What will it be, a “single version of the truth” or unabated proliferation of ad hoc data? It’s a chronic dilemma, and its resolution is crucial to big-box business intelligence. Frank Buytendijk’s new book, his second one, offers a way out of this pickle.

In Dealing with Dilemmas: Where Business Analytics Fall Short (John Wiley & Sons; 2010), Buytendijk — pronounced BOW-ten-dek, according to a Dutch friend of mine — argues that the usual this-or-that, you-or-me, and now-or-then dilemmas may not be the tough choices that they seem to be.

I had known Frank Buytendijk from his two TDWI keynotes, both of which broke down old fences. Then I got to the part of the book where he takes on Michael Porter — author of the essay “What is Strategy?,” in which he defines strategy partly by what a business doesn’t do. Southwest Airlines, for one well known example, offers no reserved seats or meals. But without that distraction, it can fly you on time at a reasonable price.

Porter’s theory, I used to say, is comparable to cropping a photo: emphasize one aspect by trimming others. Then you know what the message is for once and for all, or maybe you have to interpret it, but what you need is all there. Buytendijk’s theory may be more like making a movie. The movie, too, requires the artist to decide on emphasis and exclusion, but in a movie the story plays out over time and through multiple spaces. The movie, too, has a message. But a movie goes this way and that way as it winds toward the end — like a business as it winds through its environment toward a goal.

Of course, a movie requires the artist to think harder. A movie takes shape much more slowly. I’ve only imagined Buytendijk’s principles in practice, but I think that what he prescribes is far more involved the usual strategy formulation.

Buytendijk, in fact, has fun ridiculing strategy-formation executive campouts. Inspiration may strike while they “sing songs around the campfire.” The marshmallows and scotch taste good, but the thinking doesn’t stick, the assumptions are forgotten, and the organization is left to live on slogans.

What’s required, he writes, is deeper understanding of the theory behind the business and the nature of the dilemmas that decision makers face.

While the goal (that we chose) remains intact, and the assumptions remain in place as long as they match reality, we can travel toward our goal, assessing whether options that we create and opportunities that we see fit into the framework. If so, we capitalize on them; if not, we let them go. And the moment assumptions change, we can immediately see which activities do not lead us to the goal anymore, or which activities are lacking in making it to the goal. Choices do not turn into dilemmas.

Choices don’t turn into dilemmas the way “single version of the truth” versus spreadmarts has. The Big Brother version of decision support might have been devised in a campfire sing-along — far away from those who still had work to do.

What would Buytendijk do with that problem? I think he would classify it as a “you-or-me” type. It involves one group against another, usually IT soldiers charged with enforcing a policy against rebel cells armed with spreadmarts. But if either one had a decisive victory, it might spell trouble for the organization.

He prescribes three steps: First, examine your motives. What are you really trying to do? What’s the goal? And so on. Next, communicate. Do not fall for that old slogan of ham-fisted managers, “If you’re not part of the solution, you’re part of the problem.” The solution may be found in conversation. “By being part of the solution from the start,” he writes, “the only angle you will see is your own … Acknowledging there are multiple sides to the story, even if you do not agree, is the key to reconciliation.” Finally, reconcile and synthesize. Opposites — such as love and hate, Tea Bagger and Berkeley liberal, IT soldier and spreadmart rebel — may actually be more alike than you think.

I see what he means when, at the end, he confesses to not understanding the old saying that “you can’t have your cake and eat it too.” It’s stupid, something a burned out school teacher uses to keep order. Aren’t we smarter than that? And if there’s hope for cake, there’s hope that the “single version” and the spreadmarts can live together under one roof.

Business is ultimately not technical but social, is it not? Appropriately, this book is deeply humane and intelligent — expressed in a warm, conversational voice. That alone distinguishes it from most other business books. It eases you through difficult new ways of thinking, through what I think many readers will find is new and unfamiliar territory. Decision makers who are willing to put in the effort to understand it and put it into practice, I think, will find it worthwhile.

Dealing with Dilemmas may never become a mainline classic of the kind Porter wrote. But it will certainly be a favorite among a smart and adventurous few.

Dear Datadoodle: My title is “strategist analyst,” but I’ve become just “the data geek.” As soon as I get into the fine points of my data, they roll their eyes. In meetings, they make little jokes to each other, or they just stare out the window. Please help. I’ve got loads of great data but managers have no time for me anymore. The Data Geek

The Data Geek has lots of company, says Christine Muser, longtime data analyst, founder of CyCom Solutions, and writer of CyCom’s weblog Pharma-BI. She’s seen data analysts stumble over this problem. She had to deal with it herself.

“I love data,” she says, “so in my younger days I used to just barrel right ahead into the details.” Too often, though, she’d see only glazed looks in her audience.

It was even worse for one man she once worked with. He actually became useless as a strategist. He spent so much time pulling together data, manipulating it in Excel, and poring over results that he kept managers waiting for results. After a while, those who relied on him got tired of waiting — and tired of his overly detailed explanations about dimensions, data sources, and methods.

Now, Christine analyzes more than the data. “It pays to know your audience. If you know they’re very familiar with the underlying data, you can give more details,” she says. If they’re not familiar with the data, “You can say, ‘here’s what we’ve observed’ and ‘here’s the impact,’ then be quiet and see if you get puzzled looks.”

The essential lesson she learned: “Understanding what is meaningful is a really big deal.” A strategist understands what’s significant, and doesn’t bother with the small stuff.

For example, say you’re analyzing a pharmaceuticals market. Your company makes a drug that treats only one symptom, while some competing companies make drugs that treat that symptom plus several others. That difference makes a straight comparison — pill for pill or dollar for dollar — useless. So you have to adjust the data to allow for that difference. But managers usually don’t want to hear how you did it, only that you did take care of it.

A strategist also knows when to ignore buzzwords. A manager who liked to stay current once asked Christine, “Can you do neural networks?” Perhaps, but dare go into what that would take and you risk running out your clock.