"Complicated" vs. "Complex"

Someone asked for comment, I offered it.  The background:  A gentleman who makes a living "reducing complexity" for IT systems keeps running into some of us on Twitter who study complexity.  You can imagine the entertaining exchanges, which led to his posting these observations on his LinkedIn group. The ask:

There is a group of complexity aficionados that criticize my use of the word "complexity." In general, these are folks who are influenced by the Cynefin framework that considers complexity and complicated to be different attributes of a system. I reject their use of the word "complicated" to describe what I call "complex" for three reasons.

First, complicated describes a state of mind of the observer, not the observed. To me, my car is complicated. To my mechanic, it is not complicated. Yet the car hasn't changed.

Second, complicated has no obvious relationship to simple. In my mind, complexity and simplicity must be closely related in the same way that heat and cold are related. Cold is the absence of heat. Simplicity is the absence of complexity. This relationship is absent in the Cynefin-like understandings.

Third, my use of the words complex and complexity conform to standard usage of the words.

That my position. What do you think?

My answer:

It is difficult to know where to start in responding. There are not only entire graduate courses ( on the topic of complexity, there are actual institutions involved in related research. ( Rather than attempt to capture all of the works from Ashby (1962) to Waldrop (1992) - all of which predate the Cynefin framework - I will try to address the main errors I see in your thesis. (I decided to include a select bibliography in case anyone who comes across this thread is curious enough to follow up.)

First, unless you refer to your physician as a “biology aficionado,” your language regarding scholars strikes me as somewhat odd. In my view, someone who pursues higher education is something other than an aficionado. More importantly, it appears to you that the people who contest your view above emerge from some curious cult of Cynefin practitioners who cling to definitions to support our unique worldview. This is probably the chief error in our conversations - believing that Cynefin somehow provides the intellectual framework for our understanding of complexity. Cynefin is a sense-making framework that leverages natural systems understanding - it stands on the shoulders of giants. (My bibliography below contains only one reference to my friend and mentor David Snowden.)

To your three points:

1) To your mechanic, your car, unless it is 20 years old or so, is actually quite complicated thanks in part to pervasive embedded computing. This is why he uses diagnostic technologies to understand its current state. Complicated systems are the playing field for domain experts, but that does not mean these experts consider their systems as simple.

2) Complicated has a remarkably obvious relationship to simple. Cause and effect are related in these ordered systems - and system behavior is predictable as a result. In your mind, complexity and simplicity are related like heat and cold. Standard usage aside, complexity is not some spice added to a complicated system - that mucks up the gears when it reaches a certain threshold. (I’m reminded that Aquinas famously used the heat and cold analogy to discuss how evil is the absence of god.) But analogies aren’t proofs - generations of systems science are not discarded because of a tidy analogy. There actually are relationships among systems in Cynefin, but not as you cast it above.

3) This is what you’ve repeated in past conversations. It’s how most people think of complex - and you are comforted because you conform to ‘standard usage.’ Pardon me, but I’m reminded the common approach to medical problems 100 years ago involved leeches. In my view, “standard usage” is an insufficient understanding for those who seek to advance a practice.

Overall, it is noble work to emphasize simplicity for IT systems. I was honored to support the National Military Command Center years back, and can recall the massive tangle in trying to understand all the systems that were introduced into that facility over time. Different functional requirements, different budgets, different departments, all installing systems over a few decades with no obvious design authority. But among that mess, no new systems emerged. Nothing became sentient and engaged in semi-autonomous or autonomous behavior. Systems did not exhibit any behavior that exceeded their original design. The facility, a system of systems, was incredibly complicated, but demonstrated none of the characteristics of a complex adaptive system. One can pursue this noble work without introducing terminology that confuses more than it illuminates.


[edit - added bibliography]

I then posted a select bibliography, because this gentleman does not appear to be familiar with the canon of works that go back generations. A subset of authoritative works:

Anderson, Philip, Gérard Cachon, and Paul Zipkin, “Complexity Theory and Organization Science,” Organization Science, Vol. 1, No. 3, 1999, pp 216-232

Asbhy, Ross, An Introduction to Cybernetics, London UK: Chapman and Hall, Ltd., 1957

Axelrod, Robert and Michael Cohen, Harnessing Complexity: Organizational Implications of a Scientific Frontier, New York: Free Press, 1999

Dooley, K. (1996), "A Nominal Definition of Complex Adaptive Systems," The Chaos Network, 8(1): 2-3.

