Data Storytelling Training: What You Actually Learn (And Why It’s Not About Charts)

The dashboard is polished. The numbers are right. The colours match the brand guidelines. And the meeting still ends with, “Thanks, we’ll have a think about it.”

If that sounds familiar, you’ve met the gap that data storytelling training is meant to close. It isn’t a course in making prettier charts, although your charts will probably improve along the way. It’s training in how to think with evidence, decide what’s worth saying, and help a room full of people make a decision together. Below, I’ll cover what strong programs actually teach, where many of them fall short, and how to choose one that’s worth your team’s time.

A great chart isn’t the same as a great story

Ask ten people what data visualisation is and most will say charts. Fair enough: graphs, dashboards, colour-coded tables. Data storytelling is what wraps around them. It’s why you’re showing this, what you want people to notice, and what you hope they’ll do next. One displays the data. The other helps people use it.

Imagine a school leadership team looking at attendance by year level. The chart is clear and accurate, but no one is sure what to take from it, so the conversation drifts. Now give the same chart a title that says Year 9 attendance has dipped every term, and ask the room one question: where should we focus support first? The data hasn’t changed. What’s changed is that people now have something to think about and something to decide.

None of this makes the visual side optional. Good training still shows you how to pick a chart that suits your question, write titles that actually say something, and highlight what matters while quietly greying out what doesn’t. Every one of those choices simply serves the message. It’s also why I wrote about not letting Excel’s default chart decide what your data means.

What strong training actually teaches

Programs differ, but the good ones tend to build five things. Only one of them involves a chart.

1. Start with the decision, not the data

Weak data presentations tend to be a tour of everything the presenter happened to have. Strong training reverses that. Before anyone opens a spreadsheet, you work out what needs deciding, who has to decide it, and what evidence would change their mind. Once that’s clear, the room knows what to listen for. It’s the same problem I explore in why your data can be solid and your meeting can still fail.

In the moment, it sounds like:

• “By the end of this meeting, we’re choosing between A and B.”

• “The data’s here to help us decide, not to impress us.”

2. Make sense of the data before you make a point

A number tells you what happened. Context tells you why, and that’s where smart people get caught out. Participants practise asking what’s included, what’s missing, what the number is being compared with and what else could explain it. If that sounds more like thinking than maths, you’re right. It’s why I call data literacy a thinking skill, not a maths skill, why context matters before you act, and why missing information can tell you something.

In the moment, it sounds like:

• “Compared with what?”

• “Who isn’t in this data?”

3. Find the one thing worth saying

Most datasets hold a dozen stories. Good training helps you pick the one this audience needs for this decision and park the rest in the appendix. It can feel like you’re hiding something. You’re not. You’re editing, and editing is what gets people listening.

4. Design for the whole room

Every room is mixed. Some people read charts easily, some think in stories, and a few are quietly wondering whether they’re the only one who’s lost. Training builds the habits that bring everyone along: plain language, narrating the chart instead of just showing it, and keeping “what we see” separate from “what it means”. Do that well and the quieter voices join in, and you stop mistaking silence for agreement.

In the moment, it sounds like:

• “Here’s what you’re looking at, and here’s why I think it matters.”

• “If something isn’t clear, please ask. Our decision will only be as good as our understanding.”

5. Land it on a decision, then learn from it

A good conversation about data isn’t the finish line. The story ends when people know what happens next: what was decided, who owns it, what you’ll measure and how you’ll know it worked. A lot of data analysis in Australian workplaces and schools stops one step short of that, and the report gets filed rather than used. Then comes learning from the result, including judging a decision by the thinking behind it, not just how it turned out, which I explore in why a disappointing outcome doesn’t necessarily mean a bad decision.

The skill nobody advertises: knowing when it’s not ready

Here’s the part I think most programs leave out. Teaching people to present data persuasively is easy to sell. Teaching them to pause is harder, and often worth more.

Say a team’s engagement score dips in the latest survey and a manager wants to act this week. Someone with strong data storytelling skills asks a handful of unglamorous questions. How many people responded? Is this a one-off or part of a pattern? What would we expect to see if our explanation were true? Whose voices aren’t in this data?

The answers might show you’ve found a signal worth investigating, not a conclusion worth acting on. That isn’t the story failing. It’s the story told honestly.

In the moment, it sounds like:

• “This suggests X, but it doesn’t tell us Y.”

• “Before we decide, here’s what we’d need to know.”

There’s a catch, too. A polished chart can make an unfinished insight look finished, so the better you get at presenting, the more responsible you need to be about what you’re presenting. Training should build both skills together. It’s a big part of what being data-informed, rather than data-driven, really means.

Who gets the most out of it?

Leadership teams, first, because they set the tone. When the people at the top ask better questions of data, everyone below them notices, which is why a data culture doesn’t stick until the top and middle move together. Business, government and not-for-profit teams gain when everyday decisions, from budgets to customer feedback, rest on evidence rather than the loudest opinion. My work with corporate, government and not-for-profit organisations includes keynotes, workshops (data storytelling for decision-making and influence is the most popular), a Data Review to see where you currently stand, and ongoing support through Data Advisor.

Schools get the same payoff with their own twist. Teachers and leaders hold rich information about attendance, wellbeing and learning, and the real skill is explaining what it means for students and deciding what to change. For schools, I offer Data Champions, a 12-month action-research program for the people leading evidence-informed change, plus in-person and online sessions for school leaders, middle leaders and classroom teachers. The full list is on my schools page.

