Cognitive Kanban - Lean Systems Society

Transcription

SPEAKER BIO: Michael Sivertsen received an undergraduate degree in Physics from the University of Minnesota
in 1979 and a Master of Knowledge Management degree from California State University, Northridge, in 2009.
He currently holds a Certified Systems Engineering Professional (CSEP) designation from the International
Council on Systems Engineering (INCOSE). Mike has held numerous positions in three major industries (energy,
IT, and aerospace). These have included: Radiation Scientist (Health Physicist), Nuclear Engineering
Instructional Design, Business Systems Analyst, Information Architect, Consultant - Organization and Leadership
Development, and Systems Engineer.
BACKGROUND: I'm interested in how people think (cognition) and learn. I have long 'scanned the environment'
of personal and professional interests using an efficient and effective personal knowledge management (PKM)
set of tools and daily practices. The synergy between these areas is reflected to a great degree in the Cynefin
Framework which I have studied since 2007 and is the central focus of this presentation. Scanning the
environment and observing patterns is a key part of using the Cynefin Framework.
I enjoy reading and seeking to understand new or unusual developments that contradict 'accepted' knowledge.
Science by its nature is revolutionary as it seeks to overturn obsolete or outmoded knowledge as new
discoveries are proven using the scientific method. Galileo, Richard Feynman, Michael Crichton and Art
Robinson are some of my scientist role models. Looking BETWEEN various fields of study or examining them in
light of 'new' or overlooked knowledge is a favorite of mine and is where innovation often occurs.
NOTE: This presentation is adapted and expanded from the author’s 2009 Master’s degree Capstone Paper
entitled, “Improving Decision Quality and Innovation in a Complex World.”
ACKNOWLEDGEMENTS: The author is deeply indebted to David Snowden's willingness to freely share his work
at the Cognitive Edge web site. My Capstone Paper and this presentation explores material Snowden and
others have developed since 2002 and then applies it to areas of interest in business and science. Links are
made to source material when critical to provide attribution and allow the reader to pursue additional detail. In
other cases I may paraphrase key points from research contained in Snowden’s many presentations and
podcast lectures. http://www.cognitive-edge.com/
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Cognitive Kanban: Improving Decisions in a Complex World
Traditional business and information management practices are no longer sufficient in a
world in which information overload, interdependence and complexity accompany most
problems.
How can we aggregate information in order to make a decision that will not be negated, or
make matters worse, by the all too common "unintended consequences?"
How can members of an organization, or an electorate, become part of a 'sensor network'
that actively learns and is able to communicate competitive intelligence, or threats, from the
edge of the organization?
Are you willing to disrupt entrenched patterns of thinking held by you and your organization
to foster innovation? Or is 'the way we've always done it, no newcomers allowed' too deeply
held?
It's no longer business as usual when we face a depression, the realization that practices
from the 1980s and 1990s are inadequate and pervasive social computing in which every
person with a cell phone or computer can be either a customer, a source of competitive
intelligence or a threat.
It's time to think anew.
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The Swindon, England, Magic Roundabout was built in 1972. It consists of five mini-roundabouts
inside one big roundabout. Traffic flow around the smaller, inner roundabout is counter-clockwise,
while traffic flows clockwise around the five mini-roundabouts and the outer loop. While looking
scary it has the best throughput of any design. Cars are able to make their way thru without stopping
for more than a few seconds.
The Magic Roundabout is near a large football field, two shopping malls, Intel’s European
headquarters, a regional hospital and a freeway exit. It never jams up. Locals go straight thru the
middle, tourists hug the outside.
This is an everyday example of a complex adaptive system (CAS) - which we will be explaining in
detail later. It uses the ability of a driver to see weak or strong patterns and to make choices within
the barriers. It is a lightly constrained system in which agent (drivers) decisions can change very
quickly based on circumstances (the system). No central authority is needed or desired.
What might be the result of a top-down, traditional engineering approach to handle all this
complexity? Perhaps a Christmas tree-like mountain of stop lights with long, fuel wasting, stoppages
(chart 35)? A belief in models, computing algorithms, process engineering and centralized command
and control would result in a very brittle solution (as opposed to resilient) in order to dictate
behavior. The result would be daily disasters.
The traffic designers used traffic cones as weak constraints during the design stage and kept moving
them around until the desired flow (amplify attractors and dampen negatives) was achieved.
Magic Roundabout history and take a virtual drive thru the roundabout:
http://www.cbrd.co.uk/indepth/magicroundabout/
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"Well defined" are those areas in which we know all the parameters and ambiguity is low to
non-existent - like Newtonian physics. How many of us work on projects like that?
Forcing manufacturing approaches into a complex adaptive system is destructive (e.g.,
business process engineering that morphed into Six Sigma with ‘belts’ and other
accoutrements of a highly structured system).
3-M rejected the Six Sigma initiative that a previous CEO had established in their R&D
division as it was destroying their ability to innovate. The 3M CEO (McNerney) that
introduced Six Sigma to 3M (and which was removed by his successor) did NOT re-introduce
Six Sigma to Boeing when he abruptly moved there after 4.5 years at 3M.
At 3M, A Struggle Between Efficiency And Creativity, Business Week, 11Jun2007
http://www.businessweek.com/magazine/content/07_24/b4038406.htm
Both industrial and computer age approaches do not reflect analog human cognition and
work against our pattern recognition abilities. Sophisticated analyses and especially
computer modeling mislead us in complex spaces where there are unknown unknowns and
cause and effect are not perceivable or repeatable.
“ . . .as the boundary between IT and decisions becomes more fractal, the fundamental
impedance mismatch between the analog world of human decision making and the binary
world of IT becomes increasingly problematic.” Complex Enterprise Architecture at
http://sensemakingattheedge.blogspot.com/2009/10/complex-enterprise-architecture.html
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Gary Klein, cognitive psychologist, defines sense-making as “the ability or attempt to make sense of
an ambiguous situation. More exactly, sense-making is the process of creating situational awareness
and understanding in situations of high complexity or uncertainty in order to make decisions. It is ‘a
motivated, continuous effort to understand connections (which can be among people, places, and
events) in order to anticipate their trajectories and act effectively.’”
An introduction to Klein’s groundbreaking research on human intuition and decision making can be
found at: “What’s Your Intuition?” Fast Company, Dec 2007, http://www.fastcompany.com/node/40456/print
Klein realized that pattern matching based on extensive experience was a key factor in the decisions
made by fire-fighters, emergency worker, airline pilots and others in time pressured situations.
Captain Chesley Sullenberger (Sully) landed a US Airways A320 Airbus in the Hudson River on
15 Jan 2009 after loosing both engines to bird strikes. All 150 passengers survived. He only
got through one page of the normal three-page checklist used for such emergencies at higher
altitudes.
"For 42 years, I made small, regular deposits of education, training and experience ....and the
experience balance was sufficient that on January 15th I could make a sudden, large
withdrawal" - Chesley Sullenberger
A simple sense-making definition by David Snowden is "how we make sense of the world so we can
act in it."
http://www.cognitive-edge.com/blogs/dave/2008/06/what_is_sensemaking.php
An eco-system such as the Amazon rain jungle (shown here) is an example of a complex adaptive
system.
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We all know what a hierarchical structure looks like and understand the flow of information (up and
down). How many of us understand how a decentralized network structure works and how we can
“make sense” of what it represents or is telling us from the various information flows?
Many problems facing America in the 21st century appear intractable if we continue to rely on
principles of scientific management first used over 100 years ago. The world and the way in which we
perceive, think and communicate has moved on. Yet we approach the solution to problems in science
and business in a fashion similar to that of the 20th century. Human intelligences can now be
connected and amplified in a real-time basis due to the advances in social software since 2001.
However, the management of people, the holders of knowledge, has lagged behind the amplifying
effect of technology used by millions. This presentation illustrates the need for an enlarged
framework that will enable better decision-making, promote innovation and effectively reap the
benefits of networked human cognition.
