I think there's a role for optimization and simulation as well. If you're in an environment in which all the decisions are made by people, you can start by modeling those decisions rather than having them stuck in people's heads. Next, maybe you can automate some of those decisions with business rules. While you're at it, maybe you could make better decisions or better rules by interpreting the available data with prediction or simulation and optimization. Gradually you get to the point where you have a more formal, modeled and mathematical view of how a decision is made and you can improve it over time.
So you would suggest people are ready to move in this direction?
We think people underestimate their ability to make their systems more usefully intelligent with proven technology… Plenty of vendors have these technologies and they're not rocket science, but they've been cast into these very narrow segments. Any credit card issuer will tell you that deciding whether a transaction is fraudulent or not is a crucial decision, but the need for the technology is less obvious in other situations.
If you're creating a marketing campaign, for example, most people would say, "I have to decide what the content of the campaign is going to be and who I'm going to target." When I look at that scenario, I don't think of it as just two decisions; I think of it as sending a particular offer to a particular customer, so it's really 100,000 decisions.
What if you gave yourself the opportunity to make each one of those 100,000 decisions differently? Would you send everyone the same letter? Maybe you wouldn't. Would they all get the same IVR options? Maybe they wouldn't. Some of these things are more practical now than they used to be, but people just aren't used to thinking about the possibilities.