Study reveals that most companies are failing at big data

Sarah K. White

"Companies with less sophisticated analytics requirements may be able to fill the skills gap using existing employees by sending them to focused training sessions such as data analytics boot camps [and] night courses," says Trombley.

For some companies, this might be the best option, considering there is currently a lack of capable data scientists since it is a relatively new and fast growing position. Simply getting an employee up to speed can help lessen the impact of a lacking data strategy, but it still might not be enough.

"There is no one-size-fits-all regarding the CDO [Chief Digital Officer] position," Trombley says. "Whether they exist or not the basic responsibilities attributed to the role need to be assigned to one or more individuals in the current organizational structure. Also, there is the supply and demand dilemma -- not enough talent available to fill the CDO position in all organizations."

Characteristics of the 'data elite'

Of the businesses surveyed, only 4 percent were classified as "data elite," with a typical business profile of medium or very large businesses within healthcare and manufacturing and engineering. These businesses, according to the study, first and foremost had a well-established "information governance oversight body." Furthermore, these businesses had fostered a "strong culture of evidence-based decision making," appointed analysts that can access data, had strong control over their data and had extensive analysis tools in place.

These progressive companies have tapped into the most valuable resource available to them and made it part of the company culture. Some of the most agile mid-market businesses are found in this category, which the study suggests is because they aren't bogged down by legacy and are in industries that are less regulated than others. However, less agile enterprises businesses are also found in the data elite, thanks to strong leadership, global information governance arrangements and relevant departments outside of IT in the data functions.

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