Navigating Leadership, Innovation, and Empowerment in the Digital Age

How many times have you sat in a meeting where someone is walking the group through performance dashboards, and twenty different people who are in that meeting, looking at the same data, walk away with twenty different narratives about what that data meant? 

I call this the “So What Gap.”  Executives and managers are bombarded with data, funnels, and dashboards brimming with numbers and charts.  But meetings where teams review dashboards that simply alert business users to a specific change — say, a dip in sales or a spike in subscriber churn — without providing insight into the entire story, are suboptimal. This phenomenon often occurs because data analysts, in their desire to appear “objective” and “unbiased,” often shy away from communicating a “so what”…even if just a hypothesis. 

As a result, each person in the meeting is left to wonder what the implications of these insights are: 

  • How does this data impact my business? My growth tactics? My investments? 
  • Why should I care about these insights?
  • What does this data mean for my product backlog? 
  • What am I supposed to do about these trends?

In other words, “This data is very interesting indeed!  So now what?!

Unfortunately, if the team presenting the data does not also articulate a clear “So What,” then the audience will make up their own.  That’s human nature; we’re always on the search for meaning.  But repeatedly, we see that different people in the same meeting can interpret the same data differently, based on their world views.

In short, data dashboards and data reviews tend to answer “what” questions, but they don’t tend to explain the “why,” or provide other contextual information.

The most successful data reviews are those where savvy, data storytellers can remove the noise from the many metrics and graphs and focus people’s attention on the key insights.  Great dashboard and metrics reviews should reveal truths which are hidden and not easy to interpret from just reading or browsing the data or through simply plotting.  Analysts must find a way to connect the data to business outcomes.  When data analysts don’t do this, the data and dashboards may be informative, but they are not necessarily actionable.

So next time you are sitting in one of these meetings, ask yourself whether the data being shared is associated with a clear “so what?”

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