Predictive Analytics, Business Rules and Enhanced Decisioning

January 13, 2011
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Business Rules are ubiquitous today. They manage the day to day operations of thousands of companies worldwide. From stocking to maintenance, rules are an integral part of the way we do business in the 21st century. This kind of knowledge, know as Expert Knowledge is forged from years of experience, or what turned out to be the “logical thing to do”.

However, along with the information age, more and more data started being gathered all over the world about the processes and services we as a society came to benefit from. In this sea of data, predictive algorithms were designed to extract its hidden patterns, i.e. knowledge that is hidden from the human eye. This is known as Data-Driven Knowledge.

In an ideal world, business rules and predictive models live side by side benefiting from each other since both encode complementary types of knowledge.

In the presentation below, originally given at RulesFest 2010, Dr. Alex Guazzelli starts by differentiating the two types of knowledge. He then makes the point that companies can get Enhanced Decisioning whenever expert and data-driven knowledge are combined. Dr. Guazzelli goes on to describe the making of a predictive solution by using a “fish processing plant” as an analogy for any process that can benefit from intelligent decisioning. He ends by showing how such a solution can be deployed using PMML (the Predictive Model Markup Language) and easily moved to the production environment using ADAPA, the Zementis Predictive Decisioning Engine.