not mean that nothing is ever made, produced, or launched. The edge of chaos is a borderline region that lies between complete anarchy or randomness and a state of punctuated equilibrium. The agile enterprise ideally operates in this region, needing the tension between constant change and the constraints that weaken change efforts to keep the organization perturbed enough for innovation and success. In other words, the edge of chaos is the space in which self-organizing and co-evolution flourish. Agile enterprise versus bureaucracy[edit] There are several key distinctions between the agile enterprise and the traditional bureaucratic organization. The most notable is the agile enterprise’s use of fluid role definitions that allow for dynamic decision making structures. Unlike the rigid hierarchies characterizing traditional bureaucracies, organizational structures within agile enterprises are more likely to fluidly adapt to changing business conditions into structures that support the current direction and any emergent competitive advantage.[7] Similarly, agile enterprises do not adhere to the concept of sustained competitive advantage that typifies the bureaucratic organization. Operating in hypercompetitive, continuously changing markets, agile enterprises pursue a series of temporary competitive advantages—capitalizing for a time on the strength of an idea, product, or service then readily discarding it when no longer tenable.[8] Lastly, the agile enterprise is populated with individuals pursuing serial incompetence[9]—they work hard to obtain a certain level of proficiency in one area but are driven to move on to the next “new” area to develop expertise. There are no “subject-matter experts” specializing for years in one topical area, as found typically in a traditional bureaucracy. Operating at the edge of chaos[edit] Although agile enterprises by definition include numerous, constantly co-evolving and moving parts, they do require some structure. The enterprise must develop specific structures (also called system constraints) to serve as a counterbalance to randomness and anarchy, keeping the enterprise optimally functioning on the edge of chaos. These structures—including a shared purpose or vision, resource management aids, reward systems, and shared operating platforms—often emerge from three key organizational processes: strategizing, organizing, and mobilizing.[10] Strategizing is an experimental process for the agile enterprise, in which individuals repeatedly generate ideas (exploration), identify ways to capitalize on ideas (exploitation), nimbly respond to environmental feedback (adaptation), and move on to the next idea (exit). Organizing is an ongoing activity to develop structures and communication methods that promote serial execution. It often includes defining a shared vision, as well as systems and platforms, that ground the enterprise. Mobilizing involves managing resources, ensuring the fluid movement of people between projects, and finding ways to enhance internal and external interactions. Typically, enterprise values, personal accountability, and motivational and reward systems are a key output of this process.
  120. To sum up and visualize a theorical process It’s a model It’s a simplification of reality (prendre une carte de Saigon) => the map is not the territory Do not mix up the map with the territory… It’s sometime what experts do... A part of reality is not the reality...
  121. To sum up and visualize a theorical process It’s a model It’s a simplification of reality (prendre une carte de Saigon) => the map is not the territory Do not mix up the map with the territory… It’s sometime what experts do... A part of reality is not the reality...
  122. To sum up and visualize a theorical process It’s a model It’s a simplification of reality (prendre une carte de Saigon) => the map is not the territory Do not mix up the map with the territory… It’s sometime what experts do... A part of reality is not the reality...
  123. To sum up and visualize a theorical process It’s a model It’s a simplification of reality (prendre une carte de Saigon) => the map is not the territory Do not mix up the map with the territory… It’s sometime what experts do... A part of reality is not the reality...
  124. To sum up and visualize a theorical process It’s a model It’s a simplification of reality (prendre une carte de Saigon) => the map is not the territory Do not mix up the map with the territory… It’s sometime what experts do... A part of reality is not the reality...