Inteligência Competitiva

Delivering Intelligence
Through the Management of
Weak Signals

IQPC Conference
April 1st, 2008, Sao Paulo
Rainer Michaeli
Board Member dcif (Deutsches
Competitive Intelligence Forum)
Board Member SCIP (Society of
Competitive Intelligence
Professionals; 2003-2005)
Director Institute for Competitive
Intelligence (ICI)

Speaker Profile Rainer Michaeli
Education Intelligence Experience
Dipl.-Ing. Aeronautical Engineering Military OR studies
TU Braunschweig/University 500+ „Competitive Intelligence“
of York, GB projects for leading German and
MBA (INSEAD) France international companies
Professional Experience CI-Trainer for IIR, Euroforum,
Project- and Product Management Management Circle, DGI, EAP
DIEHL GmbH & Co KG (Ecole Européenne des Affaires,
Paris), SCIP
Key Account Manager
COMPUNET AG Associate professor at the
University of Applied Sciences
Darmstadt on „Competitive
Founder and owner of DIE DENKFABRIK,
Intelligence“ and „Dynamic Business
Advisory Services in Business and
Technology, since 1993 Strategies“
Board Member SCIP (Society of Various publications (including a
Competitive Intelligence Professionals) 630 page textbook; Top 3 Financial
2003-2005 Times Germany bestseller)
Board Member dcif (Deutsches Contact
Competitive Intelligence Forum)
Michaeli@competitive-intelligence.com
Director Institute for Competitive
Intelligence (ICI) since 2004
© Institute for Competitive Intelligence, Korngasse 9, DE-35510 Butzbach IQPC_Weak_Signals.PPT - Page 2

Remember?
Competitive situations do not have to be like this …
Bill‘s

… and do not have to end like this!


Agenda
What are “Weak Signals”?
The Weak Signal Process
Information Gathering
Sources
Diagnosis
Bayes Theorem
Pittfalls
Early Warning Case Study
Strategy Formulation
Awareness-Motivation-Capability Analysis
Summary
Questions & Answers


What is Competitive Intelligence?
The Academic Answer
” ... an analytical process which transforms disaggregated company,
industry and market data into actionable strategic knowledge about the
position, performance, capabilities and intentions of target companies”.
new CI cycle to feedback; questions
answer new CINs initiate new CI projects
advice

KNOWLEDGE
DATA

discuss
comment

Field operations & Intelligence "Gate- Intelligence Interest groups
secondary sources Expert keeper" Manager

Filter Integrate Analyze Dis- Exchange of
Scan Clarify Assess seminate comments
Condense Prioritize Decision-
Escalate Escalate making

What are Weak Signals?
In academic research "weak signals" may be understood as advanced, noisy
and socially situated indicators of change in trends and systems that constitute
raw informational material for enabling anticipatory action.
There is confusion about the definition of weak signal by various researchers
and consultants.
Sometimes it is referred as future oriented information, sometimes more
like emerging issues.
Within Strategic Early Warning the concept of “weak signals” (Ansoff,
1975) aims at early detection of signals which could lead to strategic
surprises and to an event which has the potential to jeopardise an
organization’s strategy.
Detecting “weak signals” is achieved by scanning the organizational
environment. The concept of environmental scanning (Aguilar,1967)
describes a process whereby the environment in which an organization
operates is systematically scanned for relevant information.


Weak Signals and Potential Applications
long-term

Early
Warning Industry
Structure
Analysis
Horizon

Issues Strategic Groups
Management in Industry
short-term

Rivalry between firms
Rivalry
Analysis1
weak strong
Signal Amplitude

1A-M-C: Awareness – Motivation - Capabilities


From Information to Intelligence
Any signal analysis combines indicators from various sources and aggregates
them into meaningful signals.
Signals are then analyzed an interpreted for impact on a company

Data Input Signals Analysis

Signals Event 1
Company
assessment
Products

Market Event 2
Marketing &
Sales Event 3
Competition

Production

Suppliers

Finance


Missed Strategic Signals …

Corporate Strategy
Board; Strategic
Intelligence (2000)

Agenda


How Are Weak Signals Managed? (1)
The ideal weak signal process has three phases.

