Howard Dresner is a celebrity in the business intelligence industry, but most people at last year’s Tableau conference didn’t even recognize him when he showed up there.

Who needs BI? Tableau Software liked to think it had left BI behind. BI people, after all, were the control freaks who denied access to data. They sneered at Tableau’s “pretty pictures.” They cared more about data hygiene than data analysis.

But there he was. Stephen Few spotted him in the audience a few minutes into his keynote and paused to wonder if it was really him. Tableau vice president of marketing Elissa Fink welcomed him. I and some others said hello. Mostly he wandered alone.

But he’s coming back this year — to speak. He’ll be among 10 on the “experts track” at the Tableau Customer Conference in Las Vegas. Others include BI veteran Claudia Imhoff, Cindi Howson of “BI Scorecard,” and Performance Dashboards author Wayne Eckerson.

They’re all worth listening to. But the one most Tableau people would feel at home with is Paul Kedrosky. Unlike the others, he’s not from the BI world at all. He’s an “investor, speaker, writer, media guy, and entrepreneur,” according to his blog’s “about” page. But I know him as the man who counts ladders.

At last fall’s Defrag conference in Boulder, he told about using the California Highway Patrol’s count of fallen ladders on freeways as a leading economic indicator. Who says data must come from conventional sources? He’s serious and creative, a mix Tableau people appreciate.

He’s written that we live in a “golden age of data visualization,” but I’ve found no elaboration. I’ll be listening for that.

As for the other nine “experts,” the first thing I’ll look for is the size of their audiences.

“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.

One of the business intelligence industry’s best explainers, Wayne Eckerson, is leaving TDWI for TechTarget. For the everyday BI expert, it’s good gossip. — But for those still on the learning curve, it’s a cue to switch channels.

“It’s true,” he told me this morning about the rumors, “I’m departing the big TDWI in the sky for other pastures.” This week’s rumors were only the latest; I heard the first wave back in early 2009 that he was looking to jump the fence.

The new pasture, as of November 15, will be as director of research at TechTarget with BeyeNETWORK co-founder Ron Powell. On the side, Wayne will also run a consulting firm, BI Leader Consulting.

For him, it’s a leap. He’s been associated with TDWI since 1995, employed there since 1998. He leaves his marks everywhere: director of TDWI Research, creator of the Executive Summit, for a while director of education. See the long history in his blog post.

For us, it’s a moment to pause in appreciation. Few others I know of can explain basic BI concepts as well. Some of his long roots are in newspapering, and they showed its value in his book, Performance Dashboards: Measuring, Monitoring, and Managing Your Business (Wiley; 2005). It was the first book I ever read on business intelligence and a valuable primer. Without it, I couldn’t have penetrated most of the books, blogs, and articles I found later.

His jump happens to coincide, by the way, with the release of his book’s second edition — still on sale, at least as of Thursday afternoon, at the TDWI Bookstore.

Many in the business intelligence industry talk about organizational problems getting in BI’s way, but few talk about them very much.

Scratch the surface of most presentations and conversations — such as last week at the TDWI conference in San Diego — and you find people problems bobbing right up alongside data problems: indifferent executives who undermine BI, short-sighted silo keepers, and IT people who enrage business users with paternalism, to name a few top quirks. If only data were all we had to transform!

One business manger at last week’s TDWI conference in San Diego told me that one of his most daunting tasks during a recent data warehouse implementation was persuading silo managers to release their death grip. For this task, he was on his own. Couldn’t someone have briefed him on the objections he was likely to hear? Or tactics to overcome resistance?

One organization that seems to have solved its people-problem was Blue Cross Blue Shield of Kansas City. Their impressive success with Hewlett-Packard tools was based on commitment to data for strategic advantage and shrewd orchestration. They also had a steady, guiding hand from HP. For example, as Blue Cross Blue Shield built new structures, it avoided upsetting stakeholders by leaving old structures in place for 18 months. (I hope to have much more on that story in the next couple of weeks, thanks to John Santaferraro, HP senior director of marketing, business intelligence.)

