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Baseball and Data Quality: America’s National Pastimes

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By the time October rolls around, the top Major League baseball teams in the country are locked in combat, in the playoffs and then the World Series. And as teams take the field and managers sit in the dugout, everyone has one thing on their mind.

Data.

Honestly, I am not just using a cheap sports analogy here. Many people don’t realize that before my current career in data quality, I was a young pitcher with a 90+ MPH fastball. I eventually made it as far as the Triple-A level of the Pittsburgh Pirates organization. So I know a little bit about the game and how data plays into it. We really ARE thinking about data, almost every moment of the game.

One batter may have a history of struggling to hit a curve ball. Another has a good track record against left-handed pitching. Still another one tends to pull balls to the left when they are low in the strike zone. All of this has been captured as data. Have you noticed that position players shift their location for every new batter that comes to the plate? They are responding to data.

Long before there were even computers, baseball statisticians tracked everything about what happens in a game. Today, with real-time access to stats, and the ability to use data analytics tools against what is now a considerable pool of big data, baseball has become one of the world’s most data-driven sports. The game’s top managers are distinguished for what is on their laptops and tablets nowadays, every bit as much as for who is on their rosters.

And then there are the people watching the game who help pay for all of this – remember, baseball is fundamentally in the entertainment business. They are all about the data too.

A recent interview article with the CIO of the 2016 World Champion Chicago Cubs underscored how a successful baseball franchise leverages fan data at several levels: for example, tracking fan preferences for an optimal game experience, analyzing crowd flow to optimize the placement of concessions and restrooms, and preparing for a rush of merchandise orders in the wake of winning the World Series (although, as a lifelong Cubs fan, I realize that they’ve only had to do that once so far since 1908). For any major league team, every moment of the in-game experience – from how many hot dogs to prepare to the “walk up” music the organist plays when someone comes up to bat – is choreographed on the back of customer data.

Baseball has truly become a metaphor for how data has become one of the most valuable business assets for any organization – and for a competitive environment where data quality is now more important than ever. I couldn’t afford to pitch with bad data on opposing players, and you can’t afford to pursue bad marketing leads, ship products to wrong customer addresses, or accept fraudulent orders. Not if your competitors are paying closer attention to data quality than you are.

So, pun intended, here’s my pitch: look into the ROI of automating your own data quality, in areas such as marketing leads, contact data verification, fraud prevention, compliance, and more. Or better yet, leverage our demographic and contact enhancement databases for better and more profitable customer analytics. By engineering the best data quality tools right into your applications and processes, you can take your business results to a new level and knock it out of the park.

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