Storytelling With Data: Part 1

This is Part One of a multi-part series on how to use data to influence people and get them to do things.

In ancient Ireland, the seanchaí were storytellers, masters of transforming complex histories into tales that educated, entertained, and influenced their audiences. They were skilled communicators who understood that information's true power lies not just in its content but in how it's shared. Today, in business, we face a similar challenge: taking complex information and turning it into insights that resonate, illuminate, and drive action.

My old boss Rutger would ask two simple questions about any analysis: "What do you want people to know?" and "What do you want people to do?". These cut through everything else and get to what matters. While we data folks naturally gravitate toward models and statistics, I've learned across roles at Google, YouTube and now Tines that technical excellence alone rarely drives change.

In this article, let's break this down into three parts:

• Getting the analysis right
• Building your message
• Delivering it effectively

The Analysis: Getting It Right

The technical work - crunching numbers, running stats, cleaning data - is where most analysts feel at home. It's important work, especially for newer analysts who are building their skills. But it's just the start.

Good analysis needs clear business context - without this, you'll produce technically perfect work that solves the wrong problem. Do the basics well: validate your assumptions, document your approach (because Future You will thank you), and be clear about any limitations. I'm not going to dive deep into analysis techniques here - that's another article. Suffice to say, it's vital - but it's just table stakes for any good analyst.

The Message: Making It Matter

When you're deep in the analysis, you understand every input, every calculation, every nuance in the data. You've lived with it, watched patterns emerge, and drawn your conclusions. Your audience hasn't taken that journey with you - they need you to be their guide, helping them understand not just what the numbers say, but what they mean and why they should care. This is where a lot of us stumble.

Think about structuring your message like this:

• State the situation clearly ("Here's what we looked at...")
• Present the discovery ("This is what we found...")
• Provide clear implications ("This matters because...")
• Make specific recommendations ("Therefore, we should...")

Try this: can you boil your message down to two sentences?

1. "Our analysis of [X] shows [Y]..."
2. "This means we should [Z]..."

If you can't fill those blanks clearly, step back and simplify. Getting to this level of clarity often takes longer than the analysis itself.

The Delivery: Don't Miss The Landing

How you package your message often determines whether it drives action or gets ignored. Match your approach to your audience and situation.

What Format?

• Documents: Best for complex stuff that needs detailed explanation. People can read at their own pace and add comments. Tools like Notion or Google Docs work well here.
• Presentations: Good for high-level concepts or when you need to walk people through your thinking. Keep them focused and visual.
• Direct Communication: Sometimes a simple email works best, especially with people you work with regularly.
• Spreadsheets: Almost never the right choice, even though it's where we do our work. Save these for other analysts who need to dig into the details, and always consider adding a text overview/summary.

Standalone or presented?

Sometimes you'll present your work directly, walking people through it. Sometimes they'll read it on their own. Each needs a different approach.

For stand-alone content, where the audience will consume it 'unsupervised':

• Add more context - they don't have you there to explain
• Make your method clear
• Answer the obvious questions upfront
• Match technical detail to your audience

For presentations:

• Keep text minimal
• Focus on key visuals
• Leave room for discussion

The trickiest scenario? When people see your analysis before you present it. They'll form opinions before you can provide context, but you still need to add value during the presentation. You don't want to just read what they've already read.

In these cases:

• Make your document clear enough to stand alone
• Keep some insights for the presentation
• Be ready for misconceptions
• Use the meeting for discussion and decisions
• Focus on next steps

Remember, your job isn't just to analyze data - it's to help people make better decisions. That means having a clear point of view and showing people how to act on what you've found.

Next time, we'll dig deeper into crafting messages that actually land and get people moving.