When Stats Don’t Tell the Story
I have been a fan of cricket since I was a young one. In the mid-90s, I would remain glued to the TV set watching cricket games, with hours of seeing my favorite batsmen smash the opposition bowlers across the park. But my obsession didn’t end there. I would scour the newspapers, looking for the scorecards of particular games, and then would cut them out and paste them in my scrapbook. But my obsession didn’t even end there. I would peruse the individual statistics of each cricketer, going over their batting or bowling averages, the runs they score and all sorts of obscure numbers that would appear to be gibberish to the uninitiated. I would track their average uptick or downtick every game.
That lasted for a few years. Instead of viewing cricket from the standpoint of a fan enjoying the spectacle, the actual gameplay took a backseat to the figures. I would see the game as a rolling series of numbers, almost like the scroll screen we see in the Matrix, and the excitement came in players or teams achieving their own statistical milestones, not even winning games. The power of the batting blows or curve of the ball in the air mattered less than the digits on the scoreboard.
At one point though, after a particularly disastrous performance, my favorite players retired collectively. In one fell swoop, my stats-mongering seemed an entirely pointless endeavor. It was like my joy behind the numbers had been sucked out. I left viewing the game for a few years, and when I returned, I found myself back to following cricket from the perspective I had when I first glanced the game, for its pure watchability.
The Limits of Data
Our modern world is saturated with data. Since the Big Data revolution in the early 2010s, the tendency to map out phenomenon such as consumer behavior, employee satisfaction, economic markets, etc. with broad and precise statistical measures has only increased. The utility of such data and its predictive power is so compelling that it is completely understandable why businesses have embraced data-driven approaches for aspects of their organizational culture.
Without compromising on the value of data, we should also recognize the shortcomings to a data-first method. One limitation is that standalone data can have a reductive quality to it. It can reduce complex human personalities to simplistic models of behavior, for example. Data can also be prone to multiple interpretations and require holistic analysis. Companies can choose to continually mine more data to get answers rather than distil and refine the data they already have.
Lastly, communicating data itself can be challenging. With the expectation that the ‘numbers will speak for themselves’, data can often go right over the heads of our target audience. We owe it to our audience then to know what message the data is telling us and what vehicle is best for articulating that message.
Mobilization doesn’t come from Information
In terms of a persuasive hierarchy, numbers may be last on the list after visuals and words in terms of its raw impact on delivery. It may be tempting to dish out numbers in a presentation because it is so easy to do. But will they land? How many stats do we know about saturated fat content or glycemic indexing that prove useless in stopping us from taking a bite out of a burger or cake?
This mistaken impression that delivering more information will lead to corrective behavior has been thoroughly debunked but remains pervasive. Instead, we need to acknowledge that humans are fundamentally emotional beings. No matter what sort of logical covering we give for our decisions, emotions trump thoughts when it comes to mobilizing us to action. We have to tickle that emotional underbelly to get us to move. What may seem to us consciously as a rational decision can be guided by all sorts of unconscious passions and insecurities.
This is where the power of stories come in. Stories are the unique tool humans have used throughout history to convey big ideas or morals that can spur us to action. This is because the common themes in stories instinctively connect to us on an emotional level and speak to our hearts first. Incorporating our data within our stories is an effective way to drive our teams towards our stated goals.
Build a Story around Numbers
Numbers can serve a higher purpose though within a story. We build a story use a few basic elements (characters in a particular setting move along a plot with a beginning, middle and end). Taking that structure, we can use our data to highlight its role in progressing our story. In essence, giving the numbers context. Data on declining sales may not mean as much in isolation unless we put it in the context of the story of how your company uses every challenge, even a low sales cycle, as a teachable moment to become more resilient.
We need to be careful in making a distinction between fancy presentation of data versus actual storytelling with data. In the former, often called data visualization, our focus is trying to stylize the visual demonstration of data points for further clarity and receptivity, often with illustrative graphs, charts and animations. In the latter, we try and give the data meaning within the story of the organization, and therefore can be more selective of the information we choose to make our big points.
Storytelling is both and art and a science. For all the corporate buzz on storytelling this past decade, we may not have truly tapped into its pure potential the way our grandparents’ did. We have to search for that right balance between communicating necessary points while always touching the right heartstrings as we do so.
