Storytelling with Data. Knaflic Cole Nussbaumer
to forecast delinquency and loss. This meant taking complicated stuff and ultimately turning it into a simple communication of whether we had adequate money in the reserves for expected losses, in what scenarios we’d be at risk, and so forth. I quickly learned that spending time on the aesthetic piece – something my colleagues didn’t typically do – meant my work garnered more attention from my boss and my boss’s boss. For me, that was the beginning of seeing value in spending time on the visual communication of data.
After progressing through various roles in credit risk, fraud, and operations management, followed by some time in the private equity world, I decided I wanted to continue my career outside of banking and finance. I paused to reflect on the skills I possessed that I wanted to be utilizing on a daily basis: at the core, it was using data to influence business decisions.
I landed at Google, on the People Analytics team. Google is a data-driven company – so much so that they even use data and analytics in a space not frequently seen: human resources. People Analytics is an analytics team embedded in Google’s HR organization (referred to at Google as “People Operations”). The mantra of this team is to help ensure that people decisions at Google – decisions about employees or future employees – are data driven. This was an amazing place to continue to hone my storytelling with data skills, using data and analytics to better understand and inform decision making in spaces like targeted hiring, engaging and motivating employees, building effective teams, and retaining talent. Google People Analytics is cutting edge, helping to forge a path that many other companies have started to follow. Being involved in building and growing this team was an incredible experience.
One particular project that has been highlighted in the public sphere is the Project Oxygen research at Google on what makes a great manager. This work has been described in the New York Times and is the basis of a popular Harvard Business Review case study. One challenge faced was communicating the findings to various audiences, from engineers who were sometimes skeptical on methodology and wanted to dig into the details, to managers wanting to understand the big-picture findings and how to put them to use. My involvement in the project was on the communication piece, helping to determine how to best show sometimes very complicated stuff in a way that would appease the engineers and their desire for detail while still being understandable and straightforward for managers and various levels of leadership. To do this, I leveraged many of the concepts we will discuss in this book.
The big turning point for me happened when we were building an internal training program within People Operations at Google and I was asked to develop content on data visualization. This gave me the opportunity to research and start to learn the principles behind effective data visualization, helping me understand why some of the things I’d arrived at through trial and error over the years had been effective. With this research, I developed a course on data visualization that was eventually rolled out to all of Google.
The course created some buzz, both inside and outside of Google. Through a series of fortuitous events, I received invitations to speak at a couple of philanthropic organizations and events on the topic of data visualization. Word spread. More and more people were reaching out to me – initially in the philanthropic world, but increasingly in the corporate sector as well – looking for guidance on how to communicate effectively with data. It was becoming increasingly clear that the need in this space was not unique to Google. Rather, pretty much anyone in an organization or business setting could increase their impact by being able to communicate effectively with data. After acting as a speaker at conferences and organizations in my spare time, eventually I left Google to pursue my emerging goal of teaching the world how to tell stories with data.
Over the past few years, I’ve taught workshops for more than a hundred organizations in the United States and Europe. It’s been interesting to see that the need for skills in this space spans many industries and roles. I’ve had audiences in consulting, consumer products, education, financial services, government, health care, nonprofit, retail, startups, and technology. My audiences have been a mix of roles and levels: from analysts who work with data on a daily basis to those in non-analytical roles who occasionally have to incorporate data into their work, to managers needing to provide guidance and feedback, to the executive team delivering quarterly results to the board.
Through this work, I’ve been exposed to many diverse data visualization challenges. I have come to realize that the skills that are needed in this area are fundamental. They are not specific to any industry or role, and they can be effectively taught and learned – as demonstrated by the consistent positive feedback and follow-ups I receive from workshop attendees. Over time, I’ve codified the lessons that I teach in my workshops. These are the lessons I will share with you.
How you’ll learn to tell stories with data: 6 lessons
In my workshops, I typically focus on five key lessons. The big opportunity with this book is that there isn’t a time limit (in the way there is in a workshop setting). I’ve included a sixth bonus lesson that I’ve always wanted to share (“think like a designer”) and also a lot more by way of before-and-after examples, step-by-step instruction, and insight into my thought process when it comes to the visual design of information.
I will give you practical guidance that you can begin using immediately to better communicate visually with data. We’ll cover content to help you learn and be comfortable employing six key lessons:
1. Understand the context
2. Choose an appropriate visual display
3. Eliminate clutter
4. Focus attention where you want it
5. Think like a designer
6. Tell a story
Illustrative examples span many industries
Throughout the book, I use a number of case studies to illustrate the concepts discussed. The lessons we cover will not be industry – or role – specific, but rather will focus on fundamental concepts and best practices for effective communication with data. Because my work spans many industries, so do the examples upon which I draw. You will see case studies from technology, education, consumer products, the nonprofit sector, and more.
Each example used is based on a lesson I have taught in my workshops, but in many cases I’ve slightly changed the data or generalized the situation to protect confidential information.
For any example that doesn’t initially seem relevant to you, I encourage you to pause and think about what data visualization or communication challenges you encounter where a similar approach could be effective. There is something to be learned from every example, even if the example itself isn’t obviously related to the world in which you work.
Lessons are not tool specific
The lessons we will cover in this book focus on best practices that can be applied in any graphing application or presentation software. There are a vast number of tools that can be leveraged to tell effective stories with data. No matter how great the tool, however, it will never know your data and your story like you do. Take the time to learn your tool well so that it does not become a limiting factor when it comes to applying the lessons we’ll cover throughout this book.
While I will not focus the discussion on specific tools, the examples in this book were created using Microsoft Excel. For those interested in a closer look at how similar visuals can be built in Excel, please visit my blog at storytellingwithdata.com, where you can download the Excel files that accompany my posts.
How this book is organized
This book is organized into a series of big-picture lessons, with each chapter focusing on a single core lesson and related concepts. We will discuss a bit of theory when it will aid in understanding, but I will emphasize the practical application of the theory, often through specific, real-world examples. You will leave each chapter ready to apply the given lesson.
The lessons in the book are