Cole Nussbaumer Knaflic understands that data is worthless if people can’t make sense of it. So she’s dedicated herself to turning even the most data-phobic businesspeople into masters of visualization and storytelling. In this exclusive interview, she reflects on her journey from Google to becoming one of the most influential voices in data visualization since Edward Tufte, plus she gives us a preview of her new book, a follow-up to her bestseller, storytelling with data: a data visualization guide for business professionals.
How did you go from being an analytics expert inside Google to becoming a bestselling author and successful consultant?
My whole life, I’ve always been drawn to the intersection of mathematics and business. That’s my educational background, and when I worked in banking, straight out of undergrad, I discovered how making data visual makes it accessible in totally new ways.
I flexed these skills early in my career, and then I landed at Google. I worked on the People Analytics team in an analytical role in the Human Resources organization—a role that was at that point unique to Google. I discovered there are parallels in the analytics you can do with people and the analytics I'd been doing previously with loans. If you take, for example, predicting someone's likelihood to default on a loan, it’s somewhat similar to predicting when someone might leave an organization. That gave me the chance to hone my data visualization skills in a completely new space.
Eventually, I was asked to teach other people how to do it. I developed a 90-minute internal training course and it attracted broad interest. I had the great opportunity to travel around the world and teach Google employees this content, and I soon recognized that this skill set isn’t needed by Google alone—that most people can have greater impact in their day-to-day work life if they learn how to visualize data effectively and communicate with it.
And that led to you starting your own business?
Well, I started getting invitations to speak outside Google, and I was fortunate to have a very supportive manager at the time who let me do that. I was able to build the business while I still had the benefits of the day job, so that by the time I left Google, it wasn't as much of a jump as I think someone would typically have, because there was already a proven demand there.
But still scary, yes?
Oh, yeah. I think anytime you leave a stable career and go do something on your own, it’s scary. If someone's not scared by that, then maybe they're doing something wrong.
What were the challenges you had to deal with at first?
One of the hardest things, and a lesson I still struggle with today, is how to say “no.” I imagine that this holds true for most people who just start out. You want to say yes to everything. I'd go into an organization, spend half a day with a team, and it would be common that someone would reach out afterward and want some ongoing consulting. And those are hard things to say no to, right? But I discovered very quickly that if I didn’t, I wouldn't have the bandwidth to be out teaching. And for me, teaching is the way to reach more people.
What criteria do you use to decide whether to say yes or no?
For me it’s about reaching people. Being able to get the message out to the most people has always been the driving force behind everything I do. Saying “yes” or “no” means stepping back and thinking about how we do things in a way that is scalable and won’t limit our ability to reach more people later.
Reflecting on it, I think having a family gave me a good reason to say no to a ton of stuff. That made me focus my limited time on the spaces where I do my best work and where I enjoy working the most. I wouldn't have been able to point that out at the time, but I think it’s one of the things that set the foundation for a successful business.
When it comes to scale, your book storytelling with data is a pretty unbeatable asset, I imagine. Tell me how you made that happen.
It's funny because my husband always gives me a hard time about this. He says, “I always said you should write a book, but it took you a long time to listen to that advice!”
I could only write the book after I’d done a ton of workshops and I was able to codify the lessons in a way that was teachable. That's where it came from. One of the things that was critically important was to make the book something that anyone could pick up and get something out of. I didn't want it to be intimidating.
And data can be pretty intimidating to a lot of people.
Well, for people who are used to working with data, it's easy. They don't think twice about it, and they have really complicated conversations around it and use words that are maybe more difficult than they need to be.
But data scares a lot of people who aren't using it day-to-day. And the thing is, more and more people, in all sorts of different roles, are being asked to use data in some way now.
I don't think you have to be a quantitative analyst to be able to do great things with data. And so I mapped everything out, and I wrote the book basically a chapter at a time. I have a dear friend who has a history as an editor and has no background in data whatsoever, and she was my first reviewer. And that was such a useful thing. Anytime anything was confusing or just more complicated than it needed to be, she was the first lens, and I would write and rewrite and rewrite until it made sense to her. Coming back to your point, I think one of the reasons the book has been popular is because it's simple. Tips and tricks. A lot of the advice and strategies are just common sense when you step back and think about them.
