Whitepapers Tagged: Predictive Analytics

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 […]

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 […]

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 […]

Enterprise Architecture from Agile to Analytic

Decision Management Systems combine business rules and advanced analytics technologies to deliver an agile, adaptive and analytic enterprise architecture. Enterprise Architects are chartered with fitting business rules and analytic technologies like data mining and predictive analytics into their enterprise architecture. A service-oriented platform and architecture, supported by integration and data management technology does not have […]

Predictive Analytics in Retail: Building Customer Engagement and Loyalty

The challenge for retailers is determining where to focus their predictive analytics and decision management efforts. They need to understand the real-world decision-making scenarios that predictive analytics can address across three strategic areas – building customer engagement and loyalty, controlling costs and driving a successful strategy for growth. Building Customer Engagement and Loyalty: How do […]

Enterprise Scale Analytics with R

As R has become more popular, the role of analytics has become increasingly important to organizations of every size. Increasingly, the focus is on enterprise-scale analytics—using advanced, predictive analytics to improve every decision across the organization. Enterprise-scale adoption of analytics requires a clear sense of analytic objectives; an ability to explore and understand very large […]

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 […]

Optimizing Customer Relationships in the Era of Big Data

At the heart of a good customer relationship is a series of great customer decisions. Every time the customer interacts with the company the right decision has to be made. When is a good time to make a marketing offer and which offer will be best? Should this fee be reversed? How should this customer […]

Operationalizing Analytics

The most powerful examples of analytic success use Decision Management to deploy analytic insight into day to day operations making more profitable operational decisions. Organizations are increasingly adopting predictive analytics, and adopting these predictive analytics more broadly. Many are now using dozens or even thousands of predictive analytic models. These models are increasingly used in real-time decision-making […]