In my last post, I examined John Boyd’s OODA Loop framework and discussed its relationship to double-loop learning. I mentioned there that OODA was one of a number of similar Decision Learning Cycle (DLC) frameworks developed by various writers over the years, including my own Decision Execution Cycle (DEC) framework. In this post, I’ll compare the OODA and DEC Cycles, and then, because the DEC is coupled in my own work with the Knowledge Life Cycle (KLC), I’ll also write about the relationship of both to it.
The DEC and the DOKB
Let’s begin with routine decision making and learning. When we see a gap between the way the world is and the way we want it to be, we typically decide what we have to do to close the gap between the two. Once we Decide, we 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. Let’s call this pattern, illustrated just below, the Decision Execution Cycle (DEC). I’ve written about the DEC on many occasions previously, but this treatment is a revision of previous accounts in that it shifts the locus of planning outside the DEC and into the broader area of knowledge making to be discussed briefly later.
The Decision Execution Cycle
The generic task patterns or phases of any DEC are: Deciding, Acting, Monitoring, and Evaluating. Deciding means forming an intention to do something involving an action or sequence of actions. This may mean selecting among alternative decision options in a specific situation, or it may mean deciding on the basis of the first decision-consequence pattern we can call up from our previous knowledge. Sometimes we form such intentions in the context of broader plans of actions. Planning, however, is not part of a routine DEC. It is, in some part, a knowledge making activity.
Acting means implementing a decision by performing the specific activity or activities decided upon. Acting involves using the results of planning and deciding along with other knowledge to implement decisions, but acting does not, by itself, produce new knowledge, except knowledge that an act was performed.
Monitoring means retrospectively tracking and describing activities and their outcomes. Monitoring involves gathering data and information, and using previous knowledge routinely to produce new descriptive, impact-related, and predictive knowledge about the results of acting.
Evaluating means retrospectively assessing the previously monitored activities and outcomes as a value network. Evaluating means using the results of monitoring, along with previous knowledge to assess the results of acting and to produce knowledge about the descriptive gaps between business outcomes and tactical objectives and about the normative (benefits and costs) impact of these gaps between outcomes and objectives.
The DEC applies to any business process (in a manner to be discussed shortly), and monitoring, evaluating, deciding, and acting all use previous knowledge. Where does the previous knowledge come from? It comes most immediately from what we will call the Distributed Organizational Knowledge Base (DOKB). The DOKB is the combination of biological knowledge found in genes and synaptic structures, previous belief knowledge and belief predispositions of enterprise agents, and artifact-based explicit knowledge claims, and meta-information (or meta-claims) stored in both electronic and non-electronic enterprise repositories. The figure below illustrates the DOKB.
Previous Knowledge: The Distributed Organizational Knowledge Base
Routine DECs use previous knowledge in the DOKB. In fact, the DOKB is a very important source of patterns for pattern-based or Recognition-Primed Decision Making. However, the DEC also adds new knowledge to the DOKB. It does this in two ways DECs that produce mismatches between expectations and perceived reality in monitoring and evaluation, call into question or refute previous knowledge. And second, DECs also provide new knowledge about specific situations, conditions, circumstances, and events.
The DEC can be easily related to a Complex Adaptive Systems framework and also to a business process perspective. From the viewpoint of a CAS framework, the DEC becomes the basic unit that generates transactional activity. And from a DEC point of view, processes are inter-related sequences of goal-directed DECs.
DECS and Business Processes
The connection between the DEC and the Knowledge Life Cycle and also the connection between routine and creative learning arises out of mismatches between expectations and perceived reality. These mismatches tell us that previous general knowledge is wrong or unreliable, and lead us to initiate creative learning in Knowledge Life Cycles. I’ll discuss this in more detail after we compare the DEC and OODA.
OODA and the DEC
In my last post, I discussed Boyd’s OODA loop at length. Here’s a quick review. Observation refers to the task of sensing the world both external and internal to oneself and of feeding the results of sensing on to the task of Orientation. Orientation refers to the task of fitting the observations to our predispositions and expectations about the world in order to arrive at an interpretation of the situation one is facing. It involves various kinds of filtering and processing about which more will be said in a moment, and also formulating decision alternatives. Deciding is the process of reviewing alternative actions and selecting an alternative. Boyd views the decision as a hypothesis. And Acting is the process of implementing one’s alternative. Boyd views implementing as testing a hypothesis. The results of Acting are available for Observation, and the loop starts again.
Comparing the DEC and the OODA loop it appears that Deciding and Acting match up one-to-one in the two DLCs frameworks. The question is how does Observation, match up with Monitoring, and Orientation with Evaluation?
