Last week I listened the webinar “The Art of Knowing How to Leverage Decision Intelligence” presented by Roy Schulte, Distinguished VP Analyst at Gartner. Describing the major trends in decision intelligence and why it is growing, Roy concentrated on the question “when to use machine learning, optimization or business rule engines”:
I took the liberty of adding 4 red boxes to the above Roy’s slide:
- BR: Business Rules and Decision Management system
- ML: Machine Learning tools
- OPT: Optimization tools
I was glad to see that Gartner’s trends in decision intelligence reflect exactly what OpenRules is doing! We provide practical tools in all 3 areas of decision management:
These tools are well-integrated to support the BR+ML+OPT approach and they are oriented to business analysts (subject matter experts) working in concert with IT/DevOps.
On the following slide Roy discussed how the results of the deployed decision service (decisions) produced in Runtime are used as a feedback for modification of business rules in Design Time:
It is especially useful when some rules are automatically generated from historical data using machine learning algorithms. OpenRules Rule Learner uses a similar integration schema to support “Ever-Learning Decisioning”:
I was especially glad when Roy introduced the term “Continuous Decision Improvement” that perfectly corresponds to “Continuous Digital Decisioning” that I discussed during my DecisionCAMP presentation in Sep-2021:
So, Gartner’s latest trends in the decision intelligence confirm that OpenRules is at the cutting edge of the modern decision management. More importantly, OpenRules products are used by many major enterprises worldwide in real-world decision-making applications, and OpenRules popularity keeps growing.