Entertain or Empower?

Ok, maybe it's a false dichotomy, but I think it's at least a contrast worth mentioning.

Neil Postman's classic "Amusing Ourselves to Death: Public Discourse in the Age of Show Business" has been one of my favorite books since I read it in the late 80's. In it, he asserts that an image-centric age (TV, etc.) is inherently unable to engage in deep rational discourse.

He may overstate the case, but I think he has a point. His focus was political discourse and education, but the same observation has been applied to televangelists, popular scientists, and in this satirical video, to television news.

So, what does this have to do with enterprise KM? If you're trying to convey concepts of any complexity, you face a real challenge: how to convey the knowledge to an audience whose frames and micro-narratives lean toward entertainment. This is not just a challenge of a short attention span...it's also a challenge of a lack of practice in thinking about complicated cause-effect structures.

Sophisticated tools and visually sophisticated audiences often equals flashy pablum. I suppose that's ok for Madison Avenue, but I'm not sure how effective it is for in-depth education, especially where training budgets are tight.

We've all had talented teachers who had a knack for engaging, challenging, educating, and empowering students without wasting their time with superficial entertainment, so we know it's possible...but that's a topic for another post.

I generally don't like making a negative statement without pointing out some possible solutions, but in the interest of space, I'll limit this post to highlighting the challenge of corporate communication and education in a culture that is visually hyper-literate.

Core Prerequisites for Effective KM?

Hagel & Seely Brown's Big Shift blog is usually worth reading...the latest post is a nice description of what seems to be an emerging agreement that catalyzing informal collaboration is the "sweet spot" of organizational KM.

This sentence caught my eye: "We've found in our research ... that new knowledge comes into being when people who share passions for a given endeavor interact and collaborate around difficult performance challenges." Though I'm sure they don't intend this statement to comprise a list of core prerequisites, it does seem like a plausible jumping-off point for discussion:

• Passion - it takes hard work to create distinctive new knowledge that clearly adds new business value. Sometimes it's difficult to find folks who are truly passionate about their work/customers/market.
• Specific Endeavor - serves to focus individual and group attention.
• Collaboration - even individuals working alone "collaborate" with themselves via an internal conversation.
• Difficult Challenge - forces folks to get outside of their normal thinking patterns
• Performance Challenge - provides constraints, resulting in more innovation within the remaining degrees of freedom?

Seems like traditional KM captures the past, while & Hagel & Seely Brown's "creation spaces" catalyze the creation of the future.

Knowledge and the Chief's Mess

There's way too many threads to chase (and far too little time to chase them) in a fascinating discussion of how the Chief's Mess has evolved in the U.S Navy. Here's at least a few of the issues that came to mind when I read this:

• The perhaps hidden risks associated with "rationalizing" work (roles, training, rotation frequency, etc.)
• How much in-depth knowledge needs to be available to deal with capabilities that are large tightly-coupled chunks of knowledge (often requiring deep technical knowledge to perform more than routine maintenance).
• The challenge of providing leadership that requires both robust people skills and robust technical expertise...one common solution being splitting the job between two people since individuals who have both types of skills are rare.
• Whether the mechanical (vs. IT) "tinkering" culture that was common a couple of generations ago has faded (again, see "The Puritan Gift"), and if so, why?, what are the implications?, etc.
• The risks associated with the loss of transparency that comes with building capabilities up from layers of interoperable components (e.g., cloud computing, multi-layered derivatives, etc.)

The author also explicitly addresses related issues (e.g., generalist vs. specialist).

Anyway, if organizational behavior/knowledge is something you're interested in, you might find this worth reading.

Panarchy

I debated saying anything on this topic...it just doesn't seem significant enough.

About the time Noah Raford's video discussing panarchy and Cynefin came to my attention, I had an e-mail exchange with a professor who has a long-time interest in panarchy (per Gunderson & Holling), but had never heard of Cynefin (he was, BTW, quite excited by Cynefin when I suggested he take a look at it).