Formulation
Information
Diagnosis of Response
Gathering
Strategy

Bear in mind that every industry has its specific signal characteristics
Set up your individual set of sources and diagnosis techniques!
Pragmatic approaches should consider cost-benefit ratios per signal process
Watch out for cognitive dissonances when processing and assessing signals!

How are Weak Signals Managed?
Phase 1 is characterised by the information gathering of “weak signals”, or
trends and issues. Detecting “weak signals” is achieved by scanning the
organizational environment. The concept of environmental scanning
(Aguilar,1967) describes a process whereby the environment in which an
organization operates is systematically scanned for relevant information. The
purpose is to identify early signals of possible environmental change and to
detect environmental change already underway.
The scanning itself relies primarily on examining various media sources,
the technique of content analysis (Nasbitt, 1982).
The scanning activity is complemented by monitoring trends and issues
that have already drawn attention.

Formulation
Information
Gathering
Strategy

Retrieved from "http://en.wikipedia.org/wiki/Strategic_early_warning_system"

Kit for the CI-Analyst
For meaningful signal analysis, we need to identify signals with powerful
characteristics! Ideally they have been tried out already
Methodologies to find meaningful signals
Bayes’ Theorem
(Structured) Brainstorming
System Dynamics/Analysis
Timeline Analysis (“Propagation”/Analogy)
Scenario Analysis (“signposts”)
Environmental Analysis (STEEP, etc)


Propagation of News/Issues in an Industry
Think about the propagation of news/issues in your industry. Information flows
from primary sources via media to secondary sources.
Track typical flows in your industry over time
How many people do know the news/issues at a given moment of time?
Try to set up networks at each of the typical propagation points

General Journals, Magazines
No. of sources aware of

Politicians
Consultants Hindsight Gurus
the news/issues

Expert’s Magazine’s

Expert’s discussion forums (conferences, blogs, ..)
Expert/Opinion Leader

Researcher forums (conferences, blogs, ..)
Researcher

© Institute for Competitive Intelligence, Korngasse 9, DE-35510 Butzbach
Time
IQPC_Weak_Signals.PPT - Page 13

How to Assess Signals?
List per issue potential signal as follows
Rank signals by sensitivity and specificity
Sensitivity: How good is the signal to indicate an upcoming event
Specificity: How good is the signal to not raise false alarms?

Indicator Name Sen- Speci- Costs to Lead time Source/Update
sitivity ficity monitor (expected) frequency
(per
month)
Competitor hires new 90% 70% 100 Euro 2 months Mr. Smith/
Marketing Agency monthly

Patents filled 60% 80% 200 Euro 18 months Ms. Realit/
quarterly

Domain name registered 30% 10% 5 Euro Any day Dr. Tube/weekly


Define Thresholds for Signals
Define for each indicator threshold interval
Within this interval the signal behaves normal
Once the boundaries are crossed the signal is „active“

Observed values

Tolerance interval (t)

Launch Time
Checkpoints

Develop and Maintain
Information Networks
Communities of practices are key to retrieving and analyzing signals from multiple sources

CI Analyst

+ =

Sensors


Organisation of the
Signal Retrival Process
Networks are key to success!
Continuous scanning of factors
signals and trends

Sources External Network
Brecht Schulz
Sources Meyer
Kong Müller

Sources
Sources
Scanning
Sources International Network Network Networks
Sources
Region1 Region2 Operating by issue
NN internal/external
Sources
Region3 Region4
Opportunity / Risk
Sources Monitoring
Sources NN Topic mapping
Topic analysis
Sources Sources Internal Network
Tech 1 Tech 1

