What's in a Name, Part II

I've done some occasional browsing in Intellipedia and it is turning out to be a nice, if still limited, resource. The search feature is useful; for instance I found xx (a moderate number) of hits on the term "knowledge management." These hits are from the Intelligence Community's commentary, a meta-meta-data if you will. You won't find these connections through a conventional Google search as Intellipedia's search is not "federated." I've found some useful stuff that I plan to return to again sometime soon.

More exciting is the random page feature, something every wiki should support. The first few tries led me to pages similar to the CIA World Factbook. The next one was a serendipitous discovery of...

BOSPIAR - Innovation on Demand

My first impression was this was a serious case of acronymitis. But as I read the short series of posts, I find that the author is on to something. He is a describing the symptoms of a common organizational behaviour.

In IT, we are always using BOSPIAR for problem solving. It is used frequently in engineering, and more often than not in finance. It also seems to be the prevelent approach to our fledgeling LEAN efforts. Where do you use it in your organization?

BOSPIAR is a useful name for a common pattern, and I'm putting it into my Acronym Watch List.

How Intermediation Scales

This is an update to a talk I’ve prepared on knowledge management in organizations.  In a twitter conversation I said “intermediation scales.” When questioned at the time I couldn’t explain. Since then I’ve experimented and discovered how intermediation perpetuates and grows.

I draw upon the work of Michael Roberto’s “Why Great Leaders Don’t Take Yes for an Answer” and in my talk show in Slide 18 how his three Cultures, along with the addition of a “Culture of Self,” align with the process learning forms:

Process Learning	Culture	Framing
Manager	Self	Front line
Core Group	Maybe	Transparency
Executive	Yes	Decisions
Shadow Core	No	Secrecy

Organizations skew towards these cultures and the culture amplifies a certain framing of knowledge.  When we remove the Core and Shadow patterns we have a bipolar pattern of “Self versus Yes”. This occurs when knowledge flows freely and feedback is immediate and responsive. This direct and intimate relationship is the elusive Self-Organizing Team.  

Adding time, distance, people and even technology increases complexity.  Scaling up involves communications loss.  Scaling out is more desirable, however we don’t understand complex social systems well enough to understand how.  For scaling up, the mechanism is rather simple:

• ·         Intermediation increases through inattention
• ·         It scales up through norms of inattention (normalization of deviance)
• ·         It is reduced by focusing, which restores context 

Hence overly strong cultures which are fixated on a single purpose may also attend to unnecessary things.  And looser cultures and certain types of competitive cultures can improve focus.

This perspective on scaling supports my claim in Slide 22 that loose coupling is essential to smoothly functioning networks. 

Science and Sense-making and Hype and Promises

I was reading the slides from Dave Snowden's (@snowded) talk at KMWorld this week.  Most unfortunately I could not make the show and his Keynote.

In his talk two slides stand out for me. The first is titled “The nature of the system constrains how we can act in it.”  In this slide, Dave describes an ontological based set of principles for working with Ordered, Chaotic and Complex systems.  In regards to the Complex domain, one of the principles is “Real time feed back for control via modulators”

I think we need to carefully consider the wisdom Dave shares.  Modulators are not algorithms. Modulators are people who have the experience, gained by praxis, to disintermediate the contextual data.  From an anthro-centric standpoint, algorithms cannot sensibly switch the variable links.  For sensible means sense-making, in the manners that Dave describes in the slide titled “How do we avoid the hype and the false promises.”  

I’ve annotated the quadrants with my understanding of philosophy, which is nowhere near the caliber of Dave’s.  The annotation in the lower right (Prediction & high risk Scaling) is drawn from contemporary events. Readers might recognize it more readily by the old adage “History is written by the victors” (Walter Benjamin).  

I also think there is a spiritual dimension in sense-making that needs to be included; for it is the spiritual connections between us that most strongly influence the promises we give and receive.  However I am not at all qualified to describe where the spiritual lies in this framework.

Thinking about Governance and Managing Constraints

I follow Dave Snowden's writings on a regular basis.  The following tweet by Dave grabbed my attention, as it is in line with my evolving ideas on complexity in bureaucratic systems.

—“We need to stop talking about governance and start talking about constraint management”

I was about to reply with a quick question on governance, but didn't. In pausing I gave the matter some further consideration. In the shower I asked myself, what other practices do we need to consider?   The answer I found is posted here

Constraint management from tony1234

Basically what we have a 2X2 matrix of Managed Constraints, Algorithms, Instinct and Governance. These correspond with the Cynefin domain's ideas of practice:

• Managing Constraints is emergent, and thus locked to the Complex domain. 
• Algorithms are Complicated, but note that there is a penchant for local optimization. As a result, we miss the black swans. 
• Governance is overly constrained and thus fixed in the Obvious domain. 
• Instinct is inherently Chaotic as the combination of individuals and circumstances is path dependent (see slide 4).

Further consideration of this matrix reveals the characteristics of the system (slide 6):

• In the complex domain we design rituals to modulate decision processes.  See the Wikipedia entry to gain a sense of  how rituals are enacted into practice.
• Treating governance as programmable as suggested by Daniel Kkahneman's 'Strategy firms can think smarter', is just the latest idea in a long string of algorithmic management approaches dating back to Taylorism, McGregor's Theory X, and others. 
• In the obvious domain we design rules to modulate behaviors. It is easy, nay obvious, to prohibit bad behavior, and most rules are written accordingly.  In government every incident of fraud, waste and abuse seems to result in another rule, the consequence of which is bureaucracy by straight-jacket - an employee's hands are tied behind their back and the public is left wondering why service is so poor.
• In both the Algorithmic and Governance quadrants the activities we choose - local optimization and a penchant for stability - serve to hide key aspects of social systems. Intermediation is amplified in these domains.
• Engagement with the subject in both Managing Constraints and Instinct are by definition means of disintermediation. They differ in their approach. Dave recommends probes and safe-to-fail practices along with other ideas; please read his blog.
• Instinct is far from perfect, witness the many types of cognitive bias that have been cataloged. And after all, the future is unknown. There is a particular class of these unknowns that are important here in the Chaotic domain.  This is the subset of unknown-unknowns we recognize as unintended consequences. This result of these consequences is damaged relationships and a loss of potential relational energy.