Fromm, Jochen. The Emergence of Complexity. Kassel, GE: Kassel University Press, 2004.

Gell-Mann, Murray. The Quark and the Jaguar: Adventures in the Simple and the Complex. New York, NY: Freeman, 1994.

Gleick, James, Chaos: Making a New Science, Penguin Press, 1988

Holland, John H. Hidden Order: How Adaptation Builds Complexity. Reading, MA: Addison-Wesley, 1995.

Holland, John H., Emergence: From Chaos to Order, Cambridge, MA, Perseus Books Group, 1998

Johnson, Steven. Emergence: The Connected Lives of Ants, Brains, Cities, and Software, New York: Touchstone, 2002

Juarrero, Alicia, Dynamics in Action: Intentional Behavior as a Complex System, Cambridge, MA: The MIT Press, 2002

Kauffman, Stuart, The Origins of Order: Self-Organization and Selection in Evolution, New York: Oxford University Press, 1993

Kauffman, Stuart, At Home in the Universe: The Search for Laws of Self- Organization and Complexity, New York: Oxford University Press, 1995

Lewin, Roger, Complexity: Life at the Edge of Chaos, Chicago, IL: University of Chicago Press, 1999

Lorenz, Edward, The Essence of Chaos, The Jessie and John Danz Lecture Series: University of Washington Press, 1996

Maxfield, Robert, “Complexity and Organization Management,” Complexity, Global Politics and National Security, David Alberts and Thomas Czerwinski (eds.), Washington, D.C., National Defense University Press, 1996

McKelvey, Bill, “What is Complexity Science? It is Really Order-Creation Science,” Emergence, Vol. 3, 2001, pp 137-157

Nicolis, Gregoire, and Ilya Prigogine, Exploring Complexity: An Introduction, W.H. Freeman and Company, 1989

Prigogine, Ilya, The End of Certainty: Time, Chaos, and the New Laws of Nature, New York, NY: Free Press, 1997

Snowden, David J., and Mary E. Boone. "A Leader's Framework for Decision Making." Harvard Business Review November 1, 2007: 69-76.

Stacey, Ralph D., Douglas Griffith, and Patricia Shaw. Complexity and Management: Fad or Radical Challenge to Systems Thinking? Complexity and Emergence in Organizations. Ed. Douglas Griffith Ralph D. Stacey, Patricia Shaw. London: Routledge, 2000.

Tsoukas, Haridimos. Complex Knowledge: Studies in Organizational Epistemology. Oxford, UK: Oxford University Press, 2005.

Waldrop, M. Mitchell. Complexity: The Emerging Science at the Edge of Order and Chaos. New York: Simon and Schuster, 1992.

Job-Killing Processes

I’ve been wrestling with a thought lately - if organizations are complex systems, and complex systems are continuously self-organizing, then why do we believe formal processes make these complex systems more efficient? Worse, when an organization is in need, why do we engage in process improvement - when what may be needed is process reduction or elimination? This is not the first paragraph to question process improvement, this is not some original Eureka moment.  This is a personal journey, and the enormity of the mistake is beyond what I had considered previously. Friends, more erudite than I, have used similar words before - but for some reason I’m realizing, only recently, a simple truth: the implications for the baseless faith in the machine-based approach to management and the firm are global and profound.

A process-heavy enterprise isn’t cold and impersonal - because humans are still warm and social.  Instead, a process-heavy enterprise creates the need for larger social networks.  Formal processes do not capture the natural evolving paths people take to confront their tasks.  In response, people do what is natural, they use their social network to navigate the workplace - looking inward to find others who have succeeded despite the process.  We know that excessive time spent focused inward leads to burned-out employees, who must work the “second eight” to comply with organizational reporting and the like.  On a larger scale, this wasted effort presents - at the limit - an opportunity cost for the enterprise as a whole.  Perhaps the path to efficiency is to set the conditions for processes to emerge at the point of need, rather than Six Sigma-ing the (majority of) tasks that require creativity and agility.

In the famous early mistakes in business process re-engineering, managers believed once their processes were “streamlined” and “documented” (and embedded in enterprise software tools), they could realize savings by reducing the number of humans.  For routinized tasks, this may be a reasonable assumption - however, what percentage of your workday is routine?  Look to your own environment - do you rely on your social network to find the informal work-arounds for corporate process?  When faced with a challenging problem, do you find solace in the documented process?

