What Story Is Your Data Trying to Tell You?

By MarkRoberts

What story is your data trying to tell your team? What if I told you… The secrets to drive organic sales growth are in your data. There are prescriptive insights in your data on pricing to increase your profits 2%-4% in 90 days. Your data can tell you the net profit by customer to help you make strategic decisions. Are your sales managers and salespeople skilled in the sales competencies required to execute your sales plan? There are tools that can tell this story too.  Does your team know how and where to look for data and produce actionable insights to drive performance improvement? In this post we will discuss how to use storytelling best practices to deliver data insights in a way that drives profitable sales growth.

For years sales teams have been provided all kinds of tools to slice and dice their customer information. We want them acting on data and not emotion but for years they have lacked the training and the tools to convert data into actionable insights, stories if you will, to drive bottom-line performance. 

Organizations continue to collect and store data at a growing rate. There are 2.5 quintillion bytes of data created each day at our current pace, but that pace is only accelerating with the growth of the Internet of Things (IoT). Over the last two years alone 90 percent of the data in the world was generated. Many organizations are growing through acquisition and with each acquisition…more data…. does that data speak with your data?

The challenge is how do we listen to the story your data is trying to tell your team to create profitable sales velocity?

Described as the “Leonardo da Vinci” of data and the “Galileo of Graphics” polymath Edward Tufteis both a statistician, artist and the father of modern data visualization. Tufte’s work is why we can tell stories with data. Harvard Business Review author, Jim Stikeleather, proclaims, “visualization in its educational or conformational role is a dynamic form of persuasion. “Because of its conformational, educational, and influential aspects, data visualization is perfect for persuasivestorytelling for both internal efforts and selling.

Storytelling helps the audience gain insight from the data presented. 

In particular when you wish to communicate to non-analytical people. However, how does a person who has access to data and analytics find a story that the data supports? Stikeleather suggests using strategies derived from journalistic practice. In this spirit, here are some strategies to tell a story using your data and reporting:

●     Consider what question type are you trying to answer-Those of you who took a journalism class will recognize this approach. Ask yourself if this is a what, why, or how story? What stories tell what happened. These are typically the most like traditional journalism. Why stories dig at the underlying circumstances that caused the outcome. How stories, generally translate to How to address the problem. How stories examine various ways to improve the situation. 

●     Know your audience- The most compelling narratives are written with the audience in mind. Within the broad term, ‘audience’ are multiple archetypes. The first question to ask yourself is, what does the audience know about the topic? What is their role? The narrative needs to frame what the audience already knows or doesn’t know. Here are some audience archetypes:

●     Complete Novice- This type has had no exposure to the topic. They will need a higher-level overview, followed by a deeper dive.

●     Generalist-The generalist has a broad knowledge of the topic. They are looking for an overview review and significant themes.

●     Stakeholder/Expert- The stakeholder requires exploration, discovery, and options in great detail.

●     Manager- The manager looks for in-depth, actionable understanding. Relationships and detail are essential. They are also looking for recommendations. 

●     V or C-level Executive- The executive needs to understand the overall significance of the data and conclusions weighted by probability. 

●     Build context-In the background－during development, the best stories have meaning and a place in the workday of the audience or the audience’s clients. The possible impact of the story on the various audience members (and the action they need to take) has been considered. Journalists consider creating a context for the narrative part of building a relationship with the audience. In short, context is why the narrative, analytics, and data matter.

●     Be objective- Ideally, a set of graphics should not be biased. (in my opinion the hardest step for most teams) Tufte argues that “visual representations of data must tell the truth.” Although many graphics are developed to support a point, the graphic should be based upon what the data says, not what you would likeit to say. Tufte proclaims that most charts are misleading. To this end, he developed a lie-factor calculation. The lie-factor is equivalent to the size of the effect depicted in the graphic, divided by the size of the impact in the data. For example, a number that is four times bigger than another will be perceived as sixteen times bigger if shown in 3D. Some other ways to reinforce objectivity are clear labeling, graphic dimensions must match data dimensions, use industry-standard or recognizable units, and design elements should be subtle, so as not to compromise the data. Effects such as clustering, variable scaling, and alternative color palettes help inform the readability of the diagram. Decision-makers are particularly skilled at noting inconsistencies, which in term causes a loss in credibility.

●     Don’t censor-Unless you are utterly confident in interpreting the data, include more data in your narrative than you exclude — working out in advance how you work with outlier values and use discrete values when the data is continuous. Too much exclusion may cause your audience to lose trust.

●     Editing is everything- There’s an old truism that said a good piece should spend more time in the editing stage than it does in the initial creation stage. 

That’s enough from me. 

I’m curious…

How do you create stories that lead to actionable insights based on your data? 

Have you used a journalistic approach? 

What strategies do you use to share data driven stories with your sales team? 

Who owns turning the mountains of data your company has into actionable insights?

Do you provide your salespeople and sales managers data insight dashboards?

If your salespeople are responsible for mining their own data, how much sellable time are they using to find actionable insights? 

Please answer in the comments.