Decision Engine

Make analytics work to optimize your business decisions.

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Key Takeaways:


1. A decision engine is, in many ways, a fancy name for a decision tree. A decision tree is, in this context, a refinement of a web search engine that uses inputs to guide a user to the most relevant output.

2. A decision engine asks a user a series of questions, often binary questions, to specify particular criteria that refines options and search results. If a person were interested in buying a car, for example, a series of questions about automobile capabilities — such as two- or four-wheel drive, convertible, four or eight passenger requirements, etc. — can refine the car choices to just a few. The decision engine can then provide a smaller list of options that match a user’s requirements and even rank the results as best to worst in delivering on the requirements.

3. A decision engine can also be powered by the type of responses it receives and, over time, refine and improve its results or recommendations.

4. Decision engines have become popular among many buying and travel sites online to help their customers make what would otherwise be challenging purchasing decisions. However, the same capabilities can easily be built into business applications to aid organizations to make decisions that remain within the parameters of otherwise complex business, compliance, tax, or margin requirements.

5. Building complex decision trees that power decision engines is a sometimes highly complex task that often can include embedded analytics, AI, and lookups, along with approval workflows and other nuanced complexities. In many organizations, this has led to the creation of highly specialized decision rules modeling and operational science organizations.

Expanded Definition:


A decision engine is a term that represents the logic, often in the form of a rules flow or decision tree, that can be operationalized to automate a decision. Most business decisions tend to be complex and can be made up of a series of smaller decisions. A decision engine articulates how smaller decisions branch off to bigger and more complex decisions and ultimately end with a final outcome. This logic can be codified, documented, and often executed in an automated fashion. A decision engine, often crafted by a subject matter expert, articulates the decision logic, leverages decision assets to inform a decision, can be audited, and, ultimately, automatically executed through a business process system.

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