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I’ll preface this review by saying that Kat Greenbrook has been telling stories with data since before it was cool. I first met her in 2016, when I was halfway through my own self-discovery as someone who’s into data visualisation.
I was at a local data meetup with a few work colleagues, and she was one of the speakers. I remember the mixed responses when she introduced herself as someone who does a thing called Data Storytelling.
The term has a long history of being loosely confused with other forms of data communication - like dashboards, presentations or interactive news articles. The lack of a common definition was, I believe, the main reason why my colleagues weren’t immediately sold on the idea of using narrative as a device to communicate data.
There’s also the hype that comes with anything as cool sounding as Data Storytelling. Not long after that event, a couple of managers came to me with vague feedback along the lines of “But can you make this dashboard tell more of a story?”. Of course, my way-more-technical-than-me colleagues weren’t exactly thrilled. What on Earth could that even mean? And why is it suddenly a thing being asked of us, a pretty traditional Reporting Team with reliance on rather old-school ways of dealing with data? (Namely spreadsheets. It was all spreadsheets).
Data is a human artifact. It is a way for us to record, organise, archive and make sense of information. It relies on us deciding what matters enough to be recorded and kept somewhere but still be easily retrievable in case we need it. But as we started recording and keeping more and more data, systems became a complex puzzle of technical stuff - data became quite inaccessible to most people. Even if they might benefit from the information that someone else so carefully captured, organised and kept. While computers are quite efficient in reading and making sense of data organised in columns, rows and strings of digits, we’re not. We need to make it make some human sense to turn it into something we think about, act on, or learn from. And as humans, we’ve been doing that since forever - through language, visual expressions and storytelling. Data Storytelling is one of several techniques we can employ to cut through all the complexity and bring data back to its human origins - and Data Visualisation is another technique. We can even combine them! But that’s not mandatory.
Time went by, and by 2019, I started experiencing that strange itch that everyone who’s more on the entrepreneurial side of the work spectrum has. That’s when I started wondering what life could be like for a one-person data visualisation agency. Was it even possible? Did I know anyone who did that? And yes, I did. I sent Kat a quick message on LinkedIn, and she agreed to meet for a coffee, where I asked all about it. I don’t think I ever told her, but that brief chat really mattered. A lot, in fact. It was a big transition moment for me. I had always had stable employment. I had always worked for big corporations. But at the same time, I had always longed for more independence and to specialise in the bits I loved about my work (the dataviz design bits), with none of the corporate BS that inevitably laid in front of me if I followed on a promotion path. I didn’t want to get into management. I wanted to build stuff, help people with their data woes, and have fun along the way. Kat was straight to the point in her answers to my questions. And that chat gave me the final push I needed to start Data Rocks.
So, when I learned she was writing a book and looking for beta readers, I raised both hands, jumping in excitement. Well, of course, I want to read it! And here we are.
A hands-on book
The name is apt for what the author came up with here. The Data Storyteller’s Handbook does exactly what it says on the tin: it is a practical guide that you’ll want to take along with you in your quest to become someone who tells stories with data.
The book is structured in 7 chapters. And if you’re already familiar with the subject, you can skim through it and jump around to where you might be in your data storytelling journey. Kat Greenbrook says it is designed with skim readers in mind, and I can see that, too. The book is packed with super cute illustrations and visual explainers alongside the templates and guides you can employ to build your data story. The idea was to create a “kid’s handbook for adults”, and she very much succeeded at that. It is a joy to read, and even though the subject can seem intimidating if you aren’t familiar with working with data, Kat manages to keep it accessible to anyone interested in honing their data storytelling craft at any level. You don’t need prior knowledge of any specific software either - the book is tool-agnostic, and the techniques presented are universal. They’ll work in any medium you choose to work with.
The first couple of chapters are dedicated to defining what Data Storytelling is and isn’t while addressing some common misconceptions. Kat also dives into one of the core concepts she uses across the book: visualising data to Discover, Inform and Educate. She explains that you can employ data visualisation as a technique to discover insights and find your story elements, to inform others of your findings or to help them find theirs, but it’s the element of educating your audience on a subject that sets data storytelling apart.
As she explains in the book:
“Educate visuals explain the meaning of data. Educate visuals don't just show an audience the data (like an Inform visual); they tell the audience what it means. To do that, they need to include a story.”
This is a rather interesting and novel way of looking at it. I have seen plenty of articles and books defining data storytelling and differentiating it from broader uses of data visualisation.
But this differentiation in functionality and purpose nailed it for me. While you can use data visualisation for any of these purposes (to discover, to inform, and sometimes to educate), the realm of a data story lies in educating someone about a particular finding from the relevant data. And for that, different narrative devices can be used. The author writes from the point of view of someone writing stories for a business context, but the lessons can easily be adapted to other environments such as government, education, healthcare and others. This can be seen through the range of examples shown in the book. And let me talk about the examples!
