- Remember that a story is spinning a tale with visuals to help your audience connect to the meaning. People often think that you connect to others through tales about success and achievements. That's why a lot of business meetings start out with some new achievement or goal. The audience might applaud but they're not really connecting. It's actually the struggle that helps people find meaning, it's the energy of conflict that connects your audience to a story. When you're giving a storytelling session you probably have an audience that spends all of its day filtering information.
This is especially true if you're working with high-level stakeholders. Each day they'll go through hundreds of messages and probably look through dozens of reports. To be an effective storyteller, you have to communicate in a different way. You've seen how your data can tell a story, in fact, you've seen how the same data can tell several different stories. Your challenge will be to take this lifeless data and reverse engineer it back into the human beings who created it.
You'll communicate their struggle and create a plot for your data science story. So let's see what this looks like. Imagine that you're working on a data science team for a large credit card company. Your team found that credit card customers change their spending patterns just before they have trouble paying off their account. These customers increase the amount they use on their credit card just before they get into financial trouble. You could present this information in several different ways. You could present a simple line diagram that shows an uptick in spending just before a customer gets into trouble.
This might present the information but it won't connect with the audience. The best way to present it would be to tell an interesting story. You'll need a real plot with actual struggle and conflict. You can start by creating a character with a real name. This shouldn't be an actual customer's name but it could be a character based on most of the common traits of your customers. You can start your storytelling session by saying, our data science team wants to talk about one of our customers today, let's call him Alan Smith.
It's here you're setting the context, so you go back and say, in two months, Alan's not gonna be able to pay his credit card bill. He's been a customer with us for about six years. We know Alan is not gonna be able to pay his credit card bill, that's because the last two months, he spent up to his credit limit. That's pretty unusual for Alan. He's 48 years old, and using his credit card to pay for groceries and transportation. Usually he only uses his credit card for airplane tickets or hotel bills.
We know that Alan's not gonna be able to pay his bill, so now we're left with a question, what do we do about it? Notice how you finish the story with a conflict. By presenting the data this way, you've combined the data of hundreds of thousands of customers and created a plot with a real human struggle. Your audience should be able to connect with this data in much more interesting ways. Maybe they're thinking about whether or not they have an obligation to Alan. Should they send him a letter, maybe give him a telephone call? Also notice that it's not just important to give the character a name, you also want to fill in some of the details about their life.
The audience found out that Alan is 48 years old, he's been a customer for six years. It's these details that help enhance the struggle and build out the plot. The audience will have a much easier time connecting with the meaning behind the data. It's far easier to talk about what to do about Alan than it is to talk about the hundreds of thousands of customers he represents. There's a real plot with a struggle that's enhanced by just a few details. Once a basis is established, remind the audience that the story actually refers to thousands of customers just like Alan.
Even though Alan doesn't exist, he's real for the purpose of the story. He can help show the conflict in a way that the data on its own cannot. What was just lifeless data became a story with a context, a real struggle, and a plot.
- List the five threads your team should focus on when spinning a yarn.
- Explain the benefits of using scenarios as story helpers.
- Explore how using conflict in a story can captivate your audience.
- Determine how details will enhance a story and make it memorable.
- Recall the downfalls of using too many visualizations.
- Define vision in the context of data-science storytelling.
- Recognize the features of good storytelling.