Big data and analytics: Go big or go home

As Big Data continues to grow, the related opportunity to obtain a competitive advantage grows with it. By now, we have all heard about companies that have confidently moved forward, attempting big things around Big Data and reaping big benefits as a result.

How are they doing it? Simply put, with a company-wide commitment that starts at the top, and by using Big Data and analytics to drive innovation and growth. These analytics leaders are using data in predictive (e.g., optimization, simulations) and anticipatory (e.g., segmentation analysis, sensitivity analysis) ways to power themselves into the future.

This article discusses the manner in which analytics-savvy companies are achieving competitive advantage using Big Data, which was among the key findings of the first-ever Leadership Excellence in Analytic Practices (LEAP) study by A.T. Kearney and Carnegie Mellon University.


Taking the LeapThe LEAP study surveyed 430 companies around the world from a wide range of industries. Based on the maturity of their analytic competency and their ability to employ analytics to impact their business results, respondents were clustered into four populations: leaders (10 per cent), explorers (32 per cent), followers (38 per cent) and laggards (20 per cent). To date, only the leaders have attained the level of analytic competency needed to significantly impact business results.

Five themes and associated leadership practices emerged during the study team’s analysis:

  • Sponsorship: Leaders deploy executive-level “champion-practitioners” to carve out analytics mindshare throughout the organization. Two-thirds of LEAP study participants identified executive sponsorship as critical to creating enterprise mindshare for analytics.
  • Enterprise value: Leaders use predictive analytics to fuel innovation and growth, driving profitability and increasing operational effectiveness.
  • Mobilization: Leaders are more likely to use pilots and rapid proof-of-concept deployment to create traction by capturing value faster. Even though 26 per cent of laggards are emphasizing technology above all else when making their analytics start-up investments (vs. 21 per cent of leaders), 34 per cent of leaders are making their largest investments in pilot efforts (vs. 13 per cent of laggards) and 36 per cent are investing in efforts that drive repeatability (vs. eight per cent of laggards).
  • Technology enablement: Leaders take a balanced approach to building their advanced analytics technology footprint. Consider that three per cent of leaders and 48 per cent of laggards report that they are taking a “wait and see” approach to their big data and advanced analytics technology strategy, while 23 per cent of the leaders and 27 per cent of the laggards are attempting to develop a “best in breed” technology footprint. The vast majority of leaders – 74 per cent – are  opting instead to upgrade their existing technology stack through models that provide the flexibility to support rapid experimentation and innovation.
  • Talent empowerment: Leaders co-create and collaborate across data and decision-making siloes to drive the development of a culture of analytics-based decisions. In building their analytics culture, 51 per cent of leaders say that they are fostering cross-functional collaboration and co-creation, 46 per cent are working to enhance their capabilities and 41 per cent are striving to increase confidence in the value of analytics.

The first two themes—sponsorship and enterprise value—are especially salient in differentiating those that are mastering big data and analytics practices, as they speak to the importance of strategy versus more tactical approaches.

Successfully managing Big Data and analytics is not really about having the right technology, operating model or people. Instead, it’s about tying these three critical aspects together to create a culture anchored around differentiated analytics. It starts with executive sponsorship and extends outward to finding new ways to apply analytics to growth-oriented strategies.


Executive sponsorship is critical to developing enterprise enthusiasm for analytics. As seen in Figure 1, leaders are finding champions at the very top of the organization, such as the chief operating officer, chief financial officer or chief marketing officer. (Efforts at laggard companies are more typically headed by the IT chief or business lines.) At analytics-savvy companies, champions typically create demand for these services within their organizations in addition to promoting them elsewhere in the business.

Just a few short years ago, the CEO of a key business line at one leading financial institution committed to analytics in a big way by hiring a chief science officer and providing him with the necessary funds to begin utilizing the extensive data the company owned. For this company, a shift of a single basis point or two would bring significant benefits. The science team provided its services at no charge to provide a low-risk, no-cost way for the business to tap into its capabilities. In one instance, the team rationalized the company’s $1 billion in annual legal spend by building an understanding of law firms that brought the best results in matters and instituting a deep, data-driven performance tracking process. While the company’s on-ramp to analytics was accelerated through its CEO sponsorship and budget, its initial successes clearly demonstrate the value that these efforts can bring.


Leaders have developed the capabilities to succeed in their analytics efforts. Indeed, while laggards remain focused on applying data for reporting, leaders are using analytics to evaluate risks and tradeoffs, understand cost and revenue drivers, and predict trends to help drive business performance and innovation. Leaders are driving the innovation agenda through analytics to create value, as shown in Figure 2. Executives have always needed to have a forward view of their business and analytics provides them with a vehicle to develop a more comprehensive and informed view of what could impact their business.

Tremendous value can be tapped through analytics by creating new products, services and business opportunities and reducing friction throughout the business and supply chain. Armed with data around materials and parts, U.S. automakers are dropping the traditional six- to 12-month product innovation cycle down to mere weeks through powerful new simulations. Leading retailers are using analytics to ensure that delivery time, product pricing and store layouts are perfectly planned and executed across the whole chain. They also continue to address the challenge of combining targeted customer marketing with pricing and advertising to optimize the sales process.


The growth, range and speed of data hold tremendous promise for transforming management models and the ways in which organizations make decisions. But doing so will require mobilizing the organization to tap into the potential value that data offers. Data and decision making can no longer reside in their own siloes; the former must inform the latter in order to unlock competitive advantage.

Analytics brings change and executives accustomed to “going with their gut” are likely to resist this change, because they are unaccustomed to working with probabilities generated from a predictive model. But this change is inevitable. Keep in mind that only four per cent of LEAP study participants dismiss analytics as a “passing fad.” Successful enterprises will seize the Big Data opportunity by advancing their cultures to drive an enterprise-wide analytic operating model that places data science at the centre of their business strategy and management practices.