This is part 4 of 10 from the 2013 Data & Analytics Global Executive Study and Research Project.

You don’t have to lead the analytics revolution to create value from analytics. This past year, two-thirds of our survey respondents said they are gaining a competitive advantage from their use of analytics. (See Figure 1: Finding Competitive Advantage with Analytics.) This represents a significant jump from our 2011 Global Executive Survey (58%) and an even larger jump from the 2010 survey (37%). Other research supports this trend.11

Figure 1: Finding Competitive Advantage with Analytics

View Exhibit

The percentage of companies that create a competitive advantage with analytics is trending upwards.

Companies that gain a competitive edge with analytics can be found at all levels of technological sophistication. At one end are traditional companies like Illinois-based Oberweis Dairy, which have older technologies but add new analytics talent. (See the case study.) At the other end are companies like LinkedIn, which include analytics as part of their corporate DNA but still find new ways to capitalize on analytic insights.

In 2006, LinkedIn had 8 million users, but something wasn’t clicking: Users weren’t seeking connections, a key component of success, at the expected rate. Reid Hoffman, the company’s cofounder (and current executive chairman), brought in Jonathan Goldman, who has a background in physics, to test different ways to encourage members to link to one another. Goldman came up with the algorithm that would become the “People You May Know” function on LinkedIn’s homepage — arguably one of the site’s key user benefits today.12

Because the product team initially did not see value in the algorithm, Hoffman suggested Goldman run a test on LinkedIn pages in the form of an advertisement: “Find out what happened to your former colleagues or classmates.” The result was a staggering 30% click-through rate in an industry that views click-through rates of 1% to 3% as a success. LinkedIn raced ahead of its competitors.

Some of the more traditional companies struggling in mature industries are increasingly turning to analytics for insights that provide an edge. A case in point is in the pharmaceutical sector, where companies have found themselves challenged by their payers, the largest managed-care customers or governments.

For example, AstraZeneca Group found that its payers were combining data from the pharmaceutical giant’s clinical trials with proprietary data to conduct comparative-effectiveness studies. Payers, in effect, knew more about AstraZeneca’s drug performance data in some situations than AstraZeneca itself did. This gave them a distinct advantage in negotiating payments. It also made it difficult for AstraZeneca to get its drugs represented on national and country formularies, the all important drug approval lists from which physicians prescribe medications. How did AstraZeneca respond to this competitive disadvantage? It built up its own analytics program, partnering with IMS Health in Europe and U.S.-based HealthCore, a clinical outcomes research subsidiary of health insurer WellPoint Inc. The partnerships have become a crucial tool in AstraZeneca’s negotiations with payers.

In some markets, once a company finds a unique way to use data to gain an advantage, competitors quickly jump on the bandwagon and level the playing field. Simply obtaining an advantage from analytics is not enough in these cases; insights must be revitalized again and again to sustain a competitive edge.

The story of the Oakland Athletics offers a telling example. In 2002, despite being handicapped with the most significant salary constraint in Major League Baseball, Oakland A’s general manager Billy Beane built a winning team through an innovative use of analytics. He bucked conventional wisdom and began looking at previously ignored player statistics. This story — popularized in Michael Lewis’s book Moneyball: The Art of Winning an Unfair Game and the movie starring Brad Pitt — ends on a happy note, with the A’s winning their division and going to the playoffs.13

But over time, other teams copied Beane’s methods, and the A’s lost the competitive edge they had initially gained with analytics. It was only after team management created new analytical metrics that the A’s returned to the playoffs in 2012, after a five-year hiatus.14 The moral: Organizations need to find new ways to apply analytics to refashion the advantage they gain from data.

Analytics is not just about generating insights and getting those insights to the right people. To sustain the long-term success of data-driven innovation, it is necessary to continually revise one’s analytical approach in order to generate insights that lead to new innovation and competitive advantage.


1.The New Initiative on the Digital Economy,” press release, MIT Sloan School of Management, n.d.

2. P.C. Evans and M. Annunziata, “Industrial Internet: Pushing the Boundaries of Minds and Machines,” GE Reports, November 26, 2012.

3. Evans, “Industrial Internet.”

4. R. Bean and D. Kiron, “Organizational Alignment Is Key to Big Data Success,” January 28, 2013.

5.Governor Patrick Announces New Initiative to Strengthen Massachusetts’ Position as a World Leader in Big Data,” press release, Commonwealth of Massachusetts, May 30, 2012.

6. ”Governor Patrick Announces New Initiative.”

7. A. Pentland, “Reinventing Society in the Wake of Big Data,” August 30, 2012.

8. Tweeted by Joel Cherkis on 10/21/12.

9. J. Manyika, M. Chui, et. al, “Big Data: The Next Frontier for Innovation, Competition and Productivity,” May 2011.

10. Capgemini Consulting and MIT Center for Digital Business, “The Digital Advantage: How Digital Leaders Outperform Their Peers in Every Industry,” November 5, 2012.

11. E. Brynjolfsson and A. McAfee,“Big Data, The Management Revolution,” Harvard Business Review 90 (October 2012): 61-67.

12. T.H. Davenport and J.G. Harris, “Competing on Analytics: The New Science of Winning” (Cambridge, MA: Harvard Business School Press, 2007).

13. M. Lewis, “Moneyball: The Art of Winning an Unfair Game” (New York: W.W. Norton, 2004).

14. L. Melnick, "Moneyball Strikes Again: How to Use Analytics for Sustained Competitive Advantage,” October 3, 2012.

15. The two questions were:

(a) To what extent does information and business analytics create a competitive advantage for your organization within its industry or markets?

(b) To what extent do you agree with the following statement? Analytics has helped improve my organization’s ability to innovate.

Managers that checked “great extent” for both questions were placed in the Analytical Innovators category.

16. T.H. Davenport and D.J. Patil, “Data Scientist: The Sexiest Job of the 21st Century,” Harvard Business Review 90 (October 2012): 70-76.

17. “Chief Consumer Advocate: How Social Data Elevates CMOs,” white paper, Bazaarvoice and the CMO Club, Austin, TX, July 25, 2012.

18. Respondents in Analytically Challenged companies differ demographically in subtle but important ways from other survey participants. They tend to be in less senior management positions and have a slightly higher likelihood than other survey participants to work in operational functions. These demographic differences might be a contributing factor to their evaluations of their organizations as less analytically mature.

19. The prisoner’s dilemma refers to a non-zero-sum game that shows why two people may choose to betray each other even if cooperation is in their best interest. It’s based on the premise that two isolated prisoners involved in the same crime have the independent opportunity to either collaborate with each other by remaining silent or sell the other prisoner out. Each combination of possibilities results in a different outcome, with the best for both stemming from cooperation. The sucker’s side is the prisoner who remains silent but is betrayed by the other prisoner.

i. K.T. Greenfeld, “Loveman Plays ‘Purely Empirical’ Game as Harrah’s CEO,” August 6, 2010.