Regardless, I must say that I'm a bit underwhelmed by panarchy, at least what I've seen in Raford's videos & slideshares. At the risk of oversimplifying, my initial reaction is that it seems like a synthesis of 3 concepts: (a) S-shaped growth curves, (b) the dis-integration of a system that occurs when the context to which it is adapted changes enough that the system ceases to be self-sustaining., and (c) fractals.

• S-shaped growth curves - these are well known, at least in systems circles (I feel obliged to offer that caveat since it seems like someone is always kicking up a fuss by using an exponential growth curve to forecast either utopia or doom....like the concept of infinity, exponential growth curves that never flatten are found only in metaphysics).
• Systems that fail to adapt and dis-integrate (not disintegrate) - this sort of thing always triggers TRIZ (the innovation framework) for me; a well-known business example is the Silicon Valley churn of resources and knowledge...most companies that become successful go through a classic S-shaped growth curve with an initially successful configuration, then fast growth, then stagnation, consolidation, and dis-integration...with the dis-integrated knowledge and resources made available for a new configuration. This cycle is shown in panarchy as a figure "8" on its side (or an infinity sign...a perhaps not-so-subtle hint (or perhaps ironic wink) that panarchy might very well be the sort of secret knowledge that appears in Dan Brown novels).
• Fractals - panarchic infinity symbols can be nested and as a context traverses the curve of the infinity symbol, it can both be part of a larger & slower curve traversal (at a different scale), and it can contain smaller & faster curve traversals within it.

I hope that my initial reaction reflects ignorance, but panarchy seems a bit too linear/wooden to encompass contexts that are truly complex. I like each of the pieces (discussed above), but the combination as seen in panarchy seems like a case where the whole is less than the sum of its parts.

Sensemaking - Cynefin

I first became aware of Cynefin in a 2003 IBM Systems Journal article entitled "The new dynamics of strategy: Sense-making in a complex and complicated world." It is largely associated with Dave Snowden, although Snowden has a co-author in both of the primary articles describing it (the other is in the Nov 2007 Harvard Business Review).

It is one of the few truly new things I've seen, and has become a part of my everyday vocabulary and thinking.

Cynefin is in many ways a deep framework. Although the basics are straightforward, its foundations/origins are fundamental and therefore have a wide range of potential implications and application.

Since it's documented in wikipedia and there are some good videos on YouTube describing it, I'll focus on areas that are perhaps less discussed. I should state that most of what follows is an attempt to honestly summarize what I've read/heard of Snowden's writing/podcasts. I may have not fully grasped some of what was conveyed; any mis-statements are unintended and my own.

• Cynefin seems to have sprung in part from a consideration of how ontology (study of the nature of being) interacts with epistemology (how we know) when it comes to making sense of a situation and translating that sense into action. See, for example, Snowden's 2005 article entitled "Multi-ontology sense making" at cognitive-edge.com
• Cynefin describes the combination of the world and our ways of knowing it via 3 basic categories: Order, Unorder, and Disorder. Disorder is an area of epistemological and ontological uncertainty. Order is an area where cause-effect relationships are stable and knowable. Unorder is an area where cause-effect relationships are unstable and our ability to know them is limited or non-existent. You can quibble about where the line is between ontology and epistemology in Unorder, but I think most folks would agree that our current state of knowledge requires that we acknowledge real epistemological limits in current theory (e.g., it's unclear whether it will ever be possible to describe what goes on "inside the quantum box", Godel's Incompleteness Theorem with regard to formal systems, etc.) and in current practice (e.g., the tangled loops of cause and effect that characterize Complex Adaptive Systems).
• Order consists of two subdomains: Simple and Complicated. This is where the traditional scientific method reigns...observe, hypothesize, experiment, repeat. In these subdomains, a reductionistic approach to understanding and creating systems is adequate.
• Unorder consists of two subdomains: Chaotic and Complex. The Chaotic subdomain is an area where cause and effect are unintelligible. And, the Complex domain is an area where cause and effect are tangled, with only pattern recognition possible.

