At one consumer-facing company, analytics expertise and leadership were concentrated in the finance and risk-management team, which historically had accounted for significant data-related value creation. When the company began pursuing a more aggressive analytics strategy, the CFO took responsibility for several tasks, including defining the basic strategy, overseeing make-versus-buy decisions for the core risk-management analytics tools, mobilizing resources within the function’s analytics team and building expertise.
However, having made these primary decisions about analytics, the CEO and CFO soon realized that significant complementary efforts were needed to secure better data for the analytics team and to reinforce change efforts and revamp several processes across the business units. To lead these initiatives, they established a new position — chief data officer — within the CFO’s organization. This CDO proactively manages information, working with business managers to identify both internal and external data they may not even realize exists. Delivered ready for analysis, the data can be applied rapidly to needed tasks by modeling experts and, just as important, continually refreshed for new experiments and broader application. Many companies may find they need this type of leadership to support business leaders as they identify sources of data-driven advantages, work through analytics priorities, and try to accelerate frontline adoption.
When managing scale and complexity within business units is paramount
Whether elements of the effort are managed centrally or not, much of the data-analytics heavy lifting will fall on business or functional leaders within individual business units. A core question at the business-unit level is whether to add a new role or ask a key functional leader (such as the CMO or the head of operations) to add new responsibilities to what in all likelihood is already a pretty full plate.
When the senior leaders of a large financial-services company took a wide-ranging look at its strategy, they decided that one business unit could gain a significant competitive edge if it doubled down on data analytics. To push the strategy ahead decisively, the company recruited a chief analytics officer, who reports to the business-line president and oversees a new center of excellence drawing on internal consultants, analytics modelers, and software programmers.
This approach, which represents a significant organizational change, is accelerating the business unit’s data-transformation effort. As a top-team member, the CAO can drive a broad range of decisions, from setting analytics strategy to defining the responsibilities of frontline managers. Since the center of excellence spans multiple disciplines, the CAO can mobilize analytics and software-programming resources swiftly, which has sped up the creation of frontline tools. Meantime, operating from within the business unit has given him a deeper understanding of what makes it tick — its priorities, patterns of working, and ongoing challenges. This has paid off in sharper decisions about which tools to develop and a keener sense of the skills that training programs need to foster. The fact that the business unit’s leaders are engaged with the CAO on a day-to-day basis helps keep them focused on their analytics and adoption agendas.
Building on this success, the company has recently taken the further step of adding another new role, a chief data officer, who reports to the CIO but works daily with the chief analytics officer to help knit together data and new analytics tools and to speed frontline change.
For companies pursuing the potential of data analytics, a decision about leadership capacity looms — regardless of where in the end they decide to place it. For some, such as the consumer-facing companies described earlier, current top-team members will be asked to step up and assume broader leadership responsibilities, often with additional support from new, senior lieutenants. For others, such as the financial-services company we explored, establishing one or more new senior posts to drive the analytics agenda will be the best solution.
At all companies, top teams, and probably board members as well, need a better understanding of the scale of what’s needed to ensure data-analytics success. Then they must notch these responsibilities against their existing management capacity in a way that’s sensitive to the organization’s core sources of value and that meshes with existing structures. None of this is easy, but it’s the only serious way to pursue data analytics as a new frontier for growth.
Brad Brown is a director in McKinsey’s New York office, David Court is a director in the Dallas office, and Paul Willmott is a director in the London office.
This article was originally published by McKinsey Quartlery. Copyright © McKinsey & Company. All rights reserved. Reprinted by permission.