If you aren’t sure why changing data into a story is important, consider this example from the Bureau of Labor Statistics: “In July, the unemployment rate was 3.5 percent.” Compare that sentence to this: “Last month, 269,000 people found jobs. This returns the unemployment rate to pre-Covid rates.” One sentence gives you a number. The other explains why you should care about that number and gives it context. Helping people care about and understand data is what turning data into stories is all about.
Why You Need Stories
People respond best to stories. Our brains need context to make meaning of information. Numbers on their own don’t have that context, so people can’t find the meaning in them. If you don’t provide the story, the listener may provide their own. Changing data into stories means moving beyond the facts to give a deep understanding of people’s worlds and experiences. A large and complex data set might be scary, but if you tie it to specific issues you care about, to questions you need to have answered, and to problems people have, others will understand it.
How to Tell Stories
On its own, data doesn’t mean anything. Is 3.5% unemployment a lot or a little? To answer that, you have to know what unemployment was the previous month or what’s considered a good unemployment rate.
Changing data into a story does not mean creating a narrative around your numbers. It doesn’t mean that to share the labor statistics you have to invent a typical American worker who lost her job during Covid and now has a new one. Telling a story with your data means sharing the context for your data. It means explaining your information’s who, what, when, where, and why.
Keep Track of Your Questions
The best way to ensure you are telling an important story is to keep track of the question your research was trying to answer. Did you want to know why people participate in your programs? If your programs are effective? How do people feel about your programs? If you don’t keep track of the questions your research is trying to answer, then you can easily get caught up in irrelevant details. These irrelevant details can derail your story.
Focus on Themes, Not Plots
You might remember from school that you can talk about stories in terms of plots and themes. Plots are what happens (a man comes to town). Themes are what the author wants you to think about when you read the plot (good vs. evil, love, etc.). When presenting data, researchers frequently concentrate too heavily on the plot and the specifics of what happens. A bad report might simply lay out the data point by point, in the order in which people answered questions. But a good report is organized according to themes. Each theme should relate to one of the original questions.
Don’t Get Wordy
Changing data into stories does not always require a lot of words. Graphs, charts, and pictures can often tell a story better than words. Bullet points and short sentences are an effective way to get your message across.
To change data into stories, do not write about the data, and do not write about the research itself. Instead, write about the questions you had and how you answered them. At Brighter Strategies, our program evaluation process helps you discover and tell your organization’s stories. Let us know how we can help.
Program evaluation is a powerful driver to establish a culture of data-driven decision-making across your organization. It assesses how well you are using program resources, justifies the existence of your program, highlights the impact of your program on the community in terms of strong outcomes, and ensures an organization’s programs are focused on continuous quality improvement.
This workbook will teach you how program planning and program improvements are based on solid evaluation data. Learn to write meaningful evaluation questions and determine the evaluation method that works best for your program goals. Finally, you will develop a practical data collection plan that fits within the tools you currently use, and share your evaluation results with critical stakeholders.