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The hype around data and analytics has reached a fever pitch. From baseball to biomedical advances, the media highlights one money-making or money-saving corporate experience with analytics after another. Stories abound about data scientists applying their wizardlike talents to find untapped markets, make millions, or save lives. Pundits have been talking up the promise of data in grand terms for several years now: Data has been described as the new oil, the new soil, the next big thing, and the force behind a new management revolution.1

Despite the hype, the reality is that many companies still struggle to figure out how to use analytics to take advantage of their data. The experience of managers grappling, sometimes unsuccessfully, with ever-increasing amounts of data and sophisticated analytics is often more the rule than the exception. In many respects, the hype surrounding the promise of analytics glosses over the hard work necessary to fulfill that promise. It is hard work to understand what data a company has, to monitor the many processes necessary to make data sufficient (accurate, timely, complete, accessible, reliable, consistent, relevant, and detailed), and to improve managers’ ability to use data. This unsexy side of analytics is where companies need to excel in order to maximize the value of their analytics initiatives, but it is also where many such efforts stall.

Moving past the hype takes a measure of resolve that few companies demonstrate. A 2015 survey of more than 2,000 managers conducted by MIT Sloan Management Review and SAS Institute — as well as more than a dozen interviews with executives at global companies — reveals insights about the unglamorous but necessary actions required to improve decision making with analytics.

Five key findings came from this research:

  • Competitive advantage with analytics is waning. The percentage of companies that report obtaining a competitive advantage with analytics has declined significantly over the past two years. Increased market adoption of analytics levels the playing field and makes it more difficult for companies to keep their edge.
About the Authors:

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 Idea initiative.

David Kiron is the executive editor of MIT Sloan Management Review.

Pamela Kirk Prentice is the chief research officer at SAS Institute Inc.


Michael Fitzgerald, contributing editor, MIT Sloan Management Review

Nina Kruschwitz, senior project manager, MIT Sloan Management Review


Steve Allan, head of analytics, Silicon Valley Bank

Gahl Berkooz, former head of data and governance, Ford Motor Company

Bin Lin, co-founder and president, Xiaomi

Joseph Bruhin, chief information officer, Constellation Brands

Jason Cooper, vice president and chief analytics officer, Horizon Blue Cross Blue Shield of New Jersey

Angela Galeziowski, vice president of sales strategic insights & planning, InterContinental Hotels Group

J. Michael Gaziano, MD, MPH, director of science, Massachusetts Veterans Epidemiology Research and Information Center, and a principal investigator for the Million Veteran Program

Greg Jones, vice president of enterprise data & analytics, Equifax

Dev Koushik, vice president of global revenue optimization, InterContinental Hotels Group

Adam Leary, lead data scientist and senior director of the data team, CBS Interactive

David Pahl, director of analytics, The Northwestern Mutual Life Insurance Company

Saiju Pyarajan, scientific director, GenISIS (Million Veteran Program)

Hugh Scandrett, vice president of engineering, EnerNOC

David Schmitt, director of global digital operations and analytics, InterContinental Hotels Group

Larry Seligman, vice president of global sales and marketing strategic analytics, InterContinental Hotels Group

Jim Sprigg, director of database marketing and analytics, InterContinental Hotels Group

James Taylor, CEO and principal consultant, Decision Management Solutions

To cite this report, please use: S. Ransbotham, D. Kiron, and P.K. Prentice, “Beyond the Hype: The Hard Work Behind Analytics Success,” MIT Sloan Management Review, March 2016

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1. See, for example, “The 11 Best Data Quotes,” July 8, 2012,; A. McAfee and E. Brynjolfsson, “Big Data: The Management Revolution,” Harvard Business Review 90 (October 2012): 60-68; and B. Marr, “Big Data-as-a-Service Is Next Big Thing,” April 27, 2015,

2. Several surveys conducted by other organizations point to dissatisfaction with results from big data technology, but general managers, who comprise the bulk of our respondents, remain enthusiastic about the potential of analytics. For a different point of view about satisfaction trends with data technology, see Q. Turner, “Data Digest: Big Data Disappointment, Stranded Data Scientists, and Locking Down Mobile Devices,” October 26, 2015,; and D. Henschen, “Big Data Meets Trough of Disillusionment: Gartner,” November 18, 2013,

3. We did find that senior managers, especially CEOs, were more optimistic about analytics compared to middle and nonmanagers.

4. General Electric, “What’s the Matter With Owen? — ‘Hammer’,” September 8, 2015,

5. R. Clough, “GE Forms Digital Unit to Expand $6 Billion Software Business,” September 14, 2015,

6. See S. Ransbotham, D. Kiron, and P.K. Prentice, “The Talent Dividend: Analytics Talent Is Driving Competitive Advantage,” MIT Sloan Management Review, April 2015,; and D. Kiron, P.K. Prentice, and R.B. Ferguson, “The Analytics Mandate,”

7. J. Ross, D. Kiron, and R.B. Ferguson, “Do You Need a Data Dictator?,” August 28, 2012,

8. “Gartner Identifies the Top 10 Strategic Technology Trends for 2015,” press release, October 8, 2014,

9. “High Performers in IT: Defined by Digital and Driving Growth,” 2013,

i. D. Kiron, P.K. Prentice, and R.B. Ferguson, “The Analytics Mandate,” MIT Sloan Management Review, May 2014,

ii. These groupings are based on respondents’ answers to two questions that use a five-point Likert scale: “To what extent is your organization getting a competitive advantage from analytics?,” and “To what extent is your organization innovating with analytics?” The Analytical Innovators group is comprised of respondents who gave a top score in both categories.

iii. “The Bank’s Strategic Plan — One Bank, One Mission,” n.d.,

3 Comments On: Beyond the Hype: The Hard Work Behind Analytics Success

  • Todd Roth | March 8, 2016

    As an IT leader working with large enterprises, I believe we are still only in the 2nd inning of harnessing actionable insights from Analytics and applying these insights to improve customer intimacy. Social and Mobile- combined with Cloud computing make Analytics a necessity for businesses whom wish to know their customers perspective. There’s also great promise with M2M and IoT sensor data that will create huge lakes of actionable data for the industrial sectors. In the realm of the internet- Big Data is still very promising.

  • sets man | March 9, 2016

    valuable information to digest -thanks MIT

  • Nik Zafri Abdul Majid | March 12, 2016

    There are so many reasons (quoting a few examples) why analytics and big data are becoming increasingly important to corporations.

    a) As I speak now, business applying analytics is giving whole different impression to the market compared to those who do not.

    b) Customer wants ‘things done’ at touch of their fingers and we providers thought that “the click of a button age” is there to stay.

    Customers, Clients, End-users are following the latest trends surprisingly surpassing the providers’ expectation. I predict the B2C will take over and trigger mobility explosion. B2B may become history if the direction is not change.

    Soon, business intelligence will also become an integral part of marketing. (know what to market, where and when to start)

    c) Human Resources MUST now become the frontliners – no more as an “independent function” or a “separate entity”. That’s where business will start and strategies can be made. Analytics ensures that companies identify and remove net asset value from the processes to optimize the business information flow.

    d) Be proactive and not reactive – there must be a model that will analyse the cause and effect of any decision taken. (which is the very reason why Risk Management is now important to proactively identified, analysed and controlled)

    e) All data must now be integrated (consolidated)– nothing should be missing from the core business process.

    f) Ready-Available Data – Real Time must be available for ease of access

    g) And the list goes on. (the Internet of Things for e.g. where it should be fitting)

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