If you’ve worked in a line of business at a large enterprise or on a data team with a junior analyst, you’ve probably seen this scenario many times. You are asked to look at a piece of visualized data or watch the data in presentation form. Right away you see and hear far too much technical jargon. In other words, it’s mostly about the how and very little about the why. 

Or you’re watching a data presentation and all you hear is inside-out thinking. The presenter does a great job of communicating all the interesting elements of the assignment or the visualization technology and what was cool about working on the project. Problem is, as an audience member you’re not sure what’s in it for you. 

What’s clear is that the presenter has failed to ask a few critical questions:

  • What’s the business problem?
  • What does the stakeholder need from this?
  • Where has anyone identified any business value? 

Why is data storytelling important? 

Data storytelling and visualization are hugely important because they help to translate numbers and insights into something that humans can understand and that resonates with them. You could say it almost personalizes the benefits. Because data storytelling is often overlooked or misunderstood by graduates or people who are relatively new to the industry, it deserves to be discussed as a topic on its own.

Here are a few ways you can help your direct reports put storytelling front and center.

  1. Study how the masters do it. Have your junior analysts watch a few TED talks, perhaps the top five or ten most viewed ones. At its core a TED talk is a slide show made to a business audience. Ask them what makes the best ones rise above what is a boring, traditional idea? How are the most compelling presenters leveraging anecdotes and the structure of story to pull viewers in and keep them engaged? 
  2. Use data as your story’s evidence. Stories are inherently emotional and use psychology to draw in the listener. Yet data is typically dry and factual, the opposite of story. But the two can work together beautifully if you think of the data as evidence for the story your junior analysts are telling. Data assures the audience that the story has merit and is believable, that you’re not waxing lyrical without proof. It communicates that there is a reason you’re couching your story in a particular way. 
  3. Don’t tell everyone the same story. Just as you wouldn’t hand a young child a copy of Joyce’s Ulysses, data analysts need to adapt the story to their specific audience. In practical terms that means they’ll use a different slide deck for a technical audience than they would a group of senior managers. The two clearly have different interests and different needs. That means effective data storytellers should use different emotional hooks and details to explain and present their story. Even body language should be different for a management team versus a group of technical decision-makers. Think adaptability.
  4. Get to know your audience. It’s always a good idea for analysts to develop strong working relationships with the business teams they’re serving. This means more than picking up a few of their favorite buzzwords. Rather, the analyst needs to understand clearly how the work they’re doing will be used and how it adds value. Encourage your staff to move beyond pre-conceived notions around this point, so they can state it clearly as they’re communicating insights and findings.  
  5. You’re not the hero. You’re speaking to them. Inexperienced data analysts may like to come off as the star of their own show, but this is misguided. The hero of the story is the audience you're speaking to. With that in mind, what are their needs? And based on those needs, how should the message be tailored to create a compelling narrative specifically for them?
  6. Less is more. If your analysts are presenting to a business audience, especially a senior business audience, advise them to keep it short and sweet. Focus on fewer slides, fewer words, and more visuals. Use personal stories or stories that relate to the audience so the work resonates with them. Whenever possible, have your analysts conduct hands-on demonstrations for their audience so they can interact with the solution. 
  7. Educate as you present. This doesn’t mean anyone needs to come off as pedantic, rather that they convey that data science is a great field and they are evangelizing it. As we say in Australia, be really across what you’re doing; that is, fully understand the details. A common data storytelling mistake is failing to recognize that data science in particular is really about people, not the technology itself. You're there to solve a problem for people that serves people.

There’s no question that the more people come into the data profession, the more important good storytelling becomes. It’s the difference between viewing your audience as passive recipients and engaged participants. So have your junior team members put together stories using data tools about topics they're interested in, whether that’s politics, sport, or whatever industry they happen to be in. Provide feedback on it and suggest ways to improve what they're doing. 

On a related note, should storytelling be included in every data-related university degree program? Without question. In the meantime, see yourself as a mentor – for those on your staff, in your community, and in your professional ecosystem. The power of good data will only grow stronger as a result.