Smart Systems Without Rocket Science: Q&A With Fair Isaac's James Taylor - InformationWeek

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7/6/2007
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Smart Systems Without Rocket Science: Q&A With Fair Isaac's James Taylor

Most information systems are needlessly dumb, relying too much on people for the decision-making power. In the just-published book "Smart (Enough) Systems," coauthors James Taylor and Neil Raden argue that you don't need highfalutin genetic algorithms and thinking machines to get to a more intelligent, automated approach. In this interview, Taylor, a vice president at Fair Isaac, makes the case that proven technologies including predictive analytics and business rules management systems are smar

J Taylor James Taylor
"Smart (Enough) Systems" suggests that technologies are available for more intelligent IT systems but that thinking has to change. Can you explain?

The point is to focus on decision making and to think about it as something you can automate. Decisions are different and require a new mindset. For instance, there's something we call "adaptive control," which is the idea that one of the challenges with decisions is that they're not static. How you make decisions evolves over time, yet most people, when they think about information systems, think of maintenance as a bad thing. People constantly think about ways to make better decisions as they learn about their environment and then their environment changes as business conditions and regulations change. You need to have a different attitude toward code that implements decisions because maintenance is not a bad thing in this case; it's inevitable and good because it means you can improve the decision over time.

Two of the technologies you point to are predictive analytics and business rules management systems and you say they're headed mainstream. What's the evidence of that?

If you follow the discussions around business process management (BPM), for instance, there's a lot more talk about business rules as a complementary peer technology rather than as just part of the process engine. There's a lot more talk about predictive analytics as well, and it's moving away from just "predictive reporting" to actually embedding the prediction into applications to drive better decisions.

We're still at the stage where most organizations are adopting these technologies because they have one particular problem that really justifies the investment, but once it's adopted it quickly spreads. One of the biggest growth areas has been in insurance, which in the last couple of years has adopted rules and analytics in underwriting, claims and marketing, and much smaller insurance companies are investing because the big players at the top of the market have made life so difficult. For the smaller firms it's a make-or-break proposition. If they can't get their underwriting process to be competitive, it almost doesn't matter what else they do.

Part of the growth question is who's driving adoption at the top of the industry? Entertainment and leisure companies are investing because they're scared about what Harrahs is doing with the technology. Large telcos are embracing rules for CRM applications, so the smaller companies are following along. It requires a certain amount of fear to drive adoption, quite frankly, and we're seeing that fear as big players get onboard.

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