“My boss wants me to present our findings to the Head of Sales,” said Sara, a data scientist and researcher at a major social media company.

“That’s good, right?” I asked.

“Well, I’m not sure.” She paused. “No, that’s not true. It’s a good thing. I’m just not sure how to make the findings accessible and relevant.”

Sara usually presented her research to product teams, with a product manager as the key stakeholder, and occasionally to fellow researchers when the methodology was interesting. This was different. She hadn’t even met the Head of Sales.

“I know the findings will be useful to them,” she continued. “I’m trying to figure out how to make them see that right from the beginning.” Before I could offer a suggestion, she had an idea.

“I know. I’ll tell a story.”

Sara’s research involved customers who advertised on her company’s platform. One of them was Jim, the CMO of a large client, reviewing next year’s marketing budget. He had no shortage of campaign reports, spending figures and performance data. What he lacked was an answer to the question: What are we getting for all this money?

Their platform gave Jim’s team something they valued: access to a demographic his company wanted to reach. But it was clear to him that marketing was struggling with attribution—which activities were driving results, and how much of those results could be attributed to their spending. Without that, he found it difficult to make a compelling case for next year’s spend.

Sara could have presented her three research findings. Instead, she told Jim’s story first. The Head of Sales could now see the problem through the eyes of someone who had to justify spending on their platform. Customers had a compelling reason to be there, but not the evidence they needed to show it was paying off.

Afterward, the Head of Sales asked for a follow-up meeting with Sara and the product team to discuss next steps. Her research had started a conversation between two functions that could do something about the customer’s problem.

Find the decision behind the detail

When we present to people who don’t share our technical or functional context, we often spend most of our time explaining the work, hoping they’ll see why it matters. Sara started with a decision her audience could recognize instead. The CMO needed to justify a budget, missing measurement and attribution made that harder, and Sara’s research explained why. The head of Sales didn’t need to follow the methodology to see why the findings deserved attention.

A product manager presenting a roadmap, an engineering leader asking for an infrastructure investment, or an architect proposing a new system faces the same challenge.

What is someone trying to decide, and how does your work help them decide it? A story built around that question gives an unfamiliar audience a reason to care.

Ben Wellington is a data scientist who turned New York City’s open data into stories that got city agencies to act. In this TEDx talk he explains how. Notice where he starts: not with a dataset, but with something every New Yorker already knows, the corner pharmacy. Then watch the fire hydrant story near the end. A single parking spot that was quietly generating thousands of dollars in tickets every year did more to get the city to repaint the curb than any argument about data policy could have.

Among the Akan people of Ghana, sankofa means “go back and get it.” It’s often drawn as a bird walking forward with its head turned back, carrying a precious egg, and it comes with a proverb: it is not wrong to go back for what you’ve forgotten. More on sankofa here »