First, I don’t think the Monitoring phase in the DEC is an exact match for Observation in the OODA loop, mainly because it goes further into impact analysis and prediction than Observation does in OODA. That is, part of the OODA Orientation Phase is placed in Monitoring by the DEC. However, this difference seems more a question of where the cut is made between the two phases, since the impact analysis and prediction activities are present in both frameworks. Boyd may have made the cut between Observation and Orientation where he did because he was thinking in terms of isolating experience from interpretation of the situation as much as he could. My own reason for distinguishing monitoring and evaluation in the way I did was to clearly separate a descriptive from an assessment phase with the latter being the one where mismatches and future predictions would be assessed for significance. Thus, in the DEC the combination of Monitoring and Evaluation is needed to get to the final assessment of a mismatch. In the OODA loop the mismatch, if one exists, is determined in the Orientation Phase. In the end, then there doesn’t seem to be a big difference between the two frameworks on where mismatches are finally determined.
Second, however, even noting that the DEC phases of monitoring and evaluation are probably encompassed by Boyd’s Observation and Orientation Phases, I don’t think the reverse is true. It’s not that the OODA Loop is different from the DEC in its inclusion of such factors as new information, genetic heritage, cultural traditions, and previous experience, because the DEC picks up these either through monitoring or from the DOKB (which corresponds to Boyd’s results of Orientation and previous OODA Loops). Rather, the OODA loop includes more than the DEC in the degree of its incorporation of analysis and synthesis to destroy old knowledge and create new knowledge.
In the DEC, analysis is used in monitoring and evaluation to determine the agreement of the consequences of action with expectations and also to assess costs and benefits. If a mismatch is found, this may result in our deciding that some aspect of our previous knowledge is false. But Orientation in the OODA loop uses analysis both to find mismatches and also to evaluate syntheses once they are arrived at, so, in this respect, it seems at first blush that Boyd’s final OODA framework is more comprehensive than the DEC.
However, I think that this greater comprehensiveness of OODA is actually an error by Boyd. Specifically, as I argued in my previous post, Boyd presents the OODA loop as if its phases delineate one DLC, so that Orientation is presented as just a phase of a single DLC, as is Evaluation in the DEC. However, when one looks at what is involved in analysis and synthesis in the process of making new knowledge it’s easy to see that multiple OODA loops, and not a single OODA loop are involved in knowledge processing. So, in extending the OODA loop to multiple OODA loop activities, Boyd actually gets into a logical inconsistency, since single OODA that contain double-loop learning and the making of new knowledge are not single OODA loops. Apart, from this problem however, how adequate is Boyd’s characterization of double-loop learning in terms of the analytical/synthetic loop within his Orientation phase? In the next section, I’ll discuss this in more complete detail when I get into the KLC.
The DEC, the KLC, and OODA
In limiting the DEC to routine single-loop learning, rather than creative double-loop learning, I’ve always been very conscious of my own personal experience in both spheres. Take a routine activity such as driving an automobile, much of the time the mechanics of driving are on automatic pilot and I’m unaware of conscious decision making, but when conditions on the road make me conscious of what I’m doing, I’m very aware of the DLC of Deciding, Acting, Monitoring, and Evaluating, and of the continuous nature of DEC loop processing until I get to where I’m going. I’m sure that if I thought in terms of Boyd’s early and relatively simple formulations of the OODA loop, that framework could be applied equally well to such an automobile trip. With few exceptions, such processing is routine from a learning point of view, even id it involves adjusting to sudden and unexpected occurrences, since I am always using some aspect of previous knowledge to make adjustments and am even using first pattern matches in most instances.
On the other hand, when routine decision making produces a mismatch and I cannot retrieve from memory, or sources near to hand, a decision that gives promise of working, now I have one of Popper’s and also Boyd’s problems and I cannot solve this within the confines of a single DEC or OODA loop because I must formulate the problem, think up or otherwise arrive at new tentative solutions and perform error elimination before I can decide on a likely solution and return to the routine decision making I temporarily left to solve the problem. And each of these tasks, alone, requires at a least a single DEC or OODA Loop, and perhaps more than one. Collectively, these tasks define what we might call a Problem Life Cycle (PLC), in our view another name for a Double-loop Learning cycle. Here’s a graphic of the origin of the PLC and Double-loop Learning in routine DECs motivated by ordinary instrumental behavior gaps, followed by another of the relationship of DECs motivated by the learning or problem-solving incentive to the PLC.