One way that Snowden summarizes the domains is as follows:

• Order - the system constrains the agents
• Complex - the systems and agents constrain each other
• Chaos - the agents are unconstrained

Although I like that description, as someone who used to teach Statistics, I tend to want to add that the agents in the Ordered and Complex domains are probably much more heterogeneous (at least with regard to the qualities we're interested in) than the agents in a Chaotic domain. Whether Snowden would agree is unclear.

Finally, Snowden seems to enjoy the interplay between theory and practice, which is reflected in an ongoing and evolving synthesis of various concepts from the social, cognitive, and complexity sciences. Some folks find this a bit difficult to parse; personally, I enjoy the journey. See the Resources section of cognitive-edge.com if you're interested in learning more. Until Snowden's long-promised book arrives, you'll have to create your own synthesis of the ideas he's put forth over the past few years.

A caveat: as with any framework that (a) has evolved, (b) is non-trivial, and (c) has become popular in certain circles, some folks will distort it (inadvertently or deliberately)....the more sophisticated of these distortions evoke a response I first had 4-5 years ago when I ran across an astonishingly bad (yet sophisticated) misinterpretation of NCW theory (where the author tried to recast NCW into something he had created a decade earlier): "The best use of this would be as a final exam in a course on the topic, with the only instruction being 'List, explain, and correct the primary misconceptions in the following paper.'"

Work Design & Task Identity

Harvard Business Review just published their list of "Breakthrough Ideas for 2010." Since the new social-mobile information technologies hold the potential to restructure much of the work we do, I found the first "breakthrough idea" especially interesting: the single most important factor in great workday was a feeling that the worker had made progress.

One implication is that work should be structured so that everyone perceives clear progress each day. Among other things, this has a tie to Klein's Data-Frame model...work that is perceived as rewarding may be as much or more about how it's framed as it is about what is actually accomplished. Naturally, there are limits...a pig with lipstick is still a pig.

Anyway, this reminded me of one of the texts from my master's program...Hackman & Oldham's "Work Redesign" (kind of strange coincidence..tonight I was watching "This Emotional Life" on PBS and Hackman was one of the people interviewed). In this book, they propose a model of the properties that make a job rewarding. This model consists of 5 Core Job Characteristics that lead to 3 Psychological States necessary for high internal motivation. If you've not seen such a model before, you might find the 5 characteristics interesting:

• Skill variety - degree to which a job requires a variety of different activities, involving different skills and talents
• Task identity - degree to which a job requires completion of a "whole" and identifiable piece of work
• Task significance - degree to which a job has a substantial impact on the lives of other people (e.g., a fireman)
• Autonomy - degree to which a job provides substantial freedom, independence, and discretion to the individual in scheduling and carrying out the work
• Job feedback - degree to which the work activities provide direct and clear information about the worker's performance

Task identity is basically the "progress" component of a job.

I don't do this sort of work, nor have I ever used this model in any kind of analysis. And, the book dates from an era that was focused on enriching jobs (with some justification...though the enrichment in the West seems to have been much cruder and more superficial (at least in manufacturing), than in Eastern companies like Toyota), and was characterized by "expert" consultants who would come in and "fix" things.

Bottom line: even though much of Hackman & Oldham's analysis seems grounded in the older control of function & control of information paradigms, the factors they identify seem as relevant as ever...especially since we seem to be moving toward an era where knowledge workers will have an increasing amount of say in how work is organized and framed.

Sensemaking - Klein

Gary Klein is perhaps the leading researcher on how individuals actually make sense of a context. His Data-Frame model is an essential tool for anyone trying to improve decision making, especially on the edge.

