Sharda_dss11_im_01.docChapter 1An Overview of Analy.docx
Ieaust -aug15_couch-complexity_-_slides_fp_2w
1. High Order Complexity:
Never conflate size or intricacy with (high order) complexity:
• What does it mean?
• What are some key lessons?
• Management and decision making.
• Leadership.
• Innovation.
• Diversity.
• Many examples – including:
• Electricity distribution,
• Information and cyber-security,
• Others in nature, business, government, the military,
and other institutional settings and movements.
- Understanding and embracing complexity is essential to success
in management and leadership of all endeavours we encounter.
- System engineers and managers can make a special
contribution.
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2. Warning:
Beware of following the advice of
“experts” (and consultants) …
…and “Systems Engineers” (some
of who know nothing about
everything?) …
… without validating their views /
claims for your own situation.
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3. Today’s talk
…and some key take-aways.
Note:
• This work builds on previous
published papers and consensus
findings in the C&APL network.
• The presentation covers much
ground, but should be presented
in more detail on future
occasions.
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4. Couch & Associates Pty Ltd
some Background
• A wealth of experience - across cultures,
organisation types, business functions,
institutions, activity disciplines,
• Virtual business network, contracting and
consulting for some twenty-five years,
• Early work in energy systems - operations
and planning,
• Qualifications, accreditations, interests –
systems engineering, law, economics, and
their application to business and
management. (Lifetime interests in
mathematics, philosophy, and related
areas).
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5. • Many achievements, challenges,
failures.
• Success – which means many things
to different people (it may even be
to some, undertaking a series of
career-limiting, “interesting” moves).
• Everyone is different – diverse inputs
from Associates have been made to
form the conclusions in this
presentation; however I alone am
responsible for the content.
• Acknowledgements of help /advice /
collaboration of many others.
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6. Context: Global Megatrends such as these:
• All are certain to occur, but details of how and
when are largely unpredictable.
• All are complex and interconnected (one can’t be
addressed without affecting others).
In all cases their resolution will involve:
• High technology,
• New information management tools (and
increasingly use of “Big Data”),
• Intense and diverse human interactions.
Hence the potential contributions by systems
engineers (or systems managers) and leaders who, as
skilled “integrators”, can be well-placed to embrace
high-order complexity – as well as specific subject
specialists and ideology advocates for the matters being
addressed.
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7. Systems Engineering (S.E.) and Systems Management):
• a long tradition (perhaps as old as engineering and management
themselves – consider Newton, and Carnot’s representation):
• S.E. takes off with intricate schemes required to be designed and
established to tight specifications, performance, cost and schedules (esp
military for WWII).
• Physical systems – interconnections of components where the whole is
deduced or synthesised from the parts.
• Projects – interdependent tasks and resources to deliver specified and
timely outcomes.
• Other systems – e.g. chemical, ecological, market and economic etc.
systems, I.T., industrial processes, organisation systems and procedures,
policies.
• Overlap with other disciplines – e.g. project, value, cost, risk, asset,
construction, operations, maintenance, quality management
• Basis in Mathematics – defined broadly as the understanding
(and its application) of how “things” [in abstract] operate and
interconnect.
• Complexity (with some examples):
• Level 1 relating to Size; Level 2 relating to Intricacy.
• Level 3 – Complex Adaptive Systems (the [high-order] “complexity”
addressed in this presentation).
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8. Complex Adaptive Systems (CAS) – Level 3 Complexity:
• "Your watch is complicated, your family is complex."
Great Krakauer, Santa Fe Institute
• Typical features - many interconnected “agents” with degrees of autonomy,
who can help or hinder “success” of the endeavor, with:
• Private interests and agendas,
• Scope to enter / leave the system,
• Capacity to organise, form alliances, mount defence and attack,
• Potential for learning, innovation (at least in appearance – like
the ant swarm or flock of birds),
• Opportunities for escalation, activism (e.g. through alliances,
agent recruitment or elimination).
• Note: Once human agents with autonomy are included, in addition to the
mathematics base of the system, their philosophies and ideologies can figure
significantly.