A Routine DEC and the Origin of the PLC/Double-loop Learning
The Problem Life Cycle and DECs
This analysis of how double-loop learning and the problem life cycle emerge out of routine DECs applies not only to DECs, but also to a version of the OODA loop which is not quite so expansive as Boyd’s final version. That is, if Orientation in the OODA Loop is limited to “analysis” and doesn’t include “synthesis,” and if more analysis and all synthesis is left for the PLC, then the OODA loop, just as readily as the DEC can be viewed as capable of giving rise to PLCs. Put another way, as things are the OODA framework apparently assumes that a single OODA loop can encompass either single-loop or double-loop learning, as the case may be. I’ve argued previously however, that this isn’t possible because multiple OODA loops are necessary to successfully perform orientations that produce new knowledge. If this argument is valid, the current formulation of the OODA loop involves contradiction: a claim that a single-loop describes a situation where multiple OODA loops actually applies. To resolve this contradiction one needs to reformulate OODA along lines I’ve used for the DEC. That is, one needs to view OODA not as containing double-loop learning, but as a single loop learning process, giving rise to double-loop learning in the face of mismatches.
Such a reformulation is actually in the spirit of Boyd’s own thought, since he believed that mismatches (problems) drive creativity and the growth of new knowledge. Specifically he believed that analysis of our current knowledge, no matter how good it was, would eventually give rise to mismatches and to “destruction” of our model or models, at which point we would have to proceed by breaking down these models into their elementary patterns and then to arrive at new and better knowledge claim networks that matched our experience by reassembling the patterns in a new synthesis. This process of analyses and synthesis seems very reminiscent of the PLC. So, there seems no reason why Boyd’s OODA framework couldn’t be reformulated as an OODA/PLC framework, paralleling the DEC/PLC framework sketched out here.
This brings us to the issue raised above of whether Boyd’s account of new knowledge creation in “Destruction and Creation” and “the Conceptual Spiral” is an adequate account of that process. In connection with this issue, I think that Boyd’s notion that we first break down conceptual wholes into elemental patterns and then re-synthesize those patterns is not a wholly adequate theory of how we make new knowledge. Basically, Boyd is saying that we go through conceptual breakdown and then recombine our conceptual patterns in novel ways to create something new, following which we test out our results against the world. This is good as far as it goes and probably covers the processes of conceptual combination and perhaps conceptual blending that have been the subjects of recent research. However, apart from Boyd’s questionable uses of the terms “deduction” and “induction” to describe the breakdown and recombination processes, there is the problem of accounting for creating novel patterns through creative processes that go beyond aggregation of previous patterns. Not everything we create existed previously in another form. Emergence of new forms at higher levels of process is a fact of the universe. There are new things and new ideas under the sun.
The problem solving pattern of clearly formulating problems, arriving at new tentative solutions, and then eliminating errors through criticisms, tests, and evaluations, encompasses Boyd’s notion of the analytical/synthetic loop. Since it allows for radical creativity of new patterns, I think it should be used instead.
We now come to the Knowledge Life Cycle (KLC). Along with Mark McElroy, I’ve developed this framework in previous work. KLCs arise as human reactions to mismatches which occur in routine business process DECs. In brief, the KLC includes problem formulation, making or discovering new knowledge and knowledge integration. The first two of these are essentially the PLC projected to the group, organizational, or supra-organizational levels of analysis. Knowledge Integration is the process of communicating new knowledge to the remainder or an organization or system. Like the PLC, the KLC is comprised of DECs or, if one prefers OODA loops, and like the PLC, these are unified by a learning incentive, rather than a motivation to close an operational instrumental behavior gap.
In the KLC, Problem Claim Formulation corresponds to Popper’s problem phase of the tetradic schema, Information Acquisition, Individual and Group Learning, and Knowledge Claim Formulation correspond to the process of developing tentative solutions. Knowledge Claim Evaluation corresponds to Error Elimination. The Knowledge Integration process is broken into four parallel sub-processes: Knowledge and Information Broadcasting, Searching and Retrieving, Teaching, and Knowledge and Sharing. The results of Knowledge Integration and of KLCs at lower levels of analysis below the organizational level exist in an organization’s DOKB, and are used later by routine business processing which is composed of routine DECs, or, if you prefer OODAs. In organizations KLCs, ay many different levels are being generated constantly by DECs and OODAs. While routine Decs and OODAs generate knowledge about specific conditions and patterns, novel and/or general knowledge is generated by double-loop learning in KLCs. You can find a more detailed account of the KLC here.
In sum, at the organizational level, routine DECs or OODA loops create activities and are organized into goal-directed processes organized around the need to close instrumental behavior gaps. Mismatches between expectations and our experience show the existence of knowledge gaps and trigger KLCs whose purpose is to make and integrate new knowledge. Such KLCs are comprised of multiple DECs or OODAs, but these are different from routine Decs or OODAs in that they are motivated by the incentive to learn and to solve a specific problem. Once problems are solved by new knowledge and the knowledge is integrated into an organization’s DOKB, it is available for routine business processing.