Join Doug Rose for an in-depth discussion in this video Define details, part of Learning Data Science: Tell Stories With Data.
- You've seen that people are more likely to connect with the story if there's a plot and conflict. The struggle draws people into your story. Once you have these, then you want to keep your story dynamic. A good way to do this is to attach small details to parts of your story. These details are like little mental sticky notes that help you remember the larger struggle. You can use these details to draw people in. It helps them create a mental image as they listen. I once worked for an organization that was trying to use data science to get people to participate in their medical studies.
It turns out that a lot of people are afraid of needles. Specifically, they're afraid of needles that are used in blood tests. There's a large intersection of people who are afraid of needles and also scared of blood. Not being a fan of either of these, I can certainly understand how this impacts a medical study. If needles are involved, then you lose a lot of people. If needles and blood are involved, then you've lost an even bigger group of people. This left this organization in a bit of a bind.
They needed people who weren't normally interested in studies to start participating. The data science team asked some good questions, and created the reports. They found that if someone participated in a study, and had a relatively good experience, they were more likely to participate in a future study. That means that someone who didn't like needles, who had a positive experience, might participate in a future study, even if it involved needles. The data science team wanted to tell this story.
The research lead decided that they wanted to use a real participant and just change their name. Each time someone participates in a medical study, they fill out an in-depth application. Then they're evaluated by a nurse who also fills out some information. The research lead use some of these details as part of their story. The research lead started out with a small anecdote. She said, "When I was a nurse, I could always tell who was afraid of needles. They always cross their arms in a certain way.
They grab both of their elbows as a way to protect themselves from the poke of the needle. There are a lot of people out there like that, and we need them to participate in our medical studies. So I'm going to tell ya a little bit about someone in one of our reports. Let's call her Tracy. She participated in one of our medical studies for a drug that's being developed to help people sleep. The first day of the study, she showed up with her own pillow. She must've been optimistic about the results. She was hoping that this new pill would help her.
She had trouble sleeping during times of high stress. It turned out that Tracy was one of the participants who didn't get any benefit from the drug. When she left, she told the nurse that her father was a doctor, so she felt an obligation to participate. She said that she could never be a doctor 'cause she was both scared of blood and needles. A few months later, she decided to participate in a trial for a new flu vaccine. The study required needles for the vaccination, and for the later blood tests. So why did Tracy decide to participate?" The research lead ended her story by describing a call to action.
The data science team thought that getting people involved in studies without needles was the best way to increase the number of participants. Now think about the story you just heard. What are some of the things that you remember? Do you remember the name of the participant? Do you remember why she participated? You might, but chances are that you remember the details. The little tidbits that help you create a mental image. You probably remember that she brought a pillow, and that her dad was a doctor.
These details help you carry your story from the beginning to the end. They create snapshots that help your audience imagine the whole picture. When you tell your data science story, try to use these little details to add life to your story. They help your audience connect to the plot and to the struggle.
- Structuring a data science story
- Defining plot, conflict, and details
- Going beyond reporting
- Knowing your audience
- Working with data
- Introducing visuals
- Eliminating distractions
- Incorporating metaphors
- Motivating the audience
- Avoiding pitfalls