ABCs of KMAgile decision-making

How do we make decisions? [Agile decision-making series]

This is part 1 of a series of articles on modelling and enhancing how decision-making occurs in an organisational context.

There are many models that describe the process of decision making, with the earliest dating back to the middle ages. Five of the most important models are described in brief below:

  • The scientific method (hypothesis – experiment – evaluation) has been in use for centuries, although the 13th century innovator Roger Bacon is acknowledged as one of its pioneers. The testing of alternative solutions is of prime importance to a successful scientific approach.1
  • The OODA loop (observe – orient – decide – act) is one of the most famous decision-making models, created by the United States air force Colonel John Boyd. OODA promotes speed of execution as a strategic advantage.2
  • The Deming wheel (plan – do – check – act) expands the scientific method into a full quality control approach to continuous improvement of processes and products. Act becomes the fourth step of listening to feedback and undertaking research in order to incorporate updated knowledge into the next planning cycle.
  • Six Sigma’s DMAIC improvement cycle (define – measure – analyse – improve – control) is a data-driven approach to hypothesis testing and process improvement. Before any solutions can be examined, a baseline metric must be selected and measured to establish when an organisation is changing in desired ways.
  • Finally, the Knowledge Life Cycle (KLC) (knowledge production – knowledge integration – knowledge outcomes – business processes) was created by Firestone and McElroy, and focuses on the generation, adaptation, and use of organisational knowledge in order to solve problems.

All of these decision-making models emphasise that “core KM processes should not be treated as discrete and separate, but cyclic and interactive”.3

An additional consideration that is only dealt with implicitly by these models is the concept of context. Knowledge does not exist in a vacuum but within the context of a system, as well as that system”s subsystems and suprasystems. Knowledge emerges over time in ways that can be dependent upon the perception and values of system participants who use or share it. Even the decision to seek out objectively truthful facts is a value choice.

In other words, problem solving involves the creation, application, and review of knowledge at various levels of systems hierarchy. For example, the Vines, Hall, and McCarthy “knowledge hierarchy” models four levels of systems focused at the individual, group, organisational, and societal levels.

The willingness and ability of stakeholders to generate and negotiate a shared context, including shared language, needs to be incorporated as a sixth key aspect of the decision making and problem solving process.

As solutions to problems are created, implemented, and evaluated, an emergent process of sharing and contextualisation across different tiers of the knowledge hierarchy will occur. Over time, this is likely to lead to new cycles of problem solving.

Many of these models describe aspects of the same decision-making process from a particular perspective of the ultimate goal of decisions being made. These may be to find truth (scientific method), a combat edge (OODA), achieve manufacturing perfection (Deming wheel), produce measurable changes (DMAIC), or simply to better describe how knowledge is created and used (KLC).

Ultimately there are six components which describe how decisions are made and the resulting knowledge within a system evolves over time:

  1. Identification of problems
  2. Gathering information and knowledge
  3. Application of knowledge to choosing a course of action
  4. Execution and monitoring of a choice of action, and monitoring of progress
  5. Evaluation of success
  6. Sharing and contextualisation across knowledge hierarchies

In subsequent articles, we will look at problem-solving patterns for unifying all of these aspects of decision-making into a single model, and looking at practical ways to respond.

References:

  1. Clegg, B., The First Scientist: A Life of Roger Bacon, Da Capo Press, 2004.
  2.  Ford, D., A Vision So Noble: John Boyd, the OODA Loop, and America’s War on Terror, CreateSpace Independent Publishing Platform, 2010.
  3. Vines, R., Jones M., and McCarthy, G., “Collaborating across institutional and jurisdictional boundaries: enabling the emergence of a national innovation system through public knowledge management”, Knowledge Management Research & Practice, 2013.

Stephen Bounds

Stephen Bounds is an Information and Knowledge Management Specialist with a wide range of experience across the government and private sectors. As founding editor of RealKM and Executive, Information Management at Cordelta, Stephen provides clear strategic thinking along with a hands-on approach to help organisations successfully develop and implement modern information systems.

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