TotalCIO

Apr 6 2012   12:27PM GMT

Analytics technology is racing past our ability to ‘gestalt’ it



Posted by: Linda Tucci
Tags:
Algorithms
Analytics Technology
Business Intelligence
Business Intelligence Summit
CIO
Gartner

I am back from Gartner’s Business Intelligence Summit in La La Land, trailing visions of nice light and lollipop palm trees. And of real-life analytics technology r-r-racing ahead, outpacing the experts who are paid to make sense of it. The name of the conference this year was “Analytic Excellence: Transforming Data Driven Decisions.” The emphasis on analytics points to the field’s drum beat del giorno, namely, that the traditional role of BI (business intelligence) — being a reporting function for “what happened” in the business — doesn’t cut it anymore.

Companies might still need to know what they did last year or just a minute ago. The real money, however, is in predicting what is likely to happen in the next minute (or milliseconds, if you’re in financial services) and prescribing a fruitful course of action. For that, companies need to understand and be able to use analytics technology. Indeed, the promise of the Business Intelligence Summit, to quote the brochure, was to provide insight into “the latest analytic applications and information management trends” and into many other topics relevant to achieving analytics excellence.

Latency in L.A.

Yet right from the start, there was evidence of attendees wanting more on BI and analytics technology than the conference could provide. Take, for example, the BI expert from ExxonMobil who walked out of the opening day keynote with me. He was dismayed that time was being spent on an historical review of BI (including having Howard Dresner, the coiner of the term if not the inventor of BI, on stage for a bow) or, for that matter, on a description of analytics, when everybody knows, “The real story is how the cloud is changing BI.” Why weren’t they talking about migration strategies to the cloud? Well, I knew of at least one session coming up the next day on cloud, and there were probably others on the agenda, but clearly that wasn’t soon enough for him.

Later in the day, in a session with the come-hither title of “Mobile BI — Finally!” an audience member actually called out the speaker for presenting old news about mobile BI deployments. The outburst referred to the presenter’s example of an unnamed Canadian hospital deploying real-time BI in clinical settings via iPads. “This is already happening now!” the man said impatiently. Yes, of course, it is already happening, the analyst agreed, and proceeded to decode his own slide. But the attendee’s illogical remark only underscored the problem: Tell me something I don’t know, he was saying. Tell me something I haven’t already heard.

Interestingly, the conference leaders seemed to be aware of the problem — of our losing race to stay ahead of technology. The closing guest keynote was a talk on “How Algorithms Shape Our World” by Kevin Slater. Identified in the brochure as an “entrepreneur, provocateur and raconteur,” Slater talked about how computers are the nervous systems of a networked world. Computers — or rather, the algorithms that live within them — are not just quantifying and stitching together information. They’re actually determining our world: carving underground fiber highways between New York and Chicago so Wall Street can trade faster and make yet more money; forcing journalists to lard their stories — shape the news — with text optimized for search engines (for example, analytics technology) that search engines will pick up.

I don’t know that Mr. Slater said anything that anybody in this audience of highly sophisticated technocrats didn’t know. But he made the point in a way I would guess that many attendees had not heard before: He delivered a poetic meditation on the new ways in which contemporary math is coding ideas of the world and making them real. And here’s the scary part: In many instances, it is coding the world without human supervision, in ways that we can’t read, at least not fast enough. What he didn’t quite say, but what is obvious, is that the chasm between human understanding and the algorithms that run our lives is only going to widen from here on out.

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