Miracles and Nasty Surprises: Coherence and Emergence in Organizations

by Hugo Letiche, Michael Lissack, and Ron Schultz

A Web Introduction 

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Miracles and Nasty Surprises (MITPress forthcoming) looks at the role of coherence and emergence in organizations. Coherence is regarded by many psychologists as critical to day to the day productivity and effectiveness of individuals. Both scholars and managers have adapted this belief to the world of management and organizations. Coherence is regarded as a sign of a well run organization. But, the concept of a coherent thought defined as how well an idea holds together as a single entity gradually breaks down as the scale shifts to individuals, groups, and ultimately larger organizations.

Adapting to and dealing with emergence is perhaps the most important task facing managers and organizations. Coherence as traditionally defined interferes with that task. We wrote Miracles to begin to address the consequences of the mistaken idea that coherence -- in activities, in purpose, in carrying out one’s individual or the organization’s tasks -- can be measured by the degree of conformity between the activity, purpose, or task in question and some predefined definition. By restricting the concept of coherence to measurement against definition (what we will call ‘ascribed coherence”) managers and organizations implicitly are restricting their ability to deal with the unknown, the uncertain and the emergent. 

We provide another perspective on coherence. Our perspective is rooted in the felt experience of coherence and in the importance of emergence.

We call it “emergent coherence.”

This introduction to the work walks you through some of our reasoning.  We wish to emphasize that our book is not a discussion about truth.  We are not making truth claims. Richard Rorty tells us, “Knowledge is not a matter of getting reality right, but rather a matter of acquiring habits of action for coping with reality.” (By using this quote we are not suggesting we endorse a Rortian point of view. Rather more restrictedly, we like the quote and find it helpful.) In common parlance such coping mechanisms are called “models.”  This book calls for managers and members of organizations to make use of some very different models as part of their coping mechanisms.  

Let us begin by describing some of the characteristics that people attribute to the world we live in.   It is not an all-inclusive list, and its components may actually conflict with one another, but people use each of these descriptions in describing the world.  To some, the world is God-given, fixed and stable. To others, it is slowly evolving.

To still others, it is alterable by man … filled with the unpredictable, emergent, chaotic or random.

Table 1
What Kind of World Do We Live In?  

·      God Given, Fixed and Stable
·      Slowly Evolving
·      Alterable by Man
·      Filled With the Unpredictable
·      Emergent
·      Chaotic
·      Random

This list can be separated into categories. These categories are distinguishable on the basis of the models that we use to simplify reality.   To managers, to people concerned with organizations, the list breaks down such that they are most comfortable with the top four items. The world might be God-given, fixed and stable. Maybe it’s slowly evolving. Clearly, if something happens it’s alterable by man.   The challenge of management, the thing they hate the most, is that it’s filled with the unpredictable.

Complexity theory suggests that the bottom four elements seem to be more applicable.  The emergent, chaotic and random can be added to “filled with the unpredictable”. There is thus a divergence here between what complexity theory suggests is important and what managers believe is important.   Remember, this difference is not about truth claims.  It is about how we cope with reality.

Part of coping has to do with how we use words.  In terms of language, the things that appeal to managers also are things that allow us to make use of codes. Codes are items that, in theory at least, have a one-to-one mapping with something in a hypothetical lookup table.  If one was omniscient and could write the lookup table that encompassed the entire world and thus knew everything, in theory, there should be a code that would match every item and could be looked up.

We do not believe that such a codebook exists.

But, we observe there are plenty of people, especially managers, who when they speak seem to believe in that codebook. Such people speak as if they are speaking in code, and as if everyone listening has a copy of the codebook. When they use a word, they believe that all of their listeners know exactly what was meant because, in theory, this codebook is out there. With that belief, the manager is free to speak in code. Indeed, if the world were fixed and stable or only slowly evolving, there is even a reasonable possibility that the codebook could work.  Codes can be looked at as an ascribed label. One can assign a label to something, and it’ll match the codebook.  

Complexity theory has its own approach to language. The complexity approach to language suggests that many of the signs we exchange are not codes, but cues.

This approach suggests that the meaning is triggered inside the head of the perceiver and that there is some set of history, background, culture, environment, context in which the perceiver is operating. When the cue is given, the cue triggers meaning. Cues do not have one-to-one lookup tables, so cues are very different from codes.

We believe that managers and organizations need to recognize the power of cues.