Since people are the keepers of knowledge we must understand the complexity with which that
knowledge is held and transferred. While technology can AUGMENT and extend the reach of our
knowledge, it is a mistake to think that the origin of our knowledge (human cognition) functions like
the computer which transmits these thoughts to others.
Many business models built upon a hierarchical distribution method (music, books, movies, etc.) have
been financially challenged by the network model enabled by the Internet (e.g., music stores -> CDs > P2P -> BitTorrent). Blockbuster is on the verge of bankruptcy from Netflix and other changes in the
multimedia distribution model.
Nicholas Taleb, author of “The Black Swan: The Impact of the Highly Improbable,” made this quote in
Oct 2008 when commenting on the U.S. financial collapse in an article with former chairman of the
Federal Reserve, Alan Greenspan. Greenspan admitted that the computer models used by the
financial community were inadequate and they were unable to determine a clear direction due to
their poor understanding of all the issues in such a complex space.
Greenspan admits mistakes in his methods helped set stage for financial disaster , Oct 2008
http://www2.canada.com/components/print.aspx?id=b0870074-4ede-45e1-a80d-b867439e82b9
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Vitruvian Man is a well known example of the 15th century Renaissance genius of the Italian
scientist Leonardo da Vinci. Numerous measurements and proportions of the human body
are compared to one another in a geometrical image that symbolizes the symmetry of the
body and, by extension, the universe as a whole. While da Vinci visualized the PHYSICAL
appearance of man (and the universe) as an ordered system we will explore the unique
ability of our innate intelligence to make sense of UNORDERED systems or domains in which
cause and effect are not linked and do not repeat.
Humans are not machines (nor are we animals). Humans exhibit chemical, gaseous, skeletal,
hormonal and other innate intelligence that is intrinsic to the intellectual sense-making and
physical self-healing capabilities possessed by all human beings.
Many fail to appreciate the uniqueness of humans and their intelligence. This is reflected in
societal or cultural trends and government policies that denigrate humans. While humans
may act like animals or dumb themselves down intentionally or unintentionally that does not
change the fact that we are uniquely constructed as the crown of creation (Psalm 8:4-8,
Psalm 139:14). Our intrinsic sense-making capabilities extend far beyond a digital metaphor
that too often considers computer models as a suitable basis for human decision making.
The shortcomings of such models will be discussed later.
References:
- David Snowden, IRAHS lecture, Mar 2010 http://www.cognitive-edge.com/podcastdetails.php?podid=100
- Transplanted organs impart memories onto recipients
http://www.naturalnews.com/028537_organ_transplants_memories.html
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Science and theory must underlie use of human knowledge to achieve effective results. Thus,
we need to understand how we think. Our brains work by associating loosely fragmented
information and doing pattern matching. There is no “list all” function as in a computer.
It is important that theory informs our practice (praxis) and we don’t confuse correlation
with causation (e.g., every CEO of a successful company goes golfing so if I golf my company
will be successful). This type of inductive logic depends heavily on extrapolation and often
forms the basis for erroneous decisions.
London taxi driver: only 40 percent pass rate after two tries. Knowledge boy drives around
for three years on a motorbike to memorize every single street in London (second largest city
in world in street volume and NOT laid out in a grid). The Knowledge test requires the taxi
driver candidate to recite from memory turn by turn navigation between any two points
along with hotels and tourist attractions along the route.
http://en.wikipedia.org/wiki/The_Knowledge#The_Knowledge
Taxi driver brain scans revealed that part of the hippocampus (wrapped around the brain
stem and associated with navigation and memory) was actually larger. Context based
remembering and novelty are thought to be part of the function of the hippocampus.
http://news.bbc.co.uk/2/hi/677048.stm
Navigation-related structural change in the hippocampi of taxi drivers, April 2000
http://psyc.queensu.ca/~flanagan/PSYC100/pdf/MagGadJoh_PNAS_00.pdf
Important for brain research, e.g., Alzheimer’s disease.
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“How to think with your gut,” Business 2.0, November 1, 2002
http://money.cnn.com/magazines/business2/business2_archive/2002/11/01/331634/index.htm
Traders won on Wall Street AND at Quantico.
In 1995 a retired U.S. Marine Corps lieutenant general, Paul Van Riper, brought Marines to the NY Mercantile
Exchange. Van Riper had noticed that in the heat of war rational decision making and reductionist approaches
often fell short (frame problems, formulate alternatives, collect data, evaluate outcomes). The classical
checklist system never seemed to work because it’s the WRONG system for complex environments. Van Riper
consulted with a cognitive psychologist (Gary Klein) who was studying firefighters. Firefighters operate in warlike conditions many times (no time for careful planning) and Klein had observed a decision-making approach
that grabbed the first ‘good enough’ idea and moved on from there. Van Riper took the Marines to the trading
floor and the traders easily beat the Marines, as was expected. The big surprise came when the traders went to
the Marine Corps base in Quantico, VA and played war games against the Marines on a mock battlefield. The
mercantile traders beat the Marines in war games as well. The traders were simply better at acting on
imperfect, contradictory information – which is often all you get in war. The Marines concluded that the old
rational analysis model was useless in some situations. Marine Corps doctrine now reads, "The intuitive
approach is more appropriate for the vast majority of ... decisions made in the fluid, rapidly changing conditions
of war when time and uncertainty are critical factors, and creativity is a desirable trait." These conditions are
similar to those in which many business decisions are made today.
The Marines deserve credit for examining weaknesses and exploring new approaches from non-military
disciplines. In a similar fashion they teach the OODA Loop (adopt fluid and fast moving tactics) by John Boyd.
(The Marine Corps Research Center at Quantico has a stature of Boyd in the lobby with a model of the F-16
behind him. ) The Marines (and the Army) have made a conscious effort to embrace the complexity of the
battlefield with new approaches that go beyond centuries-old attrition warfare tactics.
“The traders were skilled at spotting patterns and intervening to structure those patterns in their favor. The Marines, on the
other hand, like most business school graduates, had been trained to collect and analyze data and then make rational
decisions. In a dynamic and constantly changing environment, it is possible to pattern unorder but not to assume order.”
– Snowden and Kurtz, The new dynamics of strategy: Sense-making in a complex and complicated world (2003), p.466
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Cynefin (ku-NEV-in) is an ontological framework for understanding reality and the realm of human action and
thought. The name is a Welsh derivation that, loosely translated, refers to the "place of your multiple
belongings." You, and the world in which you live, can inhabit any one of five domains within two larger
categories of ordered and unordered systems. The Cynefin framework describes the context of these domains. It
is an ontological statement of what CAN exist and the relationships between the five domains. Techniques
suitable to each domain can then discern the actual knowledge (what DOES exist) in that domain. Ontologies
are a key approach by which we establish meaning for, and define, a shared, yet abstract, concept. Clearly
defining an abstraction helps it to be useful in many different ways. Frameworks provide a structure for
considering this shared concept. Being able to use the same framework to describe and understand all human
domains of ‘belonging’ is very powerful. This is due to its reliance on complexity science, natural systems and its
ontological structure.
"Multi-ontology sense making argues that different approaches are legitimate, but within boundaries and that
methods and tools that work in one ontology, do not work in another. It is thus beholden on management to
know which ontological domain they are operating in, and what transitions between domains they wish to
achieve." – Snowden (2005), “Multi-ontology sense making; a new simplicity in decision making,”
http://www.cognitive-edge.com/articledetails.php?articleid=40
The Cynefin framework can also be characterized as a platform, as opposed to a product or a service. This is
significant as a platform affords much greater innovation potential due to the many different contexts in which it
can be applied. The top five greatest innovations of all time (greatest impact on quality of life and standard of
living) were all platforms according to Business Week in Feb 2007 (weapons, math, money, printing, free
markets and capital markets) http://www.businessweek.com/print/innovate/content/feb2007/id20070216_377845.htm
Source papers for the Cynefin discussion and Cynefin Framework images:
Kurtz, C.F. & Snowden, D.J. (2003) The new dynamics of strategy: sense-making in a complex and complicated
world. IBM Systems Journal, 42(3). Detailed explanation.
http://alumni.media.mit.edu/~brooks/storybiz/kurtz.pdf
Snowden, D.J. & Boone, M.E. (2007) A Leader’s Framework for Decision Making. Harvard Business Review.