No decision is consequence free. However, how we approach decisions matters. There is a significance difference between the probing methods of Dave's safe-to-fail, and the brute force (fail-safe?) or totally naive practices that people partake.

A Decision Lens for Complexity

This slide deck is a study of management and managing which is then set up in i-space, Max Boisot's classic reference for knowledge management. The practice of managing is drawn from Art Kleiner's "Core Group" theory. I demonstrate how knowledge work (the social learning cycle) is tangential to managing, and present a way that this can be studied using Cognitive Edge methods and tools.


A decision lens for complexity v10 from tony1234

A small repair

For some time my blog has been dysfunctional. All of the links were dead, the embedded slideshares were likewise merely static images. I have tried on a couple of occasions to adjust the template, without success. I've sent a couple of messages to the admins; with no feedback I have been at a loss for what to do. Today I tried again, changing to a new template, and suddenly my blog is working. Success, relief, and it is a sign to pick up the writing pace. For some reason, the fourth time was a charm.

A study of the Cynefin Framework

I had hoped to make the KM World & Taxonomy World meetings this year but couldn't manage it due to pressing tasks at work. I did meet up with a couple of friends and managed to meet one or two new people. In the course of conversations over what have we (each) have been up to, I mentioned this study of Cynefin that I have been working on. This is a deep dive into the transition spaces between domains which leads to some interesting conclusions.




Direct link is www.slideshare.net/tony1234/exploring-cynefin-transitions-v14 (as the slideshare frame is not functioning in some browsers)

A Look at Software Development in Government

I have been working out this thesis for a year or so and have finally wrestled it into a working draft.  The study examines DOD software development practices centered around the term "requirements" and the different contexts that we use the term in.  I use the Cynefin framework as an organizing tool, which leads to some interesting conclusions.




Direct link is www.slideshare.net/tony1234/brownfields-agile-draft-v11 (slideshare frame is not functioning in some browsers)

Exploring Transitions

I've been thinking about the new picture that covers the transitory domain since it was first posted at http://cognitive-edge.com/blog/entry/5734/...-to-give-birth-to-a-dancing-star/ and in particular I’ve been focused on the "Duffer zone" for which Dave Snowden has said:

… when you deliberately remove all constrains with no idea whatsoever about what you will do.  You deserve to die.

This does not square with what is a crucial association of this transitory framework - our awareness of the dynamic of a situation.  There is in this sub-model an area of deliberation upon the unknown and the impossible, which we attend to because we must when we find ourselves in certain situations.  As a result, I think this zone may be far richer than a first glance indicates.

The background for this discussion is a “system-of-meaning,”  where we have taxonomy and typology locked into conflict.  Taxonomies are information lattices formed under high constraints, while typologies are theories that can developed when there is an abundance of information and constraints are low.  From my post on Between Taxonomy and Typology:

(3.6)    We see the conflicts more clearly because the boundaries of systems are more visible than the rules and principles of behavior.  Thus transgressions of the rules may be more shocking because they occur in unexpected contexts, nearer the heart (center) than the edge.

(3.7)    Fragments slip through these boundaries. 

To understand this sub-model we need to look at both the high and low constraints and their interactions.

1.  High Constraints

If we consider our starting point to be the lower right corner “Deliberate Awareness of the Dynamic,” we will find in most circumstances that there are considerable constraints in place and our options for engagement and activity are rather limited.  When starting in the lower right corner of the illustration, there are only a limited number of options that one can try for.  This is an area of high constraints where only incremental change can be exercised.  There is no easy outcome in these sorts of activities or games and our choice of moves are rather limited.

I have found a concise example from classes in Political Science and Statecraft in Deterrence Theory.  When we consider the strategies through which a state can exercise its power in a bipolar relationship, we can construct movements from one cell to the next along the following lines:

    (1.1)    The desired outcome of bargaining is coercion, wherein the target party has acted through force that is real or implied.

    (1.2)    If the target does not yield, it is because one side has settled upon a strategy of escalation. This is brinksmanship wherein “…the threats involved might become so huge as to be unmanageable at which point both sides are likely to back down.” (ibid)

    (1.3)    A state can pursue an indirect strategy of diplomacy or soft power.  Outcomes are ones of mutual benefits.  Outcomes may also be the de-escalation of demands and other levers of explicit force.  Diplomacy expands the scope of engagements between the parties.

   (1.4)    The last available movement in deterrence is the opposite of brinkmanship, namely deception, propaganda or bluffing.  One party has hidden information that, when later revealed, underscores the weakness of the position.

These movements are sensible when placed within the sub-model of the transitory domain.  In the highly constrained situation these moves are all below the diagonal line.  The diagonal represents the Cynefin boundary between the complex domain and disorder, proceeding from disorder through ambiguity towards coherence as it rises to the right.

We cannot breach this line as we cannot design a strategy that moves from the deliberate and impossible to the easy and unexpected.  Such a move would require a radical change of constraints and that reconstitutes the problem into one in a different domain.  If we reframe the problem, then we are no longer oriented towards the complex domain – reframing reduces the situation to an ordered solution which by definition means the complicated or simple domain.  In similar fashion, the revelation of hidden information changes the context in the same way.  The transitory domain is fluid and we cannot fashion a deliberate strategy to “stay in place” for very long.

