The place where we feel we belong

The so-called "Age of Enlightenment" was an intellectual and cultural movement in the 18th century that emphasized reason over superstition and science over blind faith.  One of the leading intellectuals during this period was the English scientist Isaac Newton, who introduced his three laws of motion which explained how the whole universe operated.  Scientists coming after Newton believed that his laws applied everywhere in the universe and provided a framework by which the natural world could be easily understood and future events predicted.  The universe was simple, machine-like, predictable, and controllable, and events occurred like clockwork.  All of the events that occurred throughout time and throughout the universe could be reduced to a set of mathematical equations.

Newton's metaphor of a clockwork universe became the template for all the other thinkers in the Age of Enlightenment and through the Industrial Age, including Sigmund Freud in psychology, August Compte in sociology, John Locke and John Stuart Mill in political philosophy, and Frederick Winslow Taylor in management.  Taylor published his book, The Principles of Scientific Management in which he proposed an approach to management based upon scientific and mathematical principles that were designed to increase worker productivity.  However, the 20th century ushered in a new era, with Einstein's theory of relativity, Schrödinger's cat, Heisenberg's uncertainty principle, and the science of quantum physics.  These discoveries were followed soon after by chaos theory and complexity theory.  While Taylor's book remains a classic text in management, his scientific management principles, largely based upon Newton's conception of the clockwork universe, may no longer be appropriate in our world of complexity science and quantum physics.  As our notion of the clockwork universe changed, so too did the ways we approached leadership and management.

I still believe there is a role for the Frederick Winslow Taylor and the scientific principles of management in organizations today.  However, as I've posted recently (see in particular, "Connecting the dots" and "Tame the chaos" which discuss the Stacey Matrix and Grint's Wicked Problem framework, respectively), our leadership approach should be dictated by the complexity of the task or problem at hand.  Today I want to focus on one last framework called the Cynefin Framework, which was developed in 1999 by David Snowden when he was working for IBM.

The word cynefin is a Welsh word (pronounced "ku-nev-in") that literally translates to habitat or place.  More specifically, it can be defined as the place where we feel we belong, where the people and landscape around us are familiar, and the sights and sounds are reassuringly recognizable.  The idea of the Cynefin Framework is that it offers leaders a "sense of place" from which to view their perceptions of the world around them.  Snowden described the five domains of the framework in an article published in the journal IBM Systems Journal in 2003 ("The new dynamics of strategy: Sense-making in a complex and complicated world") and in an article in Harvard Business Review in 2007 ("A leader's framework for decisionmaking").  The framework is shown below:

The framework proceeds in a counter-clockwise manner in which problems are categorized as clear (also known as simple in earlier versions), complicated, complex, chaotic, or confusion.  If you've been reading my last few posts, you will undoubtedly note that there is significant overlap between the Stacey Matrix, Grint's Wicked Problem framework, and the Cynefin Framework.  The first four domains in the Cynefin Framework require leaders to appropriately recognize and diagnose the problem and respond as contextually appropriate.  The fifth domain (confusion) applies when leaders are unable to categorize the problem into one of the first four domains.

Clear Problem - Best Practice

Clear problems are analogous to Stacey's simple problems and Grint's tame problems.  Using the infamous Rumsfeld Matrix, clear problems are "known knowns."  In other words, these problems are clear, linear, cause-and-effect relationships, and the right solutions are generally well-known and undisputed.  Here, the leader's role is to sense, categorize, and respond, often using a standardized approach that is commonly accepted and considered "best practice."

Complicated Problem - Good Practice

Complicated problems are analogous to Stacey's complicated problems (of course) and are still within the domain of Grint's tame problems.  They are complicated because there may be several correct solutions to the problem.  Moreover, while these problems are usually linear and cause-and-effect in nature, not everyone can clearly see that is the case.  There are the "known unknowns" of the Rumsfeld Matrix, and the leader's role here is to sense, analyze, and respond and apply good practice, not best practice.  In other words, there is usually not a widely accepted, standardized best practice here, because multiple approaches have been used to successfully solve the problem in the past.

Complex Problem - Emergent Practice

Complex problems are analogous to Stacey's complex problems and Grint's wicked problems.  We've crossed over into the domain of complexity science and complex adaptive systems and the world of "unknown unknowns" of the Rumsfeld Matrix.  Here the leader's role is to probe, sense, and respond.  Instead of attempting to impose a "tried and true" course of action, leaders should be patient and allow the path forward to reveal itself, i.e. emergent practice.  

Chaotic Problem - Novel Practice

Chaotic problems are analogous to Stacey's chaos, and they probably fall into Grint's crisis domain.  These problems are "unknowable" (a term not used in the Rumsfeld Matrix).  Here the leader's role is to act to establish some semblance of order, then sense where stability is present, and respond by working to transform the situation from chaos back to complexity (act, sense, and respond).  These kinds of problems are generally those that the leader (or anyone else for that matter) have not encountered in the past, and so they require solutions that have never been tried before (i.e. novel practice).

Snowden provided a great "leader's guide" in the Harvard Business Review article "A leader's framework for decisionmaking".  The American author F. Scott Fitzgerald reportedly once said, "The test of intelligence is the ability to hold two opposed ideas in the mind at the same time and still retain the ability to function."  In regards to my last three posts, perhaps it is fair to say that, "The test of leadership is the ability to apply the right style of leadership to the problem at hand."

Tame the Chaos?

Hopefully I am starting to convince you that leaders working in organizations today should adopt and modify their leadership and management (i.e. decision-making and level of control) to the particular nuances and context of the situation at hand.  Last time I presented the Stacey Matrix as a framework for leaders to do just that.  I also mentioned Keith Grint's Critical - Tame - Wicked framework, which is very similar in concept to the Stacey Matrix.  I've posted about Keith Grint and wicked problems several times in the past (see, in particular, "What style of leadership works best? It depends on the problem at hand..." but also "Murphy's Law, the U.S. Navy SEALs, and High Reliability Organizations", "Wicked", and "...like a stand of trees").