November 2007. Business and leadership oriented summary.
http://www.mpiweb.org/CMS/uploadedFiles/Article%20for%20Marketing%20-%20Mary%20Boone.pdf
Dave Snowden explains the Cynefin Framework at http://www.youtube.com/watch?v=N7oz366X0-8
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Ordered systems can be simple or complicated. Examples include a manufacturing process, a nuclear power plant,
archeological fossil records, and the like. In an ordered system we know all about it (e.g., nuclear power plant operation).
Ordered systems are predictable and react in known ways. This means we can apply "best practices" (a better term is
"recommended or useful practices") as there is a clear cause and effect relationship. This relationship guarantees that "if we
do this, then this will happen." This is the realm of Newtonian physics. It is also the realm of fact-based management and
subject matter experts.
SIMPLE DOMAIN: "We know what we know."
This domain is stable and all parties share the same understanding of the system's properties. Cause and effect are directly
related. Processes are predictable and repeatable. Process reengineering, structured improvement techniques (e.g., kaizen,
lean) and standard operating procedures are used to drive efficiency. In this decision making domain you sense, categorize
and respond: assess the facts, categorize them, and then respond with accepted and predetermined practices. The 2007 HBR
paper lists several problems that can arise in this domain:
Issues that have been oversimplified may be incorrectly classified as simple, when they are really complicated or complex.
Decision-makers that routinely ask for simplified PowerPoint charts with bullets or stoplights run the risk of simplifying an
issue that may belong in a different domain with more appropriate decision making techniques. For example, events
surrounding the 2003 Space Shuttle Columbia accident indicate that oversimplified and obtuse PowerPoint charts contributed
to a decision by NASA program management that ultimately resulted in seven dead astronauts.
"The Board views the endemic use of PowerPoint briefing slides instead of technical papers as an illustration of the
problematic methods of technical communication at NASA." (Columbia Accident Investigation Board, 2003, p. 191)
http://caib.nasa.gov/news/report/volume1/default.html
"The biggest lesson, Roe said, is to curb the practice of 'PowerPoint engineering.' The Columbia report chided NASA engineers
for their reliance on bulleted presentations. In the four studies, the inspectors came to agree that PowerPoint slides are not a
good tool for providing substantive documentation of results. 'We think it's important to go back to the basics, . . . and go back
to writing engineering reports.' (Safety assessments released on four NASA projects, 2004)
http://www.govexec.com/dailyfed/0504/051204b1.htm
Leaders are susceptible to entrained thinking, i.e., they have been rewarded for doing things in a customary fashion and are
unable or unaccustomed to seeking new approaches or thinking in different ways. This can hinder innovation and the
willingness to consider thinking outside the mainstream.
Leaders can become complacent in the simple domain because everything is going as planned. This domain is next to the
chaotic domain because it reflects the situation that arises when a complacent market leader is overtaken by a small
competitor. If the context changes abruptly, complacent leaders can react too late to avoid or mitigate chaos (disaster). Thus,
it is important for leaders to continually scan the environment. For example, establish and support social media (blogs,
message forums) as well as anonymous channels that allow frontline workers to report changes in context that could portend
disaster. These channels should allow those with ideas contrary to organizational thinking (i.e., dissenters) to freely contribute
as well. Allow a workforce to operate as 'sensors' in areas of interest. EXAMPLE: 2010 U.S. census vs. Argentina
http://www.mytwocensus.com/2010/04/27/brazils-census-is-way-more-technologically-advanced-than-ours/
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COMPLICATED DOMAIN: "We know what we don't know.“
This is the realm of the "knowable" (i.e., knowable by society or by the organization). In this domain subject matter
experts (SME) hold the specialized knowledge that is often needed to understand the relation between cause and
effect when studying a problem. Decision makers must rely upon and trust these experts. Unlike the simple domain,
more than one right answer is possible. An analytical, reductionist approach to problem solving is used. Systems
thinking, the learning organization, experiment, fact-finding and scenario planning are appropriate to this domain. In
this domain leaders must sense, analyze and respond. The analysis stage may require highly specialized expertise.
Several options may need to be explored in the form of trade studies, risk management or other analytical tools.
There is not 'best practice,' but rather 'good practice.‘
Problems that can arise in this domain include entrained thinking and analysis paralysis.
Entrained thinking among the experts (rather than the leaders) is a danger here. Since the work of experts
dominates this domain, innovation by non-experts or by smaller entities may be overlooked or dismissed. The
Systems Engineering Handbook, published by the International Council on Systems Engineering (INCOSE), cautions
systems engineers in this regard: “Because systems architecting is a creative process, and because intuition and
experience play such an important role, the systems engineer must pay attention to situations where past
experience and intuition have been a handicap. . . . In each of these [hard drive size reduction] transitions, the
established companies lost out, in part because their established user base was locked-in to the older architecture,
and in part, because their entire enterprise from systems engineering to marketing to manufacturing to executive
management was unable to see the new vision.”
An 18th century example illustrates how entrained thinking by the established scientific community kept a
significant advance in ocean-going navigation off the market for over a decade. See Longitude Prize chart.
The record of Galileo further documents the danger of trusting in entrenched institutions and personnel to accept
new scientific facts when confronted by outsiders. The power inherent in the status quo means that special
techniques are needed to overcome it. To avoid the entrainment problem leaders must actively seek multiple
perspectives. Welcoming novel approaches from those outside the expert community is essential. John Harrison was
not regarded as an expert but he had the solution to determining longitude in the 18th century.
Entrainment is particularly dangerous in this domain as an error in an assumption or a premise can result in a
faulty solution that is difficult for the non-expert to detect. We will see examples of this when we discuss model
shortcomings.
Another problem that can arise in the complicated domain is 'analysis paralysis.' In this situation, the experts are
unable to agree on an answer due to individual entrained thinking or oversized egos. This can be remedied by
placing experts in unfamiliar environments to stimulate creativity and new thinking. Using game and simulation
environments or even a book club can be useful in this regard. Because the context is different, and issues are
abstracted away from specific personalities, players often come up with fresh ideas. This sort of metaphorical
environment allows leaders to experiment and choose from a wide range of options, gathering up many more
perspectives on intractable problems. Another approach is the rapid formation and disruption of small groups
working on the same problem in a facilitated environment.
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COMPLEX DOMAIN: “We don't know what we don't know” Key domain to understand. One cannot predict outcomes in unordered
systems.
This is the realm of unknown unknowns. Cause and effect do not repeat and are only discoverable in retrospect. Complex systems
operate in a non-linear fashion. Minor changes at the beginning can produce disproportionately large outcomes. One can observe
patterns but the outcome is uncertain. Discovering and managing patterns in this domain is critical. These patterns are dependent on
interactions between agents in the system and the system itself. As a result the agents and the system co-evolve and this evolution is
irreversible. The probe-sense-respond tactic used here is similar to what spies do (operating in a complex domain) and is demonstrated
in the TV series “Burn Notice.”
The difference between complicated and complex domains can be compared to the difference between a race car and an eco-system.
The race car can be disassembled and reassembled by an expert technician and each time we will end up with the sum of the parts.