We can construct similar moves from contracting and negotiations:

    (1.1)    Demands and conditions;

    (1.2)    Chicken or defense-in-depth; also see the Chicken game;

    (1.3)    Integrative negotiation, the so called “win-win”; and

    (1.4)    And various forms of misdirection.

From certain forms of negotiations and Game Theory there is one final applicable move:
 

    (1.5)    This is the roll of the dice, the deadline of the clock, and the so called “moves by nature.” This is the limit of the unknown when a move, any move, is forced upon us. This last case is necessarily ambiguous and fits in the center cell of the sub-model. 

2.  Low Constraints

Having fleshed out the incremental moves available under high constraints, we need to examine the zone labeled “Exploit Occurrence” in a similar vein.  The critical characteristic of the Easy corner (upper left) is that when there are few constraints the people or agents in the system can readily – freely – move.

The baseline example for this scenario is the Technology Adoption Lifecycle model.  With the first move already provided and oriented towards coherence and the complex domain, we can easily plot out the moves:

    (2.1)    Innovators and early adopters accept the risks to seize the rewards that are promised. This is deliberate awareness, even though the risks (and failures) are not clearly apparent.

    (2.2)    The early and late majorities are the mainstream; they follow as more information becomes apparent.  A decision can be made on the basis of risks and rewards; this decision is rational or emotional and therefore the plausible movement case.

    (2.3)    We then find the laggards who avoid making the transition.  As they wait the circumstances change, until they face an abrupt transition whose consequences are unknown.

In marketing and technology diffusion we can design our (pricing) strategies towards the early adopters, the mainstream, or the late-comers.  And it is from marketing, rather than the technology adaptation model, that we can discover the last move within this region:

    (2.4)    The final case is one of deliberate bad acts to achieve disorder.  These are the Luddites, copycats and intellectual property thieves, spammers and more.  The actor’s objective is to upset the normal system and introduce disorder which refashions the dynamics of the system in unexpected ways.

These moves are all above the line.  Curiously, in a free-movement system I haven’t found a move into the center ambiguous square.  By way of explanation, we cannot subdivide the laggards (the unknown and unexpected) in any meaningful way.

3.  Misinterpretation

While we cannot design a strategy that moves across the center line, we can all too easily mistake a situation and naively apply a strategy for a highly constrained situation to one of low constraints.  Or vice versa.

If we choose for instance to apply strategies for an open (low constraint), free-movement situation to a highly constrained, incremental movement situation, we may well end up in the “Duffer zone” suffering from Dave’s comment about “no constraints … deserve to die.”

On the other hand, we may attempt to apply high constraint strategies to a free-movement situation (or system).  The outcomes that succeed or fail in this case are likely to be more random than they are deliberate.  We will chalk up these outcomes to surprise, or intervention, or luck in post-hoc rationalization (retrospective coherence).  This case is probably a return into the chaotic domain vice an ascent into the complex realm.

4.  Collaboration

Collaboration also has a role to play in this transitory framework.  We can see a ready alignment between early adopters and the dominant power in the easy—deliberate cell (upper left right).  We also can see a natural alignment among bad actors in the impossible—unexpected cell (lower right left).  These two collaborations have no predictive power as the system will stabilize and form or collapse without either coalition’s contribution.

The horizontal axis of the unknowns is peculiar case.  There would not normally be a confluence of interest between Brinksmanship and Laggards, as the zealots pushing their increasingly radical proposals are avoided and ignored by the late adopters.  I suspect this dynamic tends to reinforce the status-quo, especially when the laggards are a large fraction of the population.

The vertical axis of the plausible is the most interesting combination.  Here we find in diplomacy and integrative negotiation a predisposition towards engagement and the expansion of boundaries in “win-win” agreements.  We also have in social networks, which are open, free-movement systems, the known accomplishments of swarming and crowdsourcing.  The combination of these two interests may well represent a significant predisposition in this framework.

In summary this transitory framework is quite rich and complex. It contains a number of surprising connections and is asymmetrical enough that it defies reduction into 2 x 2 forms.

Between Taxonomy and Typology

1   The War Between Taxonomy and Typology

David Weinberger presents a conundrum in a brief piece in KMWorld magazine, “Who Cares About Knowledge?”  Is knowledge distinct or is it indeterminate?  Is it orderly or messy? Is it true belief, or just ideas and opinions?  Is knowledge embedded in content?  Or is it free floating in a web of human relationships? Weinberger concludes that “knowledge is becoming an old-fashioned term.”

Is he implying that we don’t need to talk about knowledge anymore?  That it is a term of art, of use only to specialists (aka knowledge managers)?  Perhaps some other idea, say “memes,” will supplant knowledge?  I’m sorry but I think I’ve heard this argument before.  This is just another skirmish in a long running battle. To use another old-fashioned term, it is the latest round in a war between Taxonomy and Typology.

2   The Knowledge Battleground

The starting point for this thesis is a blog by Dave Snowden titled “Typology or Taxonomy.”  Snowden cites as a reference an excellent paper by Kevin Smith, “Typologies, taxonomies, and the benefits of policy classification” in the September 2002 edition of the Policy Studies Journal.  Snowden describes a situation from his knowledge management consultancy work at IBM where adherence to an ingrained taxonomy led the company awry.  He concludes: 

The message is very simple, rigid boundaries have huge value in static situations so taxonomies work.  But where things are subject to rapid change and the possibility of encountering novelty is high, they [taxonomies] are plain dangerous.  However we do need constructs to make sense of the world and that is where conceptual frameworks, or typologies, come into their own.

It is clear that Snowden favors typology and is exceedingly reluctant to accept taxonomy as a guide.  He consigns taxonomies to the Simple domain, and finds them unsuitable for the rapid change of the Chaotic and the novelty of the Complex.

