Decision Services: Pragmatic Real-Time Analytics

Information Management Magazine, December 2007

Gib Bassett

On a technical level, it could mean executing an action based on a series of inputs or executing predefined data mining models in real time (for example, determining a customer’s propensity to accept an offer based on their history as well as answers to questions posed in real time by a call center representative).

Although points of view may differ, few would argue that the driver for real-time analytics is almost always the desire to become a higher performing, more competitive business. Studies such as those in Competing on Analytics have shown that businesses able to quickly turn insights into action are the highest performing among their peers – the companies that all others wish to emulate.1

The question then becomes, “How do I get started?” Some vendors present an all-or-nothing approach, while others an incremental one, but most make the mistake of emphasizing how to deploy complex predictive models to a particular operational system instead of addressing the larger issue of how to make smarter decisions in real time.

Introducing Decision Services

Decision services blends two concepts to help organizations implement real time analytics in a “right sized” fashion: 

• “Decision” denotes an emphasis on selecting a given action for certain input, whether driven by analytics, business rules or some combination of the two. 
• “Services” denote a focus on service-oriented architecture, a flexible way of adding powerful capabilities to existing systems, often by way of standards such as Web services.

Decision services make it easy for an organization to bring the benefits of real-time decisioning to its operations while allowing more sophisticated analytics to be added over time.

Decision services are applications within your application portfolio, or services in your service oriented architecture (SOA), that automate and manage highly targeted decisions that are part of your organization’s day-to-day operation. They are the tangible realization of adopting enterprise decision management (EDM), an approach that automates, improves and connects decisions to enhance business performance.

Decision services originate with a focus on business performance, not specific analytic technologies such as data mining or OLAP. This distinction is important, as real-time analytics are ultimately one of many tactics deployable via decision services. Pragmatic IT organizations know that real-time capabilities need not entail complex analytics. Decision services can act as a framework within which business rules and analytics coexist to achieve a desired business outcome.

Ideally, a decision service determines the most optimal choice each time it is called, one found using both rules and analytics and then chooses with known and acceptable levels of satisfaction and risk from available options. There is a clear growth path for decision services that builds up to this level, which helps justify such an investment as well as allows an organization to elevate its effectiveness over time.

Unfortunately, many early adopters of predictive analytical solutions have overlooked decision services in pursuit of real-time enablement, often for a particular customer interaction channel or line of business. Organizations yet to embrace predictive analytics in real time can learn a great deal from those who came before them.

Real-Time Analytics without Decision Services: Placing the Cart before the Horse

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