The power of storytelling in enterprise IT

Power of Stories

For those road warriors who spend most of their time presenting in front of large groups around the world, the power of the words “let me tell you a story” are very well known. In my experience, however, there’s a subtle, but important difference between telling a story and storytelling.

So before I go too far with this, let’s explore why CIOs and enterprise IT should even care about storytelling. After all, isn’t that marketing’s job? The answer is yes, and for that reason it’s even more important for IT to understand the power of storytelling in the businesses they service. One of the foundational elements of the CIO’s personal brand is an ability to translate technology and data into understandable insight for competitive advantage in the marketplace.

Many technology leaders (and marketers) are under the illusion that dashboards and data visualization software get them off the hook for developing compelling narratives for departmental or client facing use. Anyone who has depended on technology to translate data into stories knows the risks. It’s like using Google Translate for documentation to be used in your Chinese office.

Visualization and verbalization are two totally different forms of communication. For this reason, “data storyteller” becomes one of the most valuable positions any department could add to increase or reinforce the relevance of their organization.

Storyteller Audience

So what makes the data storyteller position so different? It’s an individual skillset that does not come easily and the work begins before the data is even collected.

First, a data storyteller needs to be able to work with data scientists on the insight desired before the process begins. This notion of the story to be told can be critical in the data collection stage. Unfortunately, many data analytics projects take the approach of seeing what stories the data can unearth rather that prescribing the desired narratives in advance.

This is not to say that unexpected “bluebirds” of insight are not desirable. It’s simply saying that telling the data science team the kinds of optimal storytelling desired in advance can make the mining and analytics process more efficient.

This ability to collaborate with the data science team and speak a “dialect” of their language is a key personal brand attribute of the data storyteller.

The next key skill is the ability to think like a marketer, as scary as that thought might be. What themes and formats for telling the story will resonate with the customer? How do your customers consume and digest stories? Do they prefer video, PowerPoint, white papers, blog, case study, podcasts, YouTube, face-to-face? How much emotion does the story potentially lose by putting it into a certain format? There is a misperception that passionate stories can only be told using video and sound. But anyone glued to a page-turner novel on the beach knows that some of the best stories require nothing but ink on paper.

Last and most important is the ability to “viralize” the story. In other words, how can the storytelling be constructed such that it can be “retold” effectively and passionately by a wide variety colleagues? History tells me that enterprises cannot take for granted that even the most compelling stories will not be retold unless they’re drilled and practiced through sales enablement training.

Think about how some of your colleagues are natural joke tellers regardless of technical or marketing roles. Some of us, meanwhile, stutter and stammer through even the most simple 3-minute joke, forgetting key elements that destroy the punchline. Data storytelling practice does two things. It develops a comfort level in telling the story to internal or external customers, and it also forces the storyteller to stick to the talking points while adding some small degree of their own personality to the presentation.


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