When, when will someone write a novel about business intelligence? I can see it now. Amazon will try to sell me From Here to Analysis, Data in the Afternoon, and Lolita, DBA.

But titles are easy. Writing the novel might be tough, since the author would have to run on sheer imagination. There’s no apparent intrigue. The BI crowd plays it safe. Forget sex. The BI crowd works too hard. Forget guns. The BI crowd shoots only bullet points.

In fact, the best strategy might be Alfred Hitchcock’s favorite: the macguffin. It’s a plot element, often ephemeral, that drives the main characters to do what they do regardless of the macguffin’s value. As the plot moves along, the macguffin fades into the background.

In BI, the most common mcguffin is technology — while the real issue is effective use of data in business decisions.

Remember “Psycho”? The woman steals money from her boss and flees. Her boss is sure to follow. We’re looking off in that direction when out of nowhere comes the shower scene. Holy crap! We never saw that one coming!

Hitchcock’s aim was fear, but McGuffins have other uses, too. In business intelligence, the macguffin creates comfort. In the BI plot, the shower scene is instead endless talk about technology, data quality, data this and data that. All the time, lurking in the culture, unexamined and feared, is classic business dysfunction. But leadership can’t fix it, so they go shopping.

What’s a novelist to do? Use it all. Study up on the technology for a week and interview people on the front lines. Then drape BI technology over a standard plot set in an enterprise.

Business people buy BI tools, and so they’ll buy the BI thriller.

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!

Does it seem to you like data analysis is busting out all over the place? It might become another fun game like chess or Chutes and Ladders — so this might be good time to recall an old admonition: Don’t just consume data, mind its pedigree.

Repeating the warning, though, makes you look like a party-pooper. In 2007 at the TDWI conference in Las Vegas, a keynote speaker raised it one morning. Jonathan Koomey — author of Turning Numbers into Knowledge and one of those voices the BI world needs more of — did his best. But I could see the unfolding disaster from my banquet table, as attendees glanced at each other in scorn. When the lights went up, not one person raised a hand with any question or comment.

Now Sex, Drugs, and Body Counts: The Politics of Numbers in Global Crime and Conflict, edited by Peter Andreas and Kelly M. Greenhill, tries it again.

You may wonder what sex, body counts, and politics have to do with data analysis, but try to keep an open mind here. The book promises to let us spit out the usual cud of business intelligence, data quality, and get to the real spice: the politics of data. I can’t wait to read it. For now, see Jack Shafer’s review on Slate.

I won’t be surprised if the book points out how each organization’s core group subtly chooses the stories its data tells. I’ve just finished Art Kleiner’s Who Really Matters, which goes into detail on these groups’ formation and influence, including how they define who’s in, who’s out, and why. It’s the essence of politics.

Though core-group members may not ever lay their smooth palms on any data, data is nonetheless coiffed to suit these people. Through layers of managerial interpretation and re-interpretation, their influence cascades all the way down to tiny decisions about how data’s summarized, what’s measured, how it’s measured, and who measures it.

Like other forms of expression within an organization — speech, email, jargon, attire, hair style, suit or T-shirt — data is part of the politics. Though this has a big effect on decision making, it seems rare that I find it on a BI-event agenda. BI’s scope needs to widen.

See Oscar Berg’s post “Did You Ever Hear anyone Shout ‘Culture Failure’?” on his weblog, The Content Economy.

A culture failure is much more alarming and also much more uncomfortable than a simple process or technology failure. It signals that something is fundamentally wrong, something which is very complex and hard to change. It means that you not only have to change your own attitudes and behaviors, but also those of your colleagues, including management. You might need to change the entire incentive model, which in the end determines the bonus of your CEO. What is worse, you most likely also need to change the attitudes and behaviors of your CEO (“Impossible!”).

Originally referred by Henrik Mårtensson on Twitter.

The people in an audience who ask what seems like a rude question are often the ones worth listening to. Take, for example, one guy I heard recently. He talked about his old movie camera — which was relevant to the subject, cinema — but his question had parallels with a perennial issue in BI.

