Data Batting Averages
For many reasons, I have done a great deal of research about companies such as Amazon, Apple, Facebook, Twitter, and Google over the past year. You could say many things about these companies. First and foremost, they sport high data batting averages (DBAs). By DBAs, I mean that these companies’ records on their users, employees, customers, and vendors are exceptionally accurate.
Of course, this begs the question Why?
A few reasons come to mind. Let’s explore them.
First up, the Gang of Four allows users and customers to maintain their own information. Consider Amazon for a moment. Its customers make any and all changes to their credit card numbers, mailing addresses, and communication preferences. That’s a given. But Vendor Central, Seller Central, and Author Central each allow affected parties to submit pertinent updates as needed. So, let’s say that I want to sell a copy of The World is Flat by Thomas Friedman. No problem. No one from Amazon needs to approve it.
Self-service is all fine and dandy, but surely mistakes are made. No one bats 1.000, right? Honest errors aside, there are some unscrupulous folks out there. For instance, a clown recently claimed that he wrote The Age of the Platform—and submitted a separate and fake listing to Amazon, including the cover of my actual book.
(I’m actually honored. The same thing happened to Seth Godin.)
While Amazon didn’t catch this, the author (in this case, yours truly) did. After a bit of bouncing around, I emailed firstname.lastname@example.org and, after a few days, Amazon removed the fraudulent listing. (One small step for man…) Evidently, the company’s systemic checks and balances aren’t foolproof. At least the company provides a mechanism to correct this oversight. The result: Amazon is today a tiny bit more accurate because I noticed this issue and took the time and effort to resolve it. Now, Amazon and I can make more money.
A Recognition of the Cardinal Importance of Accurate Data
The above example demonstrates that Amazon gets it: data matters. Fixable errors should be, well, fixed.
Now, let’s turn to Facebook. The company takes steps to ensure that, to paraphrase the famous Dennis Green post-game rant, “you are who it thinks you are.” That is, Facebook is all about authenticity among its users. While it doesn’t ask for proof of identification upon joining, try singing up as Barrack Obama or Bruce Willis.
Go ahead. I’ll wait.
You see. You can’t do this—even if your name is Barrack or Bruce. Of course, there’s an appeals process, but those with celebrity names have to endure an additional step. Annoying to these namesakes? Perhaps, but in the end it prevents at least 50 apocryphal accounts for every one “false positive.”
And Facebook is hardly alone. Twitter does the same thing with verified accounts, a service that it introduced a while back, although I’m sure that there are at least tens of thousands of people on Twitter posing as other people.
The companies that manage data exceptionally well today aren’t complacent. Even “hitting” .990 means potentially tens or hundreds of thousands of errors. While perfection may never be attainable, the Facebooks and Googles of the world are constantly tweaking their systems and processes in the hope of getting better and better. This is an important lesson for every organization.
What say you?
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