Work to Rule. In labor relations, there is a term called “work to rule.”  Simply stated, this means that union workers have a negotiating tool that enables them to paralyze an enterprise - by merely doing only what is considered ‘by the book.’  No creativity, no work-arounds, no focus on task accomplishment - just fealty to the process.  Consider this message:  the way to crash some enterprises is to do what is expected by procedure manuals and process charts.

Business Development. In one company, I observed a set process for preparing contract proposals:  with clear roles, authorities, assignments, formats, and process steps.  Chokepoints were established along the way, when “pencils” down would precede a murder board review to assess the quality of the proposal against the procurement specifications.  These comments were returned to the writing team, who would tackle their task anew. The information technology consisted of shared folders, and the writers laboring over each section would be required to post their documents in the appropriate folder at the required hour.  The work was intense and draining, writers were often unaware of each other’s work, and the review team invariably excoriated the team for the lack of a “single voice” or “storyline.”

In another company, the proposal response was visible at all times to the entire proposal team.  In a shared online space, the sections were worked in parallel, each writer able to observe the other’s ongoing work.  The team met daily to talk through issues, but kept in touch throughout the process through instant messaging and email. There were roles and authorities, assignments and formats here as well - but the process was determined by the writing team, and emerged and adapted based on the demands of the work and the schedule.  As the storyline evolved transparently, there were fewer surprises, people were able to lend value across the work throughout - and the end product was coherent and compelling.  This without a review team’s intervention.

Software Development. In software development, Agile methods are triumphing over waterfall or other linear methods - users are happier because their approach to their work changes as they learn what is possible from the technology solution.  The human and the software evolve together.  The old approach was to gather what people thought they needed, build the software according to specifications, and then train the humans to operate the solution.  There may be a correlation between how much training is needed and how disconnected the solution is from how people work.  When software methods allow the humans and technology to co-evolve, when humans are co-designing the solution during “development” - we seem to have happier humans.

The thoughts bouncing in my head now are:  what needs to be in place to allow for emergent processes? Formal process has a small place - compliance processes dictated by, for example, government regulation come to mind.  However, value-creating processes must emerge from the interaction of the work and the humans.  They cannot be formalized absent the humans or the situational context - if they are, then humans will circumvent them, creating a more inefficient enterprise... or follow them to the letter, and destroy value.  In a real sense, process improvement should be replaced by process enablement.  Let the approach to work emerge from the situational context.

Raising the Dial Tone, Part 2

(Part 1 is archived at Recently, Dennis McDonald offered that transparency and collaboration should be considered as efficiency measures in the Secretary of Defense’s initiatives.  A sharp comment to this post responded by detailing the dire state of the federal procurement system, offering that the system is “completely broken, not superficially but structurally and intrinsically broken.”  The response indicated that collaboration was at best an insufficient tool to address the pathology of the system:

“The problem isn’t a communication breakdown between the people issuing requirements and those implementing them. In most cases that communication is satisfactory. The problem is that most requirements issued on federal contracts are complete birdcage liner written by people who are either totally unqualified to design a product or produced by a process/workflow that is biased toward the most verbose form of mediocrity (i.e. reams of underwhelming requirements).”

In my field of KM, there are many well-intentioned professionals who seek to increase sharing and collaboration among and across their targeted workforces.  This is a good thing.  Following what we know of network science regarding loose connectors, the amplifying effect of linked networks is primarily achieved through loose connectors, also referred to as ‘weak ties.’  This is how disparate networks form ‘small worlds.’

What are these?  Consider the social or professional groups with which you primarily associate.  You may be central to the interactions within this group, helping keep the group together and moving forward.  Network scientists call this increasing network cohesion.

The problem?  You likely spend less energy meeting people with whom you have little in common.  At the edges of your group, there are these people. The folks who don’t show up at every happy hour.  The ones who are known, but not seen as core to the group’s identity.  The accountant who is also involved in community theater.  The developer who takes long weekends in the Spring to cycle across hundreds of miles with a like-minded group.  The conversations here, for the most part, do not involve their work.

