Keep your eye on the ball! Good eye! Way to watch! Baseball season is in full swing (pun maybe intended) and, with three sons, I have begun to hear these phrases in my sleep. Enough so that it sent me down a rabbit hole of curiosity. I began looking for the origin of the phrase “Keep your eye on the ball.” Turns out, there is an interesting parallel with data governance.
The literal and keenly obvious expression suggests you must see the ball to catch it or hit it. Well, duh! But, the phrase means quite a bit more. It means a player must move and act based on the context of where the ball is in play. In some respects, it is a flawed statement to just say, “Keep your eye on the ball.” What the phrase really means is: Stay focused on the ball, pay attention to everything going on in the field, and make your decisions as to what to do with the ball accordingly. For data governance, the metaphorical ball is our data.
Our data governance activities should always be driven by business need, and as our business needs shift, so should our “game play.” Not every play will be the same, but every play will be made to support the overarching goal to score runs (data governance quick wins/low hanging fruit) and ultimately achieve a win (successful data governance program) over the competition (obstacles and challenges).
The story behind the phrase “Keep your eye on the ball” extends the ball/data metaphor further. In 1920, Ray Chapman was struck in the head by a pitch in the fifth inning of an evening game. He died of the injuries sustained from the impact.
Until this pivotal moment, the same ball would be used throughout an entire game unless the seams busted, or it began to unravel. It was not against the rules to alter or dirty the ball. In fact, it was common for pitchers to apply foreign substances or to make cuts into the balls to alter pitches. Dirty and altered balls make it difficult for batters to keep their eyes on the ball as they are difficult to see, and their movements are often erratic. Because Chapman never moved from the plate to avoid being hit by the ball, it is believed that the ball was excessively dirty and with daylight fading, he never saw the ball.
After this tragic event, Major League Baseball transitioned from what is referred to as the dead-ball era to the live-ball era. It changed the rules around how game balls were to be treated. New balls were brought into play at any point in a game when the ball in play showed wear. The new rules, which are still in effect today, allow for a “livelier” fair-play ball that is brighter and more visible. With new, clean balls came the ability for batters to keep their eye on the ball. The impact on scoring in the game was immediate. Not only could batters hit the ball more regularly, but they could knock it out of the park. If you ever wondered why the home run records dramatically changed in the early 1920s, now you know.
This story applied to data governance is equally impactful. Businesses are notorious for reusing data until it is “busting at the seams” or until it has become unraveled. Without governance, users are free to dirty the data and alter it as they see fit. Accurate data becomes difficult to see, and “erratic” is an understatement as to the output and performance of the data.
Like the dead-ball era, if you are in a dead-data era, your “games” will always be low-scoring. Data governance introduces the rules necessary for “livelier data use” and to keep data more visible, more accessible. It provides consistency with a framework that ensures the right data is in play at the right time. Of course, fouls and strikeouts will always be a part of the game, a part of doing business. But at least if the data is right and ready, we up our game and increase our chances of home runs. Here’s to the live-data era. Now, play ball!