Sources NN
Tech 1 Tech 1
Decision
Sources Focused Maker
Sources Projects Key
Intelligence
Questions


How to select „Sensors“ for
Weak Signals Community?
Internal Experts (technicians, scientists, marketers, sales reps, investor relation,
HR, etc) have several years of experience in their given discipline
Nominate experts in a formal selection process. Make sure they understand
role, assignment and incentives (if any)
External Experts (retirees, academics, consultants, representatives of
associations) have a standing relationship with the EWS team. Select
candidates for their technical expertise, market knowledge, industry experience)

Agenda


Exercise:
List Potential Signals in Your Industry

A O
B P
C Q
D R
E S
F T
G U
H V
I W
J X
K Y
L Z
M
N


Phase 2
1) In-depth analysis of the trend or issue, examining the core and the
various contexts of this phenomenon. The aim is to gain an impression of
the possible potential development of an issue or trend.
2) The second step has several objectives.
The attempt should be made to think creatively about how the particular trend
or issue could evolve.
The nature of the contexts needs to be examined in order to cluster several
trends or issues, thus providing an understanding of the mutual influences on
and of trends and issues.
It is important, due to the limited resources in any organization, to identify and
select those trends and issues that are particularly relevant.

Formulation
Information
Gathering
Strategy


The Signal Diagnosis Loop
Make sure to establish a rigid routine to manage signals!

Needs of the Impact
Users Reports

Check: Analysis:
Primary & Abnormalities? Escalation?
Secondary Discontinuities? DB Threats?
Data from Irregularities? Patterns?
multiple sources Emerging Trends? Clusters?

Standard
CI-Reports
DB - data base


Signal Analysis Basics:
The Bayes‘ Theorem
Properly understood, Bayes’ theorem is the fundamental law governing the
process of logical interference, of deciding what conclusions we can make and
the degree of confidence which we can make them, based on the totality of
relevant evidence available. The theorem of Bayes is the mathematical
equivalent of “logical” and “rational” thinking. It therefore possesses all the
power of logic itself.

One way to think about Bayes‘ theorem is that it provides a mechanism to update
prior probabilities when new information becomes available –
.... sounds like an blue-print for signal analysis, right?
Let‘s work through an example and learn how to apply the Bayes‘ Theorem

The Challenge
Boss: „Find out, whether our competitor ALPHA will launch a new product! No
rocket-engineering analysis, no fancy intelligence riddles, no mind games, just
your defendable assumption about the likelihood of their product launch. Isn‘t
that what I pay you for?”
What should you do?

...guessing?
... ask 5 experts?
Might end your CI career earlier than you desire ...

P (A)
yes
?%
market Luckily enough you remember Rev. Bayes,
entry some basic stats and .... this workshop

no
P (A)
?%

The Approach
Signal I:
P (A) ALPHA hires a new marketing agency
yes ?% Our HUMINT team learned that ALPHA is
dissatisfied with their existing agency;
market ALPHA’s marketing manager indicated in a
entry speech that ALPHA will never use their old
agency again for a major product launch;
no
?% however, they might continue to work
P (A) through the existing marketing agency under
new terms & conditions ...

Rather than trying to guesstimate the absolute probability P(market entry),
one can more accurately estimate the conditional probability of a market
entry, given that an indicator was observed, denoted as P(A|I)

P(A) is the probability of event A (here: market entry of ALPHA)
P (A) = P(not A) = 1-P(A), i.e. only two possible outcomes. The sum of all
possible outcomes must add up to 100%

How to determine the Entry Probability?
What your boss wants to know

P (A | I) Indicator Indicator
no “I-“ yes “I+“
P (I) market Yes -?
yes entry No -? (A-, I-)
(A-, I+)
Event no true
Hire new false positive
agency P (A | I) “A-“ negative
no market Yes -? “specificity“
P ( I) entry (A+, I-)
No - ? (A+, I+)
Event yes false
true positive
“A+“ negative
“sensitivity“
Indicator “I“ Event “A“

