Decision analytics is a transformative technology.

End-users who do not yet have familiarity and IT experience with concepts like decision management, predictive analytics, and discrete choice analysis are advised to take aggressive steps to quickly move up the learning curve. While some areas of decision analytics such as Bayesian inferencing and adaptive systems do qualify as rocket science, many highly useful aspects of decision analytics are far more easily approachable. However, the scope of decision analytics is wide enough that it takes time and experimentation to fully appreciate how best to leverage these analytical techniques. Pursuing decision analytics is clearly a journey that will take time, investment, and experience. Having a Chief Data Officer (CDO) is a good start, and so is having a decision analytics programs office. Because of the time necessary to develop a decision analytics program with depth (which includes data and decision analytics that reflect policy and result in actions), it is important to start sooner than later. It’s also better to force your competitors to come to terms with decision analytics rather than the unfortunate alternative.

There are vendors that have decisioning products such as business rule management systems. There are also vendors that provide advanced analytic products. However, there is only a rarified set of vendors that provide both decisioning and analytic products. Why is this important? Although most analytic models are developed offline, some of these models will need to be integrated with decisioning tools in order to address process automation and process improvement needs. To ease this integration process, you will want to look for vendors with explicit experience in both the decision and analytic dimensions of decision analytics to ensure the easiest and smoothest implementation of technology that some will find complex. Due to the large number of categories identified in the decision analytics continuum, enterprises should also look for a vendor that has deep product and service expertise across the decision analytics continuum. As we mentioned earlier, some of the leading vendors in the decision analytics domain include FICO, IBI, IBM, Oracle, Pegasystems, SAP, SAS, and TIBCO. Table 1 provides a list of these vendors and products that support decisioning and analytics.

Vendors and end-users should both consider the implications of the decision analytics reference model. The application architecture necessary to deliver the decision analytics reference model involves a number of newer platform-based capabilities such as messaging, event servers, business rule management systems, business intelligence, advanced analytics, push technologies, and application management. Consequently, enterprises are advised to think strategically about their decision analytics needs and the technology stack necessary to deliver on these objectives even if the technology is to be phased in over time.