How do you help people become creative data storytellers?
A lot of it comes down to thinking deeply about the audience. It's easy to make a graph for just yourself about your data. But there's a paradigm shift that has to happen to make a good graph that works for someone who is different from you. You have to think first and foremost about what works for your audience. You have to truly understand them. The challenge is that your audience doesn't live in your head. So to make clear something important in your data to someone else, you have to take intentional steps in how you design the visualization. There are some relatively simple things that you can do to facilitate that understanding. For example, using color sparingly, getting rid of things that don't need to be there—just being thoughtful about how you design, and how your audience will process it.
What value do corporations or other organizations get when they hire you? Why is it worth the investment?
Yeah, it's a great question. People increasingly ask me things like “What is the ROI on this?” And there's no easy way to answer.
Here’s how I think about it. We have more and more data every day, and with that comes the need to make data-driven decisions—to do smart things because of the data we have and what we can learn from it. There’s also a huge and growing demand for data scientists, people who can interpret data and make sense of it. Companies are doing big searches to find these people and they’re paying them huge salaries. But if those people can't communicate effectively, that money is wasted.
The skills that are needed to translate data into information that's meaningful, that resonates, that people can do something with—these are critical skills for modern businesses.
Data is malleable, and people can use it for good or bad outcomes. Do you focus much on ethics and integrity?
Yeah, absolutely. The underlying principle is that you should never bend data to make it say what you want it to say. There may be people who want to intentionally mislead with data, but I feel that that’s the smaller population.
The bigger, and maybe even scarier problem in some ways, is when people inadvertently do wrong with data, not on purpose, but by virtue of not being clear on the assumptions they're making, or on what pieces might be missing.
How then do you handle data in a way that is unbiased?
A lot of people ask that question, and for me it doesn't even make sense because everything we do when we touch data biases it, right? We are biasing the data when we figure out what to collect in the first place, and then when we make decisions about how to aggregate or disaggregate it, and what we choose to show and how.
So how do you proceed with integrity? What’s the North Star?
The underlying idea is that we need to be ethical. That means doing the best we can in terms of both understanding the data and then communicating it in the right way. The goal shouldn't be unbiased data because that doesn't exist. The goal should be to be as robust and thorough in our analysis as possible.
I think it's the responsibility of everybody who works with data to hold each other accountable and ask tough questions. As an analyst, you need to consider alternative hypotheses, to use your colleagues or others around you to play devil's advocate and try to poke holes. It's a hard thing to do on one’s own.
Great insights. Tell me about your new book.
The new book is called storytelling with data: let's practice!, and it's a practice book. It takes the content of the original book and makes it even more practical through additional examples and exercises.
Each chapter includes three exercise sections, the first of which is called “Practice with Cole,” where I pose a problem or a case study that you're meant to first work through on your own, and then I present my solution as a way of illustrating the thought process. The second exercise section is “Practice on Your Own,” with similar exercises and examples but without prescribed solutions. And then the third section is “Practice at Work.” There will also be more updated content and a ton of additional examples.
It's a fun one. And it will be available Fall, 2019.
Fantastic—I cannot wait to see that. One final thing. I know that you’ve moved out of Silicon Valley to Wisconsin. How is this new chapter in your life going?
It's been amazing. My husband and I had been in San Francisco for ten years and we just needed to get out of the craziness of the city. We have little kids and so wanted some space and to get close to Grandpa and Grandma. Silicon Valley is an interesting place, obviously a very influential place for me because a lot of this started there. But I’m enjoying having more time to spend with my family and get some perspective on some of the other things that are important in life.
Sounds like a dream come true.
Yeah, it does feel that way. I know that I'm very fortunate that my work allows for this sort of flexibility. And I am appreciative of it every day.
To learn more:
Check out Cole’s website here.
Order storytelling with data here.
Watch Cole below: