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
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.