Many of my previous posts have described the relationships among various types of knowledge: decisions, criteria, alternatives, requirements, risks, plans, etc. There’s method (actually science) to my madness; here’s the Decision Driven® Information Architecture that I believe illustrates how decisions glue together all other types of future-creating knowledge.
If you unbundle this information architecture and represent it as a single decision transform, you get a Decision Trace diagram:
From my experience, all of these information objects and relationships are both true and useful. Failure to capture these types of data increases the risk of decision failure. Failure to understand the relationships creates lots of knowledge that floats about, disconnected from its decision context. Failure to maintain appropriate and continuous traceability (links) between these objects condemns you to have to recreate (if possible) your thinking if and when things change.
Of course, there are probably 10 synonyms for every class of object shown, so your first task may be to map your terminology to this universal model. Once you do, I’ll be surprised if you can identify any additional types of information or links that are vital to the “future-creating” parts of strategy, systems engineering or new product development.
Filed under: Decision Concepts | Tagged: alternatives, analysis tasks, criteria, decision, decision context, decision data, decision patterns, derived requirements, implementation tasks, information architecture, information model, issues, knowledge management, models, opportunities, opportunity growth, performance estimates, product development, requirements, risk mitigation, risks, strategy, systems engineering, traceability