Decision Tree 2x2 table

P(A|I) ... probability of A given I (conditional probability)

The Solution: Bayesian Analysis
known
What we need to know
(CI analyst/expert knowledge)
P (A | I) P (A) P (I | A)
P (I) market Yes -? yes Hire new
yes entry No -? agency
Hire new market
agency P (A | I) entry P (I | A)
no market Yes -? Hire new
P ( I) entry no agency
No - ?
P (A)

“Indicator“ “Event“ “Event“ “Indicator“

Bayes Theorem is used to “flip” the left tree, i.e. to determine the
probability P that an event “A” occurs, when indicator “I” was
observed:
P(A) ⋅ P(I|A)
P(A|I) =
P(A) ⋅ P(I|A) + P( A ) ⋅ P(I|A )

Note!

What‘s the difference between
P(A|I) and P(I|A)?

Probability that event A (market Probability that indicator I (new
entry) will occur if indicator I (new marketing agency) will occur if event
marketing agency) was observed (market entry) will occur
- This is the fundamental question in -This should be known by experts!
any signal analysis! - Indicators will have a lead time,
otherwise they are not useful


Bayesian Analysis (2) - Prevalence
What do we need to know for the Bayesian Formula?
1) P(A) = ?
Probability that event “ALPHA market entry” will occur based only on the prior
information (i.e. NO ADDITIONAL INFORMATION / OBSERVATION
AVAILABLE – a dull world without CI), called the a priori probability
Note:
This might very often be a rough estimation or simply a 50/50 assumption
It could sometimes be based on track records of past behaviour: How many
times in the past did “Alpha” enter a new market once the opportunity was
given? Say in 3 out of 9 cases, i.e. we associate an empirically derived
probability of 33%.
Good idea to maintain a fact sheet of past events (time-line analysis) ...
P(A) is often called the “prevalence” of the event A

We take P(A) = 33% based on our track record of similar events


Bayesian Analysis (3) - Sensitivity
P(I|A) = ?
Probability that indicator I “hire a new marketing agency” will occur if event
“ALPHA market entry” will occur
Often called the “sensitivity” of an indicator (“how good is the indicator to
indicate an upcoming event”)
CI-analyst’s judgement: P(I|A) = 90% (i.e. a strong signal/high sensitivity)
How to generate such probabilities?
Human judgement (interview experts revealing relevant data; mind games)
Simulations (statistical/dynamic)
Experience of the CI Analyst
yes - P (I | A) = ? 90%
yes Hire new
agency 10%
no -? P ( I | A) = 1 − P (I | A)
market
entry yes -? P (I | A) = ?
Hire new
no agency
No- ? P ( I | A) = 1 − P (I | A )


Bayesian Analysis (4) - Specificity
P ( I | A) = 1 − P (I | A ) =?
Probability that indicator “new agency” will NOT be observed if the event “market
entry” will not occur
Often called the “specificity” of an indicator (“how good is the indicator to not raise
false alarms?”)
(ALPHA might hire a new agency simply for legal reasons or they might have
intended to launch the new product, hence hired the new agency, but later had
second thoughts about the launch)
Notes:
We give credit to the fact that we learned about ALPHA’s general
dissatisfaction with their recent agency); i.e P ( I | A) = 1 − P (I | A ) = 70%
yes - P (I | A) = 90%
yes Hire new
agency
no - P ( I | A) = 1 − P (I | A) = 10%
market
entry yes P (I | A) = 30%
Hire new
no agency
No- ? P ( I | A) = 1 − P (I | A) = 70%

