There’s a narrative that’s recently emerged in the data and analytics industry. It’s that storytelling is a skillset that analytics practitioners need to have in order for business users to understand the analysis that they’re presenting.
But, we see this narrative as potentially problematic. Primarily because the premise of becoming better ‘storytellers’ could support the idea that we can get away with not taking people on the journey with us from the start. Which is usually why we feel like storytelling is the answer in the first place. If we just tell a better story, our users will buy into what we’re telling them. It excuses us from recognising that landing on a meaningful ‘story’ is actually an iterative process between two parties. Just like landing a meaningful analysis or metric is also an iterative process between two parties
The D&A agenda
In our experience, analytics professionals are inclined to do their practice in a bubble and then aim to provide previously unknown insights to a business and, in doing so, be the ‘hero’. In essence, the practice of storytelling risks the potential for this agenda to extend itself even further.
It’s not to say that storytelling isn’t an important skill. But the most effective form of storytelling lies in collaboration. We know that visions are best achieved when they are co-designed by the people participating in that vision. That purpose is best fulfilled when it is co-designed by the people who belong to that purpose. And, similarly, that the best, most memorable stories are the ones that people have had a part in informing.
Good storytelling, therefore, is not a skill we develop to make others understand our point of view, but a skill we develop to connect with others on a shared journey.
It’s just one of many tools in our kit bag
Storytelling can’t be used as a means to excuse us from the real solution, which is: engaging the business in a meaningful way.
Because here’s a hard truth: It’s not up to the Data Analyst to decide what insights may or may not be important to the business. And when others can’t understand the analysis that is shared, the real problem is that the groundwork hasn’t been done for them to understand the process gone through to get to this point.
By that we mean that the Data Analyst hasn’t taken the time to:
Listen to the business
Understand what goals they’re trying to achieve (and/or help them understand and agree themselves what they’re trying to achieve)
Agree on metrics that represent those goals
Work collaboratively and iteratively together with them to help them get there, using analytics as an enabler to bring clarity to questions like: ‘Where are we at?’, ‘How far from our goals are we?’, ‘What was the impact of our last action?’ and ‘What move do we make next?
It’s our view that if our aim is to improve ‘data literacy’ across a business, we need to focus on the journey (engagement), not the destination (story). If you want to hear more about our approach to this, we’re happy to have a (no obligation) chat. Book in a call via the link below.