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Chapter 2

Big Data & Automation

Thanks to technology, companies are positioned to collect more customer and operational data than ever before—but Big Data aggregation and analytics are critical in order to reap the rewards of these growing information sets.

Although companies collect massive amounts of data, it’s not always used to its full potential. Some data is stuck in disconnected systems; other data is unstructured or qualitative. Finding ways to bring all that together into one dataset is what is typically meant by Big Data.

But Big Data is about more than just the data itself—it’s about using that information to develop data-based insights that drive decision making. While the Big Data trend is nascent at all but the most innovative companies, it’s highly valued and recognized as the wave of the future. In a 2014 cross-industry survey, 90 percent of senior executives said that Big Data has changed or will change decision making at their organizations.

Two 2014 PwC reports found that trends in data analytics are gaining traction with leadership. 85 percent of CEOs said that they put a high value on data analytics for their companies, and 80 percent place data mining and analysis as the second-most important strategic technology initiative for CEOs (just behind mobile technology). Meanwhile, business analytics tops CEOs’ priority lists in terms of anticipated investment.

While innovation and technology can mean automation, automation won’t necessarily help companies cut manpower. Instead, it can help companies improve cost per unit while shifting workers into more strategic roles, such as those around process improvement where data analysis is fundamental. Today’s workers need critical thinking skills to analyze that data and do what machines cannot.