Reading Chris Anderson’s recent Wired Magazine cover story about the End of Theory prompted me to do something I had been meaning to do for sometime: buy Michael Lewis’s Moneyball.
Chris’s piece examines how computers, the Internet and the era of massive data are changing our assumptions about science and scientific method. Moneyball looks at how the use of data enabled the Oakland Athletics to amass one of the best overall records in baseball with one of the lowest team payrolls.
And it is the power of data that is transforming the way we in marketing and PR do business. Through data, we can identify trends that we never knew existed, find previously ignored market segments and gain an advantage in a very competitive marketplace.
So beginning at the All Star break, I started reading and finished the book at 2:30 one recent morning. Now I am no baseball expert and can’t prove or disprove Lewis’s theory, but I was struck by one thing in particular: The story of how Oakland A’s general manager Billy Beane used Ivy League number crunchers parallels the work we are doing with social media.
It is a story about questioning assumptions, challenging orthodoxy, tapping new ways to engage fans and measuring performance. It’s about a new kind of expertise that is creating a whole new approach to doing business.
Challenging Unconventional Wisdom
For the longest time, stats like batting averages, stolen bases, and RBIs have governed baseball. Leading the majors in any one of these categories is worth millions of dollars. What Beane did was unconventional. He looked at the statistics that others overlooked, ignored, or rejected to sign ballplayers that other scouts had overlooked, ignored, or rejected.
His conclusion: on base percentages and slugging percentages are a far more accurate way to assess talent and predict success. They were the best indicators of which players would produce the most runs for the team as a whole. More runs, more wins. And today, while these stats are more widely used, that has not always been the case.
The story really begins in the late 1970s with an eccentric visionary, Bill James. Back then, there was no such thing as a blog, so he self-published a book that challenged the orthodoxy governing the measure of baseball success. Without search engines, he placed a single ad in the Sporting News. He grew a small but loyal following and responded individually to reader mail.
At the time, management and traditional sports journalists were very skeptical. In much the same way bloggers were initially dismissed, sportswriter Thomas Boswell wrote, “What we really need is for the amateurs to clear the floor.”
There was also no place for companies to share information with their customers. Data was not transparent; stats were held by major league teams and only one company – the Elias Sports Bureau – was authorized to sell that data. Major League Baseball wasn’t interested in new metrics and wasn’t interested in giving fans the data they asked for.
Quoting James, Michael Lewis writes: “The entire basis of professional sports is the public’s interest in what is going on. To deny the public access to information that it cares about is the logical equivalent of locking the stadiums and playing the games in private so that no one will find out what is happening.”
James advocated that the accumulation of baseball statistics should be taken out of the hands of baseball insiders and put instead in the hands of volunteer scorekeepers. The huge success of Rotisserie Baseball in the mid 1980s demonstrated that fans were hungry to engage with each other.
These developments along with the growing power of computers and the drive for new kinds of expertise (like the use of derivatives in financial markets) all contributed to a new way to think about stats, baseball and managing teams.
Does the story of self-publishers, companies unwilling to engage their customers, skeptical journalists, empowered fans and the lack of transparency sound familiar? These are the elements that social media advocates experienced in the beginning and, to a lesser extent, experience today.
While most of us are not involved in managing sports teams and picking players, the lessons learned from Moneyball are transferable. Most importantly, data is king.
In making their selections, the A’s crunched millions of bits of data, analyzing the outcomes of thousands of plays in a given game and in a given season. It’s the same approach we should be taking: looking at the connections among and interactions between individuals to understand innovation, collective decision making, and problem solving, and how the structure of organizations and social networks impacts these processes.
Blogger Steve Rubel refers to it as Moneyball marketing.
We need ask ourselves: Are we looking at the data that social networks yield? How and where does data factor into PR decisions? Can we use data to target the right audience – especially in the age of the long tail where we can go after niche markets?
Identify the right data and you can help improve products, increase sales, engage customers and build brand.
Once more, as the Oakland A’s demonstrated, data collection can save dollars. The challenge of course is to identify the right data. And that data must directly relate to your company’s business objectives. In the case of the A’s, the goal was to maximize limited dollars.
Number crunching and computers may seem incongruous with the traditions that govern our nation’s past time. And after all baseball is just a game. But Moneyball demonstrates once again that how you play the game often dictates whether you win or lose.
Let me get back to you.
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