The Analytics Mandate

As analytics becomes a common path to business value, many companies are changing how they make decisions, operate and strategize.

by: David Kiron, Pamela Kirk Prentice and Renee Boucher Ferguson
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Few know the thrill of victory using big data better than the U.S. statistician and writer Nate Silver. His accurate prediction of the 2012 U.S. presidential election results for all 50 states made him the toast of Washington, D.C., elevating him to the status of celebrity geek. Television host Jon Stewart of The Daily Show called him “Lord and god of the algorithm.”1 Indeed, Silver’s abilities to identify the right data sources, ask the right questions and apply the right math have turned Silver into gold.

Silver now spends much of his time talking data and managing a staff of analysts who immerse themselves in statistics and information. They discuss data and make predictions on Silver’s website,, about everything from basketball tournaments to job growth. Though their predictions are often interesting, if not always accurate, Silver and his team are under intense pressure to stay relevant — and right. How do you sustain your momentum when you’re only as good as your last prediction?

And so it goes with the new world order of big data and analytics. As more organizations make better use of data, the path to value with analytics is getting crowded — and longer. Many companies find they must reconsider and refresh not only their analytical insights, but also the organizational factors necessary to turn insight into advantage.

This report, based on a survey of 2,037 professionals and interviews with more than 30 executives, reveals the pressure companies are under to both improve their analytics capabilities and find unique and relevant insights in their data — to try to be as good as their last prediction every single day. (See “About the Research.”)

As more companies look to analytics to gain an advantage, achieving such gains is becoming more difficult. That is, as analytics becomes a more common path to value, the implications for industry competition are coming into focus.

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1. The Daily Show:, November 7, 2012.

2. Dan Vesset, Ashish Nadkarni, “Worldwide Business Analytics Technology and Services 2013–2017 Forecast,” IDC Report, December 2013.

3. There are several possible reasons for this backward movement. Organizations may be trying to do too much with data or the amount, variety or speed of the data could be overwhelming.

4. David Kiron, Pamela Kirk Prentice and Renee Boucher Ferguson, “From Value to Vision, Reimagining the Possible with Data and Analytics,” MIT Sloan Management Review, March 5, 2013,

5. NewVantage Partners, "Big Data Executive Survey 2013: The State of Big Data in the Large Corporate World," September 9, 2013. See also Renee Boucher Ferguson’s discussion of the survey in her blog,

6. Ibid.

7. Tim Catts, "GE’s Billion-dollar Bet on Big Data," Businessweek April 26, 2012. See:

8. Additional evidence of this trend can be found in Tata Consulting Services, "The Emerging Big Returns on Big Data," 2013. See:

9. Entravision’s story is discussed in more detail in an MIT Sloan Management Review case study called Luminar Insights. See

10. This example is discussed in more detail in David Kiron, Pamela Kirk Prentice and Renee Boucher Ferguson, “Raising the Bar with Analytics,” MIT Sloan Management Review, Winter 2014, pp. 29-33.

11. David Kiron, Pamela Kirk Prentice and Renee Boucher Ferguson, “Raising the Bar with Analytics,” MIT Sloan Management Review, Winter 2014, pp. 29-33. Quote is on p. 29.

12. Accenture: "Analytics Culture: The Secret to Success," 2011,

13. One exception is “Analytics: The Widening Divide: How Companies Are Achieving Competitive Advantage Through Analytics,” David Kiron, Rebecca Shockley, Nina Kruschwitz, Glenn Finch and Dr. Michael Haydock. MIT Sloan Management Review Research Report, Fall 2011.

14. Having an analytics culture does not require that all business questions addressed with analytics utilize in-house skills and technology. Analytics outsourcing is a growing trend that may be an option for certain business issues, whether companies have sophisticated or unsophisticated analytics capabilities. One limiting factor in these relationships, though, is outsourcing the analysis of strategically valuable data. A recent article on this topic in MIT Sloan Management Review quoted an analytics BPO manager: “We know we can add a lot more value to our customer’s analytics program if they came to us with a more strategic outsourcing arrangement, where we could be responsible for a certain aspect of their competitive analytics program that our capabilities have shown to be superior. If we suggest this to our customers, they usually become threatened, and this can put the overall relationship at risk.” From David Fogarty and Peter C. Bell, “Should You Outsource Analytics,” MIT Sloan Management Review, Winter 2014, pp. 41-45.

15. Renee Boucher Ferguson, “A Process of Continuous Innovation: Centralizing Analytics at Caesars,” July 30, 2013.

16. Adam Bryant, “Avinonoam Nowogrodski of Clarizen, on the Rewards of Listening,” New York Times, March 13, 2014,

17. This quote first appeared in David Kiron, Pamela Kirk Prentice and Renee Boucher Ferguson, “From Value to Vision, Reimagining the Possible with Data and Analytics,” MIT Sloan Management Review, March 5, 2013. Quote is on p. 5.

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Comment (1)
Peter Bonisch
Nate Silver's psephological work is of a commendably high standard. But there is a world of difference from electoral predictability to most business analysis. 'Big data' is a  buzzword for application of sensible questions to large data sets; no matter how big the data set, the utility is driven by the validity and applicability of the question, even before one begins to consider the provenance of the data. Most firms are a long way from formulating sensible questions with which do interrogate the data sets they have available. The problems remains interpretive, rather than analytical.