For brains, read “intelligence.” More specifically, “decision intelligence.” The term was first coined in the early 1990s. However, a structured methodology didn’t appear until around 2010, when it was introduced by Lorien Pratt and Mark Zangari. The methodology consists of five steps:
1) Decision requirements, including carefully framing the decision;
2) Decision design and modeling;
3) Decision reasoning (applying simulation and assessment tools and methods, including risk assessment);
4) Decision action (clear communication, execution, and monitoring); and
5) Review (good old-fashioned lessons-learned).
Best of all, it ties everything into a single structure, called a causal decision diagram, or CDD. You can learn more in Pratt’s and Nadine Malcolm’s Decision Intelligence Handbook (O’Reilly, 2023).
Role for KM: Some assembly (and lots of facilitation) required, which means innumerable opportunities, especially when it comes to building and reifying those CDDs. This includes managing the flow of money and resources; identifying and mapping a potentially vast ecosystem of people, organizations, and systems, along with their interrelationships and interdependencies (including all the technology platforms supporting the decision processes); external (i.e., uncontrollable) influences; and outcomes (measuring how effectively and efficiently the requirements were met). And so much more, including those lessons-learned mentioned in Step 5.
To gain a greater appreciation of what’s involved and how KM can help, check out the sample CDD developed during the COVID pandemic, along with other interesting examples (github.com/quantellia/di-handbook-supplemental-materials/blob/main/dihb_0002.png).
Do try this at home
According to Quantellia (quantellia.com/Data/HighPerformanceDecision-Making.pdf), 86% of organizations don’t follow a formal decision-making methodology. Don’t let yours be one of them. Start today by thinking about an important decision you or your organization is facing. Build a CDD for that decision, paying particular attention as to where KM could help produce a better outcome. Measure and refine. Rinse and repeat.
Like trains, planes, and automobiles, these trees, chains, and brains are part of our journey to a better future. As the world continues to grow more complex and the consequences of poor decisions become more detrimental, we’re going to need these tools—and more.