Grint writes, "Much of the writing in the field of leadership research is grounded in a typology that distinguishes between Leadership and Management as different forms of authority...with leadership tending to embody longer time periods, a more strategic perspective, and a requirement to resolve novel problems."  Well that is certainly the classic distinction between leadership and management, at least in most of the literature that I've read, but I want to dig a little deeper into this distinction.  Perhaps Ralph Stacey was right - the application of leadership versus management should depend upon the type of problem at hand.  The classic tools of scientific management may work for the simple problems that organizations encounter, but we unfortunately live in a VUCAT world and our problems are never quite that simple.

Grint further writes, "Another way to put this is that the division is rooted partly in the context: management is the equivalent of déjà vu (seen this before), whereas leadership is the equivalent of vu dàjé (never seen this before)."  He continues, "If this is valid then the manager is required to engage the requisite process to resolve the problem the last time it emerged. In contrast, the leader is required to facilitate the construction of an innovative response to the novel problem, rather than rolling out a known process to a previously experienced problem."  Here is where his Critical - Tame - Wicked framework comes into play:

Again, the framework follows the classic 2x2 matrix with the degree of uncertainty on the vertical axis and the need for collaboration and/or compliance on the horizontal axis.  Rather than the classifying problems as simple, complicated, complex, or chaotic as in the Stacey Matrix, Grint uses the terms critical, tame, and wicked, depending on where on this 2x2 matrix the problem falls.

Tame problems are analagous to Stacey's simple and complicated problems (but really, how many problems in our VUCAT world are truly simple?).  They are those problems that, while complicated have probably occurred before.  The solution to Tame problems is fairly straightforward.  Here, Management probably works best.  

Wicked problems, analagous to Stacey's complex problems, have probably never occurred before.  The solution to Wicked problems aren't readily apparent, and they may be as complicated and complex as the problem itself.  Here, the Leadership style that leverages the expertise of the group ("deference to expertise") fits the best.

The last category is most similar to Stacey's chaos, which organizations should try to avoid at all costs.  When you think of Critical problems, think of a crisis.  The world is falling apart all around you, everyone is looking to you to tell them what to do.  In other words, with Critical problems, Command is the best approach.

So what is exactly the difference between wicked problems and tame ones?  I've alluded to some of the differences between these two types of problems above.  Let's look at the problem of climate change - is there a straightforward solution here?  Not really.  Are we able to apply some of the lessons we've learned in the past?  Probably not.  If the solution was readily available and straightforward, we would've probably done so by now.  So climate change is really a wicked problem.  In this same vein, increasing the utilization of renewable energy sources such as solar and wind would be a tame problem.  Make sense?

Wicked problems are characterized by the following:

1. They do not have a definite formulation.

2. They do not have a "stopping rule" (i.e., there is no way to tell for sure when you've reached a solution).

3. There is no way to test the solution to the problem - trial and error approaches will not work (sounds a lot like what High Reliability Organizations have to contend with, right?).

4. There is no real end to the number of approaches or solutions that can be attempted.

5. Every problem is unique and has probably never been dealt with before.

6. They can always be described as a symptom of another problem (e.g., climate change is a symptom of global warming, etc).

Next time, I want to introduce one last framework for describing problems, the Cynefin Framework, and then I will hopefully tie all of these last several posts together in a nice package!

Connecting the dots...

The last several posts have included topics on complex adaptive systems ("The myth of the ant-queen"), network science ("Six degree of Kevin Bacon"), small world networks ("It's a small world after all..."), self-managed teams ("A flock of starlings"), teal organizations ("Today's color is teal...").  I wanted to take a brief moment and try to connect all of the dots here, as I was being very intentional in how I sequenced this series of posts.  

It's seems a little strange (at least it did to me) that a blog on leadership would focus on self-managed teams, which sound a lot like leaderless teams.  I promise that there has been a method to my madness!  I still feel that leadership (good leadership anyway, because I do think there is such a thing as bad leadership) is critically important to the success of any organization (see my last post, "Any old map will do...").  My two main points are (1) we live in a complex world (it's a VUCAT world) and (2) our complex world requires a different type of leadership.

I recently started reading a book (it's an older one, but I still find it relevant) by the British organizational theorist Ralph Stacey entitled Managing the Unknowable: Strategic Boundaries Between Order and Chaos in Organizations.  Stacey was one of the first to apply the disciplines of chaos theory and complexity science to organizations and argued that organizations are complex adaptive systems.  Recall that complex adaptive systems consist of (1) systems made up of many individual parts or agents that (2) interact with each other and follow simple rules that lead to the emergence ("the whole becomes greater than the sum of the individual parts") of complex behaviors that occurs (3) in the absence of any centralized leader who is coordinating the interactions of the individual parts or agents.  Stacey further argued that because organizations are complex adaptive systems, leaders could rarely forecast or predict all of the consequences of their actions (i.e. their strategy and tactics).  As such, management is not always the rational, analytic, and scientific decision-making process as outlined by individuals like Frederick Winslow Taylor (see The Principles of Scientific Management).  Instead, leaders within complex adaptive systems should adopt and modify their leadership and management (i.e. decision-making and level of control) to the particular nuances and context of the situation at hand.

Stacey created a diagram of contingency leadership that is now called the "Stacey Matrix" (apparently he regretted creating it).  It's a classic 2x2 matrix, with the "degree of certainty" on the horizontal axis and "level of agreement" on the vertical axis:

Degree of Certainty

Problems, issues, or decisions are close to certainty when a strong cause-and-effect relationship can be established or if a similar problem or issue has been addressed in the past.  In other words, leaders can easily extrapolate from their past experience to predict the outcomes of an action or decision with a high level of confidence.  Conversely, when problems, issues, or decisions are new and unique, extrapolating from past experience may not be possible, hence the proper course of action is far from certain.  

