The difference between first place and the rest can be a matter of tiny increments. But achieving that narrow winning margin masks a huge amount of preparatory activity behind the scenes. And, increasingly, one key member of the support team is the data analyst.
Sports teams have long collected large amounts of data. But advances in the way that data can be analyzed mean that the focus is no longer on simply amassing volumes of performance-related information. Attention has switched to how the data can be mined to improve performance and achieve winning outcomes. It is now critical to identify the metrics that matter.
For instance, raw data about how far a soccer player ran during the course of a game used to be seen as a key measure of performance. Now, however, analytics have shown that a player’s ability to reach top speed quickly and consistently is a better determinant of success.
Another example of how data and analytics can extend across the breadth of a sporting endeavor is the British sailing team, Skandia Team GBR. The team enjoyed considerable success in the London 2012 Olympics, winning five gold medals. Along with collecting the data required to monitor their athletes’ and competitors’ performance, everything about the team’s entire operation, encompassing 80 sailors and 50 support staff, was fed into a performance management system. Information spanning everything from athletes’ gym sessions to finance and HR was used to generate KPIs needed to assess sporting achievements, optimize operations and create reports for funding bodies.
As perhaps most notable example, Major League Baseball was one of the first sports organizations to leverage analytics to powerful effect. The Oakland A’s had had a relatively undistinguished post-war record. That changed decisively when the team turned to analytics. A radical new approach to statistical analysis of players’ performance enabled the team to recruit players who had been overlooked by competitors. By 2002, this strategy powered them to what was, at that point, the longest consecutive run of wins in major league history.
Given results like these, it’s little surprise that competition amongst sports teams for skilled analysts is reaching a similar intensity to the battle for top athletic talent. And it’s a development that is mirrored in the business world. Just as sports teams have been able to use analytics to focus on previously overlooked attributes, businesses are increasingly deploying analytics talent to help them sharpen their focus on what really drives performance.
It’s the right solution at the right time. With the huge surge of data now available to businesses, understanding the measures that make a real difference to performance has never been more important – or more challenging. And one thing’s for certain: The scale of opportunity, and challenge, is rising all the time. IDC estimates that between 2005 and 2010 the amount of data increased ten-fold. But that pales against predictions for future growth. Reported earlier this year in Forbes magazine, Cisco sees annual Internet traffic reaching 1.3 zettabytes by 2016, 10 times more than all the data ever generated, as recently as 2008.
In such a data-rich world, analytics can be used to drive game-changing business value and create lasting competitive advantage. One car manufacturer, for example, embedded an analytics culture across its entire business, from manufacturing to sales. As a result, its ability to spot and track changes in customer attitudes enabled it to create a sales program that directly addressed changes in consumer sentiment following the financial crisis.
Other businesses that use analytics make surprising – and even counterintuitive – discoveries that can have a big impact on strategy. For example, one company decided to withdraw a high-priced item that was not selling well, but it discovers that overall sales drop following the decision. Analysis reveals that the mere presence of the higher priced item attracted a large number of customers who then proceeded to buy that company’s lower-priced goods. Analytics justifies the continued inclusion of the high price item in the range.
Scenarios like this highlight the need to go beyond face-value readings of available information. Subjecting data to more rigorous analysis and comparisons through analytic methods and techniques often delivers surprising results that suggest different but far more productive strategies.
Analytics showed that the soccer player who runs fastest more often is likely to be a greater asset than the one who simply runs farthest. Businesses need to make sure that they can discover similar performance enhancing insights that will enable them to outperform their competition. To do that, they need to take a number of decisive steps.
The first is the willingness to invest in analytics talent. That means developing core analytics skills at all levels within the organization and encouraging the development of an analytics culture with a deep respect for data and fact-based decisions.
Organizations also need to ensure that they collect the right data and make it available when and where it is needed. That means ensuring that barriers to data flow are dismantled; analytical organizations are marked by a high degree of collaboration and information sharing.
And thirdly, just as in sports, leadership is critical. Leaders need to set the example, allowing the data to identify what really makes a difference, by constantly asking their teams what the data tells them, acting on the answers and encouraging the rest of their team to do the same.
Narendra Mulani is the managing director of Accenture Analytics. Leading an integrated community of more than 15,000 management consulting, technology and outsourcing professionals who serve clients around the globe, he is responsible for driving Accentures strategic agenda for growth across business analytics. Mulani is a member of Accentures Global Leadership team. He graduated from Bombay University in 1978 with a Bachelor of Commerce. He received an MBA in finance in 1982 and a Ph.D. in multivariate statistics in 1985, both from the University of Massachusetts. Prior to joining Accenture, Mulani ran his own consulting company.