The Dow of BI

I don’t mind long lines at trade show buffets. All else being equal, the length roughly equals attendance, which roughly indicates industry fizz. For an indicator, though, the analytics/business intelligence industry can do better than that.

How do we take the pulse? What if those who promote the technology, advise the clients, and build the systems actually measured their collective progress with a number? It would be an ongoing, forever-updating, simple benchmark. It would be the industry’s Dow Jones Industrial Average.

Four or five years ago, when the industry seemed simpler, I envisioned a number like this. Why not?

First hurdle: the lack of complete public data. We have it for a few vendors, such as IBM and Oracle, but not for the industry’s many startups. For example, how does Tableau’s ascent figure in, and how do we measure it?

Could we count the number of BI-related hash tags in Twitter? Maybe, but what does the number indicate? Is it success or marketing people out of work? Tweets from Tableau, for example, have been way down for six months or more. Here, down means up. They must have something cooking.

Slightly more credible than buffet lines are the annual surveys by industry analysts. Business intelligence as a priority is up — or was it down? — this year from last, they say. But what did survey respondents mean by “business intelligence”?

Traditional deciders say “BI” to signify plumbing — metaphorically, the path from groundwater to kitchen sink. Did you ever see a plumber’s dream house? He’s installed no drywall; he wants the pipes exposed to admire the workmanship and efficiency: No leaks, good flow. Cooking, bathing, and washing the cat all come later if there’s time.

The non-plumbers make use of the water. The “kitchen sink” is where all that nice, clean data pays off. So the ideal point of measurement would be where data-based evidence reaches decision makers’ minds — say, just before it commingles with the tarot cards.

At that point, how strong is the influence of data analysis? How good is the analysis? How good and complete is the data?

If we could find a proxy for that pulse, we just might have found the Dow of BI.

I’ll ask around among industry mavens, especially the the cooks.

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