Five years ago the book Moneyball was going around the office of respond360, which is the CRM arm of BVK. The book fueled my love affair with data-driven marketing. In reviewing the book this morning, I realize how relevant its lessons have become in our economic downturn.
Wikipedia describes the account of the Oakland A’s unprecedented success on a shoestring budget this way:
Statistics such as stolen bases, runs batted in, and batting average, typically used to gauge players, are relics of a 19th-century view of the game and the statistics that were available at the time.
The book argues that the Oakland A’s front office took advantage of more empirical gauges of player performance to field a team that could compete successfully against richer competitors in Major League Baseball.
Rigorous statistical analysis had demonstrated that on base percentage and slugging percentage are better indicators of offensive success, and the A’s became convinced that these qualities were cheaper to obtain on the open market than more historically valued qualities such as speed and contact. These observations often flew in the face of conventional baseball wisdom and the beliefs of many baseball scouts and executives.
By re-evaluating the strategies that produce wins on the field, the 2002 Athletics, with approximately $41 million in salary, are competitive with larger market teams … who spend over $100 million in payroll. Because of the team’s smaller revenues, Oakland is forced to find players undervalued by the market, and their system for finding value in undervalued players has proven itself thus far.
I found the book inspiring then, and I find it even more exciting today. In spite of my general lack of enthusiasm for the sport of baseball, I found it the best business book of 2003.
Reading Digital Tea Leaves
The author argues that most teams still rely on the black art of talent scouting. Wizened, tobacco-spewing scouts watch a young athletes play and proclaim him either unfit or “slugger material.” Does this sound like the seat-of-the-pants metrics that marketing has traditionally used to evaluate markets, products and campaigns?
Back when I read it, I was thrilled to imagine new ways to read a different sort of tea leaves — namely, the ones found in market and customer databases. What I’ve learned since is that once you start looking at data in a new way, you can find breakthrough insights.
You really can.
Although I don’t think he’s a marketer, here’s what “Ryan,” in his GoodReads review of the book, wrote:
Awesome – story of how the Oakland A’s built a great baseball team on one of the league’s smallest budgets by using innovative statistical analysis to identify undervalued players. I think that’s pretty neat.
I couldn’t have put it better. Pretty neat indeed.
I’m right there with you in being inspired by this way of thinking. I’ve really tried to apply that thinking to almost everything I do since reading the book. For me it broke down into two categories.
The first was turning me into a value shopper. That doesn’t mean finding the cheapest thing – it means truly understanding what I value and therefore what I’m willing to pay more for. An easy example of this is the Sony LCD TV I just bought. I could have paid 2x for the top of the line version from Sony or the same amount for another brand that theoretically had better hardware. But through research I determined what was important to me and paid for that.
The second, obviously related way, was in trying to look at different ways to measure things. Metrics get jammed down your throat all the time, in all walks of life, but they aren’t necessarily the right metrics and tend to be sensationalist. A good example of this is the Ford Explorer being the most dangerous SUV on the road a few years ago. Did Explorers have the most instances of flipping over? Maybe, but there were also exponentially more Explorers on the road than any other SUV.
That doesn’t mean you should buy and Explorer – I just sold mine 🙂
I venture to say that a link is being made between the power of statistics in ranking baseball teams much like within the marketing realm; you need the intricacy of all intermittent numerical factors to gage past, present and future progress? And sometimes bad numbers – accessed at the right time have a crucially different “meaning”…. And could in actuality signal rare success…
Insert bold supposition here: I believe this relates to everything in life and design, tools for creating the right (marketing/artistic) message are ever-present; they are context & syntax!
You’re right of course, Chris and Daria. I shudder to use this shopworn phrase, but it’s about “Thinking outside the box.”
Okay, now that the nausea has passed, consider what the phrase really means. Look for answers in unexpected places, and from unexpected people.
The Oakland A’s decided not to go to the traditional baseball “oracles” — the scouts. Instead, they plowed through numbers, mostly from college baseball statistics.
But even before they chose what data set to examine, they had a revelation: If we do what everyone else is doing, we’ll lose. Especially if they have deeper pockets than us.
So let’s try something different.
They were led to data mining not because they were in love with the tactic, but because the tactic made sense.
In this way, the book is, more than anything, about new ways to do strategic thinking.
It’s why, for the right type of person, it can resonate far beyond marketing. But in marketing especially, it reminds us that we too are surrounded by data we can use, if we’d only open our eyes to it.