Analytics as a Source of Business Innovation

The increased ability to innovate with analytics is producing a surge of benefits across industries.

by: Sam Ransbotham and David Kiron
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Not long ago, Keith Moody was the only data analyst at Bridgestone Americas Inc. He was located in the credit division in Brook Park, Ohio, and saw analytics take off — in other companies. When Bridgestone Americas named a data-savvy executive, Gordon Knapp, as chief operating officer in March 2014, Moody was given the opportunity to build a new analytics department for Bridgestone Retail Operations, the company’s U.S. network of tire and auto repair stores. Today, Moody reports to the interim president, Damien Harmon, as director of analytics for Bridgestone Retail Operations, where he is making up for lost time.



Moody’s team is influencing management practice in virtually every part of the organization. Working with the real estate department, the analytics team pinpoints the best locations for new stores. Working with operations, it automates provision of inventory to 2,200 stores.1 Working with human resources, it determines the best allocation of 22,000 employees so that Bridgestone retail locations have the right people on-site to deal with peak demand — and don’t have workers sitting around with time on their hands. What’s more, Moody’s team is looking for ways to use driver data, such as odometer readings and other telematics data, to encourage car owners to come in for new tires or a tune-up before they hear a rattle under the hood and have to look for the nearest repair shop. This new reliance on analytics to inform executive decision making and to develop new services reflects a cultural shift for Bridgestone’s operations in the United States.

What’s happening at Bridgestone provides a window into the state of analytics across industry. After years of enthusiasm and frequent disappointment, a growing number of companies are developing the tools and, increasingly, the skills to move beyond frustration. They are progressively able to access large pools of data and use analytics to inform decision making, improve day-to-day operations, and support the kinds of innovation that lead to strategic advantage and growth.

MIT Sloan Management Review’s seventh annual data and analytics survey, conducted during 2016, reveals a sharp rise in the number of companies reporting that their use of analytics helps them beat the competition. These survey results include responses from 2,602 managers, executives, and data professionals from companies around the globe. (See “About the Research.

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References

1. These figures are for the entire Bridgestone North America retail operation, which includes stores operated under the Firestone name.

2. Third-party data vendors have, and likely will continue to have, a large role in helping companies understand customer behavior. Indeed, Nedbank Group Ltd., the Johannesburg, South Africa-based financial institution, offers a data service to its small- and medium-sized merchant customers, using credit and debit card transactional data. This gives its business customers insights into their own customers that would have been impossible for them to do themselves. However, other companies are becoming less dependent on third-party vendors and are now developing their own data capabilities to build their own distinctive perspectives on their own customers.

3. See also B.H. Wixom and J.W. Ross, “How to Monetize Your Data,” January 9, 2017, https://sloanreview.mit.edu.

4. S. Ransbotham, D. Kiron, and P.K. Prentice, “Beyond the Hype: The Hard Work Behind Analytics Success,” MIT Sloan Management Review, March 2016, https://sloanreview.mit.edu.

5. K. Safdar, “As Gap Struggles, Its Analytical CEO Prizes Data Over Design,” Wall Street Journal, Nov. 27, 2016.

6. E. Auchard, “HERE, Automakers Team Up to Share Data on Traffic Conditions,” Sept. 25, 2016, www.reuters.com.

7. L. Winig, GE’s Big Bet on Data and Analytics, MIT Sloan Management Review, February 18, 2016, https://sloanreview.mit.edu.

8. T.H. Davenport, “IT Drinking Its Own Automation Champagne,” Nov. 10, 2016, http://data-informed.com.

9. J. Manyika, M. Chui, M. Miremadi, J. Bughin, K. George, P. Willmott, and M. Dewhurst, “A Future That Works: Automation, Employment, and Productivity,” January 2017, www.mckinsey.com.

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