And if you’re thinking, “but we’re not numbers people”, that’s fine. Nobody needs to be. If you’re not sure where your team sits right now, the Data Diagnostic assesses data literacy, data visualisation and data storytelling skills, and thousands of people have already completed it.

How to spot training that’s worth the money

Not every program is built the same. A few questions will tell you a lot:

• Does it start with questions and decisions, or with software features?

• Does it teach interpretation, limits and uncertainty as well as design?

• Does it use your own data and context rather than generic examples?

• Does it work for mixed confidence levels?

• Is there follow-through, so the skills stick beyond one day?

Tool-based courses have their place, especially if your team needs skills in a specific platform. But if the outline is mostly chart types and menu options, expect better charts rather than better decisions. The strongest programs treat the chart as one of the last steps, not the first.

Want to go deeper? Start with my book

I’m Not a Numbers Person: How to Make Good Decisions in a Data-Rich World is the book I wrote for anyone who has ever said (or quietly thought) those exact words. I wrote it because I don’t believe that line is helpful anymore. Whether you’re running a household budget, leading a team or steering a whole organisation, somebody needs to ask the right questions of the numbers, and that somebody is all of us.

The book walks through why data matters, how to understand numbers, how to visualise data and spot trends, and how to turn all of that into decisions and action. It brings together the three skills this post keeps coming back to: data literacy, data visualisation and data storytelling. The thread running through it is the idea I care about most: being data-informed rather than data-driven, using numbers alongside context, people and circumstances to make better decisions.

If you’d like a practical, easy-to-follow way to build your confidence before investing in training, it’s a great place to start. You can find it in my shop, and there’s an audiobook too, which I narrate myself.

Frequently asked questions

What is data storytelling?

Data storytelling is the skill of turning data into something people can understand and act on. It combines the data itself, clear visuals and a narrative that explains what matters and why, so a decision can follow. In my work, the goal is always better, evidence-informed decisions, not prettier reports.

Why is data storytelling important in business?

Because decisions are made by people, and people don’t act on data they can’t understand or trust. Data storytelling helps teams spot risks and opportunities earlier, agree on what the evidence means, and move from reporting to action without relying on a handful of analysts.

What does data storytelling training teach?

It teaches you to start with the decision, interpret data in context, choose the one insight worth sharing, communicate it in plain language to a mixed audience, and finish with a clear next step. The best programs also teach you to recognise when an insight isn’t ready to act on yet.

What are the three elements of data storytelling?

The three most commonly named elements are data, visuals and narrative. I’d add a fourth that often gets forgotten: the decision. If your story doesn’t help someone decide or do something differently, it’s still just a presentation.

What is the difference between data visualisation and data storytelling?

Data visualisation is the chart or graphic itself. Data storytelling is the purpose, narration and decision that sit around it. You can have excellent visuals and still fail at storytelling if the room is left to interpret the chart alone.

How can data storytelling improve decision-making?

It brings discipline to the conversation: agreeing on what the data shows before debating what it means, naming assumptions and limits, hearing from the whole room, and finishing with a clear, testable decision. Better questions and clearer thinking tend to lead to better decisions, although no training can guarantee a good outcome.

What skills do you need to be a good data storyteller?

Curiosity, critical thinking, a solid grasp of what the data does and doesn’t show, the ability to choose clear visuals, and the confidence to explain it in plain language. Just as important is judgement: knowing when an insight is strong enough to act on and when it needs more work.

What are the most common data storytelling mistakes?

Showing too many charts, leading with the data instead of the decision, using jargon, ignoring context, and presenting an early insight as if it were settled. Most of these come from skipping the thinking that should happen before the slide gets made.

Do you need to be good at maths to learn data storytelling?

No. Good training starts with thinking, questions and communication, not formulas. Many of the people who get the most out of it are the ones who’ve always felt a bit uneasy around data. I wrote more about this in why data literacy is a thinking skill, not a maths skill.

How can schools use data storytelling?

Schools hold a huge amount of information about learning, attendance and wellbeing. Data storytelling helps staff ask better questions, interpret results in context and decide what to change. My school programs include Data Champions, in-person and online sessions for leaders and teachers, and an online course for educators.

What types of data storytelling training are available?

It depends on what you need. A keynote can spark a conversation across a whole organisation, a workshop builds practical skills with a team, and ongoing support helps the habits stick. You can see the options on my corporate and not-for-profit page, or contact me to work out what suits your team.

How do we know if our team needs data storytelling training?

Start by finding out where your team currently sits. The Data Diagnostic looks at data literacy, data visualisation and data storytelling skills, so you can see where development would make the biggest difference before you invest in anything.

Where can organisations find data storytelling training in Australia?

There are several options, including university short courses, corporate training providers and specialist consultants. Compare them against the questions above. I work with organisations and schools across Australia through keynotes, workshops, a Data Review, ongoing advisory support and school programs like Data Champions. If you’d like to talk it through, get in touch.

Bringing it all together

With so much data landing on our desks every week, the ability to make sense of it and turn it into a clear story is a skill worth building on purpose. Good data storytelling helps people ask better questions, read evidence honestly, say something clear, and sometimes say “not yet”. Those habits spark action and better decisions, whether that’s in your business, your school or your leadership team.

Contact us to learn more about our keynotes, workshops, Data Review, Data Advisor or school programs, including Data Champions.