Level of Agreement

If the group or team has come to a consensus about a problem, issue, or decision, then the group is close to agreement.  Conversely, when consensus cannot be achieved, the group is far from agreement.

The figure above is slightly different than the typical 2x2 matrix, which forms four distinct quadrants (albeit with some overlap at the margins).  There are still four zones, but they are more dynamic and fluid than the usual four quadrants.  What is valuable with the Stacey Matrix is that it provides a way for leaders to select the appropriate management action in a complex adaptive system, based on the degree of certainty and level of agreement on the problem or issue in question:

Simple problems are those in which there is a high degree issues or problems are usually amenable to Taylor's scientific principles of management.  The goal is to repeat what has worked in the past and monitor the efficiency and effectiveness of the tried-and-true approach. 

Complicated problems can involve those in which there may be a high level of certainty / low level of agreement or low level of certainty / high level of agreement.  The former requires coalition building, negotiation, and compromise in order to reach consensus on how the problem will be solved.  Focusing on a shared mission and vision (remember there is a high level of agreement) will help the team to move to an agreed upon future state, even if the specific path to get there cannot be determined in advance.

Complex problems exist in what is often referred to as the "edge of chaos" (Stacey himself called this area the "zone of complexity").  The traditional leadership and management approaches will not work here.  Complex problems require creativity, innovation, and breaking with the past.  

Chaos (also known as "Anarchy" in some versions of the Stacey Matrix) is characterized by very high levels of disagreement and uncertainty.  Organizations should try to avoid chaos, if at all possible.

The Stacey Matrix is often compared to two other models called the Cynefin Framework (pronounced coon-a-fin) and Keith Grint's Wicked, Tame, Crisis Framework (the one I prefer the most).  Regardless of which framework that is used, all three suggest that the same leadership and management approach can't be used to solve every problem that an organization faces.  Instead, the best approach is to use the best leadership and management approach for the specific problem at hand.  And here is where self-managed teams (and similar concepts that I will cover soon) and "deference to expertise" assume critical importance.

"Any old map will do..."

There's a famous story, likely apocryphal (more on that below) of a group of Hungarian soldiers who were sent on a scouting mission in the Alps during World War I.  They were caught in a heavy snowfall and quickly became lost.  After they failed to return to base after several days, their captain assumed that they had all perished in the mountains.  One day, they showed up unexpectedly back at the base.  The captain asked what had happened, and one of the sergeants replied:

"We were lost in the snowstorm and started running low on food and water.  We had given up hope and resigned ourselves to die. Then one of the men found an old, crumpled and tattered map in his pocket. With its help we knew we could find our way back. We made camp, waited for the snow to stop, and then as soon as we could travel, we found our way back to base."

The captain nodded and replied, "Show me your map."  When the captain unfolded the map, he discovered that it wasn't a map of the Alps.  It was a map of the Pyrenees!  

The old, crumpled and tattered map of the Pyrenees proved valuable because it represented hope.  Rather than waiting until they froze to death in the mountains, the soldiers now had something believable and tangible to follow. The map of random mountains and valleys had, fortuitously, pointed the way towards home.

The story of the lost Hungarian stories has a rather interesting backstory.  As I mentioned in the first sentence of this post, I'm not even sure that it is true.  I've read versions where the story takes place during World War I and others where it takes place during World War II.  The story has always involved Hungarian stories though, perhaps because it was first told by the Hungarian physician-scientist, Albert Szent-Györgyi whose medical studies were interrupted by World War I (notably, Szent-Györgyi was awarded the 1937 Nobel Prize in Medicine for his discovery of vitamin C).  Szent-Györgyi told this story several times over the years to different individuals, including to the Czech immunologist and physician Miroslav Holub.  Holub was also an accomplished poet and wrote a poem about the Hungarian stories, called "Brief Thoughts on Maps" in 1977:

Albert Szent-Györgyi, who knew a lot about maps

according to which life is on its way somewhere or other,

told us this story from the war

due to which history is on its way somewhere or other;

The young lieutenant of a small Hungarian detachment in the Alps

sent a reconnaissance unit out onto the icy wasteland.

It began to snow

immediately, snowed for two days and the unit

did not return.  The lieutenant suffered: he had dispatched

his own people to death.

But the third day the unit came back.

Where had they been? How had they made their way?

Yes, they said, we considered ourselves

lost and waited for the end. And then one of us

found a map in his pocket. That calmed us down.

We pitched camp, lasted out the snowstorm and then with the map

we discovered our bearings.

And here we are.

The lieutenant borrowed this remarkable map

and had a good look at it. It was not a map of the Alps

but of the Pyrenees.

Goodbye now.

Apparently, the organizational psychologist (and one of the leading investigators on high reliability organizations, HROs), Karl Weick heard this story and used it routinely in his writings and lectures.  Weick often ended his retelling of the story with, "The moral of the story - when you are lost, any old map will do." Unfortunately, he apparently didn't credit Holub or Szent-Györgyi and claimed the story was a true one (and occurred in Switzerland), leading to claims of plagiarism, which Weick vehemently denied.  Regardless, the lessons here are important, especially given the topic I've been discussing in the last several posts.

I've introduced and talked about the concept of self-managed teams and self-organizing teams, particularly as they relate to complex adaptive systems.  While not every organization has completely adopted self-managed teams (Morning Star, a tomato processing company - see the HBR article "First, Let's Fire All the Managers!" and Zappos - see the HBR article, "Beyond the Holocracy Hype" are at least two) or the concept of Teal Organizations, several companies are starting to flatten the traditional hierarchical org chart and adopting methods like Agile, which emphasize self-managed teams and self-organizing teams.  The logical question, then, in these new organizational structures, what, if any, role does a leader play?  Here is where the story of the Hungarian soldiers becomes important.  Just like the tattered and crumpled old map of the Pyrenees, leaders "show the way."

