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March 29, 2016

Survey: Operational Analytics Gaining Traction

Early adopters of analytics are looking inward as they gradually shift the focus of their organizational efforts away from uses like gauging customer preferences to internal operations.

A report released by Paris-based business consultant Capgemini (EPA: CAP) underscores the growing shift towards operations analytics as more companies recalibrate their data efforts to back-office processes. The study released last week by Capgemini Consulting’s Digital Transformation Institute found that 70 percent of company’s surveyed have shifted the priority of their analytics effort from front- to back-office operations.

At the same time, only 18 percent of those companies implementing operations analytics have so far a negligible return on the investment. One early advantage, according to the report, is improved data and governance processes that are increasingly important as more private data lands in enterprise databases.

Despite the focus on operational analytics, “there are factors limiting the success of these projects,” warned Anne-Laure Thieullent of Capgemini’s Insights & Data unit. These include “siloed datasets, fragile governance models, inability to harness third party data sources and an absence of a strong mandate from leadership teams,”

While the shift to organizational analytics is ramping up slowly—the French consulting firm said U.S. companies are making the most progress—the approach is allowing early adopters to leverage an integrated data approach. That enables organizations to integrate datasets across their organizations to obtain a holistic view of their operations.

The inward shift to operational analytics also is allowing companies to boost the quality and breadth of their operations data by making greater use of external and unstructured data. The Capgemini study found that 59 percent of early adopters were improving operational analytics through use of varied data.

As a result, more than half of early adopters said operational analytics were now integral to their decision-making process.

Cognitive computing is expected to help enterprises make sense of greater volumes of structured and unstructured data. Meanwhile, the consultant sees machine learning and artificial intelligence will aid decision making and “operational optimization.”

“We have only scratched the surface of operational analytics,” noted Jerome Buvat, head of Capgemini’s Digital Transformation Institute. “More elements of the demand chain, from the factory floor to the products sold to customers, are becoming connected and are producing data.” However, Buvat added, “few organizations are well set up to take advantage of these technology developments.”

The consultant noted that research conducted along with MIT Sloan Management Review in 2013 found that 40 percent of survey respondents remained focused on consumer-facing analytics. Only about one-quarter were focused operations analytics. Fast forward to 2016: the latest survey found that more than 80 percent of respondents agreed with the proposition that “analytics in operations plays a pivotal role in driving profits or creating competitive advantage.”

The business consultant said it surveyed about 600 operations executives in the U.S., Europe and China who are managing operational analytics initiatives.

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