IT, business have different views on data

September 18, 2012 | By Ariella Brown

While businesses have a lot in common when it comes to attitudes about big data, there is a lack of common ground between the IT and business teams, according to a Harvard Business Review survey. While its survey is not yet fully analyzed, it considers it ripe enough to identify three primary "takeaways."

• "First, the people we surveyed have high hopes for what they can get out of advanced analytics."
• "Second, it's early days for most of them. They don't yet have the capabilities they need to exploit Big Data."
• "Third, there are disconnects in the survey results--hints that the people inside individual organizations aren't aligned on some key issues."

The first two are consistent with some other studies, including a recent one from CompTIA. However, the third highlights something some other surveys don't: the fact that not all decision makers within an organization are on the same page with respect to big data plans. The disparity is due to the different perspectives of the business and IT end of the organizations.

Some examples include:

• "How would you rate the access to relevant, accurate and timely data in your company today? World-class or more than adequate--IT 13 percent, Business 27 percent."
• "How would you rate the analytic capabilities in your company today? World class--IT 13 percent, Business 0 percent."
• "How would you rate your company on leaders' ability to use data and analytics to improve or transform the business? Less than adequate--IT 57 percent, Business 18 percent."

A "proximity bias" may account for IT reflecting a rosier view of their ability to handle analytics, and for business teams ranking their own ability to "to transform the business higher than their IT colleagues." However, they believe that another factor is that the IT knows more about the silos that keep the data from being effectively integrated in their organization, and thus are somewhat more realistic in their estimation of the odds of a big data transformation.