But some do.  Sometimes the accountant meets a CFO while preparing for a community production - and banter leads to a greater understanding of each other’s professional perspective.  Sometimes the developer meets an entrepreneur over dinner in a small-town diner as they restoke the cycling fires.  The conversation exposes each to the challenges of the other.  Weak ties are established across two previously disconnected social networks.

Monday morning, the accountant and the developer are back at work.  During a project meeting, they sound different.  As if they’ve been reading a different manual, suddenly expressing views that are not usually heard in the tight group.  The CFO and entrepreneur likewise return to their labors with a new perspective, a new voice tucked away in their heads.  With new contacts in their smart phones.

Who knows what may come of these chance interactions?  We cannot know, but the theory and experience both tell us that diversity in a social system leads to a healthier, more sustainable system.  From a systems science perspective, open systems are more efficient - this openness is not simply a benefit resulting from increased collaboration, but a core characteristic of a healthy system.

Connecting disparate social networks is as important - I would argue more important in many cases - than connecting within the core group.  This is the reason we speak of openness of interaction, transparency of data, and collaboration across agencies and organizations.  We do not - or rather, we should not - pretend that connecting people and opening the conversation will solve thorny systemic issues (health care, national security, acquisition reform); but we should set expectations that a wider dial tone will lead to serendipitous innovation.  Establishing weak ties across disparate networks is the first step towards finding innovative solutions to these long-standing problems.

In our new march towards efficiency, let’s continue to raise the dial tone and open systems.  This is not an end state or resolution, but a necessary path towards shared goals.

Controlling the Invisible

Recently, I was engaged in a listserv conversation (remember those?) regarding the balance between standards-based enterprises and the need to engage creative talent who may bristle at standard processes. The conversation moved to the question of new processes and standards that respected the nature of complex organizations (rather than early 20th century bureaucracies), and I offered the rather offensive idea that we don't know enough to ponder the appropriate intervention strategy.

Expanding a bit here:

An organization I observed had a tenuous and negotiated balance between horizontal teams and client-focused divisions.  This balance was negotiated constantly, as new actors and situations questioned the flexible structures.  While the negotiations resulted in oscillation, the situation "worked," and value was created and delivered.

Over time, new leadership came on board, and began their due diligence to understand the "horizontals."  Using time-honored MBA tools, however, they could not grasp immediately the nature of the relationship.  As is appropriate, they established new financial and reporting controls for "visibility."  These collected data, however, did not reflect the negotiations or relationships - as classical business measures rarely do.  Thus armed with (incomplete) data, this new leadership determined new directions for the horizontal teams.  One can write the ending to this tale.  New directions meant new managers, who lacked the relationships that were invisible to the financial and reporting controls.

Management science has yet to catch up with the notion of networks and relationships that drive business value.  There is some early work regarding complexity-informed leadership for organizations (one compilation I'm slogging through is referenced at the end of this post), but few tools to inform the praxis.  Private sector firms are experimenting with various open models, to some success, and proving the theory: experimentation is critical to finding the 'right' set of standards and processes for a particular organization at a particular time. I was reminded this week of Gell-Man's caution:  The only valid model for a complex system is the system itself - we know to despise the notion of "cookie cutter" solutions, but lack alternatives, particularly in the public sector.

So how to proceed? We know we need accountability at every step, and we know experimentation is an unwelcome leadership tool in most agencies.  How do we evolve the practice of public sector leadership to recognize what we already know:  people are not fungible, the relationships they bring to the workplace are as important as their knowledge and skills, and what matters is often invisible - even when using a balanced scorecard.  How do we control the invisible?

A remarkably relevant Ted talk from Chip Conley:

Ref: Hazy, J. K., Goldstein, J. A., & Lichtenstein, B. B. (Eds.). (2007). Complex Systems Leadership Theory:  New Perspectives from Complexity Science on Social and Organizational Effectiveness (Vol. 1). Mansfield, MA: ISCE Publishing.

Shun The frumious Bandersnatch!

gordian knotWords mean things.  One of the more obnoxious statements of the obvious, and yet I find myself saying it more often these days.  The more I delve into understanding complexity theory, network science, and struggle to understand cognition and neuroscience, the more frustrated I get when people use terms in ways appear at odds with the literature. As I was preparing this blog to address the use of 'complex' versus 'complicated,' I found that I am certainly not alone in trying to retain some clarity of language.  Paul Jansen, in particular, has a great blog post on exactly this topic.  Nevertheless, I owe the nice people who followed this exchange on Twitter this week a brief explanation of my frumiosity.