I’m not sure that I can agree with this proposition, as knowledge forms from the constant interplay between structured information and the amorphous, even formless, mass of data we are immersed in.  If we are to accept that ambiguity is a principle component of fragmented knowledge, then we must take a closer look at taxonomies and typologies and their interactions.  The patterns that are found in one frame of reference are different from patterns that are prevalent in the other.

3   Systems of Meaning

It is tempting to consider that our patterns are degrees of order, and to try and map them through the Cynefin framework. That approach leads us into the "I-space" described by Max Boisot.  However, "I-space" is too confining, and does not account for certain attributes of complex knowledge that are essential to understanding this puzzle.

(3.1)    Human systems are mutable – they are stable for a long while, until they suddenly change.  Stability is a property of the system, which suggests predictable behaviors in the ordered domain (simple and complicated) and probable ones in the unordered complex domain.  We will see that the form of the system is an emergent property based on how much information was available at its origin.

(3.2)    As we construct a taxonomy or a typology, we create a system of meaning.  As a novice, by the time we can talk cogently about a subject we are enmeshed in a taxonomic system of meaning.  The same holds true for experts constructing theories, for all theories are typologies.

(3.3)    So what we face is the continuous interplay of systems of meaning.  Patterns are more apparent when contrasts are strong, that is, when conflicts occur vice agreements.  When conflict happens, it will most often occur at the boundaries.  What we look at and think about human systems, what we see most often are the borders of systems.  That systems are constrained by their boundaries is inherent in the definition of all systems.

(3.4)    This isn’t to say that there are no conflicts over principles, which are the operating rules of a system of meaning.  There are plenty of conflicts over principles!  Still, it is genuinely hard to tell which type of conflict we are seeing: edge or inner.  The disagreements on the edges, the rubbing of boundaries, are conflicts that won’t change the running system inside.  The result is lots of noise and smoke, and infrequent change, which is what we see in all communities and social networks.

(3.5)    Human systems are consistent, although that consistency may or may not be coherent.  Each transaction that emerges from disorder drives the system towards consensus or coherence.  The transition itself forms a dampened oscillation, along with a shift in the community towards an empirical proof, or else towards a satisfaction that is fallible, the new consensus.  See Rotate-45-degrees-and-think-anew for an illustration of this process.

(3.6)    We see the conflicts more clearly because the boundaries of systems are more visible than the rules and principles of behavior.  Thus transgressions of the rules may be more shocking because they occur in unexpected contexts, nearer the heart (center) than the edge.

(3.7)    Fragments slip through these boundaries.  Stories move without difficulty as carriers of fragments and the providers of context.  In this sense of carrying, stories are dis-intermediated.  However, stories are more limited than fragments that are obviously “good” or “evil” or noticeable in some way.  Stories are filtered by culture, and what types of stories are acceptable are dependent on the norms of storytelling and the rituals of listening.  There are many more constraints on stories than on fragments.

4   Taxonomy

Taxonomy starts with scarce information and some observations or empirical evidence. We then search for some alignment of the evidence, producing an ordered set, which is new information.  When we build out taxonomies we aggregate information, and leave behind the scarcity that we started with. 

A taxonomy … classifies things based on clear empirical characteristics and will have rules that allow determination of location. They have clear boundaries … On the downside, once a taxonomy is established if something does not fit, it will be made to fit as the taxonomy itself creates a filtering mechanism through which we filter observable characteristics.  Kevin Smith

(4.1)    We can see the emergence of a system of meaning from praxis of a profession.  Practice is experience – an increase in knowledge - and eventually there is recognition, with or without titles, that you have knowledge and are an expert in some domain of information.  Within an organization, work leads to the formalization of a role, or even an office (organizational unit) as the system.  These patterns persist in the norms and cultures long after the condition of sparse information has disappeared.  What has emerged is a system of meaning where identity and knowledge grow together.  This is how the practice of “knowledge management” formed and how it grew into a recognizable domain of information.

(4.2)    Management is in its essence the making do with limited resources, inadequate time, and other severe constraints.  To talk of managing is to use language and metaphors of making do and accomplishing things when resources are limited.  It makes sense to talk of knowledge management when information is hard to come by, and when knowledge is scarce.  As we depart the condition of scarcity, we can still talk with our companions in the organization with the shared management concepts and terms that we grew up with.  KM makes sense in scarcity.  KM doesn’t work in a framework of abundance because management does not have terms and language for a world without constraints.

(4.3)    An autopoietic system is a system that grows and renews. (wikipedia/wiki/Autopoietic) We have just seen how taxonomy forms such systems from praxis.  Without the impetus of growth, the system destabilizes, turns chaotic, and decays into the confusion of disorder.  The system may also devolve into a simple and stable form that is superstition.  These systems of meaning are self-sustaining, unchanging, and have legitimacy in an information-is-sparse sense.  Conspiracy theories are one example of the devolved form of taxonomy.

5   Typology

Typology is possible when we have ample information. Typology also holds when there is more than enough and often far too much information.  We construct theories of various combinations of information and then filter by some measure of importance.  Filtering discriminates and excludes information, eventually reaching a balance that is the theory. 

In a typology the dimensions represent concepts, they do not necessarily exist in physical reality (although they can). As such typologies generate heuristics which are more adaptive under changing circumstances. On the downside the concepts can be arbitrary, may not be exhaustive and can easily be subject to clashes of interpretation.  Kevin Smith

The typology scenario differs from taxonomy because of the condition of ample information where disruption is far more pronounced.  I’m certain that systems of meaning will form, but the nature of these systems is not as clear.  It is much harder to isolate persistent patterns, and we will find a variety of system forms when there is an abundance of information.