Bayesian Analysis (5) – So what?
P(A|I) = (0,33*0,9) / [(0,33*0,9) + 0,66*0,3)] = 0,6
Rather than having to use the a priori probability of 33% likelihood of market
entry the observation of the indicator “new marketing agency” increases the
likelihood of occurrence to 60% (a posteriori probability). There’s only a 7%
probability that ALPHA will enter the market, despite the fact that the indicator
was not observed (makes you sleep well!)
The difference between the a posteriori and the a priori probability is called the
“predictive gain”, here 60%-33% = 27% (that’s what you are paid for!!!)
known
What we need to know (CI analyst/expert knowledge)
Yes: 60%
Yes: 90%
market P(AI I) yes Hire new
yes entry agency
No: 40% No: 10%
Hire new market
agency Yes: 7% entry Yes: 30%
no market Hire new
entry no agency
No: 93% No: 70%

Bayesian Analysis for
Signal Analysis (1)
To design early warning systems or secure our findings, we can combine
several (conditional independent) indicators.
Calculation is usually done with a decision analysis software

Indicator Sensitivity Specificity
New Marketing 90% 70%
Agency
Press Release 30% 80%

M&A 50% 20%

Calculation in software with indicator “New Marketing Agency“ only


Bayesian Analysis
Tree With Several Indicators
69% (60%) – increase of
likelihood, if all three
indicators are observed!

Full tree with 3 indicators

Agenda

6% (7%)

Phase 3 describes the formulation of an appropriate strategy to react to the
trends and issues which have been identified and labeled as relevant.
Use the Awareness – Motivation – Capabilities Analysis for Formulating
Dynamic Responses in direct rivalry situations

Formulation
Information
Gathering
Strategy


Competitive Dynamics
Competitive strategies are executed on the interfirm rivalry: Action – Response
with direct impact on customers
CI-Professionals should be aware and proficient in managing these activities
Key to understanding competitive dynamics are signal analysis
Typical operational competitive activities are
Change in prices
Acquisitions
Entry into new markets (regions or product segments)
Launch of new products
Internal organizational restructurings
R&D initiatives
Global purchasing measures
etc.


Economic Returns
from Competitive Actions
Advantages based on competitive activities will be negated over time by
competitive responses
If a competitor‘s response follows quickly to an initiative then exploitation phase
has a limited duration. An aggressor should strive to optimize the entire
trapezoidal area constituted by TS, TN, TA .
CI Professionals should be able to predict types and impacts of actions and
responses – Signal analyses is key to achieving this goal
Returns/Advantage from

Launch Competitor‘s
Response
Competitive Action

Exploitation Decline

Time
TL TE TD

Characteristics of Competitive Actions
and Responses
Use these attributes to describe competitive actions
Likelihood
The probability that a firm will initiate an attack or that a defender will retaliate
Speed
The timing of the action or response, in terms of announcement speed and
execution speed
Type
Strategic or tactical action or responses
a) Pricing b) Marketing c) New product offerings d) Capacity-related and scale-
related types of action e) Service and operation change f) Signaling
Magnitude
Designates for instance, % of price cuts, the increase in advertising
expenditures, or the number of products involved in an action or response
Scope
Designates for instance, the number of product lines or geographical markets
involved in an action or response
Location
The market(s) where the action or response is taken, with special emphasis on
whether a response is offered in the same or different market(s) where the
action is initiated© Institute for Competitive Intelligence, Korngasse 9, DE-35510 Butzbach IQPC_Weak_Signals.PPT - Page 37

Action and Response Speed
Competitors can be characterized by their action and response execution speed
Often competitors use initial announcements to manipulate customers,
competitors and industry observers (i.e. Microsoft – 18 months leadtime to
announce vaporeware)
B‘s B‘s
A‘s Announcement of A‘s Response Execution
Announcement of Intended Response Action Execution
Intended Action

a1 b1 a2 b2

Action Execution Speed

Response Announcement
Speed

Response Execution Speed


Prediction of Competitive Responses
Ultimate goal of the Analysis of Competitive Dynamics is the prediction of the
response time b1 and b2 and the actual type of reaction!
Essential for this is to understand how a competitive action affects the internal
behavior of the defending organization. The A-M-C (Awareness, Motivation,
Capability) perspective provides an integrated understanding of the three key
components of internal behavior that eventually define a competitor‘s response.
For some industries it has been advisable to maintain a log-book where actions
and reactions are traced.
Especially deviations from typical patterns might signal a change in competitive
behavior.


