Business Data Lessons from Journalism (Yes, Journalism)

Loraine Lawson

It’s an exciting time for data geeks. It now ranks right up there with land, labor and capital as fundamental to business.

(Queue the dramatic come-back music.) Yes, after years of being neglected in both IT and the business, data is moving out of that tiny office beside the server room to the center of a veritable transformation — the Data-Driven Enterprise.

Let’s hit the pause button for a moment, shall we?

I’m a journalist, or at least I used to be, back when we had newspapers that actually tried to publish news and real reporters who literally hit the streets and talked to real people every day to find news.

Now, I’ll grant you, newspapers may not be in the best position to offer many lessons that apply to businesses, but when it comes to facts — and the frustration of clarifying them — you’ll be hard pressed to find someone more experienced than a newspaper reporter.

I’ve seen a lot of surveys, reports and data in my time, and here’s what I’ve learned: Data can speak for itself, but all too often, it can also be held hostage and made to say what someone wants it to.

Of course, it’s not the data that’s the problem. It’s the transformation of data into “information,” where you’re applying things like words and pretty graphics, which can make something look more important than it really is and trick us into thinking the data is apples-to-apples, when it’s really cranberries-to-pineapples.

And therein lies the problem for businesses, and the potential pitfall for IT and data management experts: Once you’ve managed all this data, you’re going to have to turn it into information. And if everyone’s not very, very careful to ensure that the data is being used and interpreted correctly, rather than manipulated to reflect what you want to see, then that information could lead you horribly, horribly astray.


This is a particularly important point now, with many BI initiatives focused on giving more end users access to data.

Eric T. Peterson, founder of Web Analytics Demystified, wrote an excellent piece on this problem in September. He states:

A "data-driven business" would be doomed to fail. I simply have not seen nearly enough evidence that eschewing the type of business acumen, experience, and awareness that is the very heart-and-soul of every successful business in favor of a “by the numbers” approach creates the type of result that the “data-driven” school seems to be evangelizing for.

Peterson used to think otherwise, until he tried to preach the “Good Word” of data to a CBS editor.

"Son, we’re not going to let the data make the decisions for us regarding editorial content," he said with all sincerity. “Because if we let the data drive editorial, all you will read about at CBS News is Paris Hilton’s breasts and Lindsay Lohan’s drinking problem.”

(I checked, by the way. Neither were on the front page of CBS News today — but Britney Spears nabbed one mention.)

“Needless to say, I stopped talking about real-time, data-driven changes to editorial content,” Peterson adds.

It’s not just about the potential for dumb decisions, though. It’s also about misuse. Jonathan Gray of The Knowledge Foundation recently published an eloquent reminder to journalists about the dangers of viewing data as “fact.”

But as users and advocates of this potent and intoxicating stuff we should strive to keep our expectations of it proportional to the opportunity it represents. We should strive to cultivate a critical literacy with respect to our subject matter. While we can’t expect to acquire the acumen or fluency of an experienced statistician or veteran investigative reporter overnight, we can at least try to keep various data-driven myths from the door.

The piece goes on to caution data-loving journalists that:

  • Interpreting data is not easy.
  • Data does not speak for itself.
  • Data is not a perfect reflection of the world.

Personally, I think it’s great that data’s being taken seriously, but the temptation here will be to dive into the data without regard to the discipline of understanding proper data analysis. Organizations might want to think through these issues:

  • Do your employees need training to interpret data?
  • What are appropriate ways to use data?
  • How will you keep data from being misused, as a means of obtaining and yielding power over those who do not have data?
  • Are there policies you can put in place to ensure data is used appropriately?

Business executives, CIOs and data management workers should keep that in mind before embracing the mantra of a “data-driven” anything.



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