Future Of Business Rules Platforms: Events And Decision Management

Business rules platforms are a mature technology for automating decision and policy logic and for managing fast changes to that logic to keep up with business changes. Now customers are seeking more: capabilities allowing them to employ business rules to help detect and respond to business events hiding in streams of data and to automate decision life cycles. This research reveals how well vendors are responding to these new requirements.

Application development and delivery (AD&D) pros are taking business rules platforms in two new directions. The technology's future will be determined in large part by whether or not customers can successfully apply it to business event processing and decision life-cycle management.

Business event processing applications answer the question "What activities are happening in the business now that I need to know about?" by searching for patterns and values within several streams of actively flowing data. The streams almost always represent information about the real world, such as customer activity in a casino, stock prices fluctuating in real time, or the location of transportation vehicles and the goods they carry. AD&D professionals often build business-events applications using complex event processing (CEP) platforms — some of which use rules to define event patterns. Other AD&D professionals use business rules platforms to build business-events applications. These overlapping uses set the stage for the convergence of CEP and business rules platforms.

The second emerging scenario for business rules platforms is decision management, an ill-defined term many customers and vendors use in different contexts. The focus of our research is applications that automate the definition, execution, management, and optimization of business decisions using business rules platforms and often business process management (BPM) as well. For example, retail organizations model the propensity of customers to buy certain products and then implement the decisions implied in those models using business rules platforms.

Mike Gualtieri and I wrote this research.

For the full report, see this link. Forrester subscription required.

Comments

Another key difference

John, I think one key difference missed here is that (in theory) CEP is built to handle heterogeneous information and apply rules that identify patterns in those. So, pattern matching vs. decisioning. When you build a product to take on these very different end games, they shouldn't really look too much alike. They do (and get confused) in the case that a "rules" metaphor is useful in pattern articulation.

Decisioning is built primarily around homogeneous, normalized information of similar type. Thus the rule articulation and management is often much deeper to deal with that.

You have done a good job at pointing out the uses. IE - one identifies fraud, compliance, issues and the other one helps decide what to do with it.

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