Accenture Outlook, Jun 2010
Your company maybe sitting on data gold mines buried among its most basic operations that could help you out perform the competition.
Britain's Royal Shakespeare Company used an examination of seven years' worth of ticket sales data to sell more to existing customers and identify new audiences. Using analytics to look at names, addresses, performances attended and prices paid for tickets, the company developed a marketing program that increased the number of regular attendees at its showcase Stratford-upon-Avon location by more than 70 percent.
Other companies like Netflix, Capital One, Amazon.com, Tesco and Progressive Casualty Insurance Co. have gone even further. They have learned how to use data and sophisticated quantitative models as strategic tools in their efforts to achieve high performance.
But not every company has the ability or desire to put analytics at the heart of its strategy.
After more than a decade of research looking at hundreds of companies and talking with scores of executives, Accenture uses a five-step model called DELTA (data, enterprise, leadership, targets and analysts) that addresses the essential requirements for the successful use of analytics through a series of questions.
1. Data: What’s unique about my data? Few companies realize there is special value in the data they collect since it’s normally the by-product of efforts to reach another business goal. So recognize the uniqueness of your data and put it to work. Think creatively, which probably means capturing some new data and creating new performance metrics.
2. Enterprise: To take advantage of analytics, how much integration is needed throughout the enterprise? Though an enterprise wide focus is essential to the effective use of analytics the vast majority of organizations think of it as an exception rather than the rule. It’s a major challenge to integrate data, analyses and processes in a diverse and far-flung company, with different types of customers and products, operating in a variety of markets and a volatile economic environment. A company that is committed to helping its customers and suppliers make better decisions will share not only data, but also analytics and analytical expertise, to create an extended enterprise. But this is a sensitive issue and while integration is critical to the success of analytics, it has to be done for the right reasons, and with a healthy respect for its limitations.
3. Leadership: What does an "analytical leader" actually do? To compete effectively with analytics, senior leadership, especially the CEO, must be committed. Analytical leaders are well-rounded individuals with both analytical and people skills. Research by Accenture identifies a dozen specific characteristics that define that role. Analytical leaders:
· Develop their people skills.
· Push for more data and analysis
· Hire smart people, and give them credit for being smart.
· Set a hands-on example.
· Sign up for results.
· Teach
· Set strategy and performance expectations.
· Look for leverage.
· Demonstrate persistence over time.
· Build an analytical ecosystem.
· Work along multiple fronts.
· Know the limits of analytics.
4. Targets: How do I target my investment in analytics to achieve the biggest payoff?Companies constantly have to make choices about where to invest resources, and it’s no different with analytical initiative
5. Analysts: Who is an analyst? Executives leading analytical projects rely on analysts from many quarters. Accenture defines analysts as those who use statistics, quantitative or qualitative analysis, and information-modeling techniques to shape and make business decisions—a broad range of activity. But analysts vary widely in their characteristics and responsibilities. They’ve identified four general types of analytical talent: champions, professionals, semi-pros and amateurs.
· Analytical champions
· Analytical professionals
· Analytical semi-professionals.
· Analytical amateurs
The authors conclude that not every company is in a position to base its strategy on the use of analytics and sustain it over time. But putting the DELTA model—data, enterprise, leadership, targets, analysts—into practice can go a long way toward building an analytical capability.
Information You Can Use. Knowledge You Can Trust
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