Government // Enterprise Architecture
Commentary
10/25/2007
05:09 PM
Sandy Kemsley
Sandy Kemsley
Commentary
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Business Rules and BI Make Great Bedfellows

David Straus of Corticon gave an engaging presentation at this week's Business Rules Forum about BR and BI. He characterized BI as "understanding" and BR as "action." He started with the basic drivers for a business rules management system - agility (speed and cost), business control while maintaining IT compliance, transparency, and business improvement (reduce costs, reduce risk, increase revenue) - and then offered three use cases for rules-driven analysis...

David Straus of Corticon gave an engaging presentation here at this week's Business Rules Forum about business rules and business intelligence, starting with the Wikipedia definitions of each. He characterized BI as "understanding" and BR as "action" (not unlike my statement that BI in BPM is about visibility and BR in BPM is about agility). He started with the basic drivers for a business rules management system - agility (speed and cost), business control while maintaining IT compliance, transparency, and business improvement (reduce costs, reduce risk, increase revenue) - and went on to some generalized use cases for rules-driven analysis:

• Analyze transaction compliance, i.e., are the human decisions in a business process compliant with the policies and regulations?

• Analyze the effect of automation with business rules, i.e., when a previously manual step is automated through the application of rules

• Analyze business policy rules change (automated or non-automated)By modeling the policies in a business rules system, these conflicts can be driven out to establish integrity across the entire set of rules. This approach can also be used in cases where an organization just isn't ready to replace a human decision with a business rules system in order to validate the rules and compare them to the human decisions; this can establish some trust in the decisioning system that may eventually lead an organization to replace some of the human decisions with automated ones to create more consistent and compliant decisions.

Straus had a number of case studies for this combination of rules and analytics, such as investment portfolio risk management, where mergers and acquisitions in the portfolio holdings may drive the portfolio out of compliance with the underlying risk profile: information about the holdings is fed back through the rules on a daily basis to determine whether the portfolio is still in compliance and to trigger a (manual) rebalancing if it is out of compliance.

By combining business intelligence (and the data that it's based on) and business rules, it's also possible to analyze what-if scenarios for changes to rules, since the historical data can be fed through the new version of the rules to see what would have changed.

He challenged the BI vendors to do this sort of rules-based analysis; none of them do it now, he asserted, but it would provide a hugely powerful tool for providing greater insight into businesses.

There was a question from the audience that led to a discussion about the iterative process of discovering rules in a business, particularly the ones that are just in people's heads rather than encoded in existing systems; Straus took this opportunity to plug Corticon's modeling environment and its rules discovery capabilities. I'm seeing some definite opportunities for rules modeling tools when working with my customers on policies and procedures.

Sandy Kemsley is an independent systems architect specializing in business process management, Enterprise 2.0, enterprise architecture and business intelligence. She is also the author of the Column2 blog on BPM, Enterprise 2.0 and technology trends in business. Write to her at Sandy [at] Column2.com.David Straus of Corticon gave an engaging presentation at this week's Business Rules Forum about BR and BI. He characterized BI as "understanding" and BR as "action." He started with the basic drivers for a business rules management system - agility (speed and cost), business control while maintaining IT compliance, transparency, and business improvement (reduce costs, reduce risk, increase revenue) - and then offered three use cases for rules-driven analysis...

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