Make Data Storytelling Personal: Stories with data

In Paul Smith 's book?Lead with a Story, he describes how the CEO of Procter & Gamble would come to presentations and sit with his back to the screen. Smith describes how he delivered a presentation to the CEO, who didn't once turn around to look at the slides. After the presentation, he realized that this wasn't by accident. CEOs in large companies see data all the time. They know the data is the vehicle and that the story the presenter tells holds all the value.

When your data team is composing a story, don't get hung up on the data and on creating dazzling visualizations. Spend more time to make data storytelling personal. Without a great story behind them, the data and visualizations are relatively useless. The story connects the dots, reveals the data's meaning and significance, and educates and transforms the audience.

Your job as a data science team is to reveal the humanity behind the numbers. You need to get personal.

Case in Point

Suppose you're walking through an airport and you notice a cell phone on an empty seat with nobody near it. You pick up the phone to discover that it's unlocked. Being the considerate person you are, you want to return the phone to its rightful owner. How would you go about doing that?

You carefully consider your options. Maybe you should just leave the phone where it is, because you know that there's a high probability that the person who left it there would soon remember and return to the spot to reclaim the phone. However, there's also a high probability that someone else will pick up the phone before its owner returns. Maybe you should turn it in to the desk at the nearest gate, thinking that the person may have boarded a plane at the gate and hoping that one of the flight attendants could get the phone to the passenger prior to departure. Or, maybe you should hold on to the phone assuming the owner would use a borrowed phone to call his own phone and find out where it was.

Now suppose you're telling your story later and recounting the thought process you engaged in to decide on the best course of action. You're a data scientist, so after the event, you perform some research on lost cell phones, analyze the data, and create charts to illustrate the probability of the different scenarios you considered. Now the time has come to tell your story.

You have two options. First option: You could flip through your slides and explain each one in turn. Maybe you have a slide that shows a correlation between the phone value and the likelihood that the owner would return to claim it. You may have another slide that shows the percentage of phones that are turned in at airports and train stations and never claimed. A third slide shows a correlation between lost phones and the number of owners who find their phones by calling their own numbers.

Second option: You get personal. You tell the story in a more human way. For example, you might start with the following:

Two weeks ago, I was passing through LAX, when I spotted a cell phone on a seat at one of the gates with nobody near it. I picked up the phone and was surprised to discover that it wasn't locked. I checked text messages and emails to see if I could find any flight information. I walked over to the desk at the nearest gate and asked the attendant whether anyone had reported a lost phone. She pulled out a box from below the counter and showed me its contents — about 20 phones that were turned in only this past week. I returned to the seat where I found the phone and sat there for about ten minutes hoping that the owner would return to claim the phone or would borrow a phone from another passenger to call. No such luck . . .

Which presentation would you find more interesting — the slide show or the story? Rhetorical question. Of course the story is more interesting, but why? With the slide show, you're removing the human element from the story. You have no characters — no you, no owner of the lost phone, no flight attendant. You have no plot, no setting, no conflict, no resolution. All you have are numbers, statistics, and slides. Boring.

When you tell your data science story, you want to take the focus off the data and place it squarely on the story. You want all eyes on you, pens down, and electronic devices stored safely and quietly away. Audience members should only glance occasionally at the slides. If they spend too much time looking at charts or graphs, chances are they’re thinking about something else. Only after the story hooks the audience members and connects with them personally and on an emotional level will they be receptive to the knowledge and insight you impart and be inspired to embrace whatever change you recommend.

Frequently Asked Questions

What is data storytelling?

Data storytelling is the process of transforming raw data into a compelling narrative that communicates insights and trends in an engaging and informative way. It combines data visualization, data analysis, and storytelling techniques to present data in a way that is easy to understand and relevant to the audience.

Why is data storytelling important?

Data storytelling is important because it helps to convey complex information in a more accessible and engaging manner. By weaving data into a story, data storytellers can make their insights more relatable and memorable, helping stakeholders make better-informed decisions. It also allows for the presentation of data in a way that highlights key trends and patterns, making the data more actionable.

What are some key components of data storytelling?

The key components of data storytelling include a clear narrative structure, engaging data visualizations, relevant data points, and actionable insights. A good data story should have a beginning, middle, and end, with a compelling narrative that ties the data together. Visual elements like charts, graphs, and infographics help to illustrate the data and make it more understandable.

How can data visualization enhance a data story?

Data visualization can enhance a data story by making complex data more accessible and easier to comprehend. Using visual elements like charts, graphs, and maps, data storytellers can highlight important patterns and trends that might not be immediately apparent in raw data. Data visualization tools can also help to make the data more engaging and visually appealing, helping to capture and retain the audience's attention.

What skills are needed for effective data storytelling?

Effective data storytelling requires a combination of analytical and creative skills. Key skills include data analysis, to interpret and draw insights from data; storytelling, to craft a compelling narrative; and data visualization, to present the data in a visually engaging way. Additionally, understanding the audience and their needs is crucial for selecting the right data and tailoring the story to be relevant and impactful.

Can you provide an example of data storytelling?

An example of data storytelling could be a company presenting its annual performance. By using data visualization tools to create graphs and charts, the company can illustrate their growth trends, market performance, and customer satisfaction. The narrative might highlight key achievements, areas for improvement, and strategic goals, all supported by compelling data points that bring the data to life and make the story engaging.

How can a data analyst improve their data storytelling skills?

A data analyst can improve their data storytelling skills by practicing the art of data storytelling regularly, studying examples of successful data stories, and continuously enhancing their data analysis and visualization skills. Taking courses or attending workshops on data visualization and storytelling can also be beneficial. It's important to focus on understanding the audience and their needs, as this helps in selecting the right data and crafting a narrative that resonates.

What are the benefits of data storytelling for businesses?

Data storytelling can help businesses by making complex data more accessible and actionable, enabling better decision-making. It can also enhance communication across the organization by providing clear and engaging insights that different stakeholders can easily understand. Moreover, effective data storytelling can highlight key trends and opportunities, fostering a data-driven culture within the business.

How can one start using data storytelling in their presentations?

To start using data storytelling in presentations, begin by identifying the main message or insight you want to convey. Collect and analyze relevant data to support your narrative, and use data visualization tools to create charts and graphs that illustrate your points. Structure your presentation with a clear beginning, middle, and end, and focus on creating a compelling narrative that ties the data together. Practice delivering your story to ensure it is engaging and easy to follow.

This is my weekly newsletter that I call The Deep End because I want to go deeper than results you’ll see from searches or AI, incorporating insights from the history of data and data science. Each week I’ll go deep to explain a topic that’s relevant to people who work with technology. I’ll be posting about artificial intelligence, data science, and data ethics.?

This newsletter is 100% human written ?? (* aside from a quick run through grammar and spell check).

more sources

1. https://online.jcu.edu.au/blog/the-importance-of-data-storytelling
2. https://flourish.studio/blog/importance-of-data-storytelling/
3. https://powerbi.microsoft.com/en-us/data-storytelling/
4. https://storyiq.com/global/data-storytelling/
5. https://data.europa.eu/apps/data-visualisation-guide/storytelling-and-data-visualisation
6. https://shorthand.com/the-craft/examples-of-powerful-data-storytelling/index.html
7. https://www.vev.design/blog/data-storytelling-examples/
8. https://www.correlation-one.com/blog/6-elements-of-an-effective-data-story
9. https://www.coursera.org/learn/data-storytelling