In Brief

The Challenge

To remain competitive, companies must wisely manage quantities of data. But data theft is common, flawed or duplicate data sets exist within organizations, and IT is often behind the curve.

The Solution

Companies need a coherent strategy that strikes the proper balance between two types of data management: defensive, such as security and governance, and offensive, such as predictive analytics.

The Execution

Regardless of its industry, a company’s data strategy is rarely static; typically, a chief data officer is in charge of ensuring that it dynamically adjusts as competitive pressures and overall corporate strategy shift.

More than ever, the ability to manage torrents of data is critical to a company’s success. But even with the emergence of data-management functions and chief data officers (CDOs), most companies remain badly behind the curve. Cross-industry studies show that on average, less than half of an organization’s structured data is actively used in making decisions—and less than 1% of its unstructured data is analyzed or used at all. More than 70% of employees have access to data they should not, and 80% of analysts’ time is spent simply discovering and preparing data. Data breaches are common, rogue data sets propagate in silos, and companies’ data technology often isn’t up to the demands put on it.

A version of this article appeared in the May–June 2017 issue (pp.112–121) of Harvard Business Review.