Even though more organizations are attempting to become data-driven, many of them still aren’t able to link data analytics to business outcomes. Some of the challenges are obvious. Others aren’t. Here are our tips for avoiding the common pitfalls.
One could argue the purpose of data analytics has always been to achieve business outcomes. Yet, enterprises still struggle to realize the potential business value of their investments. Despite the availability of a wide array of improved technologies, it’s easy for company cultures, organizational structures, and even problem-solving approaches to get in the way.
“The fundamental premise is it’s a technology problem. It reminds me of the early Internet days [when people said] ‘We have this capability, what problem can we solve?'” said Jeff McMillan, managing director at Credit Suisse. “That’s not how it works. You have a business issue and need to bring a set of capabilities to bear.”
Departmental barriers continue to impede progress. Some companies are restructuring to compete more effectively in the digital economy, but the expanding C-suite may frustrate the ability to drive business outcomes.
“Not too long ago, we had a CIO and a group of people who were the caretakers of the databases,” said Anthony Scriffignano, VP and chief data scientist at Dun & Bradstreet, in an interview.;