Why: A Vital Variable in the Insight Equation

Data and Analytics
Data + analytics + visualization = insight. And insight yields outcomes, right? Possibly, but achieving the desired outcome becomes much shakier without understanding why the data’s being reviewed. Without a why, the timeless ready-fire-aim problem arises.

Now, don’t get me wrong; on more than one occasion I’ve waded chest-deep into a data set hoping to find something useful and sometimes have. In most cases though, I find:

  • Focus on the critical question lacking or
  • Inappropriate data to answer the question

Just last year, I helped with a high-priority project in advance of an upcoming executive meeting. I was given an inadequate set of data and asked to discover what caused a particular situation. The haphazardly collected data was not only incomplete but hadn’t been purposefully collected with the why in mind. 

Regardless, I dove head-first into analytical method after analytical method attempting to generate any meaningful insight. At conclusion, the focus became storytelling to describe the nuanced insight rather than a focus on actions to solve the situation.  

As data sets get bigger and algorithms get smarter, it can be tantalizing to lean toward a haphazard approach of finding a question to answer versus answering a question that’s been asked. So, as you embark on your next extreme data challenge, ask yourself, do I feel lucky or do I know why I’m drowning in data? 

Have ideas or feedback to share? Please leave a comment, or if you would like to discuss privately, please connect with me on Linkedin or send me an email (david.kocher@ge.com).

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