For organizations to thrive in the digital age, they need dynamic processes to implement thousands of business decisions they make day in and day out. Whether it be for sales commissions, claims verifications, benefits administration, or something else, a primary feature for executing processes effectively are business rules. A business rules engine is what helps to manage business rules without interacting with code. Thus, business end-users can update business rules without relying on assistance from the IT team. As business rules set the conditional statements to manage organizational processes, business rules engines are the application side that outputs whether the results are true or false. With business rules engines in play, organizations can increase their ability to respond to market fluctuations at any given time. In this article, we’ll expand upon data-transfer models used by business rules engines:
Forward-chaining
Forward-chaining is also described as data-driven reasoning. The reasoning executes from known data and moves forward with it. In addition, inference rules are applied consistently until the objective is achieved. Also, with forward-chaining, all rules are set in a predefined order and you can specify by terms, including:
- Conditions
- Actions
- Bindings
As each step finishes, another is added until the entire “chain” is completed. The best scenario for forward-chaining is when data has been collected, and you want to better understand and use the information. For instance, you can use forward-chaining in task analysis.
Backward-chaining
Another term to describe backward-chaining is goal-driven reasoning. The point of execution begins with a list of objectives. However, unlike forward-chaining, backward-chaining works backwards--as the name implies. The premise is to find paths that enable goal completion. Also, this data-transfer model will search for the most appropriate rule that aligns adequately with the desired outcome. Imagine coming up with a hypothesis, and looking for supporting evidence--this scenario is similar to the concept of backward-chaining.