• Examples - in all arenas - nature, business, governments, non-profits, families
and tribes, conflict, war, terrorism, markets and competition, negotiation,
diplomacy, industrial relations, other institutional settings and movements
generally.
• Note: While CAS thinking provides useful ”model” of behaviour, it is not a
replacement for the “real world” situations being studied.
For an endeavour to succeed in a hyper-complex environment, it must itself take on
features of a CAS (Law of Requisite Variety – see Ashby &c).
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9. Guidance and insights for management under (high-order) complexity can
be derived from:
• Shared experiences (and learning) from success and failure,
• Understanding of complex endeavours and their environments.
(With limited willingness to use double-blind trials &c. in develoing
management theory, it is usual to revert to consensus processes - quicker,
with more powerful conclusions, but can be hijacked /distorted [and in
management are subject to many fads and fashions].
The first key for management is in recognising and understanding patterns
in the complexity of the situation and using the insights in sound decision
making – distributed and encouraged throughout the endeavour being
managed.
• Note: Innovation and diversity are crucial (more on these another
time – they are not just “nice to have” but essential to “seeing” the
complexity, and to discovering relevant alternatives and
opportunities in decisions to be made).
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10. Why Decision making? On one perspective an endeavour may be defined in terms of the aggregation of
all its decisions (implicit and explicit) impacting on its available resources [see previous published papers]
– whether in:
• The few high-level decisions that have huge consequences, or
• The many “storefront and shopfloor” decisions that each usually has lesser impact (but
remember the non-linearities [scope for activism and reputation loss ]), or
• Everything in between.
Ubiquity - Every person (perhaps not those whose jobs can be automated entirely) who is:
• engaged in or connected with an endeavour - has capacity to enhance or detract from its
reputation and value, through the decisions they are making all the time (whether formally or
informally).
• available to work for an endeavour – should as far as practicable:
• be skilled and motivated in making sound decisions affecting their particular area,
• understand what is likely to be good for (and bad for) the endeavour
Learned and informed - The techniques must therefore (more on these another time)
• be simple and easily internalised (and taught) [note: simple doesn’t mean “easy” to do well],
• be applied
• using information available (or knowing what information if unavailable would be
useful)
• Knowing the resources available that can be deployed
Hence the importance of leadership - influencing how decision making is done and how it should be
distributed, structured, and scoped (more on these another time).
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11. Leadership:
Key lesson – In a hyper-complex environment:
• Leadership is about effectively influencing others (all
who are connected) in all of the components (1-9 on
previous slide) for sound decision making.
• Leadership must be distributed, and exercised by all
who have capacity to do it (the endeavour must be able
to operate without interruption and thrive/survive if
some leaders (or even an entire board etc.) are absent /
leave the endeavor [for any reason]).
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12. Take-away:
As complexity increases
Without intentional and competent decision-making
i.e. if decision-making is:
• Unsound (Process),
• Mis-aligned (Structure),
• Restricted (Distribution),
• Incomplete (Content),
• Unsupported by:
• Intelligence,
• Learning,
• Leadership,
Value is lost and prospects of success are jeopardised
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14. Examples:
Electricity Distribution:
• Background.
• History of transformations to date.
• Emerging circumstances:
• Emerging economic feasibility and technical capacity
(although not without challenges) for customer and 3rd party
owned and controlled, stationary and mobile, energy
generation, processing, distribution, demand management /
smart use.
• Regulatory framework unable to keep up with emerging
opportunities.
• Apprehension (escalated through social media), even if
misinformed among the public that utilities want to kill solar
and other alternative or distributed energies, and “tax”
customers who want to connect but not take “net” energy.
• Need for further and continuing transformation (although the past
models may have served well) to date.
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15. Examples:
Electricity Distribution – an industry in transition (again):
One hopes that the industry’s traditional one-size-fits-all service approach, and its
current pre-occupation with revenue entitlements and tariff structures, as important as
these are, will grow into establishing a needed new overall business model – a model
recognising (among other matters) that its services are becoming progressively
“contestable” at the margin.
