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Mobilizing Your C-Suite for Big Data Analytics 14 Jacopo Rosati Mobilizing your C-suite for big data analytics Leadership-capacity constraints are undermining many companies’ efforts. New management structures, roles, and divisions of labor can all be part of the solution. Brad Brown, Over the past 30 years, most companies entirely new businesses puts new demands David Court, and have added new C-level roles in response on companies—requiring not only new talent Paul Willmott to changing business environments. The and investments in information infrastructure CFO role, which didn’t exist at a majority of but also significant changes in mind-sets and companies in the mid-1980s, rose to promi- frontline training.2 It’s becoming apparent nence as pressures for value management that without extra executive horsepower, and more transparent investor relations stoking the momentum of data analytics gained traction.1 Adding a chief marketing will be difficult for many organizations. officer (CMO) became crucial as new channels and media raised the complexity of brand Because the new horizons available to 1 For more on the rise of the building and customer engagement. Chief companies typically span a wide range of CFO role, see Dirk Zorn, “Here a chief, there a chief: strategy officers (CSOs) joined top teams to functions, including marketing, risk, and The rise of the CFO in the American firm,” American help companies address increasingly complex operations, the C-suite can evolve in a variety Sociological Review, 2004, and fast-changing global markets. of ways. In some cases, the solution will be to Volume 69, Number 3, pp. 345–64. enhance the mandate of the chief information, 2 Dominic Barton and David Today, the power of data and analytics is marketing, strategy, or risk officer. Other Court, “Making advanced analytics work for you,” profoundly altering the business landscape, companies may need new roles, such as a Harvard Business Review, and once again companies may need more chief data officer (CDO), chief technical officer, October 2012, Volume 90, Number 10, pp. 79–83, hbr.org; top-management muscle. Capturing data- or chief analytics officer (CAO), to head up “Putting big data and analytics related opportunities to improve revenues, centers of analytics excellence. This article to work,” September 2012, mckinsey.com. boost productivity, and, sometimes, create seeks to clarify the most important tasks for 15 Takeaways As data and analytics transform the business landscape, they place a range of new demands on top teams, which often lack the management capacity to respond. executives playing those roles and then sets radiate through the organization. An impor- Without sufficient senior out some critical questions whose answers tant question to ask at the outset is “Where leadership, it’s difficult to will inform any reconfiguration of the C-suite. could data analytics deliver quantum leaps catalyze the widespread Daunting as it may seem to rethink top- in performance?” This exercise should take organizational change management roles and responsibilities, failing place within each significant business unit needed to capture data- analytics opportunities. to do so—given the cross-cutting nature of and functional organization and be led by a many data-related opportunities—could well senior executive with the influence and The biggest leadership gaps span six areas. mean jeopardizing top- or bottom-line growth authority to inspire action. Companies should decide and opening the door to new competitors. how to fill them by assess- Leaders at one large transportation company ing the importance of asked the chief strategy officer to take charge centralized databases and analytics resources, Six top-team tasks of data analytics. To stretch the thinking as well as the ability of behind data analytics and boost the knowledge of top managers, business-unit leaders to the CSO arranged visits to big data-savvy drive frontline change. Crafting and implementing a big data and companies. Then he asked each business advanced analytics strategy demands much unit to build data-analytics priorities into more than serving up data to an external its strategic plan for the coming year. That provider to mine for hidden trends. Rather, process created a high-profile milestone it’s about effecting widespread change in related to setting real business goals and the way a company does its day-to-day busi- captured the attention of the business units’ ness. The often-transformative nature of that executives. Before long, they were openly change places serious demands on the top sharing and exploring ideas and probing for team. There’s no substitute for experienced new analytics opportunities—all of which hands who can apply institutional knowledge, helped energize their organizations. navigate organizational hazards, make tough trade-offs, provide authority when decision Defining a data-analytics strategy rights conflict, and signal that the leadership is committed to a new analytics culture. In Like any new business opportunity, data our experience, the concerted action that’s analytics will underdeliver on its potential required falls into six categories. Leaders without a clear strategy and well-articulated should take full measure of them before initiatives and benchmarks for success. assigning responsibilities or creating roles. Many companies falter in this area, either because no one on the top team is explicitly Establishing new mind-sets charged with drafting a plan or because there isn’t enough discussion or time devoted Senior teams embarking on this journey to getting alignment on priorities. At one need to both acquire a knowledge of data telecommunications company, the CEO was analytics so they can understand what’s keen to move ahead with data analytics, rapidly becoming feasible and embrace the particularly to improve insights into customer idea that data should be core to their busi- retention and pricing. Although the company ness. Only when that top-level perspective moved with alacrity to hire a senior analytics is in place can durable behavioral changes leader, the effort stalled just as quickly. To be 16 McKinsey on Business Technology Number 33, Spring 2014 Capturing the potential of data analytics requires a clear plan that establishes priorities and well-defined pathways to business results. sure, the analytics team did its part, diving and tools designed to improve performance. into modeling and analysis. However, The resource demands often are considerable. business-unit colleagues were slow to With multitudes of external vendors now train their midlevel managers in how to able to provide core data, models, and tools, use the new models: they didn’t see the top-management experience is needed to potential, which, frankly, wasn’t part of work through “build versus buy” trade-offs. their strategic priorities. Do strategic imperatives and expected performance improvements justify the As we have argued previously,3 capturing in-house development and ownership of fully the potential of data analytics requires a customized intellectual property in analytics? clear plan that establishes priorities and Or is reaching scale quickly so important that well-defined pathways to business results, the experience and talent of vendors should much as the familiar strategic-planning be brought to bear? The creation of powerful process does. Developing that plan requires data assets also can require the participation leadership. At a North American consumer of senior leadership. Locking in access to company, the CEO asked the head of online valuable external data, for instance, may and digital operations, an executive with deep depend on forging high-level partnerships data knowledge, to create the company’s plan. with customers, suppliers, or other players The CEO further insisted that it be created along the value chain. in partnership with a business-unit leader who was not familiar with big data. This The radically diverging paths different partnership—combining a data and analytics retailers have chosen underscore the range expert and an experienced frontline change of options leaders must weigh. Several operator—ensured that the analytics goals retailers and analytics firms have established outlined in the plan were focused on actual, long-term contracts covering a broad sweep high-impact business decisions. Moreover, of analytics needs. Other large players, after these executives shared their progress both brick-and-mortar and online, have with top-team counterparts, their collabo- invested in deep internal data and analytics rative model became a blueprint for the expertise. Each of these choices reflects planning efforts of other business units. a dynamic set of strategic, financial, and organizational requirements that shouldn’t Determining what to build, be left to middle management. purchase, borrow, or rent Securing analytics expertise Another cluster of decisions that calls for 3 Stefan Biesdorf, David Court, and Paul Willmott, “Big data: the authority and experience of a senior Under almost any strategic scenario, orga- What’s your plan?,” McKinsey leader involves the assembly of data and the nizations will need more analytics experts Quarterly, March 2013, mckinsey.com. construction of advanced analytics models who can thrive amid rapid change. The Mobilizing your C-suite for big data analytics 17 data-analytics game today is played on business lines, analytics, and training experts. an open and frequently cloud-based infra- The possibility of failure is high when compa-
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