(5.1)    For typology in the extreme, the condition is that there is too much information – a super-abundance.  Discordant information is the norm.  Snowden’s property of coherence is a necessary condition to attaining stable patterns. It isn’t a sufficient condition, as these patterns may be more like islands in the stormy sea than emergent, self-sustaining social systems.

(5.2)    We need look no further than the IT Department to find one example of the organizational form.  The practices of work may change fairly quickly, but the norms and culture of the group serve as memory that evens out the information flows.  When there is too much information, we must filter to reduce the level of discordance.  Filtering avoids disruption by creating compartmentalization or specialization.

(5.3)    Memory fails in larger groups as communications media do not scale effectively.  Diversity is lost because it is outvoted, it is not in the mainstream, and it is not loud enough to be heard in the Echo Chamber of the media.  Even with the best social media technologies, loud voices and hyper partisanship will drown out the diverse and obscure.  Consequently what forms is the notorious silo.

(5.4)    Silos exist to preserve order, because they are social structures that make knowledge simple and complicated (the ordered domain).  The primary characteristic of order is equifinality, therefore silos are open systems. (wikipedia/wiki/Equifinality)

(5.5)     Without silos the knowledge that the organization holds is at best complex and chaotic (the unordered domain).  It is an open question as to whether we can have an organization that is completely disordered and thus holds no knowledge.  I expect that any organization would collapse and disband well before the truly disordered stage, as smart people decamp into other organizations or communities.

(5.6)    An open system can easily devolve into conflict.  The conflict pattern is a situation where opposition becomes the operating principle for the social system.  The focus of the system becomes obstruction in all things, to the detriment of coherence. On the surface the conflict pattern seems similar to the silo and it’s equifinality, in so far as conflict is the emergent property.  Conflict breeds conflict; consider the so-called Law of the Jungle: “kill or be killed.”  On deeper inspection we will find that the language of the conflict pattern is one of provocation and escalation, and the conflict pattern hardens into a conflict system of meaning that is autopoietic, not open.

(5.7)    When there is too much information available, a group can reach consensus without coherence.  They can cherry-pick from the facts and construct the simple theories that we call fantasy.  This is another variation of the open (equifinal) system of meaning.

6   Balancing

To distinguish system forms in the case of ample information we need to examine an organization’s culture and its reaction to incoming (additional) information.  How does it react?  Does it avoid discordant incoming information?  Avoidance shows us a closed system.  Redirection and deflection are likely the hallmarks of a complex adaptive system - we can see that some change or some work (information processing) actually occurs in the handoff.  As noted in the definition of systems of meaning above, it isn’t clear whether any transaction impacts the system at a larger scale.  However, if we consider the interaction of information and constraints that bear on the system of meaning, we have illuminated the field where the patterns can play out.

(6.1)    When there is too much information, we can see in the equifinal characteristic of open systems the motivation to maintain the status quo.  Here we can see the roots of the antagonism of certain topologists who hunt the KM zombies and the other undead fantasists.

(6.2)    There is the reinforcing pattern of “remembering” that Patrick Lambe has described from his taxonomy work (http://wiki.sla.org/download/attachments/54264068/Taxonomy_KM_Lambe.pdf).  We filter naturally and we down-select based on preferences and aptitudes. Consequently, systems of meaning emerge.  Lambe’s remembering suggests that to change the form of the system there is a rigid set of bad habits to overcome.  We will find there is a particular rhythm that must develop to achieve effective remembering.  It is something that is uniquely found in story circles, campfires, and skilled tellers of stories.

(6.3)    Organizations consist of two or more silos.  Disorder occurs between the silos when they cannot agree and create a common meaning.  Where the silos do agree we will find a complex adaptive system where dialogue occurs.  The CAS system of meaning is one where taxonomy and typology are balanced and rapid change is possible.

(6.4)    There is one other case to include: exaptation.  Bricolage is less ordered, and less structured, than an open system; it takes more energy to cope with the abundance of information.  Bricolage is less safe than an open system, as the primary safety net of equifinality is missing.  But safety is not the operative motivation here, for if you want safety then fantasy is the easiest world to reach and inhabit.  Remember fantasy is the devolution of typology, and superstition is what devolves from taxonomy.  Bricolage is of course more familiar as pragmatism, the seeking of small gains from the system that one resides within.  Dave Snowden suggests that diversity may be key characteristic of the adbuctive reasoning of exaptation, see http://cognitive-edge.com/blog/entry/5575/exaptation-managed-serendipity-ii.  Also see Yiannis Gabriel’s discussion of bricolage at http://www.yiannisgabriel.com/2012/08/on-paragrammes-theory-of-organizations.html.

Emergent System of Meaning Types
Taxonomy	Typology
Praxis and learning (growth, autopoietic)	Silo (equifinal, open system)
Confusion (disordered, not a stable pattern)	Conflict (growth, autopoietic)
Superstition (equifinal, open system)	Fantasy (equifinal, open system)
Dialogue (complex adaptive)	Bricolage (complex adaptive)

7   Knowledge Redux

By the time we can talk cogently about searching or filtering, we are already embedded in an information system.  It may be a system of learning or remembering, or one of collaboration; these are stable patterns of information as we can see from Patrick Lambe’s taxonomy practice.  Other patterns of information which we can discover from following Dave Snowden’s principles of coherence are systems of power, of privilege, and of ignorance, both willful and blind.  These too are coherent systems of meaning.

(7.1)    What lies between taxonomy and typology is not a difference of information or even ideas.  What we are really seeing is the clash of systems of meaning in opposition.  Systems have boundaries and that is where the conflict occurs.  We do not often see the conflicts at the center, the heart, which is the ground from which the system forms

(7.2)    In the center of information space is a perpetual collision of systems. Concepts compete at the boundaries, but fragments easily slip through. 

