Decision Management Applications
Information Management Special Reports, May 2005
A decision management application (DMA) isolates the logic behind business decisions from the mechanical operations of application procedural code. Treating decision logic as a manageable enterprise resource in this way makes it reusable by multiple applications in many different operational environments. It makes advanced decision making available as a service to legacy applications, eliminating the time, cost and technical risk of trying to simultaneously reprogram the individual systems to keep up with changing business requirements. It enables developers to swiftly and inexpensively deliver new decisioning applications by flexibly combining business rules, data-driven strategies, thresholds, calculations and other elements. A DMA also makes it possible, for the first time, to use predictive analytics as an integral part of a real-time decision process. As a result, businesses can reap the benefits of analytics - clear forecasts of customer behavior, deep insights into customer needs, the ability to compare many related factors and criteria in a single measurement - to apply operational strategies that give them the greatest return.
The most sophisticated DMAs allow the application of analytics to the development of decision strategies, considering the mathematical relationships between varying business objectives, actions, probable customer reactions, constraints and outcomes. This enables companies to take market and economic uncertainties into account and arrive at optimal action strategies immediately, instead of after months of iteration - thereby sustaining the highest levels of performance for the longest possible duration.
Advertisement
A decision management application is designed to ensure that these decisions are:
- Precise in that the risk and reward of the decision is known and managed.
- Consistent so that the decision does not vary by time, channel, customer unless the organization means it to.
- Agile so that it can be evolved rapidly in the face of new regulations, new policies, new risk or reward calculations.
- Cost-effective so that no more money is spent on it than absolutely necessary.
- Fast enough so that it is taken in "right time" or as near real time as adds value for both the organization and its customers.
Indeed these five aspects of a decision can be managed and improved to measure the "decision yield" of the decision.
The Benefits of Real-Time Decision Management
The returns of developing a decision management application come from faster, less costly application development and maintenance as well as from operational cost savings, more accurate risk management, reduced losses due to error and fraud, and increased revenue generation and profitability.
Clearly a decision about whether or not to approve credit involves risk, but so does a decision about whether or not to make a promotional offer to a customer. It's a decision that involves committing limited resources, making them unavailable for other opportunities. Every interaction with a customer also involves the risk that the attempt to target their requirements will miss the mark, not stand up against competitive offers, and so increase the risk of attrition.
The ROI for a DMA generally comes from increased productivity - of both the people who create the decisioning applications and the people who use them. The use of specialized decisioning infrastructure to develop these often complex applications can reduce development time greatly with resulting cost savings. In addition, developers spend less time building and particularly maintaining these applications, so they deliver more projects. DMAs have been estimated to automate 85 percent or more of many business decisions, which can reduce labor costs or free up staff to focus on higher value work such as portfolio analysis.1 Once a DMA has been developed, evolving it over time becomes easier allowing additional improvement when new data can also be leveraged, new analysis techniques applied, new rules of thumb integrated.
Ultimately, when improved decision making in more than one functional area is linked, the benefits expand exponentially. Ultimately, the aim of an organization should complete enterprise decision management - the linking of as many decision areas as possible, so that all decisions yield more value to the enterprise.
Increased Efficiencies and Productivity Benefits
Using traditional techniques, decision logic is hidden deep inside software and is time-consuming and costly to develop. Developers have had to translate business requirements ("If this condition is encountered, then respond in this manner") into abstract representations in programming languages. The process is laborious and full of opportunities for error through misinterpretation.
By separating decision logic from application code, and making it visible and accessible, companies have estimated a cost reduction of developing new decisioning applications ranging from 25 to 80 percent.2 If organizations go further, and give business users the power to make their own rule changes, IT will spend less time supporting deployed applications, and reduce maintenance expense s by as much as 75 percent.2 In addition, IT resources are no longer consumed by trying to support multiple decisioning applications for different channels and operating environments, because the same application can be deployed across them all.
Improvements also come from reducing labor and cycle times through automation, increasing decision quality and consistency, better and earlier detection of various kinds of risk (credit, attrition, fraud), more sophisticated balancing of risk/reward, more granular segmentation enabling more precise targeting of offers and treatments, and deeper insights into customer behavior and preferences.
Reducing the Latencies between the Time Information is Received and Action
Closed-loop decisioning enables organizations to capture results from production systems and immediately put them into useful form for development and refinement of rules, models and decision strategies. These results include decision outcomes (e.g., Did the customer accept the offer?) and other data from the point of decision as well as subsequent performance data (e.g., Has the account proved profitable?). This acceleration of the cycle from design to execution, and back again, increases ROI from DMAs. Companies gain marketplace agility and compress decision learning time down to a fraction of the norm. In fact companies can keep moving "the bar" upward, executing a new or enhanced strategy before competitors have even had the chance to react to their last move - i.e., they can begin to process multiple decision cycles within one decision cycle of the competitor.
Better Business Decisions with Improved Visibility - Business Process Improvements
Page 1 of 3.