A-M-C Model:
Awareness
Knowledge about competitor actions and the relationship to the attacker
If a company simply does not know that it is under attack, than no response can
be expected
If a company is well informed about competitors intentions than a response is
likely and fast

Actions that generate high Actions that result in low
awareness include awareness include
Widely advertised price cuts Incremental improvements in service
Aggressive, name-calling advertising and product quality
campaigns Improvements in operational efficiency
The global launch of a new product or Internal reorganizations
service offering Investments in primary research
Publicly announced ambitious growth projects
targets and strategies Agreements with suppliers or retailers
Acquisitions and mergers with other
competitors
Acquisitions of key suppliers or
retailers

A-M-C Model:
Motivation
What is the motivation for a defender to react?
Usually the motivation for a response is high if the expected financial rewards
are high (or losses are significant without a response i.e.
Attack on Cash Cows products triggers responses
Attacks on Dog products are ignored
If a company is highly motivated than a response is likely and potentially fast

Attacks that generate a high Attacks that generate a low
motivation to respond motivation to respond
Direct attacks on a competitor’s core or Attacks on noncore markets
central markets (e.g., largest, most Attacks that establish a strong
profitable, or strategically most presence that would be difficult to
important markets) dislodge
Direct attacks on a market that is Situations in which a response would
noncore, but holds great potential for result in a damaging battle (e.g., price
growth and future expansion war) that destroys returns for all
players


A-M-C Model:
Capability
„Capability“ refers to the capability of a defender to accumulate resources for a
response and the ability to organize a response within the organization
A response can be expected, if it is easy, economical and without any
organizational restructuring, i.e.
Price adoptions are easily achieved
Product developments might require complex processes and ties
resources
Attacks that are more Attacks that are easier to
difficult to respond to respond to include:
include Price-cuts
Ones that leverage proprietary Advertising campaigns
technology, skills, or resources to Promotions
which competitors may not have
access
Ones that involve complex coordination
between various functions within a
company
Ones that involve alliances with
external partners

Asymmetrical Competitive Information
Bear in mind that every competitor might have a different A-M-C perspectives on
its environment. Reasons might stem from asymmetrical information or from
skewed perceptions of available information

Boeing and Airbus, direct Asked about his key
competitors for passenger competitors, Scott McNeil CEO
aircrafts had completely and founder of Sun
different perceptions for the Microsystem answered, “IBM,
future of long range, long haul DEC and HP“
aircrafts. Consequently When asked why he didn‘t
developments (A-380), mentioned NCR, twice the size
announcements and signaling of Sun and a global top 5 PC
to customers were quite manufacturer, McNeil
different. answered:
“We never see them“


Lessons Learned from
Attack and Defense
How should attacking and defending companies behave?
Empirical studies seem to indicated specific rules per industry when
competitive interaction and its outcomes are investigated
Final results: Profits, Growth, Mkt. Share, stock prices
Use these insights to implement attack/defense patterns in your
competitive arena – based on the signals you analyze

Action Repertoire

Defender

Attacker

Time

Impact of Action-Response (1)
Higher profitability for attacker expected, if defender‘s response is slow and
unlikely

Implementation Req.
Irreversibility
Better Profitability
for Attacker

Radicality

Action
Characteristics

The potential market share gain increases, if complexity of measures increases
and if several responsive activities are required.
If the response speed is slow, market share gains increases
Market Share Gain

