In earlier posts, I discussed Dave Snowden’s Cynefin framework from the viewpoint of systems classification, offered an alternative to it, and then offered some critical comments. I did this because (a) Dave sometimes used the term “system” in describing one or another Cynefin “domain” and (b) a lot of the recent discussion on Cynefin in the act-km group focused on the issue of Cynefin as a framework for systems classification.
However, looking at Cynefin from the above perspective is not consistent with Dave’s primary application of the framework as a model and tool for aiding “sensemaking” for decision making. Using Cynefin is mostly all about sensemaking for decision making and isn’t focused on categorizing types of systems for purposes of studying them, or developing general knowledge about them, or better understanding the holistic character of a system. In short, using Cynefin is not about systems analysis. Instead, it’s about context analysis, and about helping people and groups to decide on and take actions that are appropriate in an immediate situational context.
In order to develop my view of Cynefin as a sensemaking framework, I will need to rely on my own way of seeing the world, namely a framework that combines decision cycles, processes, knowledge life cycles, and, at least, an abstract notion of KM. So, I’ll first provide an abbreviated version of that framework, and then move to Cynefin and my critique of it.
The DEC-KLC-KM Framework
Let’s begin with routine decision making. When we see a gap between the way the world is and the way we want it to be, we typically plan what we have to do to close the (instrumental behavior) gap between the two. Once we develop a plan we then act. After acting, we monitor the results of our actions. Finally we evaluate the results we’ve monitored, and then if we haven’t reached our goal, and sometimes even if we have, we begin the cycle of decision making again with a new round of planning. Let’s call this pattern the Decision Execution Cycle (DEC).
The Decision Execution Cycle
DECs, of course, produce decisions and decisions, actions. And actions – activities – are the stuff that social processes, social networks, and (complex adaptive) social systems are made of. These are all built up from activities that are inter-related by their objectives, goals, effects, and the values that are associated with them.
Another very important aspect of DECs and decisions that I need to emphasize here, is that they are undertaken in the expectation that they will have some influence on ourselves and/or the world around us. That is, decisions are viewed by us as “causes” that will, directly, or indirectly, affect, or at least influence something in the world, This relates to the idea that DECs are about closing instrumental behavior gaps. They can’t do that unless our decisions and actions can change the reality that we see. And, of course, if our decisions are expected to produce effects, then it also follows that our decisions are undertaken in the expectation that cause and effect relationships exist that our decisions are in accord with. Otherwise, we could not expect that our decisions would have specific effects on the outcomes we expect.
Now, in saying the above, I am not committing to an assumption that we expect our actions to necessarily cause specific and precise effects. That is, I am not saying that we assume determinate relationships between our decisions and their outcomes. No such strong assumption is needed here. But only the much looser requirement that we make decisions in the expectation that they will help to bring about the effects or outcomes that we seek or contribute to these outcomes in some way. Far from assuming determinism we may only be assuming that our actions make the outcomes we seek more, rather than less, probable or likely.
Business Processes are Networks of DECs
Now let’s distinguish three categories of business processes: operational business processes, knowledge processes and KM processes. Operational processes are those that are comprised of routine DECs. Examples are Sales, Marketing, Logistics, Accounting, etc. They use knowledge. And also make new knowledge about specific events and conditions that are important aspects of situations, but they do not produce or integrate new general knowledge.
Knowledge processes are also composed of DECs. But these DECs are primarily motivated by the need to guard against and solve problems that arise in operational business processes; and while there are some routine DECs in knowledge processing, there are also creative DECs in which new ideas are created. There are three primary knowledge processes: problem seeking, recognition, and formulation, the process that transitions processing from operational processing to knowledge processing and produces the problems that drive other knowledge processes; knowledge production, the process an agent (individual or collective) executes that produces new general knowledge; and knowledge integration, the process that presents new knowledge claims to storage containers and agents comprising the system.
Knowledge production is a process made up of four sub-processes:
— information acquisition,
— individual and group learning,
— knowledge claim formulation, and
— knowledge claim evaluation.
Knowledge integration is made up of four more sub-processes, all of which may use interpersonal, electronic, or both types of methods in execution:
— Knowledge and Information Broadcasting (KIB),
— Knowledge Sharing (peer-to-peer presentation of previously produced knowledge), and
— Teaching (hierarchical presentation of previously produced knowledge).
Knowledge processes, of course, produce outcomes. Chief among these is knowledge, which I’ve defined and specified at length elsewhere (For example, here). The various outcomes of knowledge processes may be viewed as part of an abstraction called the Distributed Organizational Knowledge Base (DOKB). The DOKB has electronic storage components. But it is more than that, because it contains all of the outcomes of knowledge processing in electronic, and non-electronic media. And since it includes beliefs and belief predispositions, and memories as well, it also includes all of the mental knowledge in the organization, as well as the changed synaptic structures that result from organizational learning processes.
