💥The core foundation of the #DecisionIntelligenace Platform is Decision Modeling. Plain and simple.
If you cannot model business decisions, you cannot improve them, analyze them, communicate them, or manage them.
🚩Business decisions are different from any other entity in your organization. Do not treat them like #process #data #machinelearning #algorithm or #rules.
The irony is that just modeling decisions is not enough to create automation based on decision models. Decision models should be able to incorporate multiple methods of implementing a decision, such as #businessrules #optimization #machinelearning, and so on.
✨A decision model brings together all the different pieces (decision units) of business decisions. The decision model is the “what” and “why” of the business decisions. The details of “how” will be the decision logic implementing the decision units.
There are several ways to model business decisions such as Decision Graph, Decision Requirements Diagram (based on DMN), Decision Tree etc. but workflows and processes are not any good in the context of decision modeling.
Why?
Because essentially the purpose of modeling business decision is to be able to separate “what” and “why” from “how”.
💣This separation of concern gives tremendous power to clarify, communicate, improve, and manage business decisions. The next step is to automate them.
💡The automation of business decisions requires dealing with many moving components such as #data connectivity and processing, #businessrules modeling and execution, training and using #machinelearning algorithms, modeling and solving constraints for #optimizations, as well as #orchestration, to coordinate between all these moving components.
But remember…
🚀All these are happening around your decision models to manage and automate them in a single unified platform based on an open standard to guarantee your success. That's what you should expect from a #DecisionIntelligence Platform or DIP.
Posted here.
Published July 25th, 2024 at 07:30 am