Let me be clear - it would not be right to say that "any old map will do" if we are using the word map in this context as a metaphor for leadership!  Leadership still matters, even in the world of Teal, Agile, flattened hierarchies, and self-managed teams.  Whether that leadership comes from an individual at the top or from amidst the team itself doesn't matter as much, as long as someone is "showing the way".  Here is a summary of the key differences in leadership within a hierarchical organization versus a self-managed team:

When I think about self-managed teams, I am reminded of the Navy SEALS, who emphasize decentralized leadership, the U.S. Army Rangers motto Sua Sponte, the U.S. military doctrine of "commander's intent", the German Wehrmacht doctrine of "Auftragstaktik", and of course the High Reliability Organization principle of "Deference to Expertise".  The message is not lost on me (and I hope it's not lost on you either) that all of the aforementioned examples come from military organizations, who are traditionally considered very hierarchical.  Perhaps not.  If the military is moving more towards decentralized leadership and "deference to expertise", why aren't other organizations doing so?

Today's color is Teal...

Towards the end of my last post, I referenced a concept known as Teal organizations.  I wanted to take a moment to explain this concept further.  Teal is a greenish blue color (as opposed to turquoise, which is a bluish green color).  The name apparently comes from a species of duck called the Eurasian teal (Anas crecca) that has a teal-colored stripe on its head.  Teal was quite popular as a color in the 1990's, with several sports teams - including the Miami Marlins of MLB, the Jacksonville Jaguars of the NFL, the San Jose Sharks of the NHL, and the Charlotte Hornets of the NBA - adopting the color for their uniforms during this period.  I have to be 100% honest though, I'm not sure I could tell the difference between the colors teal, turquoise, and aqua.  Regardless, the management consultant Frederic Laloux uses the color teal to describe organizations that have adopted self-managed teams.  

Laloux wrote a book called Reinventing Organizations (for a shortened version, see his article "The Future of Management is Teal" in Strategy + Business) in which he described different types of organizations using a color scheme developed by the social psychologist Ken Wilber.  Wilber's integral theory of consciousness claims that humans have different levels of consciousness, each of which have a different associated color.  Laloux argues that just as human consciousness evolved in stages, organizations evolved at the same time and to a similar degree as well (as shown in the Figure below).  Each stage of development, denoted by a color, correlates to a particular time in human evolutionary history when these levels of consciousness, and the respective stage of organizational development, were prevalent.

Laloux claims that over the course of human history, there have been at least five distinct organizational paradigms.  Teal organizations are the latest developing paradigm and are based on worker autonomy, self-management, and flattened hierarchical structures (if hierarchy exists at all).  Red, Amber, Orange, and Green organizations, on the other hand, are based on hierarchy and meritocracy.  It's an interesting theory, and given the topic I've been discussing with the last few posts, it's probably worth discussing in a little more detail.

Laloux starts over 10,000 years ago, when humans first shifted away from small bands or tribes to form proto-empires.  These early "organizations", which Laloux labels Red organizations (he also uses the metaphor "wolf pack"), were based upon the division of labor and command authority with little in the way of hierarchical structure aside from a sole leader at the top who had power over the rest of the organization.  These organizations remained successful as long as the leader was able to exercise power over the rest of its members, similar to the alpha wolf in a pack.

Starting around 4000 BC in Mesopotamia, Amber organizations (he also uses the metaphor "army") became the most prevalent type of organization, which are the classic pyramid-shaped hierarchical, process-driven, command-control organizations.  Formal roles were clearly defined and allowed organizations to scale up in size.  Workers at the bottom of the pyramid had be told what to do and how to do it by those at the top of the pyramid.    

Starting with the Renaissance and lasting up until the early Industrial Revolution, innovation (through research and development), accountability, and meritocracy came into fruition.  This era saw the the creation of modern HR practices, budgets, KPIs, yearly evaluations, and bonus systems for performance.  Organizations adopted Frederick Taylor's principles of scientific management, and the concept of management by objectives first came into use.  Laloux labels these Orange organizations (he also uses the metaphor "machine").

Green organizations (Laloux uses the metaphor "family" here) emphasized cooperation over competition, equality, and empowerment.  While these organizations operated with the pyramidal structure of the Amber and Orange organizations, leaders share at least some of the control over what goes on in the organization.  These organizations follow the stakeholder theory of the firm as opposed to the shareholder theory first advanced by the economist Milton Friedman.  Empowerment and egalitarian management are the order of the day.

Beyond the Green organization, we finally have the Laloux's Teal organization (he uses the metaphor "living organism" here), where self-management replaces the hierarchical pyramid and organizations are seen as living organisms.  In Teal organizations, the whole is the greater than the sum of the individual parts.  Here, we see organizations as complex adaptive systems.  

Laloux writes, "Every stage of organizational evolution is more mature and effective than the previous stage, because of the inherent attitude toward power. A Red leader asks, How can I use my power to dominate? An Amber leader asks, How can I use it to enforce the status quo? An Orange leader asks, How can we win? A Green leader asks, How can we empower more people? A Teal leader asks, How can everyone most powerfully pursue a purpose that transcends us all?"

One of the main criticisms of Laloux's work is that there is little scientific basis for some of the arguments he made in his book.  I am less concerned with the historical or scientific accuracy of his claims and more interested in his conceptual model of the different types of organizations.  I do think he makes some very interesting points here.  Laloux talks about several organizations that have adopted the Teal organizational structure, including Patagonia, Morning Star, and Sun Hydraulics.  

Whether the Teal organization will become more common is still under debate.  According to a review published in 2004 in the journal Public Performance & Management Review, large numbers of U.S. businesses are experimenting with the use of self-managed teams.  A survey of Fortune 1000 companies found that 27% of organizations used self-managed teams in 1987, though more recent estimates suggest that this percentage could be as high as 82%.  So, as I have stated in the last few posts, I do think there is a place for these models in organizations today.  If you choose to call organizations that utilize self-managed teams, "deference to expertise", or some of the characteristics that we find in complex adaptive systems a Teal organization or not is entirely up to you.  

