DMN

80% of insurance carriers aren’t delivering high impact analytics. Here’s how you can do better.

80% of data and analytics leaders with global life insurance and property & casualty carriers surveyed by McKinsey reported that their analytics investments are not delivering high impact. What’s stopping them from delivering high impact? 38% of those surveyed cited a failure to integrate analytics into workflows and frontline systems. This was the leading obstacle to […]

Decision Modeling and DMN for IBM Customers – New Brief

We have a new Leading Practices brief available – Decision Modeling and DMN for IBM Customers. IBM has long been a leading player in business rules management systems and Decision Management Solutions has many customers using IBM Operational Decision Manager in North America and Asia. Our DecisionsFirst Modeler software decision requirements modeling using the Decision […]

Delivering the Business Value of Analytics

Learn three critical success factors in delivering business value from your advanced analytics investments. Many organizations still struggle to get a business return on their investment on advanced analytics. The biggest barrier? An inability to integrate analytics, especially predictive analytics, into frontline systems and business processes. Work with a number of global companies has revealed […]

DMN had a great year and looking forward to 2018

Happy New Year! 2017 saw strong growth in decision management and decision modeling with DMN, especially in claims, underwriting, marketing and origination. Customers increasingly are choosing Decision Management to integrate advanced analytics, business rules and AI into their operational systems, and deliver consistent decisions across multiple applications and channels. There were also notable changes in how customers […]

Upcoming Training: Decision Modeling with DMN

A hands-on course for analysts and architects developing decision requirements based on the Decision Model and Notation (DMN) standard for business rules analysis, BRMS implementation, predictive analytics requirements, business process optimization and decision-centric dashboard design.

Leveraging Organizational Knowledge with Decision Modeling

Organizational decisions are not as effective as they could be because organizational knowledge is not directly connected to the decisions that impact business performance. Decision modeling helps deploy existing knowledge and highlights knowledge gaps that need to be filled. Knowledge is diffused across the organization How do we know if we are making good decisions? […]

DMN and TDM Compared – New Brief

We are pleased to announce a new resource, DMN and TDM Compared, posted to our Briefs Page. The Decision Model and Notation (DMN) industry standard and The Decision Model (TDM) are decision modeling approaches that have both similarities and differences. TDM is a proprietary approach established in 2009. Because it is well established and still practiced, […]

DecisionCamp 2017 Recap: DMN and Analytics

I was pleased to be able to both attend and present at DecisionCamp 2017 in London on refinements to DMN and decision modeling for analytics. I want to thank my fellow members of the organizing committee and I would like to recognize the efforts of the conference Chair, Dr. Jacob Feldman, for making this important […]

Upgrading Clinical Decision Support Systems with Decision Modeling and Business Rules

Kaiser Permanente is developing Clinical Decision Support systems using a combination of Decision Modeling, DecisionsFirst Modeler and IBM’s Business Rules Management System ODM. Their experience is that well-designed decision services can replace existing guideline documents. This is critical as guideline documents are expensive to develop (they involve significant investment from SMEs) and even good guidelines are of […]

Can Machine Learning Solve Your Business Problem?

One of my LinkedIn contacts recently pointed to this great little article on HBR – How to Tell If Machine Learning Can Solve Your Business Problem – and it makes some points that show the potential for decision modeling to help you better apply machine learning and other analytic techniques. The author begins by pointing out that automation is […]