Data Storytelling : An insight alone is not a Story

Finding a data insight and believing you can now make the change happen with the insight alone, is one of the common data storytelling mistakes.

To understand this let us look at what happened with Sam and his team.

Sam and his team worked hard to find an insight from the data they had received from their ecommerce team. They finally had a meaningful insight after weeks of slicing and dicing the data. Excited, they walk in to a presentation to share the insight.

Their presentation is structured like this:

– We are here to make the following suggestions for an ecommerce strategy (These are suggested actions)

– The reasons we are making these suggestions are… (This is a future outcome)

– And here is the insight from the data that proves why we are making these suggestions (This is the insight.)

Insight, action and future business outcome are all there. But despite all the information, Sam and his team do not get the reaction that they were expecting from their audience. What they thought was a brilliant presentation left the audience expressionless and shrugging their shoulders.

Why? Because it was just noise.

The author of Building a Story Brand, Donald Miller explains this really well using an example of music and noise. He explains that music and noise are technically made up of the same thing, sound waves at different frequencies. Then why music is so pleasing to our ears and noise is not. The difference is that in music sound waves are put together in a systematic way and in noise they aren’t.

Data Storytelling

Your insight, action and outcome are like sound waves but if you do not string them together properly they will sound like noise. So how do you do that?

Let us go back to Sam and his team who are forgetting that they have experienced the process of arriving at an insight, it speaks to them, it’s their hard work, it’s their slicing and dicing the audience but that back story is not known to the audience.

The suggestions  originated from the reasons. The reasons originated from the insights. The insights originated from the hard work of slicing and dicing the data.It’s almost like telling someone who has not run a marathon to appreciate the finisher tee that you are wearing after running a marathon.

So, what can one do in such a situation? Get your audience to appreciate what you can see by taking them through your process.

Do not share suggestions, but share how you arrived at those suggestions. If you can’t make them go through the process with you, you can surely make them experience it by effective Data Storytelling.

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