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.

How to Succeed with AI

AI is a decision-making technology. A focus on decisions, not a separate AI initiative, delivers business value and a strong ROI. As companies invest in artificial intelligence (AI) and machine learning, it is clear that a technology-led approach does not work. To get business value from AI, companies should focus AI efforts on improving business […]

Enabling the Predictive Enterprise

Today it seems that everyone is talking about Predictive Analytics and Machine Learning. Organizations of every size and in every industry are investing to compete in this new world. For most organizations this means adopting new analytic capabilities. Most organizations have BI capabilities such as reporting, dashboards and performance monitoring. However, today’s business needs more […]

New Approaches for CDS

Using Proven Industry Standards for Clinical Decision Support. Clinical Decision Support (CDS) is a foundational capability to reduce cost and improve outcomes. It has long been a strategic and high-priority initiative across most healthcare providers. There have been some successes but scaling up remains a challenge. New standards-based approaches and the use of proven technologies […]

Innovation in Insurance: Profit by Focusing Innovation on Decision-Making

The most important decisions are made every day. Insurers that adopt a decision-centric approach to analytics and artificial intelligence are improving business outcomes. Setting the stage There has been a level of frustration and insecurity in the past few years about the fate of the insurance industry. At first, vendors and other service providers raised […]

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 […]

5 Steps to Streamline Reporting for Better Data-Driven Decisions

Everyone wants to make better data-driven decisions. While reporting can support decision making, often existing reporting approaches seem more likely to get in the way, bogging down progress toward analytic decision-making. Take these 5 steps to streamline reporting and focus on decision-making. Find out what decisions the reports are for See what decisions matter to […]

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 […]

Putting Predictive Analytics To Work in Operations

Small operational decisions, especially those about customers, are made over and over. The value of these decisions rapidly adds up. Making these decisions well is critical to business performance.  Maximizing the value of each operational decision is at the core of Decision Management. Because these decisions about customers are made at the front line of an […]