A Flock of Starlings

I talked about two concepts, self-managed teams (albeit very briefly) and complex adaptive systems (to a greater extent) in my last post, "The Myth of the Ant-Queen".   To recap, an ant colony is a great example of a complex adaptive system, which is defined as a group of semi-autonomous agents or individuals who interact in interdependent ways to produce system-wide patterns.  The behavior of each individual ant in the colony is governed by a few simple rules, yet the behavior of the colony as a whole can be quite complex.  Simple rules lead to complex behavior, in the absence of any centralized coordination or leadership.  The ant-queen is not really a leader at all - all she does is lay eggs to sustain or grow the colony.  Nigel Franks, a specialist in ant behavior, wrote, "The solitary army ant is behaviorally one of the least sophisticated animals imaginable...Yet put a half million of them together, and the group as a whole becomes what some have called a superorganism with collective intelligence."  As it turns out, all insect colonies (ants, termites, bees, etc) behave similarly, in that the individual behavior of each insect is governed by a surprisingly few number of rules, leading to a significantly more complex behavior when considering the colony as a whole.   

Admittedly, insect behavior is not the same as human behavior.  Can groups of higher order animals, even humans, behave in a similar fashion to that of the ant colony?  As it turns out, they certainly can and do.  Witness the incredible beauty, order, and symmetry of a flock of starlings in flight (see a beautiful video here).  It's called murmuration, and it's absolutely fascinating to observe.  

I would argue that starlings are a lot more intelligent than ants, termites, and bees.  However, it would be wrong to assume that starling murmuration is centrally coordinated or orchestrated by the leader of the flock (if there is any such thing).  Individual starlings, like the ants I mentioned in my previous post follow a set of simple rules that produces the complex group behavioral patterns demonstrated in murmuration.

Surprisingly, in the late 1980's a scientist named Craig Reynolds wrote a simple computer program that simulated starling murmuration.  Reynolds called his simulated starlings "boids".  By following three simple rules, the "boids" recapitulated the complex behavior of murmuration (see the video of Craig Reynold's "boids" algorithm here and here):

1. Separation - steer to avoid crowding local boids and other objects

2. Alignment - steer towards the average heading of local boids

3. Cohesion - steer to move towards the average position of local boids

I first talked about starling murmuration in a post from a few years ago (see "Don't be an agent of chaos!").  Scientists have studied the flocking behavior of a number of different animal species, including starlings.  For example, we can observe similar behavior with schools of fish (technically, it's not called murmuration, but rather shoaling or schooling instead).  

These complex behaviors have been worked out mathematically (see "Effective leadership and decision-making in animal groups on the move"), and similar processes have even been observed in humans in the laboratory setting (see "Consensus decision making in human crowds").  We are, in fact, part of the animal kingdom.  So, whether our ability to move through crowds or in crowds is our innate "animal senses" or some other as yet unrecognized pattern of human behavior, the fact remains that we can create order out of chaos, in ways very similar to the murmuration behavior of starlings.

Just to finish my point, here's another example of murmuration-like behavior involving humans - maybe now we should avoid the term "murmuration" and label this kind of behavior, self-organization (individuals follow simple rules to produce complex group behavior with little to no centralized coordination or leadership direction).  Hisashi Murakami, a professor at the Kyoto Institute of Technology recently published the results of a series of outdoor experiments performed on the campus of Tokyo University, in which he and his colleagues filmed two groups of students walking down a narrow path about 30 feet long (see "Mutual anticipation can contribute to self-organization in human crowds").  The two groups walked towards each other at a normal walking pace.  Murakami and his colleagues noted that the groups of students effortlessly and spontaneously formed separate channels through the traffic (again, see my post, "Don't be an agent of chaos!" to learn what happened next).

My take-home point from these last two posts is that group behavior, from ants all the way to humans is incredibly complex and follows at least some of the characteristics of complex adaptive systems.  The logical follow-up question is whether organizations today can leverage some of the characteristics of these systems for better operational efficiency.  As it turns out, companies like Morning Star, a U.S. based tomato processing company (see the HBR article "First, Let's Fire All the Managers!") and Zappos (see the HBR article, "Beyond the Holocracy Hype") have embraced, at least for a time, the concept of self-managed teams (see also, the concept of Teal Organizations).  Companies like these (and others, though on a more limited scale) have flattened the traditionally hierarchical organizational structure to run more like an ant colony or flock of starlings.  And interestingly enough, when you start to look at these organizational structures, we start to see evidence of networks!

The Myth of the Ant-Queen

I can't remember exactly when it was during my childhood that I tried to start an ant colony.  I walked around our backyard until I found an ant mound, and I dug as deep as I could (which wasn't very deep) and placed all of the dirt and the ants - into a large glass jar.  My father showed me how to use a hammer and nail to poke holes in the jar's lid, so that the ants could breathe.  I don't remember asking my father whether the ants could leave the jar through those same holes, but maybe we should have considered that possibility.  Perhaps that’s why my mother made me keep the jar outside!  I remember being absolutely fascinated watching how the ants dug this elaborate network of tunnels in the dirt.  I think my colony eventually died out, not because of a lack of food, water, or oxygen, but due to the lack of a queen.

I have been reading some fascinating articles about the social behavior of insects, such as ants and termites (for example, check out the article “Swarm Smarts” in Scientific American from 2008).  And apparently I’ve always misunderstood the role of the queen of the colony.  The “queen” is not like what we usually think of when we hear the term queen.  As it turns out, Hollywood has misrepresented the role of the “queen” too, in animated films such as Antz or A Bug’s Life.  The “queen” is NOT the leader of the colony, but rather the “mother” of the colony.  Her only job is to lay eggs.  That’s it.  

So who, then, is leading the colony?  The surprising answer is that no one is leading the colony!  Each ant plays a specific role, whether it is foraging for food, building the network of tunnels in the ground, or guarding the colony from rival colonies or other species of insects.  And each ant plays its role without any direction or without any leader telling it what to do or how to do it.  The entire colony is leaderless, yet it still thrives!

