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Editor's Note: In this Q & A, Peter Schooff speaks with James Taylor, CEO of Decision Management Solutions, who offers tips on using analytics and decision management for more intelligent operations--and for better BPM.

PS: How do you see people using analytics with BPM?

JT: One of the challenges right now is that when a lot of folks think about analytics and BPM, they're thinking about analytics about their process: "Can I monitor it? How many instances do I have? How fast am I getting through? Where are my bottlenecks?" That's a perfectly valid use of analytics and BPM.



But what I'm focused on is a slightly different take on that, which is: If you look at your business processes, within that business process, there are key decisions you have to make. And if you ask a person to make those decisions, he or she would go look at data. They'd go reaping, they'd run reports, they'd analyze data with little visualizations, they'd figure out what the data told them and then they'd make a good decision--or at least you'd hope they would.

So what happens when your business process needs to make those decisions? If you could run straight through, you want it to run without intervention. You want it to support an automated environment.

Well, at that point, your system needs to make those decisions. That's another opportunity to use analytics--analytics about your customers, analytics about their behavior, analytics about the transactions you have--and inject that analytic insight into the business process to make a better decision. [As a result, users can] route the claims appropriately, to put the right terms onto the loans or to make the right cross-sell offer. Whatever that decision is can be enhanced analytically. [Ultimately,] analytics is about your customers, and your products, and your business injected into your business process to make it run better.

PS: Put that way, you could almost say you're only as good as your analytics! Now, in this decisioning that you cover, what do you see coming up?

JT: First of all, there's a tremendous amount of energy around analytics, and that's a good thing. There's also tremendous amount of confusion about analytics. People use the word to mean almost anything.

But what I think what we will see is more of a focus on data mining and predictive analytics. Those aspects of the analytic technology stack are gaining ground rapidly. I think you see an awareness on the part of large organizations that they can't just implement a data warehouse and a BI reporting environment and say "We're done with analytics." [Instead, they're understanding] that these are steps on a path, but there's a lot further to go. I think we'll see more focus on these more advanced analytics techniques.

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