Data storytelling isn't about showing off your PowerPoint skills

Data Storytelling is more about the data analysis, and not the beautification of the PowerPoint slides

Soma Tah
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Arthur Lee


In my time as a financial analyst, I spent many hours poring over financial data and encountered many roadblocks to representing my conclusions effectively. Many of these internal stories go untold, but today I thought to tell how some of these roadblocks can occur, and how to deal with them.

Let’s meet Sophia, who is a manager at a fast growing company. She is about to present to the senior board on why they should continue to ship Fresh Vegetables.

Sophia is smart and a mover within the organization, but she struggles when presenting her ideas. She also has a hard time convincing stakeholders without getting off-track during the discussion.


Typically, questions are asked and more meetings are needed since the analysis can’t be done during the meeting.  Nobody wants to see long email chains get started either.

She knows her analysis is solid, but she needs an easier and more convincing presentation. Especially because Mike, a senior manager, always asks questions that derail the meeting, and it’s hard to have the analysis ready to answer his ad-hoc questions.

Sophia heard about a new trend around data storytelling, and decided to do some homework. She came across some interesting facts written by Jennifer Aaker, Professor at the Stanford Graduate School of Business:


"Stories are remembered up to 22 times more than facts alone." (Harnessing the Power of Stories)

"Only one in 10 students used a story within his or her pitch while the others stuck to more traditional pitch elements, such as facts and figures. The professor then asked the class to write down everything they remembered about each pitch: 5 percent of students cited a statistic, but a whopping 63 percent remembered the story."(Science of Storytelling: Why and How to Use it in Your Marketing)

What is Data Storytelling?


We need to think critically when presented with a data story or series of visualizations. What is required is activity around data stories, not just listening or absorbing. Data analysis needs to be about engagement and participation.

This is why it’s critical to preserve the context (or viewpoint) of the data that the narrator/author used in building in a data story – as it acts for a springboard to ask questions, test assumptions and flex the original context. This is key in the successful communication of any data narrative.

If you are actively involved in data visualization and analytics then storytelling is seen as an essential part of how you share data insights. You simply have to ‘tell stories with the data’. It’s the key to leveraging the hot engaging and persuasive power of the narrative to support the cool, neutral facts in the data. The narrative helps you frame it, position its impact and stress the importance you have assigned to it.


Instead of thinking about how to use her analysis to augment the story and engage the audience, Sophia had been spending way too much time on elaborate slides that really didn’t help the outcome of the meeting.

What if she could weave her analysis into the presentation? What if people like Mike could ask ad-hoc questions that can be answered on the spot to eliminate the need for another meeting? What if a new, different conclusion is gathered during the meeting and you could easily integrate it for the future?

Sophia decided to try that approach for the upcoming Fresh Vegetable meeting. She knew intuitively that the more engaged the audience is, the more likely they will retain that information. There was also a higher probability that a decision will be made.


So, did data storytelling help Sophia?

Yes, with Data Storytelling, the focus was shifted to the data analysis, and not the beautification of the slides. It was easy to take snapshots of charts and it was super convenient to have them accessible in a library to tell her story.

She loved when Mike asked a question because it was natural to jump back into the analysis for the answer.  When they would find another interesting insight, she would easily take a snapshot of the analysis to re-use it in the future.

As a result of the meeting, a decision was made to continue to ship Fresh Vegetables and people complimented Sophia on how great it was to interact with the data and in turn, answer ad-hoc questions on the spot.  Even Mike asked her how she did it so he can use it in his next meeting.

The author is Vice President at Qlik Analytics