Mobilizing your C-suite for big-data analytics

Mobilizing your C-suite for big-data analytics

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.

Over the past 30 years, most companies have added new C-level roles in response to changing business environments. The chief financial officer (CFO) role, which didn’t exist at a majority of companies in the mid-1980s, rose to prominence as pressures for value management and more transparent investor relations gained traction. Adding a chief marketing officer (CMO) became crucial as new channels and media raised the complexity of brand building and customer engagement. Chief strategy officers (CSOs) joined top teams to help companies address increasingly complex and fast-changing global markets.

Today, the power of data and analytics is profoundly altering the business landscape, and once again companies may need more top-management muscle. Capturing data-related opportunities to improve revenues, boost productivity, and, sometimes, create entirely new businesses puts new demands on companies—requiring not only new talent and investments in information infrastructure but also significant changes in mind-sets and frontline training. It’s becoming apparent that without extra executive horsepower, stoking the momentum of data analytics will be difficult for many organizations.

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Because the new horizons available to companies typically span a wide range of functions, including marketing, risk, and operations, the C-suite can evolve in a variety of ways. In some cases, the solution will be to enhance the mandate of the chief information, marketing, strategy, or risk officer. Other companies may need new roles, such as a chief data officer, chief technical officer, or chief analytics officer, to head up centers of analytics excellence. This article seeks to clarify the most important tasks for executives playing those roles and then sets out some critical questions whose answers will inform any reconfiguration of the C-suite. Daunting as it may seem to rethink top-management roles and responsibilities, failing to do so, given the cross-cutting nature of many data-related opportunities, could well mean jeopardizing top- or bottom-line growth and opening the door to new competitors.

Crafting and implementing a big-data and advanced-analytics strategy demands much more than serving up data to an external provider to mine for hidden trends. Rather, it’s about effecting widespread change in the way a company does its day-to-day business. The often-transformative nature of that change places serious demands on the top team. There’s no substitute for experienced hands who can apply institutional knowledge, navigate organizational hazards, make tough trade-offs, provide authority when decision rights conflict, and signal that the leadership is committed to a new analytics culture. In our experience, the concerted action that’s required falls into six categories. Leaders should take full measure of them before assigning responsibilities or creating roles.

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Senior teams embarking on this journey need both to acquire a knowledge of data analytics so they can understand what’s rapidly becoming feasible and to embrace the idea that data should be core to their business. Only when that top-level perspective is in place can durable behavioral changes radiate through the organization. An important question to ask at the outset is “Where could data analytics deliver quantum leaps in performance?” This exercise should take place within each significant business unit and functional organization and be led by a senior executive with the influence and authority to inspire action.

Leaders at one large transportation company asked its chief strategy officer to take charge of data analytics. To stretch the thinking and boost the knowledge of top managers, the CSO arranged visits to big data-savvy companies.

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