People differ in what they accept as constituting an “explanation. ” There are people who believe that explanation consists of assigning or ascribing a label to something, and once one knows what category it’s in, one has explained it. There are other people who are far more concerned with understanding mechanism. How do things work?   How do things come to be?   To the first group, explanation is equivalent to ascribing a label, and once one has the label, the label has explained something. The second group vigorously disagrees. Labels are not mechanisms.  These people need narratives that can deal with the emergence of the context. An explanation or a mechanism that works in a fixed world may not work in a changing world.  People in the second group thus need to keep having narrative retold in current context.

We believe that the ascribed label “coherent” is not enough.

The astute reader will notice that so far in our narrative management, codes and ascribed labels have all gone together. Complexity theory, cues and emergent narratives have all gone together.

We believe that one traditional function of management is to create intentional coherence. To do this, management attempts to provide enough labels and codes to the organization and its members so that an observer might ascribe the label “coherent” to the organization and its activities. This perspective suggests that the use of labels helps people to have some actionable view of the world. We go back to the Rorty quote.  We need a way of reducing the world enough that we can cope and act. Labels form a very valuable role in limiting the world. From the traditional management perspective, one engages in activity for the purpose of applying intention and having it be coherent. Complexity takes a different view. Emergence happens.  Activity occurs in a context where emergence happens.  

Both traditional management and complexity suggest there is some kind of interaction that could occur between coherence and intention.  Traditional management tends to assert that one can create coherence through intention alone. Complexity perspectives reject this idea except in circumstances where there is coercion.  If one applies superior force, one temporarily can create intentional coherence.

That coherence, however, is fear of the force, and it does not mean there’s actually underlying coherence at all.  Once the force is removed, it becomes evident that coherence was just an illusion.

Perhaps to overstate the traditional view, if one supplies intention as a manager, one can demand coherence, and this approach should work fine in that nice fixed and stable world or world that is slowly evolving.  From the complexity view, the manager’s task is different.  The manager’s task is to attempt to guide the organization through whatever emergence unfolds. The shorthand that we use to express this is: “to a river, be a canyon. ” This is what complexity suggests a manager is supposed to do.

 Traditional View

·      Managers Supply Intention/Demand Coherence

·      No Room for Emergence or Situatedness

 

 

 Complexity View

 ·      Managers Attempt to Guide Organization through the Unfolding Emergence in which It is Situated

 

 

If the Rorty quote holds, then managers are reducing the world down to something that allows them to cope with reality. 

 ·      The first responsibility of a leader is to define reality. ”  -- Max DePree

·      “Leadership is the art of getting someone else to do something you want done because he wants to do it. ”  -- Dwight D.  Eisenhower

·      “Leadership is getting someone to do what they don't want to do, to achieve what they want to achieve. ”  -- Tom Landry

Given that the present reality is complex, the issue at hand is how do we reduce complexity so that we can cope?  The degree of complexity present is the degree to which our chosen method of reduction has failed.

If we can’t reduce it, we’re stuck with it. Models are one form of reduction.  They’re not the only one.  There are also such forms of representation as language, poetry, art, etc.  There are many forms of reduction available.  

So why model?   We model in order to feel able to act in the world. The kind of model this book focuses on is the one that allows us to create the illusion, at least, that we’ve reduced the world down to something we can understand and act upon.

Again, this is not a truth claim. It is merely that we are willing to sustain the belief or the illusion that we are capable of acting. We reduce the world to create that illusion or belief for ourselves.  Traditional management tends to be concerned with realist models of reality and realist models tend to deal with codes.

Realism is often juxtaposed to constructivism.  Constructivist reductions take far more advantage of cues. Another way of looking at this is realist models tend to leave the perceiver out. The self that is dealing with the model is not part of the model.  Constructivist reductions in cues make explicit recognition of the perceiver. The self is imbedded in the model.   There’s a tension here.

The most used model in management theory is the model of the bell curve, or a Gaussian distribution. If one were to study for an MBA anywhere in the world, one of the first things taught would be statistical control based upon a bell curve. Managers learn that the world consists of Gaussian distributions, and that one can safely ignore the occurrence of things or events past the second or third standard deviation. In theory, if one understands the bell curve, they understand how the world works.  It’s an interesting reduction. It’s clearly a way of reducing the world in order to achieve an illusion of the ability to cope, and ….  it’s dead wrong.  

 

 

The Gaussian distribution is based upon a distinct set of assumptions.  The first is that ascribed labels matter.  If a label is assigned to something, the assignment will be accurate within two or three standard deviations, and that’s good enough.  