More Actions

Complexity

Faster Avg.
Response Speed

Action Repertoire Characteristics

Potential market share gain increases with attack volume and attack duration

Attack Volume
Market Share Gain

Attack Duration

Action Repertoire Characteristics

Potentially market share gains increases if attacks are simple or complex and if
…
… attacks are easily predictable or unpredictable
Market Share Gain

Market Share Gain

simple complex predictable unpredictable
Extent of Attack Complexity Extent of Attack Unpredictability


If attacks are intense and continuously exercised than stock price development
are positively influenced i.e. number and density of TV spots
If attacks bear an element of surprise, then stock prices of rivals tend to decline

Rival’s Stock Price
Stock
Price

Sporadic, Intense, Predicable, Unpredictable,
Infrequent Sustained Inertia Change
Number of Actions within Sustained Extent of Change in Focal Firm’s
Attack per Unit Time Sequence of Actions

The stock price will be positively impacted if variation of attacks actions are
either simple or complex
Stock Price

Simple Complex
Extent to which Focal Firm’s Attacks
Consist of Actions of Many Types


Overly aggressive competitors might end up with a declining profitability –
despite gains in market shares.
CI Professionals should be knowledgeable to provide guidance for sustainable
profitability!
Insight knowledge into Awareness – Motivation – Capabilities of Competitors are
key to success
Market Share Gains
Performance

Profitability

Competitive Aggressiveness

Audit with A-M-C (1)
Awareness refers to a defender’s cognizance or knowledge of a specific
competitive action (or attack) and its understanding of the implications of the
action for its own company and the industry as a whole
Should the action formally announced? If so, by whom and under what
circumstances? How extensive should the industry and press coverage be
about the action? How much information about the action should be made
available?
To what extent should the action he kept secret before being introduced?
(Gillette’s Mach3, under development for eight years, was not even known to
Gillette largest shareholder, Warren Buffet, until nine months before its
release.)
Is the defender taking any major strategic or organizational initiative that might
distract it from paying due attention to the action?
Does the defender share similar assumptions about the industry outlook and
competitive situation?
To what extent is the defender cognizant of the short- or long-term implications
of the action for itself and other competitors?


Motivation refers to the incentives that drive a firm’s decision to respond to a
competitive action. It centres primarily on gains and losses.
1. How specific is the attack? Does the action target a specific competitor, or is it a
general move without any target?
2. From a financial and investment perspective, how important is the market(s) or
business(es) under attack? How dependent is the defender on the market(s)
und attack? A defender may consider a market (or business) critical for a
variety of reasons: e.g., revenue or profit streams, market share, growth
potential.
3. From a strategic and organizational point of view, how critical is the market(s)
or business(es) being attacked? How vital is the market(s) given the defender’s
current strategy?
4. Symbolically, how vital is the market(s) or business(es)? (e.g., a company’s
original business may be deemed vital.) Have any of the firm’s senior executive
ever been in charge of (or made his/her career in) this market or business?
5. Is success (or failure) in the market central to the defender’s reputation?


Capability refers to a defender’s organizational or financial readiness to mount a
response
1. Does the defender’s organizational structure permit an effective response, if it
decides to react?
2. Does the firm have the required war chest to retaliate? Would it be able to
continue the war of attrition should its self-defense generate a counter
response?
3. Does the firm have access to the resources and skills necessary to respond?
4. Are the opportunity costs of responding so high that the defender will forfeit-i.e.,
not undertake a response?
5. Does the defender have the drive to fight back? Does it have the management
talent for an effective response?