Nature, on the other hand, is in a state of constant flux with many different agents (weather patterns, animal migration patterns, human
settlements, etc.) interacting with one another. The whole is much greater than the sum of the parts. This is the reason computer
models have been unable to replicate or correctly predict actual global temperatures measured by satellites. There are too many
uncertainties in the complex and chaotic climate system. A review of the book, “Useless Arithmetic: Why Environmental Scientists Can’t
Predict the Future," discusses this and includes recommendations closely aligned with Cynefin techniques.
http://www.nytimes.com/2007/02/20/science/20book.html
Much of business, political and military experience has shifted to the complex domain (in which the complexity of human interaction
and thought can surpass that found in nature). In this domain the leader needs to probe first, then sense and then respond. Probes will
make patterns more visible and help to determine appropriate action. One must take time to acquire multiple perspectives in this
domain rather than rush in with predetermined practices from entrained patterns based on past experiences. A more experimental
approach (reflected in the Netflix Prize contestant methods) is needed. Desirable patterns can then be stabilized and reinforced while
undesirable patterns can be dampened.
Problems that can arise in this domain include a reversion to entrained thinking or command and control management style. One must
exercise patience and resist the tendency to demand fail-safe business plans with pre-determined outcomes. A tolerance for failure is
also needed. The complex domain affords many opportunities for intellectual diversity, innovation and new ideas. Snowden and Boone
(2007) recommend the following techniques for managing in a complex context:
Open up the discussion. Eliminate the notion that the fewer the people that know about a problem the faster it will be solved.
Set loose barriers that allow the system to constrain itself. For example, requiring all social media posts within an organization to be
associated with the employee's name drastically reduces spam and unprofessional comments without the need for 'blog police' or
comment moderation (which reduces participation). The LM internal social network site (called Unity) operates in this fashion and has
worked very well. I have written over 170 blog posts on Unity since 2005.
Stimulate attractors. EBay used this approach numerous times as the site grew. A probe that offered cars for sale quickly grew until it
became a prime reason for visitors to use the site.
Encourage dissent and diversity. Earlier examples (Longitude Prize, Galileo) indicate the value of diverse opinions. Stimulating dissent
using a safe-fail approach can be done in a face to face environment with a group facilitation technique covered in the 2007 paper.
Focus groups, surveys and questionnaires are NOT appropriate for pattern discovery in a complex domain.
Manage starting conditions and monitor for emergence. Focus on setting up an environment (including incentives) from which good
ideas can emerge rather than trying to engineer predetermined results and thus miss serendipitous innovations that may arise along the
way. This approach can reap tremendous benefits at low cost (e.g., Netflix Prize contest).
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Unordered Systems: Unordered systems can be complex or chaotic and are characterized by
unpredictability. One cannot predict outcomes in unordered systems.
Chaotic Domain: “Things are unknowable”
This domain displays no relationship between cause and effect. Agents act in a disruptive
manner. Leaders must act decisively to restore order, sense the reaction to this intervention and
then respond appropriately. There is no time to solicit input from experts on a distributed
network. There is an atmosphere of high tension. Transforming the situation from chaotic to
complex can allow emergent patterns to be managed. These patterns can then be managed as
discussed earlier to reduce risk and exploit new opportunities.
Dangers associated with this domain are significant (and are discussed later). New York City
Mayor Rudy Giuliani demonstrated command and control effectiveness during a crisis
(9/11/2001) but was later criticized for using the same top-down leadership in the normal
complex domain of government operations when he suggested postponing elections in order to
maintain order. Leaders must be able to switch leadership styles when the context switches. A
key benefit to understanding the Cynefin framework is that a leader becomes aware of the
context that signals the need to shift their leadership style. This can be both personally and
professionally rewarding while benefiting society.
Another danger is that the authoritarian style needed to restore order in the chaotic domain
results in a leader with an over-inflated self-image and cult-like adoration by followers. This
circle of followers and close advisors may then disrupt the flow of accurate and complete
information to the leader, making good decisions problematic.
Yet, the chaotic domain is the best place to promote innovation. During a period of unrest and
great change people are more open to new ideas and thinking differently. For example, when a
crisis arises appoint two parallel teams: one to handle the crisis directly and one to stand back
and determine what should be done differently as patterns emerge.
Placing experts into new or unfamiliar surroundings that have no reliable cause and effect can
also spark innovation. The use of simulations and games can disrupt entrained thinking and
allows a wide range of options to be considered in a safe-fail environment.
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Disorder Domain
This is a realm which is difficult to recognize. Lack of information and understanding prevent you
from placing the system in any of the four other domains. Multiple perspectives and voices vie for
attention. Individuals will attempt to interpret the disorder based on their training and
experience. Those most comfortable with top-down, command and control will attempt to steer
the disorder into a domain where they can impose rules. Those with knowledge in a related area
will tend to a domain where they can assume control by virtue of their subject matter expertise.
Dictators eager to assume control in a chaotic situation will seek absolute control.
Kurtz and Snowden (2003) recommend reducing the size of the DISORDER domain as much as
possible through discussions among decision makers. Break down the disorder into constituent
parts and assign to other domains as appropriate.
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SIMPLE-CHAOTIC Boundary: The close proximity between the SIMPLE and CHAOTIC domains is a warning on many
levels. “This boundary is the most dangerous and must be treated with respect.” - Kurtz and Snowden (2003),
p.475.
Item 1: Asymmetric collapse. Historical example is the trial of Galileo. The Catholic Church’s position eventually
collapsed. Trying to impose order where natural laws or the demise of a product or service is imminent is a common
trait of governments, institutions, people. Decision makers try to fit reality into outmoded models rather than
acknowledge that the models have become irrelevant or inadequate. They then punish dissent and the dissenters.
“Galileo is tried afresh in modern organizations on a daily basis” - Kurtz and Snowden, p.476. Organizations that
become complacent due to market or technology dominance can end up in chaos and organizational decline to more
advanced or consumer-friendly alternatives. Did Blockbuster ever consider that their late fees would motivate the
Netflix founder to come up with a better DVD distribution model than driving 3,000 lbs of glass and steel to a store to
pick up digital bits and bytes encoded on a small disc? Blockbuster is threatened by bankruptcy in 2010.
Item 2: Imposition. Forced movement from chaotic to the known. When a society experiences chaos at a suitable
level, citizens often accept a government imposed order which they would normally refuse or find unacceptable due
to the curtailment of basic human or Constitutionally guaranteed rights. The Patriot Act and other laws passed in the
wake of the 9-11-2001 attacks are an example of this. It is also possible for a corrupt government or organization to
foment a false chaos or crisis that allows tyrants to come to power through the promise of imposed order. This was
demonstrated numerous times in the 20th century via government sponsored "false-flag" operations that enabled
the perception of chaos or attack by an external enemy. (http://www.wanttoknow.info/falseflag) Alert citizens
should use Cynefin framework techniques (e.g., scanning the environment via social media or other intelligence for
weak signal detection) to distinguish between a true crisis and that engineered to impose draconian controls
restricting individual liberty, the foundation of American self-government. This is important for two reasons: 1) the
preservation of individual freedom and 2) centralized power and the associated limits placed on independent thought
and action degrades the ability of a nation and its people to be resilient in the face of natural catastrophes, external
threats or new opportunities. A very pernicious situation develops in which people become more dependent on
centralized power, which by its nature fosters entrained (non-independent) thinking and is slow to respond (e.g.,
Hurricane Katrina in 2005). Dealing with complex situations then becomes more problematic. Innovation declines as
agility and risk taking decrease under the weight of political constraints and ideology. For example, government
selection of a preferred technology (e.g., windmills and solar panels) removes the incentives to explore other
possibilities. This weakens a nation's competitive advantage and its ability to effectively respond to new discoveries.
16
KNOWN-KNOWABLE Boundary
Item 3: incremental improvement. This is where the scientific method would commonly
operate. “The scientific method is the process by which scientists, collectively, and over time,
endeavor to construct an accurate representation of the world.” – Frank Wolfs, Professor of
Physics, University of Rochester
Scientific Method:
- Name the problem or question
- Form an educated guess (hypothesis) of the cause of the problem and make predictions based
upon the hypothesis
- Test your hypothesis by doing an experiment or study (with proper controls)
- Check and interpret your results
- Report your results to the scientific community and make your data freely available for others to check
Scientific inquiry and discovery will also use intuition, hunches, and other complex behaviors on
the part of individuals.
