The radically diverging paths different retailers have chosen underscore the range of options leaders must weigh. Several retailers and analytics firms have established long-term contracts covering a broad sweep of analytics needs. Other large players, both brick-and-mortar and online, have invested in deep internal data and analytics expertise. Each of these choices reflects a dynamic set of strategic, financial, and organizational requirements that shouldn’t be left to middle management.
Securing analytics expertise
Under almost any strategic scenario, organizations will need more analytics experts who can thrive amid rapid change. The data-analytics game today is played on an open and (frequently) cloud-based infrastructure that makes it possible to combine new external and internal data readily and in user-friendly fashion. The new environment also requires management skills to engage growing numbers of deep statistical experts who create the predictive or optimization models that will underwrite growth.
The hunt for such talent is taking place in what has become the world’s hottest market for advanced skills. Retaining these valued employees and then getting them to connect with business leaders to make a real difference is a true top-management task — one that often demands creative solutions. The leader of a big-data campaign at a major consumer company, for instance, decided to invest in an analytics unit distant from company headquarters. This other locale had abundant talent and a cultural environment preferred by data scientists and engineers. The leader then closed the loop, ensuring that each unit of the analytics team had a direct connection to a business-unit team at the company.
Companies often are surprised by the arduous management effort involved in mobilizing human and capital resources across many functions and businesses to create new decision-support tools and help frontline managers exploit advanced analytics models. An empowered senior player is vital to breaking down the institutional barriers that frequently hamper efforts to supercharge decisions through data analytics. Success requires getting a diverse group of managers to coalesce around change—encouraging alignment across a wide phalanx of IT, business-lines, analytics, and training experts. The possibility of failure is high when companies don’t commit leadership.
Take the example of a second transportation company, where middle managers across product areas were tasked with identifying data-analytics opportunities and then pushing them forward. The analytics managers were routinely frustrated when data teams failed to deliver data on schedule or in usable formats. When it came time to embed the resulting analytics into customized tools, managers faced additional frustrations as urgent requests worked their way through routine budgeting and planning processes. The company gave the task of stepping up the pace of its analytics agenda to a top marketing and sales executive, who assembled cross-functional teams including database managers, analysts, and software programmers. The teams rotated across analytics opportunities, steering them from launch to implementation in six- to eight-week bursts. Through this rapid mobilization, the company checked off several analytics priorities only months after the marketing leader took charge.