Keeping the above notions in mind, here is how things work in organizations. Routine DECs and operational business processes are performed by agents who use previous knowledge in the DOKB: synaptic knowledge, mental knowledge and knowledge in organizational repositories, to make decisions. Sometimes the DOKB and an agent’s perceived situation doesn’t provide the answers it needs, and the agent recognizes that, and goes further to formulate the problem that has arisen, consciously or in words. The problem is an epistemic gap between what an agent knows and what it needs to know to participate successfully in the operational business process. Such a problem initiates a new knowledge production process. Once the problem is perceived, there is a need to formulate tentative solutions. These can come from new individual and group learning addressing the problem, or they can come from external sources through information acquisition, or they can come from entirely creative knowledge claim formulation, or, of course, they can come from all three.
Where the tentative solutions come from, and in what sequence, is of no importance to the self-organizing knowledge processing pattern of knowledge production. The only important thing about sequence here, is that knowledge is not produced until the tentative solutions, the previously formulated knowledge claims, have been tested and evaluated in the knowledge claim evaluation sub-process. And that sub-process, Knowledge Claim Evaluation (KCE), is the way in which agents select among tentative solutions, competitive alternatives, by comparing them against each other in the context of perspectives, criteria, or newly created ideas for selecting among them to arrive at the solution to the problem motivating knowledge production.
KCE is at the very center of knowledge processing and knowledge management. Think about it. Without KCE, what is the difference between information and knowledge? How do we know that we are integrating (broadcasting, searching/retrieving, sharing, or teaching) knowledge rather than just information? And finally, how do we know that we are doing knowledge management and not just information management?
Once knowledge and other tested and evaluated information is produced by KCE, the process of knowledge integration of the solution begins. There is no particular sequence to the integration sub-processes listed earlier. One or all of them may be used to present what has been produced to the enterprise’s agents, or to store what has been produced in the various repositories in the enterprise.
Those agents receiving knowledge or information don’t receive it passively. For them, it represents an input that may create a knowledge gap and initiate a new round of knowledge production at the level of the agent receiving it. Integration of the knowledge therefore, doesn’t signal its acceptance. It only signals that the instance of knowledge processing initiated by the first problem is over and that new problems have been initiated for some by the solution. While for others the knowledge integrated is knowledge to be used: either to continue with executing the business process that initiated the problem, or at a later time, when the situation calls for it.
Either way, the original problem that motivated knowledge processing is gone. It was born in the operational business process, solved in the knowledge production process, and its solution was spread throughout the organization during knowledge integration, and in this way, it ceased to be a problem — i.e. it died. This pattern is a life cycle, a birth-and-death cycle for problems arising from business processes.
The life cycle gives rise to knowledge, synaptic, mental and cultural (linguistic), and so I call it the Knowledge Life Cycle (KLC). Every organization produces its knowledge through the myriad KLCs that respond to its problems: KLCs at the organizational level, and KLCs at every level of social interaction and individual functioning in the organization. It is through these KLCs that new general and deep specific knowledge is produced, and the organization acquires the solutions it needs to adapt to its environment.
Organizations differ in the profile of their KLCs. They acquire information in different ways. They formulate solutions in different ways. They integrate them in different ways. And, above all, they evaluate tentative solutions in different ways. Organizations also differ in the patterning of their knowledge outcomes. They have different procedures for doing things, different software capabilities, different sales forecasting models, different performance monitoring schemes.
Knowledge Management is the set of activities and/or processes that seeks to change the organization’s present pattern of knowledge processing to enhance both it and its knowledge outcomes. So, KM doesn’t directly manage knowledge outcomes, but only impacts processes, which in turn impact such outcomes. For example, if one changes the rules affecting knowledge production, the quality of knowledge claims may improve, or if a KM intervention supplies a new search technology based on semantic analysis of knowledge bases, then that may result in improvement in the quality of models. There are at least 10 types of knowledge management activities, which, however, need not be listed here. The relationships among operational business processing, knowledge processing, and knowledge management are summarized in the three-tier model.
The Three-tier Model
Analysis of Cynefin as a Sensemaking Framework
Cynefin implicitly asserts that we will improve our decision making if, in the process of sensemaking, we gather information about a decision making context, and then distinguish, whether the context may be described by one of four ontological constructs: the simple context (Dave Snowden refers to this one and the others mostly as “domains”); the complicated context, the complex context, or the chaotic context. If we can’t describe the context of decision as focused on any of these, then, according to Cynefin, we can say the context is “disordered,” and we must try to break it down into more concrete contexts that can be described as one of the four primary contexts or domains.
Before describing and commenting on the four primary contexts, please note that from the viewpoint of the DEC-KLC-KM framework, Cynefin is asserting that when we approach any decision making situation, the first and second things thing we must do are to gather information, and then recognize that there is always an initial sensemaking task to be addressed, and that is the classification task of placing the context into one of the Cynefin categories. Again, from the viewpoint of the DEC-KLC-KM framework, such a task is a creative problem-solving task that requires us to develop new general or deep specific knowledge relating to the correct classification of the decision making context, or a further investigation breaking down the original context into more concrete contexts that can be classified.
