- So we've spent a lot of time talking about stories. You've seen the difference between a simple retelling and a story. A story has a plot, characters and conflict. Then you've seen how to present the story in a way that helps engage your audience. Still, this is a course about data science. It's about using the scientific method to better understand your data. Ultimately you have a bunch of data and you want your audience to connect to what it means. Then you want your audience to act on the data in a meaningful way. You've seen how to create the story first because that's how you'll present your data.
You need to reverse engineer the swirl of your data back into the flawed, emotional and unpredictable human beings that created it. That's the main challenge. That's what separates data science teams from data analysts. Your job as a data science team is to reveal the humanity behind the numbers. That's why you shouldn't just communicate the information in the language of numbers. Think of it this way, you're at an airport and you found a smartphone on an empty seat next to you. Someone left the phone unlocked and you had access to all their data.
How would you find the owner at the airport? There are thousands of people at the airport, each one of them has their own story. This person isn't perfect, they're not predictable. After all they did, you know, lose their smartphone. What data would you need to reunite this person with their smartphone? Chances are you would recreate the story of their lost smartphone in your head. You would imagine the person waiting for a flight and then running off to get something to eat. You would try to better understand the person and create a story from the data.
Most people wouldn't start with statistical models. They wouldn't analyze the relationship between the expense of the phone and the likelihood that someone will return. Then if you retold the story to someone you wouldn't use the language of data and statistics. You wouldn't tell the flight attendant that you found a smartphone but you left it because you found that there was a high probability that someone would return. Instead you think about it all within the context of a story. Maybe you would look at the recent calls in the smartphone to see if the owner called before they left.
You know that people often call their husbands, wives, girlfriends or boyfriends just before getting on a flight. Maybe you look in the calendar to see if there's flight information. You probably wouldn't think the smartphone as a bunch of numbers and data. You'd think of it as a cherished device with a person's photos, videos and contacts. Something they would miss. You would ultimately work with the data. That's where you'd find the smartphones phone numbers, calendars and contact information. It's just that you wouldn't start and end with the data.
The data would just be the vehicle in between. In Paul Smith's book Lead with a Story, he describes how the CEO of Procter and Gamble would come to presentations and sit with his back facing the slides. Paul Smith describes how he gave a presentation to the CEO and he didn't once turn around to look at the data on the slides. After the presentation, he realized that this wasn't an accident. A CEO in a large company sees data all the time. They know that data is the vehicle.
It's the story that the presenter tells that has all the value. That's why you should start with a story. You don't want to put too much emphasis on the data. The data won't be worth anything unless it connects with the audience. The data on its own can't do that. It's the story you tell about the data that will help the audience connect to some meaning. You want your audience to have their pens down and their laptops closed. You want them to look at you and only glance occasionally at the data you're presenting.
If they spend too much time looking at the charts and graphs chances are they're not connecting to your story. A story will help your audience connect the data to a larger meaning and that will help spur them into action.
- 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.