What’s the difference between these two statements, both of which you might hear in your company as a data leader?

  1. “Oh, cool. Yeah, that's great to know.”
  2. “Oh, okay. I can definitely decide what to do now.”

In the first instance, you’ve delivered interesting data. It might be a beautiful visualization, but it doesn’t prompt any action. In fact, its impact probably starts and ends in that meeting.

The second instance is a perfect example of what actionable data is. It’s more likely to be the outcome of someone coming to you and asking, “I’m a bit held up at this decision point. Can you help me decide whether A or B will work better?” 

Of course, most data leaders would prefer to spend their time in the second conversation, even if it’s something as tactical as figuring out the right pricing threshold for one customer versus another or one product versus another. At least you can make decisions based on data once you visualize it. 

One Size Fits None

I would take this analogy one step further, to one-size-fits-all data of the type you see in dashboards created for broad sets of users. Over time, experience has shown me that this is interesting – but not actionable – data. Because they are intended for a broad set of users, with a lot of filters, you can in theory answer a lot of questions with these sprawling dashboards. The problem is people quickly get lost in them and don’t spend the time required to answer their questions. Where we found the highest level of engagement among our users was 

  • simpler dashboard designs 
  • answering very specific questions 
  • are easily accessible

An average sales user doesn’t need to know everything, they just need us to turn our data into actionable insights. For example, they often have a burning need to know on a Monday morning what happened last week, what current bookings are, and how their forecast changed last week to today so they can begin to manage that. What's dropped out? What's dropped in? Not hugely difficult questions to answer, but highly personalized. By providing them these details in a weekly push to their phone, we’re driving real engagement because the data is so relevant. 

Now that we've done this with the sales team, we're starting to do it with our services team, too. For service users, questions are more along the lines of:

  • What should I care about this week? 
  • Where do I need to spend my time and with which customers? 
  • How has customer satisfaction gone up (or down) this past week? 
  • Do I need to have a follow-up call with a customer that may be showing signs of potential poor customer satisfaction?  

Every time I present to our steering committee, I tell them the same thing: I want to work on actionable insights, I don’t want to work on interesting insights. One kind of insight guides your decision-making, the other doesn’t. As a data leader, which would you prefer?