The social behavior of the colony is entirely determined by the collective, simple behavior of the individual ants in the colony.  Here's another example.  It is a well-known fact that ants have the remarkable ability to work together to build "ant bridges" across obstacles that block their search for food (check out a video of a massive ant bridge here).  The ants work together to form a bridge using only their individual bodies, and what is amazing is that they do so without any direction or instruction from a leader ant.  Instead, each individual ant follows three very simple rules: (1) if you come to an obstacle or gap, slow down; (2) if you feel another ant walking across your body, stay put; (3) when you no longer feel ants walking across your body, start moving again.  That's it!  Three simple rules leads to rather complex behavior!  And again, NO LEADER!

Here's one last example from the insect world.  Termites, like ants, form social colonies and build complex structures using simple rules of behavior.  Interestingly enough, we humans are borrowing some of the "design principles" (and I use that term lightly, for reasons that I will explain in a moment) that the termites use to construct their homes (this interesting and growing field is called biomimetic architecture).  For example, the Eastgate building, a shopping center and office building in Harare, Zimbawe was designed and constructed similar to a termite mound.  The building is self-ventilating and can stay cool with very little utilization of energy - see the figure below:

Again, it bears repeating that the termites build and construct these complex mound colonies with essentially no direction or leadership (the irony is not lost on me that the construction company that built the Eastgage building likely had one architect in charge of design as well as an engineer in charge of construction).  

As it turns out, this ability to self-organize and self-manage is one of the fundamental characteristics of what is called a complex adaptive system.  A  complex adaptive system is defined as a group of semi-autonomous agents who interact in interdependent ways to produce system-wide patterns, such that those patterns then influence behavior of the agents.  These systems are characterized by three fundamental concepts:

1. A system of individual parts or agents that interact with each other

2. Interaction follows simple rules that lead to emergence (the whole becomes greater than the sum of the parts)

3. There is no centralized leader who is coordinating the individual parts or agents.

Examples of complex adaptive systems, aside from ant and termite colonies, include the immune system, the brain, the stock market, and the national economy.  I would argue, as others have done, that health care organizations also represent examples of complex adaptive systems (more on this in future posts).  One of the most interesting characteristics of complex adaptive systems, at least in my opinion, is the third point above - the fact that there is no centralized coordination of the collective actions of the different parts or agents.  And this is a topic that I wish to further explore in future posts.

"It's a small world after all..."

How many times in the last week have you or someone around you uttered the phrase, "Small world" or "It's a small world"?  I bet it's happened at least once.  As a matter of fact, I just heard this phrase yesterday afternoon, when one of my colleagues was talking about another physician who happened to know me.  There is a reason for this phenomenon, and I talked about it briefly in my last post ("Six degrees of Kevin Bacon") is that it is indeed a small world!  Duncan Watts, a scientist at the Sante Fe Institute who has studied what is now called the small world problem wrote, "The experience of meeting a complete stranger with whom we have apparently little in common and finding unexpectedly that we share a mutual acquaintance is one with which most of us are familiar - 'It's a small world!' we say."  

As I mentioned in my last post, Stanley Milgram and others have shown that any two individuals selected randomly are "connected" via a chain of no more than six intermediate acquaintances.  Everyone on the planet can theoretically be linked in this manner.  It sounds like magic, but it's not.  Allow me to introduce you to the fascinating science of networks.  Networks appear virtually everywhere - the World Wide Web is a network of websites, the brain is a network of neurons, organizations are networks of people.  Food webs and metabolic pathways are comprised of networks.  Diseases, like COVID-19, are transmitted through social networks.  Energy is distributed across power grids that are networks.

Many systems can be modeled as networks, which are structures consisting of nodes or vertices connected by links or edges.  In the late 1950's, two mathematicians, Paul Erdős (remember the Erdős Number?) and Alfréd Rényi described what are now called random networks (also known as ER networks), which are networks with N nodes, where each node pair is connected with a probability of p.  All nodes have the same chance of being linked.  Erdős and Rényi showed that if N was sufficiently large, almost all nodes within the network will have the same number of links (the number of links per node actually follows a Poisson distribution, a distribution with a prominent peak and rapidly diminishing tails, indicating that the majority of nodes have the same number of links).  Translated to today's society with a world population of 8 billion, most of us have roughly the same number of friends and acquaintances (our "network" if you will).  That's pretty cool (and brings to mind something I've posted about in the past called "Dunbar's Number"), but it still doesn't explain the small world problem.  Enter Duncan Watts and Stephen Strogatz, who took the concept of random networks one step further in their description of "small world networks".  

A "small world networks" is a network in which most nodes are not neighbors of one another, but most nodes can be reached from every other node by a small number of "jumps".  "Small world networks" have a number of unique properties, and in order to explain those properties, I need to define a few terms used to describe the properties of networks.  First, "small world networks" have a high number of nodes with a large number of connections (we call these "high degree" nodes - these high degree nodes are often called "hubs").  "Small world networks" also have a short average path length (the "distance" or number of jumps between nodes).  "Small world networks" also have a high clustering coefficient (which is the fraction of pairs of neighbors of a node that are also neighbors of each other).  This high clustering coefficient is what sets "small world networks" apart from "random networks", which tend to have low clustering.  

The unique properties found in "small world networks" really explain why we can theoretically be connected to a complete stranger in less than six steps.  Our society today is one big "small world network."  "Small world networks" have a number of important implications.  On the positive side, communication between the individuals within a "small world network" is very easy and efficient (again, it takes just a few steps to reach every other node on the network).  On the negative side, the spread of disease in "small world networks" can be quite rapid (think of how quickly COVID-19 spread across the globe).