COMPLICATED-COMPLEX Boundary
Item 4: Exploration. Selective movement into the complex domain and the formation of selforganizing networks promotes the conditions necessary for innovation to occur. Trust is a
necessary pre-condition for this movement as centralized control is weakened or absent. The
shadow organization (“how things are really done”) is found here. Communities of interest
forming loosely governed social networks in an organization is an example.
Item 5: Just-in-time (JIT) transfer. The useful knowledge acquired from safe-fail experimental
environments, social networks, RSS feeds, etc. is transferred to the KNOWABLE domain on a just
in time basis (i.e., when needed). Cognitive kanban methods can facilitate this important
transfer and will be discussed later.
17
COMPLEX-CHAOTIC Boundary
Item 6: Swarming. Movement from chaotic->complex->knowable. Easier to move from chaos to complexity than
from chaos directly to known (ordered). One establishes multiple attractors or swarming points in the chaotic domain
around which un-order can instantiate itself. Set up the equivalent of a bright light and see who comes: web forum,
book club, open competition, lecture series, etc. Humans evacuating from a crowded theatre would find directions:
“move to the red lights above the exit doors” (multiple attractors) more useful that “move to the back of the theatre”
which may not be known knowledge in a smoke-filled theatre. (Kurtz & Snowden, p. 477)
Item 7: Divergence-convergence. Movement back and forth between chaotic and complex can be used to disrupt a
complex system and can promote innovation and new ways of looking at existing problems. This is easier across this
boundary than across the Complicated-Complex boundary. Self-organized networks in the complex domain find it
easier to be disrupted, move across into chaotic, and then reform with new members in the complex domain.
The Netflix Prize contestants team formation, disruption and re-forming in 2009 exhibited this. Teams and individuals
formerly competing against one another realized that they stood a better chance by reforming and combining their
work in new and unique ways. This resulted in several breakthroughs.
“. . . Better solutions come from unorganized people who are allowed to organize organically. But something else
happened that wasn’t entirely expected: Teams that had it basically wrong — but for a few good ideas — made the
difference when combined with teams which had it basically right, but couldn’t close the deal on their own.
“. . . “At first, a whole lot of teams got in . . . and then it started slowing down, and we got into year two. There was
this long period where they were barely making progress, and we were thinking, ‘maybe this will never be won.’ Then
there was a great insight among some of the teams — that if they combined their approaches, they actually got
better. . . . In combination, the teams could get better and better and better.” - How the Netflix Prize Was Won
(22Sep09) http://www.wired.com/epicenter/2009/09/how-the-netflix-prize-was-won/
Disruption of entrained thinking is desirable for many reasons. As demonstrated with the 18th century Longitude
Prize the refusal of experts (with their ‘precious’ credentials) to recognize that a blue-collar clock maker could have
the solution held up the award and resulted in more societal costs and human suffering. Effective management will
disrupt perceived wisdom and the common context of expertise in order for new ideas to emerge.
18
19
Complexity cannot be modeled and requires other forms of resolution. This may include
measurements, diverse viewpoints, inclusion of marginalized or fringe opinions and other
techniques noted during the Cynefin Complex domain discussion. Fields as diverse as
statistics, engineering, architecture, mathematics, etc., have a stake in correcting the abuse
of models and preserving the integrity of their discipline.
The use of models in a complex space facilitates the fabrication and falsification of data as
assumptions can easily be gamed to provide the output wanted. Conclusions then become
premises.
Models are only valid in those areas in which you have collected data points to validate it,
i.e., the Cynefin known or knowable domains. They should never be used to extrapolate. All
assumptions used in models must be made clear to decision makers.
•Financial models used to manage a complex financial system failed to predict a housing
price collapse.
•Global warming models used to describe a complex planetary climate system failed to
predict global cooling from 2001-2009. These models were used to extrapolate future
temperature increases and were intentionally rigged to misrepresent outputs.
20
“The problem was this: The policy makers knew how to pull economic levers, but they
did not know how to use those levers to affect social psychology. . . . The nation had
essentially bet its future on economic models with primitive views of human behavior.
The government had tried to change social psychology using the equivalent of leeches
and bleeding. Rather than blame themselves, Americans directed their anger toward
policy makers and experts who based estimates of human psychology on mathematical
equations.“ - The Worst-Case Scenario, New York Times, Feb 2009.
http://www.nytimes.com/2009/02/13/opinion/13brooks.html
Austrian economist Frederick Hayek, “The Use of Knowledge in Society” (1945) This
paper basically said that Known or Knowable economic approaches (cause and effect are
linked) are inadequate to manage a COMPLEX domain of price signals, competition and
consumer decisions. The market is very much a complex adaptive system in which agents
(consumers) affect the system (market) and co-evolve with it. When prices rise they buy
less which places pressure on rising prices. Monopolies and excessive government
regulations are attempts to manage a COMPLEX space with SIMPLE and COMPLICATED
approaches. This causes misery all around. Focus groups do NOT provide an adequate
narrative (skewed by the facilitator's bias and groups' willingness to give facilitator what
they perceive facilitator wishes to hear).
Only millions acting in their self-interest provide the IMPLICIT micro-narrative expressed
in buying or NON-BUYING decisions. These can be aggregated AFTER the fact but can
never provide a prediction of future events. Government top down economic edicts
ALWAYS end up with UNINTENDED CONSEQUENCES due to the utter inability to know
everything.
21
In the 1980s Wall Street began using software models and highly sophisticated formulae to quantify risk. The
Gaussian copula function was used for years to make lots of money for lots of people by determining
correlations between highly complex financial entities. Yet these correlations are highly unstable. When house
prices went negative on a large scale the underlying assumptions in the equation rendered it invalid.
“Bankers should have noted that very small changes in their underlying assumptions could result in very
large changes in the correlation number. [indication of a COMPLEX domain] They also should have noticed
that the results they were seeing were much less volatile than they should have been—which implied that the
risk was being moved elsewhere. Where had the risk gone? They didn't know, or didn't ask. One reason was
that the outputs came from "black box" computer models and were hard to subject to a commonsense smell
test. Another was that the quants, who should have been more aware of the copula's weaknesses, weren't the
ones making the big asset-allocation decisions. Their managers, who made the actual calls, lacked the math
skills to understand what the models were doing or how they worked. They could, however, understand
something as simple as a single correlation number. That was the problem.. . .
“Nassim Nicholas Taleb, . . .is particularly harsh when it comes to the copula. “People got very excited about the
Gaussian copula because of its mathematical elegance, but the thing never worked," he says. "Co-association
between securities is not measurable using correlation," because past history can never prepare you for that
one day when everything goes south. "Anything that relies on correlation is charlatanism."
Recipe for Disaster: The Formula That Killed Wall Street, (Feb 2009)
http://www.wired.com/print/techbiz/it/magazine/17-03/wp_quant
NOTE: Hiding behind all this complexity was a massive con job by globalist bankers and accomplices in the
U.S. government.
Dylan Ratigan explains the con job on MSNBC, 09 April 2010
http://www.youtube.com/watch?v=Gwm0ESZJSRI
The financial meltdown wasn't a mistake – it was a con, London Guardian, 18 April 10
http://www.guardian.co.uk/business/2010/apr/18/goldman-sachs-regulators-civil-charges
22
Man-made global warming proponents assume changing one thing (CO2) will affect global
temperature. CO2 is only 0.04% of the atmosphere and only 3% of that is anthropogenic
(man-made). Natural water vapor causes 95% of the greenhouse effect. If the atmosphere
was a 100 story building, our CO2 contribution would be equivalent to the linoleum on the
first floor.
