An interesting discussion started on twitter this week with @BigBlueMilky saying “Decision Management is so much more than just using business rules” – something I strongly agree with. @JeffreyGoodReq followed up by adding “But you must start with business rules” and, when I disagreed and said you must start with Decisions added “rules = context needed for decision framework, no?” Much as I enjoy tweeting 140 characters is not really enough to have this discussion.
An interesting discussion started on twitter this week with @BigBlueMilky saying “Decision Management is so much more than just using business rules” – something I strongly agree with. @JeffreyGoodReq followed up by adding “But you must start with business rules” and, when I disagreed and said you must start with Decisions added “rules = context needed for decision framework, no?” Much as I enjoy tweeting 140 characters is not really enough to have this discussion.
Why is Decision Management more than just using business rules? Decision Management involves using both business rules and predictive analytics (and sometimes optimization). Not all decision-making is best described only in terms of business rules and many decisions cannot be completely described using only rules derived from policy, regulation and know-how – there is a need to apply analytic insight to the decision as well. While you can represent a lot of predictive analytic models as executable business rules, this is not the same as treating them the same as the rest of your rules. They need to be discovered, managed and updated analytically. Decisions also need to be managed over time – data is collected about the decisions made and how well they worked so that decision-making can be analyzed, improved and evolved systematically (this is why we talk about Decision Management Systems not Decision Automation Systems).
But why not start by collecting business rules? Well Decision Management involves the discovery, automation and ongoing improvement of decisions (see these three webinars on Decision Discovery, Decision Services and Decision Analysis in our recent How to Build Decision Management Systems series). Successful Decision Management efforts begin by identifying the key objectives of a business area and then identifying, modeling and describing the business decisions that impact those objectives (this is described in more detail in Chapter 5 of my new book). As part of defining these decisions you identify the regulations, policies, know-how and analytic insight needed to make these decisions. Then, and only then, do you collect business rules.
This works better as the decision definitions provide a context and a framework for your rules. The decisions have a place in your processes and use cases (so it is clear where they will be used) and are tied to business objectives (so you know how to define good and bad decisions as well as the value of improvements in decision-making). It is clearer when you have collected all the rules you need (you have defined the decisions you were focused on) and it avoids what I call the “big bucket of rules” problem where companies end up with lots of correct business rules but no easy way to tie them to day to day operations.
Now, once you are done, the rules do indeed provide the framework for how each decision is made – they define the approach being used to make decisions. But starting with the decision, beginning with the decision in mind as I like to say, is critical to effective Decision Management.