Example for Competitive Dynamics
Gilettes product launch of the new „Sensor“ raisors January, 28th, 1990 (Super
Bowl Sunday)
Probability
Extremely high probability that the main competitors Schick and BIC will react
Speed
Simultaneous launch in 17 countries
Type
Strategic – Introduction of a new product line
Pricing – 25% premium price compared to conventional blades
Magnitude
175 M$ Marketing spendings
Scope
17 countries
Location
„High-tech“ Segment


… and Reaction
BIC does not react at all – Sensor blades are not perceived as a threat to the
disposable BIC products
Schick launched a new razor product „Trazor“
Speed
Only 8 months after the Sensor - launch
Type
Indirect, operational reaction – targeted towards the conventional low-end
Segment. One might conclude insufficient resources prevented a direct
response to the high-tech blade segment
Magnitude
Only fractions of the Sensor launch budget
Scope
USA, then other countries – Looks like damage control, defensive operation
Venue
„Low-tech“ Segment

By analyzing reactions one can assess
competitive positions and guesstimate about resources

… and Consequenses
Launch of Sensor blades were a huge success for Gilette, obviously competitors
were taken by surprise
When the Mach3 blades were introduced in 1998 Gilette followed the Sensor
launch pattern
Rivalry was extremely high …
[…] in 1997, the FBI arrested Steven L. Davis on five counts of wire fraud
and theft of trade secrets. Davis had been working for Wright Industries, a
principal subcontractor for Gillette. Despite having signed a
confidentiality/nondisclosure agreement, Davis attempted to sell trade
secrets behind the Gillette MACH 3 razor design to BIC Corporation
(Gallagher, 1998)

Agenda


Thank you for
attending!

Any questions?

Case Study
„Early Warning Systems“


Weak Signals and Early Warning
The aim of an Strategic Early Warning System (SEWS) is to assist
organizations in dealing with discontinuities or strategic “surprises”. By detecting
“weak signals” (Igor Ansoff, 1975), which can be perceived as important
discontinuities in an organizational environment, SEWS allows organizations to
react strategically ahead of time.
The underlying assumption of SEWS is that discontinuities do not emerge
without warning. These warning signs can be described as “weak signals”. The
concept of “weak signals” (Ansoff, 1975) aims at early detection of those signals
which could lead to strategic surprises and to an event which has the potential
to jeopardise an organization’s strategy. Furthermore, the concept of a SEWS is
intended to constitute an important part of a strategic management system,
operating real-time in an organization, and assisting in identifying the new,
which emerges as “weak signals”.


Benefits of an Early
Warning System (EWS)
More lead time allows better reaction!
Opportunity to react Spread of Issue
Events/activities in the market

Decision
without EWS
Improved
reaction
options

Decision
with EWS

Si Id Id De
gn wi enti wi enti cis time
al th fic th fic
la EW ati ou at ion
un
ch S on t E ion
W
S
Improved reaction
time

Case Study:
DaimlerChrysler Aerospace AG (DASA)
DASA (Munich, Germany-based aerospace company with $10 billion in 1999
revenues), a division of DaimlerChrysler AG, recognizes the need to anticipate
and rapidly respond to competitive events in the marketplace.
DASA integrates future-focused scenario planning activities with continuous,
strategically focused monitoring activities that rigorously track environmental
and market events and report critical shifts to senior decision makers
DASA‘s strategic early warning system succeeds in forecasting the 1997 merger
of two significant U.S.-based competitors (Boeing/McDonnell Douglas) by
continually gauging the event‘s probability, allowing senior executives time to
proactively formulate an effective strategic response.


DASA‘s Early Warning System Process
The Strategic EWS integrates monitoring activity with scenario development exercises to
create specific „signposts“ that enable early identification of events with strategic
implications.

Designated expert scanners report „trigger“
events to a cross-functional group of VPs who, in
turn regularly present distilled strategic
intelligence reports to top executives.

DASA: Identification of Emerging
Industry Consolidation

Agenda


Group Discussion
Why does your company need an Early Warning System?
Do you operate an Early Warning System already?
If yes:
Which indicators do you use? Who has selected them? Based on which
rational?
How do you operate this system? Sketch information and reporting flow in your
organization.
How do you measure the performance of your EWS?
If not:
Why not?
Are you often surprised by competitors?
Can you guesstimate the value of earlier insight?

Agenda


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