The second assumption is that whatever we’re encountering in the world obeys the law of large numbers.  This states that large numbers drift toward obeying the Gaussian distribution.  But, it is the third assumption that is the most critical.  The real underlying assumption of a Gaussian distribution is that events are independent and truly random (in a mathematical sense). We don’t live in that kind of world.   Rather, events are at least partially correlated, and usually not fully independent.

What we believe to be random is some illusion of randomness -- the patterns do not match the mathematical definitions of true randomness. As a result, random as the layman sees it is not really the random of mathematics on which the distribution depends, instead there are elements of connectedness and mathematical deviations from the true random.

We misunderstand the law of large numbers to suggest that when we see noise, it’s noise. Complexity theory suggests that “noise” might be a weak signal of something else.   The law of large numbers makes no room for weak signals.   The problem with ascribing a label, and using it as your method of explanation, is that once one has ascribed it, once one has said this belongs to Label X, then the explanation is done. There’s no room in that ascription for emergence. Yet, emergence happens.

If you shift your scale, if you shift your context, if you encounter something new, one might spend a lot of time trying to make the old ascribed label fit. If you are the “explanation is the assignment of a label” kind of person, you don’t spend time trying to understand the emergence that has just occurred.  

 

 
The graph above illustrates the problem. Much of the time the middle section of the graph, the part all the way over on the right, should be smaller.   Again, much of the time, the tails of the graph actually do not fall off anywhere near as sharply as Gaussian distribution suggests, and should be bigger (the supposedly rare events are less rare than the distribution suggests).  Outside events, which the Gaussian distribution suggests should be disregarded as noise, may have some validity and should be investigated.   The “average expected” middle, which the Gaussian distribution suggests will have that nice distribution around it, is also not quite as big as we are led to believe.

They don’t teach this in an MBA program. They should.

When we observe events where the Gaussian distribution does not apply, what does that signify?  Is it noise?  Is it emergence?  Has one shifted scales?  Has one shifted context?  Is it a weak signal of something?  Is there partial dependence or partial correlation?  When the Gaussian distribution is inappropriate as a label, it’s a strong cue.  If one learned statistical control, ala Edwards Deming, when Gauss is inappropriate, it’s a signal that there’s noise, and the system is broken. But this may not be at all what the signal is. Instead, when the Gaussian distribution fails to hold, it may signal that emergence is occurring, it may signal that the wrong questions are being asked, or it may signal that prior categories are breaking down.  The concept of “model” which we teach managers often fails to convey these lessons.

What implications have we reached so far?  The first is that the conclusions that managers have about noise could be very wrong.   The second and more important one is that our assumption about what predictions work and how we go about making predictions may also be wrong. This is because, again, in the organizational and management world, most of our understandings are based on the idea that we live in a Gaussian world.   And, if that’s an incorrect assumption, then again, both our understandings of what is noise might be wrong and our basis for making predictions might be wrong. Finally, our working model about models may be wrong.  The very way that we attempt to reduce the complexity in the world and how we understand the reductions that result may be wrong. Too many times we validate assumptions based on the idea of the Gaussian distribution.  And, if our method of validation is wrong, maybe our assumption is wrong.  Making assumptions can be dangerous. But, making assumptions is what managers and members of organizations have to do to “cope with reality.”

Enter the modeling relation.

It turns out that there is a nice, formal theory to talk about all of this.  It was done by a systems biologist named Robert Rosen.  He called this theory ‘the modeling relation’.

 

Rosen’s Modeling Relation

What the modeling relation portrays is as follows:on the left (#1) we have a natural system of some kind (things happen in the natural system and causality is involved).   On the right (#3) we have a formal system (Formal systems might be math, logic statements, computer simulations, etc.) We can run many experiences, thought experiences, predictions, in the formal system to see what that implies about what a corresponding action should mean in the natural system.   Rosen claimed that if we have a means of going between the two—the encoding (#2 or how to represent in the formal system a potential action occurring in the natural system) and the decoding (#4 or how to carry out in the natural system a prediction made in the formal system ) —then we have a model.

If one can’t make all of the four elements work as shown, one doesn’t have a model, but rather merely a representation.   Rosen’s work was about distinguishing between the existence of modeling relations and representations that people were mislabeling as models.   The key to a model, in Rosen’s world, is the ability to use the model to make predictions, to have implications that are then observable in the natural system. If the model can do that, it is a model; if it cannot, then it is merely a representation.