This week, caught up in the holiday mood - I found myself engaging this week in an exchange with a gentleman, Roger Sessions, who has developed a method for IT architecture designed to 'reduce complexity.'  His paper features references to "attacking complexity" and includes a method for measuring it.  He introduces the "standard complexity unit," based on something he refers to as "Glass's Law," which posits that for every 25% increase of complexity in a problem space, there is a 100% increase in the complexity of the solution space. This reflects work from a 1979 paper by Scott Woodfield, who first posed this idea.  The idea is that increasing the complexity of problems tackled by software engineers does not increase the complexity of the solution in a linear sense, but on an exponential scale.  It is this problem that Sessions seeks to take on with his approach.

Now the notion of reduced complexity is attractive, if you understand complexity as a system that has developed so many connections as to become unmanageable. This is a common usage for 'complex,' which seems to translate to "something too hard to understand or manage or control or cost."  The notion of 'wicked problems' applies here as well.  The greater the connections you find among things, the greater are your odds of decision paralysis and "failure."  Solution?  Easy, make things simple.  The danger, for me, comes in simplifying management behaviors in ways that deny the nature of the systems we are attempting to manage.  If you believe complex is nothing more than the 'opposite of simple,' you are missing some of the most promising areas of applied research in a half century.

When I engaged the gentleman on his use of the term complexity, I received what I believed was an odd response.  For someone who uses the word in titling his books and lectures, he did not appear terribly connected to the word itself.  He even invited me to suggest a different term for what he was trying to achieve. The closest I could come to his definition for complexity (admittedly, without buying his book) is an 'exponential growth in system states with regards to information technology systems.'  To me, he is trying to help people with an architectural approach that makes overly-complicated IT systems more manageable.

For his part, Roger was comfortable with my discomfort, because in his world "complex" merely means the opposite of "simple."  Several of us during this Twitter-fuffle suggested the use of "complicated," which suggests a system that has known but prolific connections.  Cause and effect in complicated systems are related and knowable, but analysis by an expert will likely be needed to connect them when something goes wrong.  My example here is the 'check engine light' on my car - while I am at a loss to understand the cause, an expert with tools can ascertain it quickly.  Modern car engines are extremely complicated.

They are not, however, complex.  My car engine is unlikely to evolve new features anytime soon.  There is a reason medical doctors have different training regimes than auto mechanics.  The latter deal with complicated systems, the former with complex ones.

Complexity is a specific term.  Complexity, as described in the literature, is a science that seeks to explain how emergent order (often called 'hidden order' or 'self-organization') is observed in systems or (most) networks. For what it's worth, I believe those seeking to develop IT architectures could benefit from a deep understanding of complexity, as their users are sloppy humans in messy and evolving sub- and extra-organizational work networks.  Methods for complex systems management show some promise in 'attacking' the unmanageable IT systems that Mr. Sessions is tackling here.  It may be that observing and nourishing self-organization among human-based networks, rather than embedding and enforcing an existing or desired organization within them, will help architects develop more manageable and relevant IT systems.

As a blog post, however, this has gone on long enough.  I just wanted to explain my bristling at a usage of the term 'complex' in a way that conflicts with the literature. At one point, Roger reminded me that he is trying to tackle an extremely serious problem.  I respect that, of course, and was doing the same.  Given the great work that is ongoing around complexity and complex adaptive systems, we owe some respect to giants upon whose shoulders we seek to stand.

Foresight and Public Policy in a Complex World


In talking about foresight, I'm reminded that this is not an attribute but a process.  No one "has" foresight, we look ahead – we envision.

In turbulent times, when we're reminded of the Black Swan effects and the connected nature of things, we tremble at our inability to predict.  Truth is, our ability to predict only occurs when the world is relatively linear and stable – that is, anomalous.  We have built up such structures and have been the primary power for nearly a generation.  We have come to believe, until recently, that the world should be predictable. 


Let me illustrate, I beg your indulgence.

You are driving along Virginia's Blue Ridge Parkway, Skyline Drive one evening.  You have set your sights on Staunton and plan to be there within two hours.  You hum along, thinking only of the dinner and wine that await you, dimly aware of your settings. As you drive, you are so given to boredom that you have music to occupy your senses as you keep an even course.  Even if you experience a flat tire, you have preparations for that.  It's the furthest thing from your mind, but the occurrence is normal enough that you have a jack and a spare.  If the spare is flat, well, you have AAA and a cell phone.  You aren't thinking of this future, however, your mind is fixed on the evening's upcoming Pinot Noir.

