6 Ways To Make Your Company Data-Driven

6 Ways To Make Your Company Data-Driven

6 Ways To Make Your Company Data-Driven
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Rich Wagner, president and CEO of Prevedere, shares six guidelines he’s developed based on his own experiences seeing good data left to waste at major enterprises, including the Fortune 500 chemical company where he once worked.

Executives around the globe are demanding their organizations become more data-driven, and for good reason. The Economist Intelligence Unit found data-driven companies rate themselves substantially higher in terms of financial success than others do. In my experience, this new data-driven mantra is easier said than done.

Executives often don’t realize what they are asking of us in IT. That’s assuming they know to ask the right questions at all. In fact, another EIU study found 35% of executives lack an understanding of how to apply big data, and 62% of CIOs report big data buzz has resulted in unrealistic expectations among executives.

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IT teams are still adapting to functional users demanding answers at the touch of a button, something they’ve come to expect because of Google and the proliferation of smartphones. So, what’s an IT professional to do? Based on my own experiences, as well as the work I’ve done with other organizations, I’ve developed six steps that can transform companies into data-driven enterprises.

[What’s hot in data science? Read 10 Programming Languages and Tools Data Scientists Use Now.]

Look forward, not backward. Leading IT strategy and innovation at a Fortune 500 chemical company, I came to the disheartening realization that the business intelligence reports my team worked so hard to produce were going unread and unused. When I dug deep to find out what would make them more valuable, the answer was the same across business functions.

In fact, I found a common theme as I looked at the broader business environment, even across companies: Executives needed to know what was going to happen, not what had already occurred.

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Determine the question. Before searching for answers, it’s critical to know what key questions your data should answer. Most commonly, the customers I speak with are looking to determine the following:

Rethink your data sources. Now that you know the answers, you need to find, take a hard look at your data sources.

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