Rosen’s modeling relation presumes some kind of objectivist stance.  Nowhere on this chart does one see a “perceiver” or “self.”  Thus, Rosen’s modeling relation assumes a realist world -- the same world as traditional management teachings.  Rosen’s modeling relation assumes that we can do one-to-one mapping, world to model and model to world. 

This same one-to-one mapping exists in how managers are taught to rely on the Gaussian distribution.  As long as Gaussian predictions hold up, it is fine to use Gauss as a model.  As a manager I can make predictions.  Those predictions have implications for the world. Most of the time those implications are validated.

Sometimes as a manager I need to tweak my encoding and decoding schemes, but in general the schemas are okay. Once we accept, however, that the Gaussian description of the world isn’t the real world because it ignores partial dependence and partial correlation, how do we fix this?    

Rosen assumes that one validates models via prediction. In general, when one is dealing with physical aspects of physical things, Rosen’s conception works pretty well.

However, when one gets into things that are more abstract, semiotic or conceptual, Rosen’s modeling relation has some problems. Rosen’s modeling relation assumes that that mapping’s existence is the definition of a model. No self; no perceiver; no observer.   The absence of self is a big deal, not a little deal.  One of the things we do in this book is to rebuild the modeling relation from a constructivist point of view.  Complexity theory tells us that a model only works if there is a self included.

Thus, we sought to fix the modeling relation by putting the self back into the model.  

Rosen started with a natural system.  Instead of a natural system, in our revised approach we are going to refer to an “external item”.   Our goal is to create a model of that external item which allows us to deal with its complexity or gives us the belief that we can deal with the complexity. We need to believe we can cope, to refer back to that Rorty quote.   Such beliefs are of course dependent on self and context.

Rosen then tells us that one needs all four elements (external item, self, context, and model) in order for the model to in fact function as a model, and that one needs to make explicit recognition of the four.  The problem with the chart above is that it starts in the wrong place. We need a chart which starts with self.

 
On the above chart, there is a subject existing in a context and doing the perceiving.  Since it is important to be explicit, we state that the goal is to recognize the essence of whatever the external thing is, however one may want to go about defining essence.  Once we have recognized that essence, we create the possibility for acting upon or with it.  We are going to define “model” as a reduced representation of the thing. It’s a reduced representation of the essence.  The chart includes three hermeneutic circles, and all three are important. The circles recognize that the self will have some ongoing, continually revised relationship with a reduced representation, which will change as one goes about making predictions and seeing whether they get validated by one’s understanding of the essence as one deals with it.  Notice that there is no room to ascribe a label to the essence.  This chart relies on an activity-based conception of the external thing and not on categories.

Changing the modeling relation in this way puts the self back, but it also changes how managers go about dealing with their world because once they recognize that the ascribed labels are reduced representations that only get validated in activity, they’re no longer fixed and stable.  They’re always open for questioning. They’re always part of a hermeneutic circle.  The questioning and thought embodied by a hermeneutic circle are not how we teach our managers to behave. The traditional approach of define, label, and then act in accordance with the label is no longer sufficient. Instead, there is a dialogue between temporary definition and potential action that must be attended to.

By doing this, the perceiving subject has been restored to prominence.  The very notion of encoding and decoding that was at the top and bottom of Rosen’s chart have been replaced by a set of hermeneutic circles – I come up with a representation; it cues me into meaning; I have a dialogue with context that may alter the representation, which cues me into more meaning, repeat. The real world has been replaced, instead, by a notion of an essence of whatever the external item is.   A model’s validity becomes a function of its usefulness in articulating that essence to self and to others.   If the model doesn’t help articulate something about the essence that is at least potentially actionable, then the model is no good. This is a very different test than can one make predictions and do the predictions have implications in the real world? 

Let us observe some lessons here.  Complexity challenges assumptions behind realist models.  Complexity and emergence can be accounted for in a constructivist model.  Constructivist models recognize situatedness in context, and management, in a world of constructivist models, is different from management in a world of realist models.  Do not rely on Gauss.  It is shorthand.  It works when it works, but when it fails, it fails badly.  Prediction alone is not enough, and one needs self in the use of a model.  If one wants to view a model as an abstract unusable thing, fine.    But if one is going to use a model, the role of self must be recognized. 

With a definition of model which includes self, let us now turn to looking at the world. 