The high degree and low average path length that characterizes "small world networks" means that we can be connected with a number of individuals.  Note that our social networks typically include both close friends (i.e., individuals that we share strong connections with) and mere acquaintances (i.e., ones that we have weak connections with) - as we will see in a future post, these strong and weak ties can have different implications as well.  For today's post, however, I will end with a quote by the author James Gleick, (Gleick's book Chaos: Making a New Science is also a great read and one I will eventually discuss) had this to say about "small worlds": 

"If we want to live freely and privately in the interconnected world of the twenty-first century - and surely we do - perhaps above all we need a revival of the small-town civility of the nineteenth century. Manners, not devices: sometimes it's just better not to ask, and better not to look."  

If we are indeed all connected (and I hope that I've convinced you of that), then that's probably the best advice we could receive.

Six degrees of Kevin Bacon

Several years ago, the social psychologist Stanley Milgram conducted an experiment that I am 100% certain that all of you will recognize, even if you don't know of the full details of his experiment.  It is called the small world problem, but you are probably more familiar with its other name, six degrees of separation.  There was a popular game played at parties a few years ago that is based on Milgram's experiment and the suggestion that any actor can be connected to the actor Kevin Bacon in six steps or less based upon whether they mutually appear in the same film.  Here's an example - let's start with the singer/songwriter Taylor Swift, who has appeared in a few television shows and movies during her superstar career: Taylor Swift first appeared in the 2009 movie, Hannah Montana: The Movie, which also starred the actor, Lucas Till.  Both Lucas Till and Kevin Bacon appeared in the 2011 movie, X-Men: First Class.  So, based on the rules of this game, Taylor Swift would have a Bacon number of two (she can be "connected" to Kevin Bacon via two steps).

If you are so inclined, there's a website on the Internet called "The Oracle of Bacon" that calculates the Bacon number for any Hollywood actor.  The author Malcom Gladwell wrote about this phenomenon in his book, The Tipping Point.  While I really liked Gladwell's book, a better and more scientific discussion of the small world problem and six degrees of separation can be found in the fantastic book Linked byAlbert-László Barabási.  As both Gladwell and Barabási explain in their respective books, there really is nothing magic about Kevin Bacon.  He just happens to have appeared in a large number of movies.  As it turns out, pretty much everyone in the world can be linked to a complete stranger in six steps or less, which is exactly what Stanley Milgram showed in his "small world experiment" in the 1960's.

Essentially, Milgram recruited individuals living in either Wichita, Kansas or Omaha, Nebraska.  Individuals were contacted via regular mail and provided with an explanation of the experiment and detailed instructions.  The materials included the name of a randomly selected individual living in Boston, Massachusetts.  Study participants that personally knew the individual living in Boston were asked to send a postcard directly to that individual.  Everyone else was asked to mail a postcard to someone that they knew who might know the person living in Boston.  Each time that the postcard made it to an intermediary, a postcard was returned to Milgram and his study team, so that they could track the chain's progression to the target individual.  

The experiment was actually conducted several times.  At times, the postcards reached the individual in Boston in just one or two steps, while at other times it took nine or ten steps to reach the individual in Boston.  However, the average number of steps from the person living in Wichita or Omaha to the person living in Boston was just under six steps.  In other words, there were six degrees of separation between the two random strangers!

The small world problem has even come up in the field of mathematics.  There are supposedly six degrees of separation between every academic mathematician and a Hungarian mathematician named Paul Erdős.  Erdős reportedly published more papers during his lifetime (at least 1,525) than any other mathematician in history (Erdős is to mathematics as Kevin Bacon is to movies, apparently).  Mathematicians proudly report their Erdős number, which describes the "collaborative distance" between Erdős and another person, as measured by authorship of mathematical papers.  For example, the physicist Albert Einstein had an Erdős number of two, meaning that one of Einstein's co-authors on a paper happened to publish another paper with Erdős.  Unfortunately, it's not as easy to calculate one's Erdős number as it is to calculate an actor's Bacon number.  

I tried to calculate my own Erdős number once using an obscure website (see the "co-authors distance computation" page on csauthors.net).  Apparently, at least according to this website, my personal Erdős number is four, which I cannot believe is true.  However, when I look at how my Erdős number was calculated, I cannot argue with their analysis.  The fact that someone like me, who has never published an article in any mathematical journal can be linked to a famous and highly prolific mathematician in just four steps only further solidifies in my mind the concept that it is a small world indeed.  And perhaps that is the take-home message for today.  We live in a world that is highly interconnected.  Perhaps that is even more true today than it was at the time that Milgram conducted his experiment.  It is indeed a small world, and I look forward to delving into this concept further in my next post.

"I'll see you when you get here..."

What would you say if you knew that whatever words you spoke were going to be your last?  Twenty-two years ago this morning, United Airlines Flight 175 passenger Brian Sweeney tried to call his wife at 8:59 AM on September 11, 2001.  His wife did not answer, so he ended up leaving a message telling her that his plane had been hijacked.  He called his parents shortly thereafter and told his mother about the evolving situation.  He mentioned that the passengers were considering an attempt to storm the cockpit and take back control of the airplane.  He also said that he was worried that the hijackers would return at any moment and that he might have to hang-up quickly.  After saying their goodbyes to each other, he did hang up.  Minutes later, at 9:03 AM, United Flight 175 struck the South Tower of the World Trade Center in New York City.  The airplane crashed nose-first into the South Tower's southern façade at a speed of around 590 miles per hour, striking through floors 77 and 85.  At that same moment, multiple media organizations were covering the first plane crash into the North Tower that occurred about seventeen minutes earlier.

Brian Sweeney's wife Julie was teaching in her high school classroom when she was pulled away to answer a telephone call from her mother-in-law.  Brian's mother, Louise told Julie that Brian was on a hijacked plane that eventually struck the South Tower.  When Julie returned home, there was a call waiting for her on the answering machine.  From Brian:

"I just want you to know I absolutely love you.  I want you to do good, go have good times.  Same to my parents and everybody, and I just totally love you, and I'll see you when you get here."