In this model, Klein focuses on two sensemaking objects: (a) the data that is constantly streaming by a decision maker, and (b) the frames the decision maker uses to organize that data. As data streams by, frames are selected, elaborated, questioned, abandoned, and created. Although this may seem simple, it is not simplistic. Klein sees it as useful in catalyzing exploration; as with Weick's Enact-Select-Retain, it provides no simple answers.

A similar approach is seen in Zhang & Soergel's Sensemaking Model, which has a structure that seems slightly more linear than Klein's.

Klein is perhaps best known for his book, Sources of Power. Although it's only 10 years old, it's already a classic on how individuals make decisions...and, another "must-read" for students of sensemaking.

Sensemaking - Weick

Karl Weick has been researching sensemaking for almost 40 years. His "Social Psychology of Organizing" (2nd edition, 1979) remains the most thought-provoking book on the topic I've read, and is the first place I'd send someone who is primarily interested in an academic discussion of how organizations know what they know, and how they turn that knowledge into action.

It's unfortunate that many people associate Weick only with his recent research into high reliability organizations. This research is narrower in scope and applicability than his earlier work, and can leave the misleading impression that Weick is primarily grounded in an analytical approach.

And, since Weick's a social psychologist, his focus is on group (vs. individual) behavior and needs to be augmented by an individual/cognitive model (e.g., Klein's Data-Frame).

Weick's basic framework focuses on how individuals and organizations use knowledge to Enact, Select, and Retain meaning. Weick's writing is provocative and challenging...he provides no simple answers.

Despite the limitations of his approach and the challenge of navigating his writing, any serious student of sensemaking should make Weick's "Social Psychology of Organizing" and "Making Sense of the Organization" (collection of papers, 2001) required reading.

Bottom line: Weick's "Social Psychology" remains for me the single richest source of provocative insights into organizational sensemaking. Even though equally rich sources may eventually emerge, I can't imagine them completely displacing it from a central place in the field of organizational sensemaking. Buy it & read it...now.

Why Sensemaking?

Looking back over 10+ years of learning, synthesizing, and applying sensemaking concepts, it seems clear that their value remains largely untapped.

Possible reasons for this include:

• It's an edge tool - sensemaking focuses on fast-changing, complex, ambiguous decision making contexts where domain expertise dominates. These situations are usually seen as "wicked", dominated by tacit knowledge that is so contextual that it cannot be formally captured...more art than science.
• The "artists" who dominate edge decision making are, for good reasons, suspicious of any framework that claims to bring structure to a context that they know is inherently unordered.
• Traditional tools (processes, organizations, IT, etc.) have been very successful in non-edge contexts. There's no pressing need to move the edge beyond art.
• "Either-or" thinking that resists seeing tools as being useful in some contexts and and dangerous in others; instead it wants a "magic formula" that can be mindlessly applied, measured, and monitored...regardless of context.

I think we're seeing these barriers start to fall. Possible reasons for this include:

• A growing recognition that some aspects of edge decision making can be captured in frameworks like Snowden's Cynefin framework and Klein's Data-Frame model.


• Information, communications, and transportation technologies, along with commoditized capital markets, are shifting the business landscape from "80-20 core" to "80-20 edge", at least on those areas related to competitive advantage & innovation.


• Technology is shifting from instantiating structured repeatable models of well-defined decision making contexts, to exposing composable chunks of business logic that a decision maker can easily integrate in an ad hoc fashion.

Dave Snowden characterizes this as a shift in emphasis from Scientific Management (control of function) to Systems Thinking (control of information) to Sensemaking (ability to situate a network).

As with all such shifts, they're subject to a Gartner-style hype cycle...with lots of either-or and magical formula swirling as expectations inflate. Perhaps the whole social-mobile web-enterprise 2.0 flurry is the leading edge of a sensemaking hype cycle...or, perhaps not.

Regardless, we seem to be moving from a "that's the way it is" era characterized by a mindless edge and centralized "control" centers, to a "collaboration" era with mindful decision makers inventing the future on the edge.