Review by Harvey Schachter
Anheuser-Busch arms its distributors to U.S. retail stores with mobile devices that record critical facts about the shelf space, displays, pricing of its competitors as well as its own inventory levels and shelf situation. BudNet, as the system is known, allows the company to know details such as whether a six-pack of Bud Light was warm or cold when bought, whether it was on sale, and what the prices were at neighbouring stores.
That is but one example of how some companies are competing these days on analytics. All companies, of course, abound in data, but some choose to gain a decisive edge based on their ability to gather better data than competitors and to use that information effectively.
The best-known examples come from sports. The success of Oakland Athletics General Manager Billy Beane in employing statistics to find the most valuable players his limited budget can afford, and gain a better won-lost percentage than that budget would augur, has been chronicled in the best seller Moneyball. But football’s New England Patriots, who won the Super Bowl three of the last four years, also has taken advantage of in-depth analytics, as have basketball’s San Antonio Spurs, and soccer’s AC Milan, which uses predictive models to prevent player injuries. In business, companies like Harrah’s Entertainment, Amazon.com, and Capital One credit card company base their success on their analytical strengths.
In Competing On Analytics, Thomas Davenport of Babson College and Jeanne Harris of the Accenture Institute for High Performance Business lay out a road map for taking your company to the point where it is wielding analytics competitively. If your firm is analytically impaired, with only some data and limited management interest in analytics, you will have to fix the data first, which can take eighteen months to two years.
“Even if an organization has some quality data available, it must also have executives who are predisposed to fact-based decision-making," they add. “A data-allergic management team that prides itself on making gut-based decisions is unlikely to be supportive. Any analytical initiatives in such an organization will be tactical and limited in impact.”
Once your organization has some useful data and management support, the next task is to take stock, candidly assessing whether you have the strategic insight, culture, skills, IT, data, and high-level support to make it work. This analytical thrust, to be productive, must be connected to your business strategy. For example, when Harrah’s Entertainment realized its growth could no longer come from constructing new casinos, it applied analytics to increasing revenue from existing customers through customer loyalty and data-driven marketing opportunities. Companies that truly compete on the basis of their people need to develop analytical superiority in human resources practices.
If your company has a CEO strongly committed to analytical competition and an encouraging top team, it can probably move full steam ahead to applying data to make a difference. Often that has been the secret to start-ups, such as Google, Yahoo!, Amazon.com and Capital One. But the authors have found most companies lack the passion and commitment to move so vigorously, and if that is your situation they recommend you try out analytics in a series of small steps. That will add one to three years to your route to being fully competitive on analytics, but will give your managers experience, build efficiencies, and create momentum for the future.
Eventually you will reach a stage they call “analytical aspirations.” Top executives are supporting competing on analytics, and you can now set out the improved business benefits you expect and metrics to measure progress. With that will come the first major projects to use analytics competitively, and the need to find the right expertise and technology to make it all work.
It’s vital as you continue this effort that you maintain a broad management consensus, avoiding the situation where one or two person leave and the efforts fizzle. “In one case, the CEO of a financial services firm saw analytical competition as his legacy to the organization he had devoted his life to build. But his successors did not share his enthusiasm, and the analytical systems developed under his leadership quickly fell into disuse,” they note.
In future, the authors expect more companies will choose to compete on analytics. And as those companies attain success, they will apply it to more and more capabilities, their motto being, “if it’s worth doing, it’s worth doing analytically.”
The first half of this book, setting the foundation and chronicling companies having success, is dreadfully dull, much of it already known to the kinds of readers the book would attract, but the last half is more engrossing, as the authors set out their roadmap for success, explain how to manage analytical people, and describe the architecture you need for your business intelligence systems.
This and other reviews by Harvey Schachter may be viewed at the Queen's School of Business Forum.