Storytelling with Data - Knaflic Cole Nussbaumer

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in the media. It happens in places where you would expect people to know better. Why is that?

       FIGURE 0.1 A sampling of ineffective graphs

      We aren’t naturally good at storytelling with data

      In school, we learn a lot about language and math. On the language side, we learn how to put words together into sentences and into stories. With math, we learn to make sense of numbers. But it’s rare that these two sides are paired: no one teaches us how to tell stories with numbers. Adding to the challenge, very few people feel naturally adept in this space.

      This leaves us poorly prepared for an important task that is increasingly in demand. Technology has enabled us to amass greater and greater amounts of data and there is an accompanying growing desire to make sense out of all of this data. Being able to visualize data and tell stories with it is key to turning it into information that can be used to drive better decision making.

      In the absence of natural skills or training in this space, we often end up relying on our tools to understand best practices. Advances in technology, in addition to increasing the amount of and access to data, have also made tools to work with data pervasive. Pretty much anyone can put some data into a graphing application (for example, Excel) and create a graph. This is important to consider, so I will repeat myself: anyone can put some data into a graphing application and create a graph. This is remarkable, considering that the process of creating a graph was historically reserved for scientists or those in other highly technical roles. And scary, because without a clear path to follow, our best intentions and efforts (combined with oft-questionable tool defaults) can lead us in some really bad directions: 3D, meaningless color, pie charts.

Skilled in Microsoft Office? So is everyone else!

      Being adept with word processing applications, spreadsheets, and presentation software – things that used to set one apart on a resume and in the workplace – has become a minimum expectation for most employers. A recruiter told me that, today, having “proficiency in Microsoft Office” on a resume isn’t enough: a basic level of knowledge here is assumed and it’s what you can do above and beyond that will set you apart from others. Being able to effectively tell stories with data is one area that will give you that edge and position you for success in nearly any role.

      While technology has increased access to and proficiency in tools to work with data, there remain gaps in capabilities. You can put some data in Excel and create a graph. For many, the process of data visualization ends there. This can render the most interesting story completely underwhelming, or worse – difficult or impossible to understand. Tool defaults and general practices tend to leave our data and the stories we want to tell with that data sorely lacking.

      There is a story in your data. But your tools don’t know what that story is. That’s where it takes you – the analyst or communicator of the information – to bring that story visually and contextually to life. That process is the focus of this book. The following are a few example before-and-afters to give you a visual sense of what you’ll learn; we’ll cover each of these in detail at various points in the book.

      The lessons we will cover will enable you to shift from simply showing data to storytelling with data.

       FIGURE 0.2 Example 1 (before): showing data

       FIGURE 0.3 Example 1 (after): storytelling with data

       FIGURE 0.4 Example 2 (before): showing data

       FIGURE 0.5 Example 2 (after): storytelling with data

       FIGURE 0.6 Example 3 (before): showing data

       FIGURE 0.7 Example 3 (after): storytelling with data

      Who this book is written for

      This book is written for anyone who needs to communicate something to someone using data. This includes (but is certainly not limited to): analysts sharing the results of their work, students visualizing thesis data, managers needing to communicate in a data-driven way, philanthropists proving their impact, and leaders informing their board. I believe that anyone can improve their ability to communicate effectively with data. This is an intimidating space for many, but it does not need to be.

      When you are asked to “show data,” what sort of feelings does that evoke?

      Perhaps you feel uncomfortable because you are unsure where to start. Or maybe it feels like an overwhelming task because you assume that what you are creating needs to be complicated and show enough detail to answer every possible question. Or perhaps you already have a solid foundation here, but are looking for that something that will help take your graphs and the stories you want to tell with them to the next level. In all of these cases, this book is written with you in mind.

“When I’m asked to show the data, I feel…”

      An informal Twitter poll I conducted revealed the following mix of emotions when people are asked to “show the data.”

      Frustrated because I don’t think I’ll be able to tell the whole story.

      Pressure to make it clear to whomever needs the data.

      Inadequate. Boss: Can you drill down into that? Give me the split by x, y, and z.

      Being able to tell stories with data is a skill that’s becoming ever more important in our world of increasing data and desire for data-driven decision making. An effective data visualization can mean the difference between success and failure when it comes to communicating the findings of your study, raising money for your nonprofit, presenting to your board, or simply getting your point across to your audience.

      My experience has taught me that most people face a similar challenge: they may recognize the need to be able to communicate effectively with data but feel like they lack expertise in this space. People skilled in data visualization are hard to come by. Part of the challenge is that data visualization is a single step in the analytical process. Those hired into analytical roles typically have quantitative backgrounds that suit them well for the other steps (finding the data, pulling it together, analyzing it, building models), but not necessarily any formal training in design to help them when it comes to the communication of the analysis – which, by the way, is typically the only part of the analytical process that your audience ever sees. And increasingly, in our ever more data-driven world, those without technical backgrounds are being asked to put on analytical hats and communicate using data.

      The feelings of discomfort you may experience in this space aren’t surprising, given that being able to communicate effectively with data isn’t something that has been traditionally taught. Those who excel have typically learned what works and what doesn’t through trial and error. This can be a long and tedious process. Through this book, I hope to help expedite it for you.

      How I learned to tell stories with data

      I have always been drawn to the space where mathematics and business intersect. My educational background is mathematics and business, which enables me to communicate effectively with both sides – given that they don’t always speak the same language – and help them better understand one another. I love being able to take the science of data and use it to inform better business decisions. Over time, I’ve found that one key to success is being able to communicate effectively visually with data.

      I initially recognized the importance of being skilled in this area during my first job out of college. I was working as an analyst in credit risk management (before the subprime crisis and hence before anyone really knew what credit

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