Analytics Global Executive Study Discussion
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Findings From The 2017 Data & Analytics Global Executive Study And Research Project
Analytics As A Source Of Business Innovation The Increased Ability To Innovate Is Producing A Surge Of Benefits Across Industries.
Spring 2017
Research Report
By Sam Ransbotham And David Kiron
Sponsored By:
Get more on data and analytics from MIT Sloan Management Review:
Read the report online at http://sloanreview.mit.edu/analytics2017
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AUTHORS
CONTRIBUTORS
SAM RANSBOTHAM is an associate professor in the Information Systems Department at the Carroll School of Management at Boston College, as well as guest editor for MIT Sloan Management Review’s Data & Analytics Big Ideas initiative.
DAVID KIRON is the executive editor of MIT Sloan Management Review.
Nina Kruschwitz, senior project manager, MIT Sloan Management Review
The authors conducted the research and analysis for this report as part of an MIT Sloan Management Review research initiative sponsored by SAS.
To cite this report, please use: S. Ransbotham, D. Kiron, “Analytics as a Source of Business Innovation,” MIT Sloan Management Review, February 2017.
ANALYTICS AS A SOURCE OF BUSINESS INNOVATION • MIT SLOAN MANAGEMENT REVIEW 1
CONTENTS RESEARCH REPORT SPRING 2017
5 / Resurgence in Competitive Advantage from Analytics
- Channeling the data deluge
- Concentrating analytics on specific business issues
- A tide of innovation
6 / Analytical Innovators at a High-Water Mark
8 / Navigating Data-Driven Innovation
- Beyond incremental improvement
- Functional areas that excel with data
10 / Sharing Data Accelerates Innovation
- Creating passages between organizations
- Data governance liberates opportunity
- Smart machines create more time for innovative thinking
14 / Conclusion
16 / Acknowledgments
ANALYTICS AS A SOURCE OF BUSINESS INNOVATION • MIT SLOAN MANAGEMENT REVIEW 3
Analytics as a Source of Business Innovation
N ot 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. Work- ing 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 re- porting that their use of analytics helps them beat the competition. These survey results include re- sponges from 2,602 managers, executives, and data professionals from companies around the globe. (See “About the Research.”) The findings reverse a three-year trend in our survey data (2013-2015), in which fewer companies’ year over year reported a competitive advantage from their use of analytics.
So, why the reversal? What changed? Our findings offer clear signals that companies are increasing their use of data and analytical insights for strategic purposes and are using data and analytics to innovate business functions as well as entire business models. Indeed, analysis of our survey results and interviews with more than a dozen executives and scholars indicates that the ability to innovate with analytics is driving the resurgence of strategic benefits from analytics across industries. In this re- port, we delve into the enablers of innovation with analytics and find that data governance capabilities, especially around data sharing and data security, form the foundation for these innovation processes.
The four key findings from our research are:
- More companies report competitive ad- vantage from their use of data and analytics, re versing a three-year trend. According to several indicators in our 2013, 2014, and 2015 surveys, fewer companies were deriving competitive advantage and other important benefits from their investments in analytics than in previous years. According to this lat- est survey, however, that trend seems to have reversed, and more companies are now seeing gains. This is due to several factors, including wider dispersion of analytics within companies and better knowledge of what analytics can do, as well as a stronger focus on specialized, innovative applications that have strategic benefits.
- Innovation from analytics is surging. The share of companies reporting that they use data and analytics to innovate rose significantly from last year’s survey. Organizations with strong analytics capabilities use those abilities to innovate not only existing operations but also new processes, products, services, and entire business models.
- Data governance fosters innovation. Companies that share data internally get more value from their analytics. And the companies that are the most innovative with analytics are more likely to share data beyond their company boundaries. Survey results show that strong data governance practices enable data sharing, which then enables innovation. To be most ef- fective, data governance needs to be embedded in an organization’s culture. Tactics are not the
This is the seventh MIT Sloan Management Review research study of business executives, managers, and analytics professionals. This year’s 2,602 survey respondents were drawn from a number of sources, including MIT Sloan Management Review subscribers. They represent organizations around the world and from a wide range of industries.
The research also includes interviews from experts from a number of industries and disciplines. Their insights into the evolving uses of analytics have enriched our understanding of the survey data. In addition, we incorporate case examples that document how analytics are being used.
In this report, we use the term “analytics” to refer to the use of data and related business insights developed through applied analytical methods — using statistical, contextual, and predictive models, for example — to drive fact-based planning, decisions, execution, management, and learning.
ABOUT THE RESEARCH
ANALYTICS AS A SOURCE OF BUSINESS INNOVATION • MIT SLOAN MANAGEMENT REVIEW 5
same as cultural norms. Data governance needs to be more than a system of tactics to derive business value — it must actually influence organizational behavior.
- Smart machines create opportunity for innovative thinking. Smart machines that draw inferences from data on their own and learn by using algorithms to discern patterns in masses of data are no longer confined to research labs and limited applications such as speech recognition. The most analytically mature companies use artificial intelligence to augment human skills and to take on time-consuming tasks, freeing man- agers to spend more time on strategic issues.
From 2013 to 2015, our annual surveys showed a steady ebb in the percent of companies reporting a competitive advantage from their use of data and analytics. As analytics became more widespread, and therefore a more common path to value, it became more difficult for companies to gain or maintain a competitive edge with data. “Those big early adopters got an early benefit,” notes Kristina McLerran, assistant professor of strategy at the University of Toronto. She points out that in many cases, even early adopters hit a slow patch after their initial successes with analytics because they weren’t embedding analytics into the organization. “Until it becomes an engine for learning, until it transforms your cost structure or value to customers in a way that’s difficult for your competitors to imitate, then I don’t see analytics as a silver bullet that lets firms get in front of the pack and stay there,” she explains.
In 2016, managers in more companies said they are getting ahead of the pack. This is a marked reversal of the trend of the previous three years. The share of respondents who say that analytics provides com- petitive advantage rebounded to 57%, still off the 2012 peak of 67%, but well above the 51% of 2015. (See Figure 1.)
Several factors contribute to the resurgence in com- panies gaining a competitive advantage from data and analytics: success applying data-driven insights to strategic issues; application of analytics to a wide range of business issues; technology advances, such as cloud computing and distributed storage; and data-driven innovations that make a material con- tribution to the company’s competitiveness.
Channeling the data deluge
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