We in IT have spent too much time and money hand-coding business rules in an onerous, time-consuming, and error-prone process. It was estimated that “.. in most cases, developers still hand-code business rules in an onerous, time-consuming, and error-prone process. One rule typically represents more than 100 lines of code, and a developer codes 50 lines of code per day.” The emphasis of business rules engineering is on specifying what to do rather than how to do it. This natural extension of data architecture will help us build applications that offer high performance, high reliability and availability. It significantly reduces maintenance efforts and shortens system development life cycle.

Business rules engineering focuses on declaring business policies in the “if-then” format. At run time, the declaration of rules is processed by the rules engine as programming logic. A typical rules engine is able to examine the parameter values (data) and determine which rules to apply. The result of rule validation is typically a true-false value. Because each rule or rule set is independent of other rules, the rules engine will be able to bring out all the necessary rules against one or more given data elements, even against derived data values. This approach shortens the development life cycle because the rules engine takes over the majority of engineering work. A project could potentially go from the phase of analysis, design directly to quality assurance, bypassing the development phase.

By combining rules engineering, workflow integration and pattern-based data structures, applications are much easier to construct, maintain or evolve. For instance, using a well crafted data architecture, an on-line e-commerce application selling auto insurance could be transformed to sell mobile phones, mutual funds or any other products that have similar transaction flows and data patterns: pre-qualifications, product selections and purchase transactions.