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Uber and AirBNB hint at BI’s future

You may have seen yesterday’s New York Times story about ratings on Uber, AirBNB, and similar outfits. Customers rate providers, but providers also rate customers. And guess what: As coarse as a five-point scale may seem, actual ratings tend to be worse. Forget the shades of gray, you’re probably either terrific or terrible.

Welcome to a chilling thought. This is what a “data driven culture” could be among the late adopters— a warning those of us who worship “data-driven culture” should be careful what we wish for. Is the failure of business intelligence’s failure to penetrate beyond the present beachhead such a bad thing? The Times story makes me wonder: Which comes first, tools or intelligence?

As important part of intelligence, we might say, is the ability to perceive subtle meaning. At least that’s the assumption underlying the design of most data analysis tools. No one needs SAS, QlikSense, or any of the others to recognize a gold mine glinting in the sun. But we do need data analysis to reveal the vein that, by the thinnest of margins, could turn a profit. And so-called “big data” offers even finer resolution on that picture, letting analysts study questions from many new aspects.

Perhaps you dispute the Doodler’s point. You say that the Uber example has nothing to do with data analysis. You say that the problem is in data quality! That would imply that those who submit data with hamfisted abandon would analyze that same kind of data with a sensitive touch — very unlikely.

What’s more likely is that, if true, the Uber and AirBNB experience portends a dark future for “data driven” cultures.

Read the Times story here. “Ratings Now Cut Both Ways, So Don’t Sass Your Uber Driver”

Data storytelling will be bigger than data itself

I heard an IBM marketing vice president say last summer, “Storytelling will be huge.” I think so, too. But what are data stories?

The big question on the table was what it would take for BI to break out of its miserable five percent penetration into business? Two regulars at the Pacific Northwest BI Summit — Harriet Fryman, IBM vice president of portfolio marketing, big data and analytics, joined Claudia Imhoff, founder of the Boulder BI Brain Trust and well known author — to consider the problem at last summer’s event.

Vendors tell us that data stories are whatever they’re selling. One product makes stories resemble the old Burma Shave signs, those series of roadside placards that, over a quarter mile, added up to a pitch. Another product purports to see narratives in any data stream’s blips.

My eye is on Qlik and its vice president of innovation and design, Donald Farmer. When he hears “story,” he says “conversation,” and that rings true.

Are stories simply told and left to die? No, real stories are retold, questioned, and adapted for new facts. You say that sales were up? Churn was down? Did you figure out why inventory was short last month? Well, what about … There’s always more to the story.

Today’s story about data stories is about the practitioners. I haven’t found many good ones. I looked at Tableau’s Tapestry Conference, but I found would-be data stories that fail to live up to the millennia-old “story” standard. Is a data story just a parade of visualized data? Gazing upon the Tapestry work, you would think so.

What is the standard? How do we know a legitimate story from a fake? It’s all about emotional connection. Traditionally, a protagonist wins an audience’s or reader’s empathy, and carries the plot through the complication, struggle, and resolution.

What would a business protagonist look like? I suppose that would usually be an analyst, who recounts the search for data and a solution. Or the protagonist could be the organization — us.

More likely in business, there would be no explicit protagonist. That would violate the common business myth about teams. More likely, a data story would perform its basic duty by hinging on values: Thriving or diving. Strong or weak. Confident or hesitant. Bold or wary.

Such basic values, expressed in what Robert McKee’s “story values,” are what he calls the “soul of storytelling.” McKee published in 1997 what has become the bible for serious screenwriters, Story: Substance, Structure, Style and the Principles of Screenwriting.

So far, the lack of emotional connection is where would-be data stories fail. These “stories” fail, I think, because the people who try it are at heart data analysts. These fine people feel at home with data but get antsy with real stories. “If it’s not data,” one devotee at last fall’s Tableau conference was heard to say, “it doesn’t exist.” The T-shirts have it right about this crowd: “I heart data.”

Data storytelling will be huge. It will be bigger than data itself. And that will be the struggle.

“Storytelling: Gimmick or Real?” My latest in Information Management

I’m stalking the data-story story. One of the first stops is with a few smart people I know and trust to have given it thought. Scott Davis, whose name long-time Datadoodle readers will recognize, has thought about it deeply. I talked to him in June, and in August finally wrote it up.

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