Dr. Ball, environmental consultant and former climatology professor at the University of
Winnipeg, Canada summarized this erroneous focus on one small part of an extraordinarily
complex system with this apt metaphor from his presentation at the International
Conference on Climate Change (ICCC) in 2008:
http://web.archive.org/web/20110718035640/http://www.heartland.org/bin/media/newyork08/PowerPoint/Monday/ball.ppt
"My car is not running very well, so I’m gonna ignore the engine which is the sun
and I’m gonna ignore the transmission which is the water vapor and I’m gonna look
at one nut on the right rear wheel which is the human produced CO2. The science is
that bad.“
“An important feature of complex systems is that we don't know how they work. We don't
understand them except in a general way; we simply interact with them. Whenever we think
we understand them, we learn we don't. Sometimes spectacularly.” - Michael Crichton
CO2 was chosen by politicians and others propounding this error because it is exhaled by
every human and animal and is an integral part of energy generation using abundant fossil
fuels. Therefore a tax on CO2 will generate the most money for the bankers.
23
Source: “Climategate: Caught Green-Handed!” Christopher Monckton of Brenchley, 07 Dec 2009
http://scienceandpublicpolicy.org/monckton/climategate.html
The spline-curve plots the monthly mean of the satellite lower-troposphere anomalies published by Remote
Sensing Systems Inc. and by the University of Alabama at Huntsville. Beneath the spline-curve, the bright red
straight line, the least-squares linear regression trend on the data, shows a (largely-unreported) global cooling
for eight years at a rate equivalent to 1.2 F°/century. The pink zone shows the UN's computer models projected
range of equilibrium warming rates. Within this zone, the pale pink region represents one standard deviation
either side of the UN’s central estimate of 7 F° warming to 2100.
The ground-based measurements have been corrupted in numerous ways and can no longer be trusted.
Al Gore stated in "An Inconvenient Truth" (2006) that the relationship between CO2 and temperature was
complicated but that CO2 increases PRECEDE temperature changes. The CO2 and temperature chart used by
Gore confuses correlation with causation, a common outcome when simple domain techniques are used in an
attempt to explain or predict complex or chaotic domain behavior. In reality, temperature increases precede
CO2 increases by some 800 years. As the oceans heat they release dissolved CO2. (Source: Statement of
William Happer, Professor of Physics, Princeton University, before U.S. Senate Environment and Public Works
Committee, Feb 2009, p. 6).
http://epw.senate.gov/public/index.cfm?FuseAction=Files.View&FileStore_id=84462e2d-6bff-4983-a574-31f5ae8e8a42
Why Global Warming Predictions by Climate Models are Wrong, Dr. Ray Spencer, May 2009
Dr. Roy Spencer has studied the climate for years and leads a NASA team that monitors daily measurements of
the earth's temperature via satellite (the most accurate). He states that the complexity and chaos inherent in a
changing climate and the earth's self-regulating and inter-dependent systems are not understood or are
minimized in the IPCC computerized climate models. Cloud formation in particular is a key variable as it reflects
sunlight. Once again, confusion between cause and effect (indicative of simple domain approaches being used
to explain a complex domain) is mentioned
http://www.drroyspencer.com/2009/05/a-layman’s-explanation-of-why-global-warming-predictions-by-climate-models-are-wrong/
24
Prominent Physicist Freeman Dyson has referred to climate models as “rubbish.“ Dyson is a
Professor Emeritus of Physics at the Institute for Advanced Study at Princeton University, a
fellow of the American Physical Society, a member of the US National Academy of Sciences,
and a fellow of the Royal Society of London. Dyson is blunt in his criticism of climate models,
mocking “the holy brotherhood of climate model experts and the crowd of deluded citizens
who believe the numbers predicted by the computer models.“
Source:
http://www.climatedepot.com/a/1813/US-Government-Scientists-Shock-Admission-Climate-Model-Software-Doesnt-Meet-the-Best-Standards-Available
"I have studied the climate models and I know what they can do. The models solve the
equations of fluid dynamics, and they do a very good job of describing the fluid motions of
the atmosphere and the oceans. They do a very poor job of describing the clouds, the dust,
the chemistry, and the biology of fields and farms and forests," - Freeman Dyson
----------------------------“Climate Modeling is not ‘science’, it is computerized Tinker Toys with which one can
construct any outcome he chooses.” - James Peden, atmospheric physicist, Oct 2008.
----------------------------Revenge of the Computer Nerds, Dec 2009
http://www.americanthinker.com/2009/12/revenge_of_the_computer_nerds_1.html
Documents examples of so-called ‘fudge factors’ used to rig computer programs in order to
falsely predict global warming.
25
Source: http://bishophill.squarespace.com/blog/2009/11/20/climate-cuttings-33.html
In a manner very similar to the Longitude Prize discussed earlier, a small number (15-25) of academics and
government-funded researchers in the U.S. and England dismissed and marginalized climate realists for over 13
years. They corrupted the peer review process by pressuring journal editors and reviewers to avoid or criticize
papers skeptical of global warming. FOIA requests were stonewalled or ignored. They refused to make their
data available for review by others and made a complete mockery of the scientific method.
An unknown whistleblower leaked over 60 MB of emails and computer code onto the Internet on 20 Nov 2009.
It was first sent to the BBC but they did nothing. This is the greatest scientific scandal of our lifetime because
those propounding it expected the entire world to pay the banks (via taxes, cap and trade or carbon offsets) for
the right to emit carbon in any form. Government agencies at various levels are still using this thoroughly
discredited hoax as an excuse to raise taxes or further regulate all types of behaviors.
The Climategate Analysis (Jan 2010) by Dr. John P. Costella (PhD Physics) revealed “shocking misconduct and
fraud.” Dr. Costella’s 149-page analysis examined 1,079 leaked emails (from 1996 to 2009) and 72 other
documents from the Climatic Research Unit (CRU) at the University of East Anglia. The CRU was a primary input
to the UN IPCC reports. Costella’s analysis has been widely accepted by all sides of the global warming debate
as a faultless assessment. You may access his report at two locations:
http://scienceandpublicpolicy.org/reprint/climategate_analysis_updated.html
http://www.assassinationscience.com/climategate/
The Climategate Poster summarizes 30 years of deception, entrained thinking, rigged computer code, and
cherry picking of data in a Google map-like experience. Use the controls in the lower right to go full screen and
zoom in and out. Requires Microsoft Silverlight (free multimedia player similar to Flash) to be installed on your
computer.
http://www.andyhcoates.com/climategate/
PDF version of the Climategate Poster:
http://wattsupwiththat.com/2010/02/02/jo-nova-and-climategate-30-years-in-the-making-edition-1-1/
26
Innovation or weak signals warning of threats can be suppressed by societal pressure to conform or
entrained thinking of the ‘experts.’
Researcher Condemns Conformity Among His Peers, New York Times, 23 July 2009
http://tierneylab.blogs.nytimes.com/2009/07/23/researcher-condemns-conformity-among-his-peers/
Dr. Shiller was concerned about what he saw as an impending house price bubble when he served as an adviser
to the Federal Reserve Bank of New York up until 2004.
“So why didn’t he burst his lungs warning about the impending collapse of the housing market? “In my position
on the panel, I felt the need to use restraint,” he relates. “While I warned about the bubbles I believed were
developing in the stock and housing markets, I did so very gently, and felt vulnerable expressing such quirky
views. Deviating too far from consensus leaves one feeling potentially ostracized from the group, with the risk
that one may be terminated.”
“Conformity and group-think are attitudes of particular danger in science, an endeavor that is inherently
revolutionary because progress often depends on overturning established wisdom. . . .
“The academic monocultures referred to by Dr. Bouchard are the kind of thing that sabotages scientific
creativity. . . .
“What’s wrong with consensuses is not the establishment of a majority view, which is necessary and legitimate,
but the silencing of skeptics. “We still have whole domains we can’t talk about,” Dr. Bouchard said, referring to
the psychology of differences between races and sexes. “
Federal Reserve suppressed housing-bubble dissent in 2004
http://www.huffingtonpost.com/2010/05/03/greenspan-wanted-housing_n_560965.html?view=print
“As top Federal Reserve officials debated whether there was a housing bubble and what to do about it, thenChairman Alan Greenspan argued that dissent should be kept secret so that the Fed wouldn't lose control of
the debate to people less well-informed than themselves.