He said that he had had a Bolex 16-milimeter movie camera back when he was a kid, and so anyone else could have, too. To him, the idea that new technology like small video cameras and inexpensive desktop editing was now unleashing a burst of moviemaking was just not true. “It’s nonsense. You know it is,” he told the Oscar-winner Walter Murch, who sat listening patiently on stage.

I didn’t write down Murch’s reply, but I have my own: Great as the Bolex may have been, amateur filmmaking back then was slow, expensive, and lonely. There were no swarms of fellow filmmakers and no audience on YouTube. Bolex Schmolex.

Cinema, and business, depend on more than technology.

Murch’s main point, which he explained for almost an hour, was about cinema’s quick success a century ago. It took off, he said, because the popular culture was prepared for it, not just because the technology had arrived.

Just one of the “three fathers of cinema,” as Murch calls them, had anything to do with the technology: Thomas Edison. Beethoven, and introduced dynamism into music instead of the ordered music of Haydn and Mozart. Also Flaubert, another name as shorthand for the new painters and fiction writers who discarded fantasy and aristocratic life for everyday reality.

Does he mean that everyone in the bargain matinee seats a Beethoven fan? No, but I wish I’d asked how it worked. For now, I go with the teabag theory: a bit of pungent herbs have a way of permeating the surrounding medium. Just ask Sarah Palin.

From Beethoven’s dynamism, it’s a short leap into the vocabulary we know today: fast cuts, close-ups followed by panoramas, stories interlaced with other stories, and so on.

Imagine a tool that falls into a culture that’s not ready. Say some ancient toymaker invented the wheel but for centuries afterward the adults kept dragging freight around on sleds. That’s apparently what the Aztecs did. Same thing happened to the steam engine invented by the Greeks.

I wish I could raise my hand now to ask Murch a few questions: For example, could cinema have taken root with a Mozartian vocabulary instead of a Beethovenian one? I suppose we’d have nothing like “Citizen Kane” and a lot of films like “This is My Railroad” (1940; Southern Pacific).

Who can say about movies, though? It’s much easier to speculate whether BI can take root in an organization with no fathers or mothers of data analysis.

Read a pile of technology marketing and you quickly assume that you alone despise many of the words you keep hearing. They’re words like optimize, leverage, synergy, and utilize. People in this industry don’t really talk like that, do they?

Many don’t, at least not in private, and they don’t tweet like that, either. One tweet trail at Gartner BI Summit complained about exactly this kind of word — these miserable words with all the wild flavor bred out of them like factory-farm tomatoes.

On the list of suggested extinction, Jill Dychè listed optimize and fact-based. Scott Davis listed leverage, co-optition, and dot-bomb. Someone also threw in win-win, synergy, and the lovely utilize.

Mark Madsen cautioned that banning all those words would leave marketing with nothing but proper names and prepositions.

The whole discussion started off when Dychè posted a link to David Silverman’s article in Harvard Business “10 Business Words to Ban.”

Now Dave Wells has followed with a weblog post. He left the TDWI conference in Las Vegas last week with his head “afloat in buzzwords.” So many new terms every quarter, and so much ambiguity. ” Maybe its time that we define our terms and differentiate between similar sounding terms.” He goes on to list a few he’d like to see on the endangered list.

Let the movement flourish.

We all know BI’s ostensible price tag: the software, the hardware and the peopleware. But a new essay by Paul Graham, author of Hackers and Painters, programmer and venture capitalist, suggests that poorly managed BI might have yet another cost: the cost of thwarting creativity and zeal.

In business, we try to control what we must. We watch, deliberate, reflect and predict. We’re often neurotic. With BI, we watch more closely than ever.

Graham talks about how these “checks”—such as procedures to verify a vendor’s solvency—inflate the cost of software. He writes that programmers are especially sensitive to checks, which can drive them out of their minds or out of the company.

For good programmers, one of the best things about working for a startup is that there are few checks on releases. In true startups, there are no external checks at all. If you have an idea for a new feature in the morning, you can write it and push it to the production servers before lunch. And when you can do that, you have more ideas.

At big companies, software has to go through various approvals before it can be launched. And the cost of doing this can be enormous—in fact, discontinuous. I was talking recently to a group of three programmers whose startup had been acquired a few years before by a big company. When they’d been independent, they could release changes instantly. Now, they said, the absolute fastest they could get code released on the production servers was two weeks.