The book uses the concept of personas to show how real people would use each lesson in their contexts. And Kat Greenbrook does it brilliantly through a mix of illustrations and little stories for each of the semi-fictional characters. Some of the characters are even based on real people in Kat’s life! (and wouldn’t you know, yours truly here cameos in one of the pages!).
Building a data story, one block at a time.
The rest of the book is dedicated to going through each part that will make up your data story. The author calls them building blocks.
The first piece is dedicated to clearly defining your audience and the reasons why you want to tell a story with your data. What is your story’s purpose? Why does it matter? And to whom? Once that’s mapped out, Kat goes into the details and frameworks that compose the core pieces of a data story. The framework employed here is called the Problem-Goal-Action-Impact (PGAI) Framework.
The other building blocks include time points, your characters and metrics. Other bits and bobs that add flavour to the narrative come next, such as the impact, the reasons, the reactions and the context. Kat goes extensively into each of the building blocks, and for each section there are practical examples, followed by templates and exercises you can use to build your story.
In terms of narrative devices, The Data Storyteller’s Handbook makes use of the classic 3-acts narrative, or the “And-But-Therefore (ABT) Framework”, originally created by Randy Olson and adopted by Kat Greenbrook here. This is the narrative structure in which you’ll arrange all the building blocks you’ll have defined in the previous steps.
It goes somewhat like this:
In the first act, you set the situation, problem, questions or your character(s).
You can join the pieces that make this first act using an AND statement
BUT is a strong contrasting word that is often used to introduce the second act or conflict of your story.
THEREFORE is a consequence word used to introduce Act 3 and offer a conclusion (or reason, or result) of your story.
For example:
AND: Kat Greenbrook is a data storytelling specialist from Aotearoa, New Zealand, and she wrote an amazing book called The Data Storyteller’s Handbook.
BUT: Even though I know the book is awesome, others may not yet be aware of how great it is and might miss out on learning how to create awesome data stories!
THEREFORE: I wrote this review to spread the word, share it on social media and try my best so that more people discover it and use this great resource (because everyone should; it’s that great!).
You may think that this story has no “data” in it yet - and that’s okay! One great little thing about the book is how it first teaches you how to think in narrative terms and how to compose a good story that you can then improve upon with your data, visuals (where appropriate), or illustrations. Your data story is only as good as your understanding of the core subject, and the narrative is what sets it apart as a data story rather than just an elaborate analysis.
From here onwards, the book becomes even more practical, focusing heavily on how to turn this narrative into a proper, engaging data story.
According to the author, there are two types of data stories you can tell using these building blocks: Time Data Stories and Character Data Stories.
While the building blocks of both types are similar, the comparisons, the tension and the changes tracked and evidenced by the narrative will change - and you might need to arrange the other blocks a bit differently. But the idea of treating this process as a big Lego set, from which you can grab pieces and arrange them into a narrative, makes it quite fun and easy to follow. Don’t be fooled - the process of writing a data story is quite involved and requires a lot of work, but the book does an awesome job of taking you through this journey.
To wrap it up, the author goes through an extensive example from her own portfolio and how she applied the methodology presented in the book to the piece she built. It is a great glimpse into the process of someone who’s been working with Data Storytelling and teaching it for over a decade, and there’s a lot to be learned from seeing how others approach their work. This is a great way to finish the book and ensure we can see all the book's concepts applied to a real-life example.
Keep it honest
I have a few favourite things about The Data Storyteller’s Handbook. One of them is the extra added section at the end of each Chapter called Keep it Honest. These are little remarks, tips and warnings about how you should take ethical considerations when writing a data story.
Are you cherry-picking your data? Have you checked if the subject might affect others negatively and how? Are you being fully transparent with your intentions when creating this data story? Are your stakeholders aware of the story’s scope and limitations? All of these questions are paramount to ensure your data stories are not only effective but also used for good, with truthfulness, kindness, accuracy and care at their core. Few books talk about this subject in such practical and useful terms. It is not about preaching how something should be done, rather than scoping clear guidelines of what you need to keep in mind and take into account when adding narrative to data.
Should you read it?
This has been easily one of my favourite reads of 2023. Data Storytelling is a term that gets thrown around a lot, and although there are books out there that talk about it, few contain such practical guidance as The Data Storyteller’s Handbook does. It is well-written and accessible, has the cutest illustrations, and will easily become a trusty companion for anyone who wants to learn and improve the way they communicate their data. It is one of those books destined to have a bazillion cliff notes and page markers hanging from its pages.
It also fills what I consider to be a bit of an empty space in the field - it is a clear, concise and extremely practical guide instead of just talking about what data storytelling is or isn’t at a macro level.
I can safely say that The Data Storyteller’s Handbook comes with my highest recommendation. Go forth and tell your data stories, everyone!
Get a copy at your local library | Amazon
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