“We run the risk, by laying out the pros and cons of a particular argument, of inducing people to join in on the
debate, and in this regard it is possible to lose control of a process that only we fully understand," Greenspan
said, according to the transcripts of a March 2004 meeting.”
Yet Greenspan admitted in the 2008 Canada.com interview that their models failed them and they
really didn’t understand the complexity of the market and what was happening underneath their
assumptions. Dissenting views are key to avoid collapse from Simple to Chaotic.
27
Cognitive kanban: keep known and knowable information close at hand.
A cognitive kanban approach relies on the unique ability of human intelligence to examine
fragmented information and discover patterns. Coupling this with the heuristic approach
found in abductive logic (using a “hunch” or “intuition”) is quite powerful. Abductive logic
is more closely related to human cognition than other reasoning processes. This form of
reasoning selects the best explanation (from a set of possible explanations) to fit a set of
observations. Spies, detectives, and intelligence analysts will use abductive logic to
understand and explain the real world based on a set of observations. Abductive logic does
not constitute formal proof but is very useful early in an investigation or analysis.
Abductive logic is part of the process that arrives at a hypothesis.
http://en.wikipedia.org/wiki/Abductive_reasoning
28
If pattern recognition helps to improve decisions, then environmental scanning will help you to detect
patterns. Increasing interdependency means you must be aware of other industries besides your own.
http://emergentbydesign.com/2010/04/11/essential-skills-for-21st-century-survival-part-2-environmental-scanning/
This cognitive disposition shares properties with an OODA Loop (Observe, Orient, Decide, Act).
The concept map illustrates an environmental scanning construct that expands your peripheral vision and
helps to avoid tunnel vision (silo thinking). It allows you to discover, archive and re-use known and
knowable information WITHOUT more email. This is a kanban approach for intellectual assets. You keep
knowledge close-at-hand and PULL on demand. Keys tool to accomplish this include:
RSS feeds and RSS feed reader
•RSS feeds have been around since 1999. They allow you to speed read the web and are the greatest
Internet advance since the web browser.
•VIDEO: “RSS in Plain English” is a short, easily understood introduction to the time-saving value of RSS
feeds. It explains the big picture and the mechanics of adding a feed from a web site to your feed reader.
http://www.commoncraft.com/rss_plain_english
•Install a RSS feed reader and scan the environment of expert knowledge in fields of interest. SharpReader
is good. http://www.sharpreader.net/
Bookmark and personal information manager (PIM)
Use a combination bookmark manager and PIM to store high value information Compass is a good one
http://www.softgauge.com/compass/
Desktop search
Use desktop search to find and re-use information and knowledge. Copernic or X1 are recommended.
29
Use Cynefin as a validation technique
The Cynefin framework can function as a VALIDATION method to help identify unethical
actions or an inadequate basis for decisions by examining the domain characteristics. For
example, the earth’s atmosphere is an UNORDERED system (resides on boundary of
COMPLEX and CHAOTIC domains). Using computer algorithms that assume a closely linked
cause and effect (higher CO2 equals higher temperature) is an invalid approach for
understanding UNORDERED systems (as the Cynefin literature has indicated since 2002).
Incorporate Cynefin techniques into leadership decision making
The principles discussed in this paper are useful by all but should be especially studied by
those in positions of authority. Of special concern is the concentration of decision making in
Washington D.C. that has been increasing since the early 1970s by both Republican and
Democrat administrations. Dissenting and diverse viewpoints are being increasingly shut out
and those with such viewpoints are now (2010) being referred to as dangerous or labeled as
potential terrorists. Not only does this fly in the face of American traditions and
Constitutional freedoms it is the exact opposite of the open discussion needed to improve
decisions and spark innovation. It is obvious that improvements in dealing with complexity
are needed at all levels of our society.
30
Contact information
Michael Sivertsen
Systems and Software Engineer
Lockheed Martin Aeronautics Company
Fort Worth, Texas 76101
817-777-5388
michael.j.sivertsen@lmco.com
Employer shown for affiliation purposes only.
31
32
In August 2009, the story of a worldwide research and development effort that will increase revenues for
decades made headlines. Netflix was able to "hire" 5,196 teams of researchers from 186 countries for only $1
million. This event indicates that the innovation needed by your organization can now come from the outside
as well as the inside. Managing this type of environment requires management techniques appropriate to
complexity. Netflix also provided progress prizes (two $50,000 awards) during the three year competition as a
means of monitoring emergence and providing feedback. This is an example of situating a network.
"The biggest lesson learned, according to members of the two top teams, was the power of collaboration. It
was not a single insight, algorithm or concept that allowed both teams to surpass the goal Netflix . . . set nearly
three years ago: to improve the movie recommendations made by its internal software by at least 10 percent,
as measured by predicted versus actual one-through-five-star ratings by customers. Instead, they say, the
formula for success was to bring together people with complementary skills and combine different methods of
problem-solving." - New York Times (July 2009)
http://www.nytimes.com/2009/07/28/technology/internet/28netflix.html
Netflix Prize winner announced 21 Sep 2009 http://www.netflixprize.com/
Seven engineers, mathematicians, and computer scientists managed to improve the Netflix recommendations
by 10 percent. Hiring seven people for three years at a $100,000 each would have cost far more – and how to
know if you had picked the right seven ahead of time?
Over 51,000 contestants from over 100 countries submitted entries. Winning team was from New Jersey,
Montreal, Israel, and Austria.
BellKor's Pragmatic Chaos winner page http://www2.research.att.com/~volinsky/netflix/bpc.html
What is interesting here is that an algorithm predicting complex behavior (movie preferences) was the goal.
Clearly individual human decisions cannot be predicted by a computer or a formula. Predicting choices in the
aggregate using millions of historical subscriber choices was possible. Distributed cognition and the combining
of various teams and individuals and numerous statistical approaches enabled the winners to meet the contest
parameters. The Wired article notes that the approaches fartherest from the mainstream proved most helpful
in the end. An example of outliers and weak signals proving valuable.
http://www.wired.com/epicenter/2009/09/how-the-netflix-prize-was-won/
33
In 1707, a British fleet ran aground and 2,000 died because they were unable to determine
their position at sea. The British government subsequently funded the Longitude Prize ($4.5
million in today's dollars) to find an accurate method of measuring longitude. This prize was
awarded in 1773 to John Harrison, a self-educated clockmaker. Harrison developed a method
of using a precision clock which kept the time of the home port and did not rely on
astronomical observations. This was combined with local time, using the height of the sun, to
calculate longitude. (For every 15° east, the local time moves one hour ahead. Similarly,
travelling West, the local time moves back one hour for every 15° of longitude. Therefore, if
we know the local times at two points on Earth, we can use the difference between them to
calculate how far apart those places are in longitude, east or west.)
The entrenched government and scientific community rejected Harrison’s chronometer
approach for 12 years (1761 to 1773) because they refused to believe physical position could
be determined without astronomical observations. In particular, a university educated
astronomer named Nevil Maskalyne, was convinced by training and background that only
observations of the stars could determine longitude. He got himself appointed to the Board
that was composed of astronomers, not engineers, and thus supported one of their own.
This consensus against one individual (a common working man with no university degree or
published papers and other ‘proof’ of expertise) forced King George himself to finally
intervene and award Harrison the prize. The film Longitude (2000) describes this effort to
improve physical findability along with resistance from ‘the experts.' It is worth watching.
The entrained thinking on the part of experts that often blocks innovative thinking is obvious
in the story of the Longitude Prize.
Complete background http://www.squidoo.com/longitude
34
Working sculpture at Canary Wharf England. Ironically posted at a roundabout but not used
to control traffic.
YouTube video
http://www.youtube.com/watch?v=ncjO3s8iD5o
35
Decision making is challenging as we never have all the information needed.
Sense-making is related to what the military calls situational awareness. The cockpit of a F-16
is designed to provide the pilot with maximum situational awareness.