This didn’t merely make them less productive. It made them hate working for the acquirer.

He writes about software and programmers, but you know this happens in many other industries. More people than we realize are like those programmers. Most people can’t flee to a startup, so they smother the inner artist and gear down.

If, as Steve Jobs has been quoted, “Artists ship,” then artists hate it when they can’t ship. Programmers are particularly vulnerable to checks, writes Graham. “These guys would have paid to be able to release code immediately.” He goes on, “If you don’t let people ship, you don’t have any artists.”

There we go again: It’s the soft stuff that matters.

Those of us in the tech world who shun jargon may forever remain an underclass. We may never rise to the mainstream, where today tech-centric vendors rule. So I’m delighted when I meet another one of our clan who declares proudly his rejection of tech-speak.

Don Farber, vice president of sales and marketing at KnowledgeSync, says that to reach business customers, you have to use words they understand. For many buyers in the mid-market, that means avoiding any jargon at all.

Here’s how he orders a steak: “I ask for ‘pink in the middle.’ When the waiter asks me, ‘Rare?’ I say, ‘I don’t care what you call it, just give me a steak that’s pink in the middle.’”

We have to be careful, though. Some buyers in the mid-market watch for tech words as if it were a secret handshake. One insightful Datadoodle reader read about Farber’s approach last week and posted a reply that began like this:

This is so true. And it cuts both ways. Larger midsize companies have IT teams who are knowledgeable about BI, and if you don’t use all of the most proper complex jargon with them, they think you’re a lightweight solution that doesn’t do what they need or, worse, that you’re a team of idiots who just happened to create what they wanted the first time…

Take that, Strunk and White (Elements of Style).

Restless minds will want to know what Asian manufacture of furniture, clothes, electronics and other goods has to do with business intelligence.

A globe-trotting industrial engineer who’d rather not be named has been telling me about different perceptions of quality among nationalities. He works on contract to American companies to ensure that product quality lives up to agreements.

When Americans buys new stuff, they assume it’ll come out of the box without dings, dents, scrapes or other flaws. Seams will be tight, electrical joints will be well soldered, paint on the fender will match the hood, wood veneer will be smooth.

According to the engineer, Chinese and Indian manufacturing and warehousing staff he’s worked with see it differently. When he flags a wooden cabinet, for example, with a deep gouge on the corner, the Chinese warehouse manager shrugs. “He’ll say, ‘That’s just because it was moved around the warehouse.’ It’s nothing to him.” Same with a chair with one shade of fabric on the armrest and another on the seat.

What about data? If that’s their cultural bias about dings in furniture, how do they feel about dings in data? Is carelessly handled data as easy to detect?

If bureaucrats were to shut down their websites and simply fed data to whoever wanted to comb it out, as one group will soon propose, would we have failed at Government 2.0?

Jim Powell, the TDWI editorial director, said yes, we would have failed. Without a built-in channel for the back-and-forth of genuine collaboration, there would be little collaboration.

At first, I wasn’t so sure.

First, who’s to say that officials really would engage in collaboration—even with that built-in channel in place?

Dave Wells, who points out the importance of BI culture, would likely say that success in Gov 2.0 would depend on culture. If officials don’t buy in, no technology’s going to make it work.

Wikipedia, Jigsaw, and Facebook and others find success within self-selected groups. Those who don’t see their value simply don’t show up. What’s to force officials to pay attention?

Until now, the main way ordinary people became powerful was by concentrating their influence in groups. The Sierra Club, for example, has no formal authority. Yet its nearly one million dues-paying, letter-writing members have as a group earned respect and fear among lawmakers. That’s the same for the National Rifle Association and many other groups, too.

These groups make better use of the new flood of data than individuals can. Smart groups hire smart analysts and publish their results. Most individuals didn’t have that reach.

Then the mob would find a voice. The swirling masses would come to a consensus like astral dust coalescing into planets. Then the crowd would have gravity. Then officials would have to take notice whether they liked all this Web 2.0 stuff or not.

At least that’s how it looks to me today.