(7.3)    It is only after we have recovered a perspective of the scarcity or abundance that once was in force, that we can finally talk about understanding and knowledge.  This perspective is what I believe Dave Snowden describes as cognition.

(7.4)    Other systems – of economics or of power – may have stronger effect than systems of meaning, and pure examples of systems of meaning may be hard to find.

(7.5)    We do not have a language for superabundance, nor do we have much language for low constraints – when there is little to hold us back from hurting others as we tell “our truths.”  I suspect this is the basis of David Weinberger’s complaint.

(7.6)    Principles may be in conflict, but if so, how can we tell them apart from the conflict over boundaries?  Complex knowledge emerges as the balancing along borders of systems of meaning.  Systems are both constrained and coupled as shown in this framework.  

(7.7)    If we balance well we have satisfied the conditions for social change; if poorly than we create the persistent resistance that we so often see.

(7.8)    Abductive reasoning is tightly constrained within certain dimensions and loosely constrained along others.  Contrast this with deductive reasoning that is uniformly constrained, and inductive reasoning which is generally loosely constrained.  Think of “best practice” and perfection as exclusivity seeking knowledge searches.  They focus on narrow criteria and as a result limit the possibility space they search.  On the other hand, “good enough” and novel need to be inclusive and thus they expand the search space of probabilities.

On Disorder in Organizations

I have finished a short series on management at Cognitive Edge. The series addresses complexity, organizations, bureaucracy and knowledge management.  A key tool in working through these topics is the Cynefin Framework with its five domains.

Disorder lies at the center of the framework. I've found that disorder is present in most organizations. Is this a familiar feeling?  Disorder acts like a black hole. We are trapped within it far more frequently then we may realize. It leads to circular arguments, self-referential knowledge and groupthink.  Once trapped, it is hard to fathom a way out. But we can escape.

Like it's physical counterpart, disorder has an edge. There is an event horizon that we can detect. We can, with an appreciation for the complex and the chaotic domains, learn to sense the boundary. I conclude my series with some ideas on how we might find this boundary.

Organizations are complex adaptive systems filled with intentional behaviour. What do we intend to do? That is the critical question in escaping from the edge of disorder.   

A Rallying Cry (3)

From a recent speech, Secretary Gates observes:

The tendence of any big bureaucracy is to revert to business as usual at the first opportunity. 

He offers a prescription that should apply to every organization: "It's time that the Army's officer evaluations also consider input from peers and subordinates - the people hardest to fool by posturing, B.S. and flattery," Gates said. "A more merit-based, more individualized approach to officer evaluations could also do much to combat the risk-averse, zero-defect culture that can take over any large, hierarchical organization."

source: Gates envisions a new game plan for the Army

The Devil in the Details

From one of the news feeds that I receive comes this wonderfull assessment of bureaucracy:

KOESTENBAUM'S WEEKLY LEADERSHIP THOUGHT
#483, 6 December, Peter Koestenbaum Ph.D.

ATTENTION TO DETAIL & BUREAUCRACY

Good business strategy requires staying in touch with reality, that is, paying meticulous attention to practical details and to the precise needs of your immediate and end customers. Visionaries often have trouble with these details. They do not comprehend that the forest is made of trees. ...

On the border between the objective assessment of reality and the ability to survive in it, is the bureaucracy that surrounds us. Balzac said that bureaucracy is a giant mechanism operated by pygmies. Concern with details is bureaucratic, but it is precisely such attention to meticulous preparation that ensures quality and thus success. ...

Bureaucracy is depersonalizing, alienating. It entails treating human beings without feeling, without compassion, without forgiveness, without consideration for their uniqueness or their special circumstances. It entails not touching their center. ...

Bureaucracy is nevertheless necessary for efficiency's sake. Bureaucracy gets you to work in the morning, provides your lunch, sends your paycheck, pays your medical bills, and sustains your job. Bureaucracy protects the nation from total chaos. It is a reality that you must confront, accept, conquer, understand, appreciate. But it is also a reality that you must never allow to destroy you as a human being, as a soul embodied in flesh and blood.

 

Between Hierarchy and Anarchy

<-ding-><-ding-> In my corner to the right, representing Big Hierarchy Inc, is Dave Snowden, a renowned expert of knowledgement management. Now entering on the left is Steve Denning , a purveyor of business narrative, representing Team Anarchy. This fight is scheduled for a few rounds or until some secrets are revealed...

In his post on November 26th, Dave talks about large organizations, big bureaucracies and businesses. On the other hand, in The Alternative to Hierarchy or Anarchy about his Radical Management book, Steve talks about techniques found in new, small, highly entrepreneurial businesses. For all the differences in their posts, and the vast difference in size, the two types of organizations have a lot in common. They are both grounded in the intellectual property business of providing software and services.

I think the real difference between the two alternatives is in how the work gets done. And so in this case we need to look deeper into the two systems being compared. In the matrix organizations that Dave discusses, and in similar large private and public bureaucracies, work comes from many points. However the rewards still come from the worker’s hierarchical connections. In essence, the boss who grants the rewards is the first among equals.

In the non-hierarchical, self-directed or even anarchical situations that Steve alludes to, work starts from within. But then were do the rewards come from? They come from the contract, explicit or implied, between the worker and the organization that is the sponsor.

If rewards matter to getting work done, then we need to consider how people are motivated. Looking at rewards under the best of circumstances provides a way to compare hierarchy and anarchy. If we look at the combinations of structure, motivation and reward, we can see that there is a relationship between both size and formality. The model I'll present here is a “best practice” one which shows all cases.

There are many subtle variations in the variables, enough so that we can find cases that “prove” the stereotypes of flawed organizations. Dave and Steve have cited some of these on a regular basis. There is plenty of evidence that monetary rewards don’t motivate very well, as Bob Sutton and other commentators describe. 

