What Your Data Isn’t Telling You

On a recent trip I was fortunate enough to be able to visit to a WWII aircraft history museum. I use the word “fortunate” because a history museum of mechanical objects is the intersection of two of my interests, and not everyone in my family appreciates how thoroughly I treat such an educational opportunity! So with gratitude, I systematically explored an hangar full of period specimens—some large, some small, some restored, some preserved, and some barely-recognizable piles of wreckage. While the nut-and-bolt restored pieces were impressive to behold, the ones that captivated me the most were the survivors. They were banged-up, rusty, and full of bullet holes. These clearly had stories to tell.

When these planes would come back from missions, the Allied forces would study the parts of the plane that were pierced with the most bullet holes. After seeing patterns develop, they sought to reinforce those parts of the plane with the most damage as a way to increase the odds of the pilot’s safe return. But a mathematician named Abram Wald observed something different; he suggested that perhaps the reason certain areas of the planes did not come back damaged was because these were the most critical, and damage to them during the mission meant that they would not return. Abram’s wisdom is directly applicable to how we draw conclusions from our own data. So today I challenge you to think about what your data isn’t telling you. Who isn’t leaving a review? Who isn’t taking your survey? Who is engaging with you? In business we don’t always have perfectly recorded, lab-controlled data points to collect, but that doesn’t mean the data isn’t valuable! It’s part of the story, but may not be the whole story.

Do you see a disconnect between what your data is telling you and what you observe on a day-to-day basis? Contact info@sphereanalytics.us to learn more about data-collection best practices and how acknowledging and understanding data “blind spots” can lead to better story-telling, decision- making, and meaningful outcomes.

—Michael Carey

Previous
Previous

Enable Data, Don’t “Govern” It

Next
Next

Tip & Tricks #3: Color matters! Here's how you make custom colors easy