Then the tire blows.  And your daughter borrowed the jack.  Your phone has no coverage in this spot.  How big a spot, you don't know. But now new possible futures are flooding your mind.  Someone may come by, you picture that scenario and how it would play out.  Even patting your pocket to ensure you have cash to compensate the Good Samaritan.

But no one comes.  You aren't aware, but a freak rockslide closed the highway 45 minutes ago.  A Black Swan event, although there have been signs warning of such things on this road for years.  You are alone. You decide to walk to see if the cell coverage improves. Walking along the dark road, hugging the shoulder in case a car comes along, as night falls hard.

Unlike an hour ago, you are now much more aware of sounds.  Is that an animal?  If so, you try to guess its size and intent.  You are now picturing personal futures that were completely unthinkable when you started your car this afternoon.  What if you trip and end up in a ravine?

Does it hurt to die of exposure?

Then it begins to rain.

We can paint a similar picture, but this time by hearing a noise in your home at night.  Animal? Fallen object?  Intruder?  We flash to several possible immediate futures, none of which were envisioned minutes earlier.

Implications for Policy Planning - Learn from Biology

What is common here?  We enter a period of heightened awareness as we simultaneously try to comprehend the changes in our environment and walk through possible futures.  This process cycles, as "new" futures enter our thoughts and obsolete ones are discarded.


These illustrations are my attempt to convey the following.  When we find ourselves off course:

  1. We become more attuned to our environment
  2. We focus mental energies as our bodies increase our capacity. "From deep within your brain, a chemical signal speeds stress hormones through the bloodstream, priming your body to be alert and ready to escape danger. Concentration becomes more focused, reaction time faster, and strength and agility increase. When the stressful situation ends, hormonal signals switch off the stress response and the body returns to normal." (NIH)
  3. We model possible futures, thinking through steps and working out actions we may take.  (I'll need a weapon if it's an intruder.  I left a knife on the counter."
  4. We explore/probe the environment. ("I'll walk just a little further in this direction, maybe the coverage comes back."  "I'll open the door now, make some noise.")
  5. Based on what we experience next, we return to step 2 until we have a path that appears to resolve matters to our satisfaction (our perception of "satisfaction" changes as the crisis deepens).

In the current global climate, therefore, foresight and policy should become more fluid and iterative.  Adopt the mindset that this is a process, not a state.  As Eisenhower warned, "Plans are nothing, planning is everything."

  • Establish mechanisms to listen
  • Focus our energies on learning interdependencies, weak links
  • Cooperate more, trust more, with allies and the indifferent. We need others more than we realize, for the weak signals in the environment may be discernible to them.
  • Establish a rigor of visioning, building on futures analysis.  I found a reference online that said in 1974, the House Committee on Committees stipulated that each Committee "shall review and study on a continuing basis undertake futures research and forecasting on matters within its jurisdiction."  If true, this is extraordinary.  And a hook by which we can begin today.
  • Explore, probe, experiment.  Is today's economic crisis the end of Bretton Woods, or Westphalia?  Or does the surge towards nationalization of banks and industry represent a resurgence of Westphalia, perhaps its last?
  • Rinse and repeat.

Human Distribution

Spent yesterday's treadmill time watching Clay Shirky's talk at TedTalks 2005 yesterday.  I believe the implications of his talk energized me as much as the "exercise" (ok, so I just walk for 30 minutes - it's a start).  His central thesis was that the low transaction costs of communication meant that new forms of organization may be preferable to derive maximum value based upon the natural laws underlying communities and human assemblies.  

Hah?  He was much more elegant, let me try again.  If you have an employee who comes to work, "drinks your Coke and plays your foosball, and after three years has only one good idea," how would you receive this individual in your firm?  For most companies, of course, the employee would have been fired ages before the good idea.  But what if that single idea sparked an innovation, or salvaged a product line, or in some other way had a non-linear effect on everyone else's work?