• While there are important technical (including stability, fault level, protection),
safety, coordination (including dispatch and allocation arrangements), equity and
commercial issues to resolve, none need ultimately to be final barriers to change
(although all add complication and impose costs).
• Keys are:
• Embracing customer sovereignty,
• Meeting diverse customer requirements,
• Recognising customer preferences and managing expectations,
• Informing customers (and the public) and overcoming apparent
alienation (e.g. from perceived self-interest, delay, resistance and
protectionism),
• Moving from a revenue entitlement mentality to one of transparent
charging for customised services,
• Developing a business model that will still satisfy regulatory
requirements,
• Updating the regulatory framework – to move from rule orientation to
anticipating future change.
• Overall, finding a way to continually, sustainably and responsibly
provide the services that customers want and can be paid for.
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16. Examples - Innovation
Modern telecommunications network
management accommodates:
• Third party and network- owned and
controlled,
• Plant and equipment,
• Mobility,
• Diverse sources and users of content,
• Aggregators etc.
Possible innovative application of this model to
• Power networks?
• Other industries ?
(These questions were considered during an
assignment with Clarity International Pty Ltd.)
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17. Clarity Software-as-a-Service (SaaS)
concept for Network Business
Management
Capacity to:
• Accommodate all potential / useful data
sources,
• Connect with legacy and new
communications systems,
• Mirror the system in unified data storage,
• Support all network business operations
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18. Clarity Software-as-a-Service (SaaS) concept for Network Business
Management
• Capacity to Accommodate all potential / useful data sources
• Plant and Equipment,
• Protection, Recording and Controls,
• Backup / auxiliary devices,
• Subsystems and “systems-of-systems”.
• Covering full range of ownership & control possibilities:
• Connected and embedded networks,
• Customers’ installations and appliances,
• Mobile, distributed, dispatchable/intermittent,
• Generation, distribution, other processing, storage,
• Third-party aggregation and other involvement,
• Metering, data, controls.
Note: Client chooses the scale (granularity, depth) to monitor.
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19. Clarity Software-as-a-Service (SaaS)
concept for Network Business
Management – a framework to:
• Connect with all known legacy and
new communications facilities.
Note: Vendor neutrality (from
proprietary plant and equipment and
SCADA) is a key feature of the
functionality.
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20. Clarity Software-as-a-Service (SaaS)
concept for Network Business
Management – a framework to:
•Mirror the system in real-time
data storage.
Note:
• Dynamic and Multiple instances
– big data and responsiveness
implications.
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21. Clarity Software-as-a-Service (SaaS)
concept for Network Business
Management – a framework to:
•Support the network business
operations.
Note:
• Database provides “single
source of truth”.
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22. A Software-as-a-Service (SaaS)
concept for Network Business
Management:
• Supported Business Functions,
• Current and Future requirements.
Note:
• When proposed five years ago this
approach was considered too
difficult and too early – it should
now be little more than
commonplace.
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23. Potential application to other
increasingly networked industries,
e.g:
• Health and public services,
• Supply chains and outsourcing,
• Property &c. regulation and
interests management,
• Development, Building, Product,
Services compliance management.
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24. Examples: Security – Today more than ever
industry is seeing:
• The information is the infrastructure; its
integrity the imperative.
• Security has become everyone’s
responsibility (as quality, safety etc. became
previously).
• Security is a complex system – (in part virtual
and remote) IT, applications, networks and
equipment, supply chains, with multiple
layers, diverse defences, and people (whether
inside the endeavour’s boundaries or outside,
and including those who are hostile and
others whose security behaviour is
inadvertent).
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27. To Summarise:
It takes a CAS for your endeavours to
succeed in a hyper-complex
environment!
1. Seeing “The Systems” in context,
2. Understanding Interests and
Agendas throughout,
3. Focusing on Decision Making,
4. Encouraging Leadership –
Influencing - Decision Making,
Intelligence and Support,
5. Striving continually for Improvement
and Innovation.
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