Several people in the BI crowd do talk often and thoughtfully about organizational problems. Maureen Clarry, CEO of CONNECT: The Knowledge Network and longtime TDWI instructor, teaches “Power, Politics, and Partnership in Business Intelligence Projects” at every TDWI conference. Participants see for themselves how position shapes behavior. Those short-sighted silo keepers, for example, could flip into data-sharing maniacs if assigned a different position.

Jill Dychè, partner at Baseline Consulting, teaches “BI from Both Sides: Aligning Business and IT,” with strategies to avoid or pave over organizational potholes. She suggests, for example, dodging the perception that BI is “so much data loading and report provisioning.” She writes in email, “We find that the extent to which BI is viewed as a program — with platforms and tools merely components — is the extent to which BI teams are productive and visible in their companies.”

Wayne Eckerson, director of TDWI Research, also addresses these issues, most colorfully with his idea about “purple people.” They are a little bit business-blue and a little bit technology-red, and the purple coloration they acquire lets them traverse the IT-business rivalry.

Wayne spells out some important characteristics for this job, such as maturity and knowledge of technology and business domains. The best are “switch hitters,” by which he probably means to imply that they’re persuasive wherever they stand. In fact, “purple” sounds like a euphemism for another “P” word that Jill actually spells out: politician.

Bad word or not, it’s a critical function. A good politician’s essential function is to coax rivalrous parties into agreement. If that’s the kind of function Wayne sees for the purple people, then they really are, as he says, “the key to BI success” — at least at one level.

Purple may not help much at higher levels. Wayne’s knowledge of of business intelligence is far deeper than mine, but my experience elsewhere makes me think these people are just one of many keys. When I was a sort of purple person myself — in the late ‘90s, bridging an arrogant Web development group and a couple of marketing groups accustomed to full control of their media — my own skill at listening, negotiating, and arm-twisting was only one key. Another key was my boss. At first I had a strong one, later I had an indifferent one, and even later I had virtually no boss at all. I felt like my district shifted boundaries each time, my agenda with it.

One friendly executive suggested I stand up and promote the Web project around the company at any meeting that would let me. He said, “Show ‘em how great it is, and the credit will rub off on you.” Just like a politician running for office.

If I were a purple person today working in BI, where would I go after I’d exhausted training by Maureen, Jill, and Wayne? Most likely, I’d turn for inspiration to books on politics and influence, such as biographies by Robert Caro. Actually, I’ve gone there already, but only because to me politics is a good word. No, you don’t want to emulate Caro’s subjects, just clean and adapt some of the principles they used.

One thing seems clear to me: If purple people, would-be purple people, red people, and blue people are to expand the BI horizon, conversations have to go longer and deeper into the people problems. We start by ending the prissy avoidance of that word that at its best connotes people, perceptions, and compromises: politics!

Now comes the hard part in business intelligence: figuring out how the humans can make better use of all our data and tools for decision making, writes Wayne Eckerson, director of TDWI Research. Let’s bring in the shrinks.

When Wayne points to a trend, it’s news even if others might have already foreseen it. He’s one of the industry’s most thoughtful observers, and one of the most deliberate.

In Tuesday morning’s blog post, he suggests improving BI by enlisting those who study how people make decisions.

To take BI to the next level, we need better insights into human behavior and perception. In other words, it’s time to recruit psychologists onto our BI teams.

He gave an example of one place that could have benefited from visits to the shrink’s couch.

A recent article in the Boston Globe called “Think Different, CIA” provides some instructive lessons for companies using BI tools to make decisions. The article describes a phenomenon that psychologists call “premature cognitive closure” to explain how humans in general, and intelligence analysts in particular, can get trapped by false assumptions, which can lead to massive intelligence failures. It turns out that humans over the course of eons have become great at filtering lots of data quickly to make sense of a situation. Unfortunately, those filters often blind us to additional evidence — or its absence — that would disprove our initial judgment or “theory.” In other words, humans rush to judgment and are blinded by biases. Of course, we all know this, but rarely do organizations implement policies and procedures to safeguard against such behaviors and prevent people from making poor decisions.

See his full post here.

Be sure to see the comments, too. He writes in reply to questions, “Like data governance, we need some principles for approaching and managing decisions. Maybe we should start a decision governance institute!?”

I can’t help notice: an institute.

See “CIA’s insights on the psychology of analysis” on Datadoodle.