Storytelling with Data: a book review and my takeaways

As a child, I loved telling stories. I’d take my favorite book and TV characters and create a world where they would oh-so-conveniently meet. Say, a magical anime girl wanders Narnia until she encounters the now-villainous Power Rangers.

As an adult in the corporate world, I still want to tell stories. But now I find that people are more critical of which stories I tell them.

It must be in the form of numbers, they said.

It’s a data-driven world, they said.

In Cole Nussbaumer Knaflic’s book Storytelling with Data, she argues we can do just that: tell stories with numbers.

language + math = data storytelling

She takes traditional storytelling concepts then re-interprets them for “adult-appropriate” tables and charts. She teaches us to edit our charts, the same way authors do their stories, by borrowing principles of visual design.

My key takeaways from the book can be found below (click for larger size), but they can be summarized as follows:

  1. Context is king. The form your data will take depends on your audience and what you want them to do with the data.
  2. Choose the right graph to best express the key message (I’ve made a flowchart in my notes to help with that).
  3. Following on #1, design around this message.
  4. Present your data as you would a story, with a beginning, middle, and end.
“Storytelling with Data” notes, by dannaisadork

P.S. Sorry about the terrible handwriting. My normal penmanship’s already pretty bad, but writing on a tablet made it worse!



In my work laptop I have a favorites folder just dedicated to Excel charts.  Its got things like “Best Charts to Compare Actuals vs Targets” and “Best charts to show progress“.

I love me some charts (duh).

So when this book was mentioned during Big Data PH 2016, I knew I had to buy it. Especially since the very first example in the book (shown below) is exactly the kind of thing I do at work. I daresay I’ve probably done a variation of this in the past.

Sample chart from Storytelling with Data, page 4. Taken from Amazon preview.

The book has been fantastic for that purpose.

Knaflic had written it with the business user in mind, so everything is translatable to corporate work. So much so that the charts from my reports now look like imitations of hers.

And people are noticing. Ever since I started applying the principles from the book, colleagues have been commenting on my “amazing charts” only to be surprised when I tell them they were made in Excel.

Possibly the only part in her book I couldn’t make use of was the last chapter where she gives tips on presenting the data via PowerPoint. It may be that Knaflic’s work environment is very different from mine, but in my line of work those kinds of classroom-type settings are rare. Data is usually just sent over email, then if needed (i.e., you didn’t present it clear enough), discussed over the phone.

Also, given I first heard of this book in a big data conference, I would say this will not be enough for THAT (big data) purpose.

I feel to visualize BIG data, you need to learn exploratory data analysis. Knaflic’s book assumes you already know what message you want to say and just need data to back it up. For this other scope, she recommends Nathan Yau’s Data Points.

For most users though this book is enough. If you and your team work with a lot of charts (HINT: If you have a variation of “manager” or “analyst” in your job title you probably do), I recommend getting a copy for your team to share and keep as reference.


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