Julie would later say in a video produced by the 9/11 Memorial & Museum, "When I got it, it was just so Brian.  I’m thankful for it. So thankful for that message. Because, at least I know, without a shadow of a doubt, what he was thinking. The calmness in his voice soothed me… And it’s very powerful. He made very powerful statements with that message."

Brian’s answering machine recording is now a part of the 9/11 Memorial & Museum’s collection.  In that brief moment of absolute terror, there's not a trace of anger, despair, or fear.  Just love.  As the ancient Greek Stoic philosopher Seneca said, "Pure love, careless of all other things, kindles the soul."

Today, I want to remember 9/11 with Brian Sweeney's message of love.  We need more of that in our world today.

Swing through the ball

I was never very good at golf.  Several years ago, my son and I signed up for golf lessons at one of the local public golf courses.  After about five or six lessons, I felt like I could at least do the basics.  It was a lot of fun.  But I am still not very good.

One of the things that I remembered most about the lessons is that when hitting the ball, you should swing through the ball (also known as "Ball is in the way of the swing; it's not the target").  In other words, rather than stopping your swing at the moment that the club makes contact with the ball, you should keep swinging and following through as though the club was constantly in contact with the ball.  But does that make sense?  Check out this slow motion video of PGA professional Brooks Koepka.  The ball literally gets launched into the air as soon as the club makes contact with it.

The whole point of a good golf swing is to reach maximum swing velocity at the exact moment that the club makes contact with the ball.  Golf instructors will say that swinging through the ball makes sure that you don't slow down your swing as you approach the ball. "Golfers who see the ball as the ultimate destination will undoubtedly start to decelerate shortly before impact. This happens because your mind has been trained to coordinate – more or less – the end of your swing with the wrongly defined final act – the ball."

As I think about it more, the same concept is true for setting personal and professional goals.  Once you set a goal (and we've talked about the concept of using SMART goals, i.e. setting goals that are specific, measurable, achievable, relevant, and time-bound), you should keep pushing through and even past the target, just as you would keep swinging through the ball in golf.  The point is to maintain maximum effort until the goal is reached, and the best way to do that is to aim past the goal!

"The Few and the Proud"

Whoever came up with the marketing slogan, "The Few.  The Proud.  The Marines." was brilliant!  The slogan has been used by the United States Marine Corps since the late 1970's.  Major General Richard T. Tryon was the Commanding General of the Marine Corps Recruiting Command when he said, "This slogan reflects the unique character of the Marine Corps and underscores the high caliber of those who join and serve their country as Marines."  I could not agree more.  I was proud to help our Marines during my brief stint as a pediatrician at the Naval Hospital in Camp Lejeune, North Carolina (now called Naval Medical Center Camp Lejeune).

The United States Marine Corps is one of the eight uniformed services of the United States (see if you can name all of them!) and has been part of the Department of the Navy since June 30, 1834.  The Marine Corps was first established on November 10, 1775 by resolution of the Second Continental Congress during the American Revolutionary War.  The Marine Corps was originally founded to serve as an infantry unit aboard naval vessels and was responsible for the security of the ship and its crew during boarding actions and raiding parties.  

Today, the Marines play a critical role as both an expeditionary and amphibious warfare force.  Former Marine Corp Commandant General Alfred M. Gray, Jr established the doctrine of "Every Marine is a rifleman", emphasizing the fighting spirit and combat abilities of the Marines.  As I have posted in the past, the Marines in my mind uniquely qualify as a High Reliability Organization with their doctrine of "commander's intent" which is the ultimate example of the High Reliability principle of "Deference to Expertise".  "Commander's intent" is designed to provide frontline leaders with the flexibility of execution and deviate from a specific plan of attack as the conditions dictate, yet still meet the overall goals and objectives of the commanding officer.  The guiding principle of "commander's intent" is that operational orders should specify the end state but leave open the method of execution.

As you can imagine, the process by which a man or woman becomes a Marine is not an easy one.  As the Marine Corps Boot Camp website states clearly, "There are few reputations more storied and none more deserving than that of Marine Corps Recruit Training. The difficulties this process presents to every recruit are as deliberate as they are legendary, as physical, mental and moral toughness are prerequisites to fight among our ranks. During these 13 weeks of intense battles, it is not enough to simply endure, you must prevail. Pushing through surrender’s pull. Pulling together to prevent all from falling apart. Tapping into the purpose that brought you here, to win for the Nation you fight for."

The final challenge of Marine Corps Boot Camp training is known as "The Crucible", a 54-hour test of the recruits' physical stamina, mental toughness, and ability to think critically under the most challenging of circumstances (check out the documentary produced by the Marine Corps here).  The name comes from the word "crucible" which is defined as "a severe test, or, a place or situation in which concentrated forces interact to cause or influence change or development."  First introduced in 1996 by then Commandant General Charles Krulak, "The Crucible" is what separates recruits from Marines.  It is both a test and an indoctrination, and it is the defining moment of recruit training.  

For many recruits, "The Crucible" will be the first time that they push themselves to the limits of their mental, physical, and emotional endurance.  If they do not quit, they will know what they are capable of in the future, which is usually much more than they ever could have imagined.  During their 54-hour test, recruits will encounter unique obstacles and challenges, all of which bear the name of a heroic Marine from the long, proud history of the Marine Corps.  After they complete each obstacle, one of their Drill Instructors will provide feedback and retell the story of the Marine for whom the obstacle is named.

Theodore Roosevelt once said, "Nothing in the world is worth having or worth doing unless it means effort, pain, difficulty… I have never in my life envied a human being who led an easy life. I have envied a great many people who led difficult lives and led them well."  I think that Theodore Roosevelt would have loved the concept of "The Crucible".

While most, if not all of us, will likely never go through an onboarding process quite like "The Crucible", we can certainly appreciate the great lengths to which the Marine Corps goes to make sure their recruits are properly onboarded and indoctrinated in their organization's culture.  Perhaps there is something here that other organizations can learn from in their own onboarding process.