I think that the capacity to reward does matter significantly, and that there is a theoretical framework that  governs organizational practice. In order to follow the arguments and to recognize the claims and counterclaims, we need a framework that puts the discussion in order. Here is an attempt at such a model, a simple 2x2 management tool for looking at the alternatives:

 

They are both right. Hierarchy and Anarchy are opposed. It is just that context that lies between them that is different.  This round is a draw. <-ding-><-ding->

What is Lean Management?

If the word "excellence" is to be applicable in the future, it requires wholesale redefinition. Perhaps: "Excellent firms don't believe in excellence--only in constant improvement and constant change." That is, excellent firms of tomorrow will cherish impermanence --and thrive on chaos. --Tom Peters

An ongoing discussion theme on the Value-Networks list at Google Groups has been the intersection of “formal process and informal networks.” A new posting on the ValueNetworks.com website provides a graphic output of some of their latest Value Network Analysis (VNA) thinking, along with the claim:

“Value Network Insights™ fills the important white space in business performance – aligning the power of human interactions with processes to effectively manage complex business activity. Our more human-centric, role-based network view delivers the needed analytics. It brings a sharper business focus to collaboration platforms and reveals hidden network patterns that drive business performance.”

I first encountered this graphic in a posting which included the far more succinct and provocative question “Where does Lean Management fit in?”

To an IT Manager or a Project Manager, the diagram makes a lot of sense. Clearly someone has applied VNA to several companies that are heavily engaged in an IT effort for a complex supply chain. Details are not available, yet the graphic would be useful for insurance, e-Business (external focus) or even ERP (in a multinational).

Replace “Supply Chain” with your business and “BPM/BI” with your technology stack and it remains coherent, for it requires a tight focus on the internal activities of the company in order to effectively use the IT systems. And to run them as well. A tight focus on your external customers is by definition the nature of all business.

To begin to find out why this is such an interesting picture, we need to break Lean Management down a bit. To borrow an idea from top chefs, we need to deconstruct the conventional IT management recipe.

Set Boundaries (Plan the menu)

In a Cynefin based map the process and the product will reside in different quadrants. The Lean Manager rightly considers both to be equally important, and getting both the right product and the right process is an essential measure of quality for the management service. This is the practice of management and the praxis of better management.

The approach I am taking is grounded in the latest thinking in Knowledge Management as described by Dave Snowden at Cognitive Edge. The Cynefin Framework is the critical tool; it will be used to supplement the Lean Management graphic. VNA and Cynefin complement each other -- VNA is a discovery tool and Cynefin is used for organizing and classification in these assessments.

Knowledge Map (Assemble Ingredients)

The ingredients of Lean Management can be found as we examine the question “What do we manage?” Within the boundaries we have set the answers are startlingly easy:

• The supply chain is managed by contracts. All contracts are quite clear on deliverables. With rare exceptions all IT shops have service-level agreements (SLA); these are measured contract deliverables.

 

• All IT systems are managed by requirements. Traditional and agile development methodologies each deal with collections of requirements, even though they intentionally use different terminologies to distinguish one methodology from another.

• Collaboration is managed continuously as we manage people. We manage through employment agreements and performance appraisals. VNA analyzes Roles as a first-class object.

• Last and most important is the Social Network. It is fundamentally unmanageable!

The knowledge map at this stage can be used to supplement the VNA data collection effort. A knowledge audit using the techniques from the Knowledge Management experts at Straights Knowledge/Green Chameleon could be used. Their video series is great. I also recommend consideration of the anecdote circle as practiced by Anecdote.com.

Value Map (Mise-en-place)

A remarkable strength of the VNA approach is how it articulates the tangible and intangible values of the extended organization.

• Tangible deliverables are carried in transactions

• Intangible deliverables are knowledge exchanges, benefits and favors, and reputation.

Collectively, Roles, Deliverables, Transactions, Exchanges, Tangibles and Intangibles are first class objects of a VNA. To use our cooking analogy, these are the characteristics of the original dish which will be retained in the new creation.

As will be shown in a moment, Roles and Deliverables are firmly anchored in Cynefin based knowledge maps. Notably they are anchored in opposing quadrants separated by Disorder. This demonstrates that these two attributes are truly orthogonal. This characteristic can be used as a integrity test of your efforts; if you find these two in adjacent quadrants then you have not found the right level of analysis. Most likely your boundary conditions are not strong enough or your VNA has been forced to a premature and disordered conclusion.

The Cynefin framework is also an important tool to avoid over-analyzing your data. Especially with regard to social networks, I offer a caution that attempts to investigate the internal or external social network using these techniques for Lean Management will be doomed to failure. An excellent resource on the many reasons why social networks are unmanageable is The Relationship Economy.com

When using Cynefin we need to remember the Patterns as well as the labels. Simple and complicated form the Ordered set where knowledge can be discerned. Complex and chaos form an Unordered set where knowledge emerges retrospectively. Probe and act are not interchangeable, and in the chaos quadrant I dare say that sensemaking is found from reactions to your desired action; a pattern of Act-Respond-Sense.

The Cynefin framework has been rigorously validated -- you can’t change from act-sense-respond to sense-analyze-respond and discover reliable knowledge from the results because, in doing so, you have changed the boundaries of the social system.

Knowledge Re-Map (A cooking method)

We are finally ready to begin the cooking, or in our case, to actually classify the Value Network Analysis methodology and analysis that we have started.

The first step is to transform our Lean Management graphic into the prescribed Cynefin orientation. (Trust me on this; because there is so much to remember, you will be hopelessly confused if you don’t place chaos in its proper place).

We can test this transformation by applying the highly refined definition of Collaboration that Anecdote has discovered. Can we see the ascending scale of coordination, cooperation and collaboration in the work we are studying?

