Understanding complex knowledge systems and revitalizing knowledge programs at KMWorld 2022
Complex systems shape the landscape of any industry, whether knowingly or not. While knowledge management is often referred to as the avenue for successful enterprises, effectively employing KM strategies and consistently adhering to them requires real-time information and a variety of implementations to realize its potential.
At KMWorld 2022, Dave Snowden, chief scientific officer at The Cynefin Co, explored successful KM methods and reimagining the function it assumes within organizations during his workshop, “KM Strategy.”
Snowden journeyed through the implications of complex systems theory when applied to knowledge management and its current state. The goal is to transform KM into a strategy-based operation—not just an amalgamation of IT teams—using simple rules to provide radical outcomes that affect organizational processes. Snowden quoted Brian Arthur from the Santa Fe Institute, “complexity is looking at interacting elements and asking how they form patterns and how the patterns unfold. It’s important to point out that the patterns may never be finished. They’re open-ended. In standard science, this hit some things that most scientists have a negative reaction to. Science doesn’t like perpetual novelty.”
Snowden summarized the basics of complexity management, involving key actions and necessary questions. Questions that need be asked are, “What can I change?”; “Out of those changes, where can I monitor my impact?”; and “Out of those changes, where can I amplify success or dampen failure?” These questions lead to critical actions, optimizing granularity, distributing cognition over diverse sensor networks for multiple perspectives, and disintermediating decision makers to deliver raw data to the decision makers themselves, without interpretation.
Retrospective coherence, Snowden warned, insinuates that hindsight does not lead to foresight. Meaning, you cannot determine what will happen in the future based on the past. Premature convergence on a decision/assessment, or coming too quickly to a decision, is discouraged to ensure decisions are made with maximum optimizations. Abstaining from pattern entrainment of past success or failure refers to avoiding repetition of modes towards success, as they cannot always work uniformly.
Though KM can be invaluable to an organization, its performance is hindered by an unwillingness to implement and adhere to it. To re-energize or create successful knowledge programs, the following principles can encourage KM project adoption throughout an enterprise:
- Middle-bottom-up: Selling KM projects to middle management first sets the foundation for adoption at lower and upper levels.
- Avoiding perverse incentives: Explicit goals impede intrinsic motivations, producing perverse incentives.
- Small projects: Ensures that KM program adoption will not be overly taxing to existing enterprise operations.
- Asking meaningful questions in a meaningful context: asking workers what they know is a meaningless question in a meaningless context; providing context triggers human knowledge, empowering knowledge flow.
Snowden elaborated on the concept of meaningful context, highlighting that knowledge is revealed when people make decisions. To make this measurable, that knowledge can be mapped via decision mapping which records information received, information that received attention, artifacts used (i.e., checklists, processes that led to a final decision), social networks/advice used, as well as how the decision is communicated and/or enacted to visualize the knowledge-decision relationship. The initial capture of information should be simple, Snowden implored; additions to the data points can be made after initial capture. In reviewing the decision map, compare with a formal process map, then identify gaps and agree to a set of micro-projects.
A dependency grid, which is another method in which you can measure decision and knowledge, employs Ashen typology to view multiple perspectives in a single cluster. For each decision cluster, information such as artifacts used, necessary skills, habits that make things better or worse, necessary experience, and significance of natural talent should be harbored. These various types should then be clustered into manageable things, called knowledge objects. In tandem, ask decision makers what keeps them awake at night in terms of KM; proceed to gather those insights, cluster them, and rate them. These two variables, knowledge objects and decision makers’ worries, can be mapped onto a dependency grid which reveals dependencies, or what knowledge object impacts what challenge.
KMWorld returned in-person to the J.W. Marriott in Washington D.C. on November 7-10, with pre-conference workshops held on November 7.
KMWorld 2022 is a part of a unique program of five co-located conferences, which also includes Enterprise Search & Discovery, Office 365 Symposium, Taxonomy Boot Camp, and Text Analytics Forum.