“Analytics,” the term, has been twisted so badly that Wayne Eckerson last month felt moved to rescue it with a definition. Rather, two definitions, possibly more.

One definition is capitalized, the other is not. What “analytics” might mean in italics, all caps, or underlined he doesn’t say.

Whatever the typography, Wayne just might have the stature to make it all stick. He’s been around the industry for nearly two decades, now as the TechTarget director of research and president of BI Leader Consulting. People know him, respect him, and like him.

The capital-A meaning takes the “macro perspective.” He says it’s “the processes, technologies, and best practices that turns data into information and knowledge that drives business decisions and actions.” The small-A version means “various technologies that business people use to analyze data.”

Referring to Tom Davenport’s use of “analytics” in his book titles instead of “business intelligence,” Wayne seems to imply that “analytics” should replace it elsewhere, too.

That suits me. “Analytics” does something “BI” can’t do. It throws light on the real point of the industry: making sense of data.

But Wayne’s proposal is doomed. No definition will stick that makes us refer to a dictionary before each use. I would still have to pause before dropping either one into a conversation, and that would probably be the same for most other people, I suspect. That kills it.

Am I the only slow learner around here? I asked for opinions from my modest network of data analysts. A reply came from just one of them (who asked for anonymity), far fewer than normal. That analyst emailed that he doesn’t care what “analytics” means. He added, “What is the deal with such pompous, elaborate definitions?”

Exactly. What is the deal?

The terms that stick do so in an instant. Tableau seems to have pulled it off with its word for visualizations, “viz.” It’s simple and sounds like it must have been picked up on “the street.” They also repeat it often in their blog, and a cadre of devoted users sing along.

Wayne muses toward the end of his post, “There’s more than one way to skin a cat.” Yes, sooner or later, we’ll come up with a best practice. But for now, this cat has run away, unskinned.

Does “slice and dice” connote canned, pre-defined reports? An industry leader I talked to the other day used the term to describe data analysis based on aggregated data. Come to think of it, I don’t recall ever hearing those who like to receive their data raw ever using the term.

What a radical idea: break business intelligence down by the types of work to be done — financial intelligence, human-resources intelligence, risk intelligence, etc. — instead of by the technology — data warehousing, data integration, dashboards, etc.

“If I put my feet in the shoes of a business person listening to someone pitching ‘business intelligence,’ what I hear is another IT silver bullet,” eLearningCurve education director Dave Wells said recently.

If you’re talking to a finance officer, for example, about forecasting cash flows or predictive analytics based on the economy, you might call be describing “financial intelligence.” If you’re talking to an HR manager about retention, recruiting and pay scales, you might be talking about “human-resources intelligence.”

Imagine: BI terms that mean something — exactly what he’s trying to promote. Radical, but smart.

“We’re confusing folks who can benefit from this. It’s sleight of hand.”

– On drifting BI terminology by a keen observer who’d rather not be named

You say dayta and I say dahta. You say business intelligence—and now Colin White and Claudia Imhoff say “decision intelligence.” They may want you to say it, too, depending on what you mean.

Now or later—yesterday afternoon it didn’t sound clear just when—they’d like you to say “decision framework.” Perhaps that’s in addition to “decision intelligence” or instead of it. I’m not sure.

They’re both veterans of technology wars, fads, shifts, realignments and convergences. Both are among the most eminent of BI thought leaders. They’ve given their suggestion a lot of thought.

You may ask why? For one thing, they explain, business intelligence has become too closely associated with analytics and data warehousing. They decided it would be easier to offer a new term than try to straighten out the old one. What will keep the same thing from happening to the new term? A fair question.

A second reason for the new term: they’d like to get your attention.

They hope to have the attention of several hundred attendees tomorrow morning at 8 a.m. at TDWI World Conference in Las Vegas. They’ll explain in detail during their keynote. The hot breakfast, restored by popular demand since last August, won’t hurt.

Forty percent of business executives trust their guts over data? I admit those survey results made me raise an eyebrow — but then I put it down again. False alarm.

Forty percent may be significant, but compared with what? Is that worse than last year? For all we know — at least from the press release, since I can’t seem to find the actual report — this could be a huge improvement for the analytics industry.

I’d like to know more about that 40 percent who prefer “guts” over data. How many used pure clairvoyance, and how many used aids like tarot cards, tea leaves and pig entrails?

If the survey had probed more — I assume it didn’t — it would have found the answer: Data is everywhere, and it’s often stored layer upon layer and called experience. “Guts” is another way to say, “I don’t know where I got the data.”

Even a lot of thought leaders in the analytics industry would admit to deciding by gut. Imagine if 254 of them were asked “guts or data for most decisions about your own business?” They decide every day things like whether they’ll attend this conference or that one, when to take a vacation, how to replace that failing keyboard, and whether to go to the mall with the wife or finish that damned course outline. What’s it gonna be, Charlie, data or guts? My gut says most would pick guts.

Here’s what the results do say: Sixty-one percent of those who opt for guts cited lack of good data — I suppose as in, “Hmm, no data. Let’s eyeball it.” Wouldn’t anyone say so? The survey’s base of 254 managers and executives working at companies earning $500 million or more in 2007 are no fools. (At least as reported here.) Sixty percent — apparently overlapping the first group — cited no past data, data that could show trends. Fifty-five percent gave the excuse that their decisions relied on qualitative or subjective factors.

Guts or judgement is a murky choice, but the results are total waste if the questionnaire forced respondents to define terms for themselves. Were respondents given the simple choice of analytics or “judgment”? If so, the “40 percent” results mean nothing.

To see why, look at the comments after Thomas Wailgum’s “To Hell with Business Intelligence: 40 Percent of Execs Trust Gut” on CIO.com. Most confuse analytics with tools, architecture, or Dilbertertian obstacles. So what did respondents really mean when they chose guts or judgment? Did some, for example, think of a bad interface and select judgement as a way of voting against the tool? We don’t know.

Only a few commenters, such as Kalido CTO Cliff Longman, try to untangle the false choice of guts-or-data.

Longman writes, “Managers make all decisions by gut feel (a mixture of experience, beliefs, observations etc.) — but if there is trusted data available for them to see, I think it becomes part of the ‘gut feeling.’ … Digestible data — good for the gut.”

Me, I use tea leaves. Good for the guts.

Also see Neil Raden’s “Gut Versus Analytics: What’s the Real Story?” and Marcus Borba’s “Several executives trust gut.”