Whitepapers Tagged: DMN

Agility and Efficiency with Decision Modeling

Decision modeling is the proven requirements gathering and documentation approach that bridges the gap — between business process, business rules, and artificial intelligence (AI), machine learning, and predictive analytics technologies — for true Digital Decisioning.

Maximizing the Value of Business Rules

Decision Management streamlines and focuses business rules projects for faster, more effective deployment. Business Rules Management Systems (BRMS) deliver on the promise of costs savings, agility and happy customers. Yet for many organizations, these efforts remain point solutions. Decision Management is a proven framework to drive the widespread adoption of business rules and improved business […]

Decision Modeling with DMN

Decision Requirements Models based on the Decision Model and Notation (DMN) standard deliver a powerful ROI by improving processes, effectively managing business rules projects, framing predictive analytics efforts, and ensuring decision support systems and dashboards are action-oriented. This paper describes the iterative steps to develop and complete an effective Decision Requirements Model using the DMN […]

Framing Analytic Requirements with Decision Modeling

How to achieve analytical, data-driven decisions with decision modeling and the Decision Model and Notation (DMN) standard.  The value proposition of analytics is almost always to improve decision-making. Being explicit about the decision-making to be improved is an effective tool for framing analytic requirements. Organizations are making significant investments in analytic technologies. These investments range […]

Decision Modeling for Dashboard Projects

Decision modeling provides a formal framework to design dashboards that link explicit decision making to the knowledge required for them. Dashboards are decision support systems but their design does not usually consider decisions. Most designs are driven by user interface and information visualization requirements and by the underlying data models. A dashboard design based on […]

Business Process Transformation with Decision Modeling

Organizations are optimizing their operations with decision modeling, creating a streamlined and more agile business. Decision-led process innovation results in: Operational efficiency Agility Business-IT alignment Leading organizations are adopting decision modeling with the Decision Model and Notation (DMN) standard to improve operational efficiency, agility and business-IT alignment. Decision modeling gives enterprise architects and business process analysts […]

3 Reasons to add Decision Modeling with DMN to your IBM ODM Program

DecisionsFirst Modeler decision modeling software provides a diagram-based, business user friendly front-end to the IBM Operational Decision Manager (ODM) business rules environment. The integration provides: Full traceability from business objectives through decision models to business rules. Single master copy of the business rules managed in ODM. Full access to the rule management capabilities of ODM with […]

Next Generation Claims Systems

Decision Management delivers next generation claims systems that act immediately, increase agility, consistency and accuracy, improve customer satisfaction, speed response and reduce costs. Insurers can achieve significant speed-to-market gains, reduce fraud and create innovative new claims processes. Today’s insurance claims systems deliver value to insurers by increasing efficiency through business process automation and workflow. The […]

The MicroGuide to Process and Decision Modeling with BPMN/DMN – Free Chapter

The MicroGuide to Process and Decision Modeling in BPMN/DMN offers extensive coverage of the important topics related to business process and decision modeling, including quick guides to BPMN 2.0 and DMN 1.0; a comprehensive framework for integrating decision, event, and process modeling; and process and decision discovery through effective requirements gathering techniques. Quick guides to BPMN […]

Standards in Predictive Analytics

The Role of R, Hadoop, and PMML in the Mainstreaming of Predictive Analytics Just a few years ago it was common to develop a predictive analytic model using a single proprietary tool against a sample of structured data. This would then be applied in batch, storing scores for future use in a database or data […]