We will begin as manager and look at a two-by-two matrix.   In the upper left-hand corner, we have certain occurrences with defined meanings, which we can call ‘the known’.    On the diagonal, moving down, we have things that either occur with probability or when they occur, we don’t really necessarily know their meaning, because the meanings are assigned with probability.    In the lower right-hand corner we have the things that are every manager’s nightmare, or they’re golden opportunities, which are the Miracles and Nasty Surprises.  These are things that occur with undefined meaning and uncertain occurrence.

 

Consider a classical but oft told myth.  There is no way that when Pierre Omidyar decided that he needed to get rid of his wife’s Pez dispensers and put up a website to get rid of them, that he had any idea that eBay would emerge.  That was a miracle.    All the people whotried to follow him on the Internet and create something similar thought they were operating in one of the other three squares.  The fact that eBay wasn’t replicable -- well, that was a nasty surprise. 

When management tries to talk of best practice, it thinks it can push things to the known part of the quadrant.  Many of the things labeled ‘best practice’ are lucky occurrences that happened originally in the quadrant labeled D.  If one leaves out context, self, situation, emergence, you can isolate that best practice into some algorithm.  Then, using the traditional model of reality allows one to presume the algorithm is in Quadrant A. The problem is that the algorithm may not relate to any of the applications in which it is being applied. 

Indeed, most of the applications of best practices that go on in the managerial world make this mistake.  They assume that a best practice is a code not a cue, and that it exists in Quadrant A.  The managerial perspective is intentional coherence.  One either finds an existing path and labels it or one creates a new label and enforces categories.  This goes back to explanation by assigning labels.   One is labeling things as coherent.   Again, we call that ascribed coherence.  

 

 

In the world of ascribed coherence, Quadrant D doesn’t exist.    The sphere of activity that goes on is trying to mediate between known and probabilistic meanings.  One takes action between the known and probabilistic occurrences.  With regard to the stuff that’s fuzzy and messy, one tries to find a model that supposedly resonates, like best practices.

But the resonance is one of recurrence.  This is resonance the way a computer would define resonance.  One sees the same pattern over and over again.  It is resonating.  That is not how humans experience resonance.  Resonance is an emotional reaction.    If there is no self, there is no emotion. 

Now consider the complexity perspective.    One’s goal is intentionally emergent coherence, which is a paradox.    There are many existing paths.  There is a possibility space with many new paths.  The manager has to figure out how to adapt, improvise and embody the paths that are being encountered.   In contrast to ascribed coherence, this is emergence coherence.  This is the coherence of experience instead of the coherence of a label. 

From this perspective, using the same quadrant labels, what was known to the manager is the self and the coherent.   Probabilistic meaning is found in groups, whose members do not all share the same meaning.  We don’t have codes that function in a lookup table all the time.   There are multiple models and probabilistic meaning notions.  Probabilistic occurrences occur out in the environment; there are always multiple possibilities for future events.  There are multiple affordances that are open to us.  In that quadrant of miracles and nasty surprises, we have emergence.

 

This chart is the same two-by-two matrix, but we have relabeled it by putting a self back into it.    If we draw the action perspective, the outside elements move around a little bit.    Action stays pretty much in the same place.  Story stays pretty much in the same place.  But in-between the quadrants there’s questioning.  Out between probabilistic occurrences and emergence is the field of adjacent possibles, the things we actually can move to as next steps. 

 

Resonance now becomes part of the hermeneutic circle, because we have to include emotion.   If we can tell a story that resonates, if we can find a vignette that resonates, then it can help propel understanding and action.    The mere repetition of a label does not. 

If we simplify the chart, we now have self in one corner, group in the other, along with environment and emergence.  Things between self and environment tend to be embodied things that we encounter.  Things between self and group are where the ascribed labels come in.  Where the group is trying to cope with emergence is the space of beliefs.

 

We have added to the chart above an area marked “resistant to analysis.”  We’re not very good at figuring out how to deal with the unknown.   There are things that are occurring out in the environment and adjacent possibilities that haven’t occurred yet; those are the puzzle.    This is the stuff that the manager is now faced with as a real challenge.  The manager can guide people through the rest of this circle.  The challenge lies in the area that is marked as resistant to analysis.

This model of management suggests that one guides the journey by providing narrative, that when one encounters a resonance signal, and then articulates it over and over again to amplify the resonance, assuming, of course, one likes the signal.  However, as we learned from Prigogine, one needs to provide a container to allow for self-organization to occur.

