Analytics Culture: The Secret to Success

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Fostering a High-Performing Analytics Culture How do you get it done? What steps will help you progress along the path to analytic maturity? Three areas — leadership, breaking down silos, and developing and keeping talent — are fundamental to fostering an analytics culture. Leading from the top and the middle The single most important step you can take is to promote leaders with a passion for data analysis at every level. Leaders in the C-suite need to model appropriate behavior, but they do not own analytics in the organization. Every manager and leader in the middle ranks has to take responsibility for creating a more fact-based culture because through ownership comes commitment. It is also important for executives to take a hard, honest look at how in touch they are with the existing culture before they attempt to drive transformative change. On a recent Accenture survey, leaders in 400 organizations responded favorably to statements such as “This organization places a high value on collecting objective data to improve the quality of decision-making” and “In this organization, you get ahead based on merit and objectively demonstrated performance rather than political behavior.” In all but 2 of these 400 organizations, employees answered 4 these questions in a very different way from their leaders. 6 This is no less true for changes driven by analytic transformations. Having an accurate understanding of their organization’s readiness allows senior leadership to assess gaps and define a path forward to creating an analytics culture. And this effort, in turn, helps them to get in synch with each other regarding how analytics will be used to support their strategic vision — the value they want to gain. By translating that consensus down through the middle ranks, leaders can confer ownership of analytics to the appropriate people and thereby avoid what we call “the frozen middle.” Often an effective approach to achieving analytics goals is to recognize how factors play together. As Tom Anderson, CEO of Integrity Interactive, has said, “The beauty of analytics is that you find lots of things that can be incrementally improved. If it’s a multiplicate business, [like] medical finance, and you can improve each factor—the number of doctors times the number of patients times the percentage that seek financing—by 10 percent, it’s huge.” 7 Harrah’s took a similar approach by recognizing the role of a number of service delivery factors in a customer’s satisfaction. Tracking each of these factors, such as the time required to greet a customer or deliver a drink, allows them to be targeted separately if revenues slip. Breaking down silos Like unengaged leaders, organizational silos are quick killers of an analytics culture. Silos naturally develop as organizations grow. Analytics in the service of the enterprise, however, requires cross-functional collaboration — what one UK-based healthcare company calls “boundaryless” collaboration. To address this tension, organizations need processes to facilitate people working together from all parts of the organization. For example, they need to decide who will lead these cross-functional analytics efforts. And ask, “How do we help our people balance the interests of their unit versus the interest of the enterprise?”
Figure 1. Closed loop decision making process Performance monitoring Weekly forecast adjustment Monthly business review Questions on key metrics Quarterly health check Marketing Supply chain HR Manufacturing Finance Analytics center of excellence Core analytics Functional analytics Cross functional analytics Technology Enablers Bland packaged workbench Root cause analysis tools Statistical models optimization tools Insight generation Value realization Execution Insight validation The products of collaboration can then be applied in different parts of the organization. Procter & Gamble is an example of an analytics high performer that has established a central team to contribute to the bottom line in a variety of disciplines. This team, called Global Analytics, tackles challenges such as manufacturing site location, inventory management, supply chain design, and strategic decision making. 8 Creating a single repeatable process for integrating analytics into everyday work would be a powerful way to counteract the rigidity of “silo-think.” A closed loop decision making process such as that shown in Figure 1 defines how data is leveraged to test hypotheses and support decisions anywhere in the enterprise. Recent Accenture research shows that only one in five companies currently has such a repeatable process in place. 9 Breaking down silos also facilitates the collaboration required to stay ahead of the competition. For example, as a strategic partner rather than an order taker, IT can help business units access the quality data needed to forecast more accurately, price more appropriately, and tailor offerings to customers or citizens more effectively. Just as important is evaluating how other companies, even in different industries, are using analytics. Agile organizations know they don’t have to do all the analytics heavy lifting themselves — there is a global analytics community brimming with experts, peer discussions, and case studies. Selecting, motivating, and retaining talent A smattering of quants around an organization is not an analytics culture. Upskilling the workforce in analytic capabilities is quickly becoming essential just to keep pace with market. As Tom Anderson has said, “You have to become a teacher. Some people already have the problem-solving capabilities, and you have to teach them the math. Others know the math, but don’t know how to apply it to business problems.” 10 Training workers in IT skills has consumed the organization’s training departments in the past; the next 20 years will be about integrating analytics into everyday work. The bar is also rising for new hires. One financial services company, for example, requires all potential employees, including senior executives, to take a series of tests to determine analytical and financial aptitude. One successful hire joked that he might have been “the only HR guy who could pass their math test.” 11 Analyzing the talent in the organization is as important as hiring talent with a passion for analytics. This application of analytics can provide a clear advantage to companies that use customer satisfaction as their differentiator. Harrah’s, for example, analyzes the effects of its health and wellness programs on employee engagement. In this way, the company showed that a rise in preventative care visits to its on-site clinics resulted in an annual decrease (by millions of dollars) in urgent-care costs. 12 5
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Page 7 and 8: References 1 Dave Rich, Brian McCar

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