Cognitive Edge practitioners trained in the use of the Cynefin framework and the associated
SenseMaker software use self-indexed narratives collected from thousands of individuals and
represented in a fitness landscape (shown on the right). This provides a quantitative measure
while allowing decision makers the ability to drill into the individual narrative. In this way
computers and software are used to augment (but not replace) our uniquely human abilities
of story telling and pattern identification.
SenseMaker Suite software, http://www.sensemaker-suite.com/index.htm
Cognitive Edge applications
•Improving mine safety (Feb 2009), http://www.narrativelab.co.za/taxonomy/term/51
•Electric utility safety project (April 2010) http://www.cognitive-edge.com/blogs/news/2010/04/electric_utility_organisation.php
David Snowden also discusses medical care applications (UK National Health Service) and
rapid discovery of Pakistani attitudes towards the West in several of his podcast lectures.
36
Many examples of failed management approaches in a complex environment can be found in the 100-year
history of Yellowstone National Park. The constantly changing, non-linear, domain of the natural environment is
ill served by simple approaches to decision-making that assume a closely linked cause and effect. This fact
underscores many examples of ill-defined and immature environmental policies and the resultant
environmental catastrophes. Dr. Michael Crichton's “Complexity Theory and Environmental Management”
(2005), explains in detail why complexity theory is essential to environmental management, and uses
Yellowstone National Park as an example of what NOT to do.
http://web.archive.org/web/20080122022806/http://michaelcrichton.com/speech-complexity.html
“As the story unfolds, it becomes impossible to overlook the cold truth that when it comes to managing 2.2
million acres of wilderness, nobody since the Indians has had the faintest idea how to do it. And nobody asked
the Indians, because the Indians managed the land very intrusively. The Indians started fires, burned trees and
grasses, hunted the large animals, elk and moose, to the edge of extinction. White men refused to follow that
practice, and made things worse. Now, if we are to do better in this new century, what must we do differently?
“In a word, we must embrace complexity theory. We must understand complex systems. We live in a world of
complex systems. The environment is a complex system. The government is a complex system. Financial
markets are complex systems. The human mind is a complex system . . . By a complex system I mean one in
which the elements of the system interact among themselves, such that any modification we make to the
system will produce results that we cannot predict in advance.
“Furthermore, a complex system demonstrates sensitivity to initial conditions. You can get one result on one
day, but the identical interaction the next day may yield a different result. We cannot know with certainty how
the system will respond.
“Third, when we interact with a complex system, we may provoke downstream consequences that emerge
weeks or even years later. We must always be watchful for delayed and untoward consequences.
“The science that underlies our understanding of complex systems is now thirty years old. A third of a century
should be plenty of time for this knowledge and to filter down to everyday consciousness, but except for
slogans- like the butterfly flapping its wings and causing a hurricane halfway around the world- not much has
penetrated ordinary human thinking.”
Wolf introductions (2010): re-introduction of the WRONG sub-species of wolves infected with a parasitic
disease by the Federal government is devastating big game herds in Western states. Vast amounts of scientific
literature were ignored by ‘scientists’ in this complex environment.
http://web.archive.org/web/20100926233839/http://outdoornewsservice.com/odpkg/news/News_04-01-10.html
37
A phase shift in knowledge management theory and practice was introduced in a 2002 paper by
David Snowden entitled, "Complex Acts of Knowing: Paradox and Descriptive Self-Awareness."
http://www.cognitive-edge.com/articledetails.php?articleid=13
Knowledge was not to be considered as an object, like ones and zeros in a data set, which could be
downloaded or uploaded. It was now regarded as a flow between keepers of the knowledge (people)
and could be described and managed through discoverable patterns. One no longer connects the
dots, you discover the patterns. For example, many people think that intelligence is "connecting the
dots." A simple characterization is:
- data: random dots
- information: organize the dots
- knowledge: connect the dots
It is quite impossible as this simple figure illustrates. Rather than trying to perform an impossible task
we need to look for patterns, something which the human brain is naturally good at and which is at
the heart of sense-making.
A physics analogy may help to understand the importance of this new paradigm. When quantum
mechanics was discovered around 1900, scientists realized that classical Newtonian physics was
unable to describe the behavior of particles at the atomic and sub-atomic level. In fact, Newtonian
physics is now regarded as a special case of quantum mechanics. New words, equations and methods
were developed in the 20th Century in order to work within the field of quantum mechanics and
extend the limits of human knowledge.
In a similar manner there is now a need for a new phase of knowledge discovery and utilization, one
that will extend our ability to leverage the vast arena of human cognition in a much more effective
fashion. This new phase has its own vocabulary, techniques and methods. We will see, in a manner
analogous to quantum mechanics subsuming Newtonian physics, that this new approach subsumes
machine and information age methods while extending our ability to discover and manage additional
forms of human knowledge. We need to develop a ‘quantum mechanics of the mind’ in which we
deal effectively with uncertainty and complexity.
38
The Cynefin framework can be used to understand and then apply appropriate human interactions. Using naturalistic processes
that are more closely aligned with the cognitive patterns of the human brain results in more effective knowledge management,
plus, people LIKE it more. The Cynefin Framework recognizes the natural pattern-making ability of the human brain and works
with it rather than at cross purposes.
As an example, consider the difference between coordination, cooperation and collaboration. Shawn Callahan from
Anecdote.com illustrates the most effective means of interaction within each Cynefin domain. Once you have allowed the
environment to reveal itself and have placed it in a domain (parts of your issue may fit into more than one domain) this
illustration shows the most appropriate means of interaction. Excerpted from “When should we collaborate?” (Mar 2008)
http://www.anecdote.com.au/archives/2008/12/when-should-we.html
Simple-COORDINATE: . . .Organising performance reviews is a good example. You can predict with confidence the end result of
the activity. In these cases co-ordination is useful.
Complicated-CO-OPERATE: still a relationship between cause and effect but experts have to work at discovering that
relationship and there is often a range of possible answers. Co-operation is effective because there is often a clear end goal in
mind but you need the combined forces of a range of people to achieve it.
Complex-COLLABORATE: this domain is characterised by causes and effects that are so intertwined and intricate that things only
make sense in hindsight. People may say: “Ah, the reason that happened was because ...”, but if you rewind the tape of what
just happened and play it again, you get a different outcome; rewind and play again, and yet another outcome. This
phenomenon occurs because in complex situations everything is so interconnected that a small change in one part of the system
can have inordinate impact somewhere else, and vice versa. The system is unpredictable in detail, yet we can discern patterns.
Designing and implementing a new performance management approach is complex because, regardless of how much analysis
we do before putting it into practice, we won’t know how it’s going to work in detail. It is in these complex situations that
collaboration comes to the fore. [e.g., PM competency assessment tool I developed in 2003] Collaboration works well for
complex situations because the style of working collaboratively matches the nature of the issues that complex situations pose.
Complexity is unpredictable, and collaborating is adaptable; complexity is messy – it’s difficult to work out the question, let
alone the answer – and collaborating involves bringing together a diversity of people and talents to improvise and test possible
approaches, all learning as you go. Complexity offers unique and novel conundrums, and collaboration draws on a deep
foundation of trust to that fosters creativity and delivers innovations.
Chaos-ACT. Impossible to discern a relationship between cause and effect. The best approach in this domain is simply to take
action. Paradoxically it really doesn’t matter which group style is used here, as any way of working will either create
opportunities in the complex space where collaboration can take effect, or push the situation into the simple domain where a
co-ordination approach is effective.
Callahan concludes: “With the Cynefin framework as a guide, we can better align the type of group work with the nature of the
issue at hand. Collaboration is not the best approach in every situation and let’s not fall into the trap of thinking of it as a
panacea. Sometimes it’s simply more effective to issue a direction to get the job done when the job is simple or complicated. It’s
when things are truly complex that collaboration is most effective, and the reality is that the world is becoming more connected,
faster moving and therefore more complex by the minute. Collaboration will have a growing role to play in every organisation.”
39

Cognitive Kanban - Lean Systems Society

Transcription

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