Our classification actions occur as we place the VNA first-class objects into this map. For illustration purposes we’ll start with a blank frame. Remember that we are looking at the completed VNA study with concepts that have meaning in your business or social network as your context. For example, Manage people becomes Managing Field Office X.

Because people are managed (whether we enjoy it or not) and because the people who care about whatever is the substance of an intangible will act on it’s behalf, we can reasonably say that intangibles are the product of probe-sense-respond (complex) as opposed to act-sense-respond (chaos). On the other hand, many exchanges occur without reciprocation or expectation. Thus a set of many named exchanges is clearly chaotic.

The same logic applies for tangibles, transactions and deliverables. An occasional surprise on this set isn’t worrisome nor an indication of “mistakes.” A sudden shock may indicate the serendipitous discovery of something interesting, a “black swan” event if you will.

Having built out your VNA analysis to this stage, you can see quite clearly that in using only first class objects we have an unbalanced knowledge ontology. What we have done is to classify the Ordered set of your business objects. These items are what the collected group of participants have agreed to. It is the common knowledge that they share!   

To fill the gaps we need to find a way to go back through the collected mass of material. Because we will now be working predominantly in the Unordered set, I can’t suggest a particular method that should be used. By definition, what makes sense to your group will emerge from the discussions you hold.

I suspect that the conventional alternative to the team discussion, either locking a couple of key people in a room, or leaving this step to your internal/external consultant, will produce results that are confused, incomplete, or judged inacceptable. Comparing the conventional and VNA approaches provides an example of how fragmented knowledge -- fail-safe and safe-fail -- emerges out of chaos.

It will only take a few items to bind the gaps. As a metaphor for bind, think of baling wire and string. We are simply preparing a package and not building a bridge. Adding too many items is a sign of clutter and a poor choice for the level of analysis.

For our IT Management case I will introduce some concepts from a career in a very large Government organization.


Across the bottom we will find concepts that are simple in principle and potentially complex in action:

• Everyone in the private sector is aware of their companies P/L Statement. In Government, the Program Assessment Rating Tool (PART) is a reasonable facsimile. Our ‘awareness’ is simple knowledge readily obtained . Conversely our ability to affect the “bottom line” is far more complex in a behavioral sense. The direction of the arrow signifies the relationship.

• Audits clearly drive work behaviors. While the change in behavior may be complex, in actuality it is the unintended consequences that are most often significant. This is the definition of unordered knowledge, in retrospect the ‘Unintended’ aspect is simple.

Our analysis here is quite different than the methods used for determining cause and effect in Lean organizations. In this enhanced VNA methodology we are working with an Unordered set of intangible objects. In Lean, techniques such as 5 Whys and Fishbone diagrams are used to investigate Ordered sets of tangible objects, the work on the factory or office floor.

At this stage of our analysis we can safely entertain questions of leadership. We can examine the question of “fair outputs or fair outcomes” that was excluded in the boundary setting stage. It is safe because we now have at hand an adequate collection of data that describes the true environment, rather than the privileged, preferred or artificial explanations of the status quo that are espoused.

Across the top we must place concepts that are more complex. We are now binding with string whereas the bottom is bound by baling wire. As a test, concepts along the bottom can quickly generate consensus. The concepts on the top will engender arguments, votes and minority reports.

IT departments are under constant pressure to manage many things. They are tasked with keeping the lights on, fixing bugs, upgrading the infrastructure and being prepared. They also provide new features, support new customers, assess and implement new technologies, and aid in the development of brand new lines of business. Add in reuse and repurposing (one is copying, the other adapting) and one can see how complex managing an IT department is.

IT shops I’ve known tend to organize their staff according to these functions - Development lead by Project Managers, an Operations unit (or units) and the Help Desk or Call Center. Top management, the Chief Information Officer, is most likely situated in the Chaotic frame. The area of significant conflict is across the top, where it boils down to the most difficult CIO decision (after staffing of course): “develop something new or keep plugging with the old.” The new disciplines of Enterprise Architecture and Systems Operations are simply the post-modern form of build and manage.

What has changed in the last decade is the complexity of the infrastructure. To draw an analogy, we are no longer managing a boxing match as was the case in the mainframe era, nor the football team from the PC and LAN age. It now takes small armies to support the extended infrastructure across the web. 

Gartner predicts a hyperconnected and spontaneous workplace in the next decade as the new supply chain (Gartner Says the World of Work Will Witness 10 Changes During the Next 10 Years). If half of what is predicted is realized, I am afraid that “Cloud Computing” will require we grow an entire marketplace within the castle walls.

It will be quite informative to observe the efforts and activities of the US Government (and other governments) in these three areas.

Presentation (Service a la ruse)

I can now reveal the big picture and explain the semantics of our arrows:

The arrows represent channels. The paired set of arrows is a manifestation of the complex adaptive system or social system that spans the two quadrants. Directionality indicates the bias or scale, and to be more precise, that the simple named concept has a complicated, complex or chaotic impact.

There is no fixed relationship between the two channels: they may be independent, amplifying or conflicting. They will co-evolve because the labels are descriptive of a metastable state. To dig any deeper will break the gossamer web and doom your attempt to disorder.

We can finally test the original claim that “Value Network Insights™ fills the important white space in business performance.” My test is the following hypothesis for knowledge management as theory and practice :

• With knowledge in hand, both process and structure are mutable. Without knowledge, we are left with the rituals of disorder.

• Using Cynefin we are constantly reminded of the rituals we may not see. Value Network Analysis spans that void, giving us in turn a tool that can indeed fill-in the white space on our cognitive map

I can’t say I have found Lean Management yet. What I have found is a recipe I can use to build Lean Management into my organization. I encourage you to give this recipe a try and please let me know where your journey takes you.