However, is this implicit assumption of Cynefin correct? In the DEC-KLC-KM framework, the opening assumption is that when one approaches a decision making context, the first thing to do in sensemaking is to decide whether one has a routine decision making situation in which the knowledge needed to make a decision is at hand or easily accessible, or whether a knowledge gap exists, and it is necessary to go through a KLC to produce new knowledge. Translated into Cynefin terms, I think this conflicts a bit with the Cynefin procedure since it suggests that the first move should be not to gather information in the form of sensemaking items or other pieces of information that require appreciable effort to gather, but instead to use knowledge and information already at hand or easily accessible to decide on whether the situational context is one for routine sensemaking and decision making, or whether it is one for creative problem solving producing new knowledge carried out prior to the decision.
Using Cynefin terminology, the first move would be to decide on whether the context is a “simple” one where well-known predictive rules and/or cause and effect relationships exist, or whether it is not a simple context. If it is not, then, my alternative framework suggests that a KLC would be needed to resolve the classification question and to move further with sensemaking.
If a KLC is necessary, then the next step would be to seek and acquire information (sensemaking items or other sensemaking information) about a context that would help us to make sense of it. In short, I think Cynefin is in error in suggesting that the first step should be acquiring new contextual information other than that which is at hand or easily available. Rather, I think the first step should be to distinguish “simple” contexts from all others.
The Ordered Contexts
For Cynefin, Dave Snowden has given a number of slightly differing characterizations since the framework was first introduced. A recent version is in Dave’s 2007 Harvard Business Review article written with Mary Boone. There “A Leader’s Guide” table characterizes the “simple” context this way.
— Repeating patterns and consistent events
— Clear cause-and-effect relationships evident to everyone;
— right answer exists
— Known knowns
— Fact-based management
The “simple” context is one of the two in the realm of “order,” “where cause-and-effect relations are perceptible, and right answers can be determined based on the facts.” The context is “simple” because, within it, we know what to do. We can get facts. We can decide according to rules embodying “cause and effect” relationships between our decisions and their expected outcomes, including such relationships created by social or political norms, legal rules, cultural or economic imperatives and other connections which ensure that if we do “x,” then “y” results almost all the time, or at least enough of the time that we can count on such an expectation. In other words, “simple” contexts are the domain of “best practices.” In terms of the DEC-KLC-KM framework, simple contexts are “routine” contexts in which our learning about specific conditions and circumstances of the context is “routine,” along with our decisions relating to the context. It is when we act in such a routine context and find that our routine knowledge and expectations do not match reality, that we begin to recognize that our expectations about cause and effect are false, that we have a knowledge gap, and that we may have to create “non-routine” knowledge.
In terms of the DEC framework, Dave Snowden’s prescription that we should “sense-categorize” in this context corresponds to monitoring and evaluating in the DEC. While his “respond” corresponds to planning and acting in the DEC. In short, I think that “sense-categorize-respond” is a routine DEC cycle uninterrupted by a KLC.
Sometimes, people don’t want to believe that their routine knowledge is not working, and sometimes it is not obvious that it isn’t working. In both cases people match their expected patterns with results and don’t see a discrepancy even though there is one. They sense and categorize incorrectly, seeing a match when there is a really a mismatch. To avoid such errors, one thing we can do is to be habitually critical when we are in simple or routine decision contexts. That is, we can be careful to really ask ourselves whether reality really does match our expectations, and be as ready to accept that it does not as we are to see a match. Though this critical attitude is difficult to cultivate, it is a secret of success of adaptive individuals, since they see problems before others, and move to make new and more effective knowledge faster than others.
From the viewpoint of the DEC-KLC-KM framework, the decision to view a context as routine or non-routine itself solves a problem, the problem of whether further progress requires only routine learning or a KLC to make new knowledge. If it requires a KLC, then the next step is to acquire information from external sources and from the results of previous individual and group learning prior to arriving at new ideas about the decision context and how to cope with it. This next step may involve all manner of activities and certainly could easily include the use of narrative databases, anecdotes, alternative histories or any other information gathering techniques that might help “sensemaking.”
Looking again at Cynefin, the orientation to sensemaking it provides, suggests, however, that rather than following up this information gathering phase of sensemaking with the specific formulation of competing knowledge claims focused on providing new knowledge that might specifically inform a decision, what we ought to do is to divide the problem into two distinct KLC steps. The first step would be to continue to classify the decision/problem solving context and decide whether we are dealing with a “complicated,” “complex,” or “chaotic” context. And then, having decided which kind of context we are dealing with, we might proceed to a KLC second step to develop solutions about what to do, and then follow that with action. Now, this, construal, is, of course, relative to looking at Cynefin through the lens of the DEC-KLC-KM framework itself. It’s doubtful that Dave Snowden would look at Cynefin as involving linked KLCs, but might view activity after the decision to classify one’s context as action uninformed by further problem solving thought, followed by more sensemaking of any changes in context, followed by more actions, and so on.
End of Part One