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The fact that your client is basically a browser means that you don’t have a bunch of fat clients to manage and synchronize and update and all that kind of stuff.

That basically allows you to bring a strategic capability to users at a highly disruptive cost. “Disruptive,” here being the classic definition of Clayton Christiansen in “Innovator’s Dilemma,” and seeing what’s next. He describes it as a “good enough solution at a significantly lower—if not almost free—cost.”

MB: Yes. What we’re doing is intended to eventually disrupt the typical development process of systems integrators building large-scale data warehousing systems and doing custom-designed data schemas and so forth.

Value-chain optimization

MM: In the spirit of value-chain optimization, the idea of giving tools—not just tools, but capabilities—to the people who understand the data and who can effect an operational or a tactical decision in real time as they run their business… can you provide a couple of forward-looking comments? Or what I call “future proofs,” in terms of how you see this rolling out or evolving over the next 2 or 3 years?

MB: Well, I can certainly tell you that the sophistication of these applications will be growing. I’d say over the last 10 years—certainly 6 or 7 years ago—there was a lot of talk about data mining systems, for example. But every data mining system I saw was a tool for an analyst to use.

I think this kind of advanced analytic technology is going to show up for the end users, and it’s going to be a feature of a product. It’s not going to be data mining. It’s going to show up in a way that’s meaningful to a business decision maker—as more data for them to look at and take action upon. It’s not going to be packaged as some sort of fancy data analysis tool.

I think that is certainly what our focus would be on—leveraging that kind of technology. Customers do want the capabilities that kind of technology can bring, but they don’t want it packaged for use just by data analysts.

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