If we focus on employee productivity instead of finding a way to value ideas, we will never realize the benefit of this one good idea.  The connectivity we enjoy today means that new organizational structures may allow us to manage for good ideas, instead of busy bee workers.  In any community, whether emergent or designed, roughly 20% of the participants will provide 80% of the value.  Most companies will then try to encourage more people to "be like" the top 20%, and will trim away the "bottom 10%." Sounds great, but what ideas are you throwing away?  What is wrong with managing people as they naturally organize, rather than try to force human beings into a bell curve?

I thought the days of brutal HR were over, at least for professional services firms, but I was very wrong and very close to home wrong.  The Jack Welch dictum, which forced a ranking of employees and sought to remove the "bottom 10%," is alive and well.  And still remarkably dangerous.  While Shirky's model is backed up by complexity principles (disequilibrium is a natural state) and network science (power law distribution rather than normal law curves) - some firms still to manage their workforce because "GE did it this way."  Even the basis of Jack's marvelous scheme is flawed - employees are actually not motivated by monetary rewards and incentives (see Washington Post article on this topic).  Instead, they need to feel a sense of autonomy and purpose.  Being told to strive to be the "top 20%" in your company means you are hoping people will engage in mimicry and adapt your ideas regarding their performance metrics.  Goodbye innovation.  The effort to trim the bottom 10% will instead alienate the top 15%, who realize the implications of treating human beings like bacteria.  (Which isn't fair to bacteria, actually, who display remarkable emergent social behavior for mutual benefit.)

This is a failure of ideas, of course.  We have failed to make our case to CEOs, so they are left with just mimicking observed behaviors - which never reveal the entire story.  As with misguided "best practice" efforts, CEO aping behaviors ensure that a certain pack will follow what they believe makes the Silverbacksuccessful, and therefore never overtake him or repeat his luck.

Shirky predicts 50 years of chaos until this all shakes out.  I plan to retire within 20, so I'll need to step carefully in applying what I know to what I face.  Not that I've ever been adept at stepping carefully.



Conquering Complexity

Ok, so I am a few pages into the Michael George book: "Lean Six Sigma for Services." But I'm putting it down now for good. In the chapter entitled: "The Value in Conquering Complexity," I am struck with the misuse of the term 'complexity' when what is meant is 'complicated.' The case study shows that a certain service offering was customized for several hundred clients, each with their own 'pathway' towards receiving that service. Mr. George then labels this 'complexity.' On the next page, he makes it clear with a parenthetical that defines complexity as "the variety of products and services."

The failure to understand, or to be less blunt, address, core concepts in organizational theory is striking. Complexity refers to systems (such as Earth, human beings, businesses) whose properties emerge as the system interacts with its environment. A complicated situation as described by multiple customized pathways brings to mind pipes in a boiler room, or network cables under a server room floor. These images can be confusing to the eye, and hard to track, but the relationships are knowable. A complex metaphor moves beyond knowable pathways.

Complex systems defy causality chains. Graph a brainstorming session. What is the exact process by which a team of four professionals gather on a Thai beach and create lasting value? What is the effect of the remote locale, the different food on the cognitive processes within each? What is role of the increased trust network after six weeks swatting bugs and fighting off a rogue monkey? (Read the story, trust me about the monkey.)

This book, and presumably the application of Lean or Six Sigma to services forms, presumes that the findings in organizational theory regarding work being done in the "organizational chart white spaces" represents inefficiencies in human endeavor – not reality. This school of thought apparently holds that the only reason the gossip network is the most reliable form of communication, or the organizational chart rarely represents true power relationships or work networks – is because we have not yet driven humans back to the formal organizational processes.

Believing this is an act of faith that is beyond my abilities. Businesses are actually complex adaptive systems. Wikipedia credits John Holland with this definition:

"A Complex Adaptive System (CAS) is a dynamic network of many agents (which may represent cells, species, individuals, firms, nations) acting in parallel, constantly acting and reacting to what the other agents are doing. The control of a CAS tends to be highly dispersed and decentralized. If there is to be any coherent behavior in the system, it has to arise from competition and cooperation among the agents themselves. The overall behavior of the system is the result of a huge number of decisions made every moment by many individual agents"

Mr. George's book either ignores the finding that businesses are complex adaptive systems, or he believes that the agents can be made more efficient by mapping how each "gets to Y (results)." I lack the ability to wrap my mind around this, as it violates everything that is known and published regarding CAS. The quality movement is here to stay, and I need to find a way to accommodate those who believe in the LSS silver bullet – while keeping in mind how humans actually work and interact to create value.