Managers thus have a role to monitor the boundaries, not merely for enforcement of ascribed labels, the traditional management task, but also to be looking for signals that need to be taken into account so that the boundary can evolve and emerge.  Narratives only work if the audience can relate to them.  Telling a story that is meaningless to the audience does not do any good.  There are people who might care about yesterday’s gyrations of interest rates and the municipal bond market in the United States.  It might be an interesting story because of the failures of credit ratings agencies.  But, most people do not care about such things.  It would thus be a very poor narrative to tell to this audience. 

Managers have to be willing to revise narratives as necessary, as emergence occurs, as context changes, as situations change.  And note, narrative is not merely telling stories.  Narrative is providing enough ascribed coherence so that the people hearing the story, the rest of the audience that’s part of the group with you, has got some kind of a potential willingness to act.

The purpose of narrative is to provide the illusion of overcoming uncertainty.   Uncertainty is a lack of potential willingness to act.    If one is willing to act, one is acting as if one is certain.  Ambiguity is something else.   You can have a willingness to act in an ambiguous situation.  You are not acting as if there was uncertainty because you were willing to act.  By definition, one is taking an action that’s as if one were certain. 

Narrative is about trying to situate the possibility space for the audience so that they can see what are referred to as affordances, the opportunities that are present in the adjacent possibles.    The only things that matter for the next action are the adjacent possibles.  To set up a vision, a mission, something that is out there to be aimed at and not have a way of relating that vision to what the next steps are, to what the adjacent possibles are, is a nice story, but it gives no guidance about what to do next.    The next steps are adjacent possibles, and they have to be situated in the possibility space.

There is always a space for articulating visions and great hopes and dreams.    But visions, great hopes and dreams seldom include the articulation of the next step, the adjacent possible.    So it’s great to spend time talking about where one hopes to end up in a year or five years, or how we’re going to be No. 1  in market share, or how we’re going to do this, or how we’re going to do that.   If one cannot tell a narrative that allows people who are part of the organization to know what to do next, that gives them a better understanding of the adjacent possible, then all one has done is to leave them floundering.  They have no idea what they’re supposed to do.  They may eventually stumble on a possibility and then there will be some distribution, which may even be Gaussian, about how lucky or unlucky they are about finding the right thing to do.

Vision alone is not enough.  Plans alone are not enough.    One has got to situate those things in the present context and then give the people of the organization some understanding of which adjacent possibles create what affordances -- so that they have some idea of what they should be doing.   One might be able to summarize a vision into a tagline, into some convenient phrase that can serve as a guide.  Southwest Airlines empowers its employees to take whatever action they think is necessary, as if the employee was the customer trying to travel on the journey.  In effect the little tagline they give everybody is:  “Do what one thinks is necessary as if one were the traveler, and we’ll worry about the rest of it later.” That tagline tells employees what their adjacent possible is, and it fits in with the airline’s vision that they will get to have significant market share and significant profits by providing superior service.   (That service does not include food or assigned seats, but in the long run, what their customers wanted was the planes to be flown, loaded, and dispatched more quickly.   It was a distinction of situating adjacent possibles to allow for action.)

Narrative is very respectful of the importance of cues.  It understands that the meaning of a narrative is triggered in the mind of the receiver and that there’s a dialogue between the story that’s being told and how it’s being received, and that this dialogue is critically important.  Stories as opposed to narrative tend to leave out their audience.  They make use of code.  The storyteller presumes that the meaning is obvious from the story that’s being told. 

Managers have recently spent a lot of time, especially in the U.  S.   and Europe and Australia, learning about storytelling.  It’s the wrong thing.  They should not be telling stories.    They should be trying to find meaningful narratives for the people that they’re trying to interact with.  That task places far more emphasis on looking at what meaning is being triggered in their audience’s heads, rather than looking for a great story to tell.

In the political world, stories are spin.  They’re the stuff that politicians come up with to cover things up.  The difference is the politicians recognize that we all believe these to be stories and don’t pay a whole lot of attention to them.  Managers haven’t learned that mistake.   We will close this web introduction with a final lesson:  Predefined ascribed labels are NOT the only means of finding coherence.

Consider the photo below:

 

We all could tell a great story about that photo.  Our stories would be vastly different.  All would be coherent. 

And when we tell you that the explanation is that the lady’s clothing got caught on the seat back just as the plane hit turbulence ….  . 

Managers face issues like this all the time.   Welcome to emergent coherence… the world of Miracles and Nasty Surprises.