Nancy Duarte, author, speaker and principal and chief executive officer of Duarte Inc., sits down with Matt to discuss data, storytelling and how to effectively communicate data with a human-centered approach. Duarte Inc. is the largest design firm in Silicon Valley and the fifth largest employer in the Silicon Valley area. Find out more about her company: https://www.duarte.com/nancy-duarte/ and listen to her TED Talk: https://www.ted.com/talks/nancy_duarte_the_secret_structure_of_great_talks?language=en.

You can feel them in the room and you're lit up by their passion. And you'd follow them anywhere. That kind of abilities, rare.

Excellence, professionalism, innovation and collegiality. These are the values the salmon, Walton College of Business explores in education, business and the lives of people we meet every day. I'm Matt Waller, Dean of the Walton College, and welcome to the be epic podcast. I have with me today, Nancy Duarte, who's a principal at Duarte Inc, which is a firm in the Silicon Valley area. It's the largest design firm in Silicon Valley, as well as the fifth largest female employer in the area. They have a very impressive list of brands that they worked for, including Apple, Cisco, GE, Google, HP, World Bank, and others. She's the author of six books. And she has a very popular TED Talk that is been viewed by 2.5 million people. And I just finished reading a book by her called data store. And I really liked it. And we're going to talk a little bit about that today as well. So Nancy, thank you so much for taking time to visit with me about this.

It's great to be here, Matthew.

So So Nancy, I also noticed that on LinkedIn, you have 181,000 followers, which, which is a lot. And I read some of your LinkedIn articles, and you started writing LinkedIn articles back in 2013, when it was kind of a rare thing. And I also see that you started your company back in 1990. So you've been doing this for 30 years, your company's been through the.com, boom, and bust. And many other things since then, including COVID-19. Yeah. How did you get interested in design?

I love that question. You know, my husband actually started the firm in 88. And I joined him in 90, and he's a fine artist. Beautiful. I mean, just stunning. In fact, he's back to his fine art, I fell in love with him, because it literally like in the eighth grade, this whole chalkboard was transformed into a scene of a forest. And I was like, who did that? Because I think I'm in love with him. And sure enough, I married him, but I think he's taught me and teaches me how to be an appreciator of anything beautiful. So I'm way more visual than verbal. And I've always had a very strong appreciation for beautiful things. So when my husband became a technical illustrator and wanted to start the company, like he and I literally checked out all the books from the local library about design about, like, what is typesetting? What is this, and this was like, the Mac was only out for like a year and a half or two. So I didn't get a degree in design. For some reason, the present the internet thinks I'm a presentation designer, but I'm not. And so I just went on a journey falling in love with design, wanting to be followed around by designer so they could clean up anything I made that was ugly, and make it just effective and beautiful. So that was kind of a roundabout way of answering Yeah.

You know, again, your your TED Talk. It, it's on the secret structure of great talks. And I found that very interesting. Your your whole notion of, you know, what is and what could be as a structure and alternating between them. I actually tried it after I watched your TED talk. And I noticed it definitely made a big difference.

Oh, yeah, that was fun. Because I I've gone through about a three and a half year journey through storytelling and, and the gap between what is and what could be is one of the things that a great story does in the sense that you get, there's this rise and fall this cathartic rise of tension and then the release of that tension. And to do that in a great talk. You use this tension between the current realities and the future opportunities. And you just create, like, here's, here's what it is, here's what's going on. Here's what our current state looks like. Just imagine our future could look like this. And it's an influential device and it creates that rise and fall that beautiful storytelling does. And so that was a blast. Yeah, that was 2011 Yeah, I wasn't expecting it to explode like that, it's had quite an impact on on my business to have a successful TED Talk. So I appreciate you that you enjoyed it.

Moving on to the book now, let me back up a second, one of the reasons I was looking for a book on this topic was because we have really emphasized data science. At the University of Arkansas, we have a interdisciplinary undergraduate program and data science, but we also have several specialized master's programs that use a lot of data science and and more of it's in our MBA programs now. And we have courses specifically on data visualization. And I've not been super impressed with some of the data visualization curriculum that I've seen. And so I really was just Boundary spanning a little bit. And I saw that you popped up with that book. And, and I recognized you. I think I read.

Yeah, maybe,

Because I've watched it a few times. And so I went ahead and bought the book, and I read it, and really liked it. One quote you have that really like his data doesn't speak for itself. And it needs a storyteller. That's your quote. And it's, it's kind of it's an interesting quote, because a lot of people, you hear the phrase a lot, the data speaks for itself. But clearly, it doesn't speak for itself. It needs a storyteller. And what, what led you to that thought that idea?

Yeah, you know, a lot of times that people, I kept hearing them say that, and I thought, well, if data could speak for itself, it could say, Hey, I found this problem over here in the data, go do something about it. Well, it can't do that. Like it can't do that. So when you cruise through data, and or you're using data, or the purpose of even having data is to find a problem or an opportunity in the data, that's it, it's pretty binary, I haven't had anybody say that it's anything other than that. So you created the data, you find a problem or an opportunity. And you're done with the data at that point, at that point, you have a communication problem, you need to say, oh, we need to do this about the opportunity I found in the data, or oh, we need to do this about the problem I found in the data and it becomes a communication problem. And so the data can't solve your communication problem. You a human has to solve that a storyteller has to solve that. And so that's how I demarcate between once you're done analyzing the data, you communicate it. And there's a real big distinction to me, between those two things.

Well, I know, early on in the book, you mentioned that, you know, you explain data with empathy, if you want it to be effective. Uh huh. What do you mean by that?

Yeah, that's a good question. So you have to understand who you're going to be communicating this data insight to. And you need to not only use this kind of channel in which they consume information, the level of density of information they may be able to receive, like, some people, you may, you may need to go present to the board at your company about this finding. And some boards do it as a formal stand up presentations, others want to get a pre read, and they want to read a document and only have a discussion about the data like you need to know who you're communicating to how senior they are in an organization, because there's certain ways to communicate data that appeals to the executive suite, you just kind of know and profile them, and then say, and then tee up the data and the findings from the data in a way that they process information, and in a way that they can make decisions from the data quickly. So it's the whole book is around them for empathy, even about how you visualize the data that you found create can be done in an empathetic way. Because data scientists I think they love the whiz bang nature of some of these tools and love to output charts that are complex, so they look smart. Well, you need to empathetically think about if you're talking to a broad audience, you need to take your findings and make them consumable to them and maybe talk about the findings in the logarithmic scale. Instead of feeling compelled to show them you know how complex the data was. If you do show how complex the data is, then show the findings of the data in a very simple tool. The takeaways from the data need to be visually simple.

You know, in your book, you talk about inspiring others with data in a way that causes the inspiration to stick And would you mind sharing a little bit about the idea?

Yeah. So when you're presenting data, there's certain ways that you can make it go from being relatively neutral and emotional appeal. And then you can also do things that make it have a little bit of an emotional appeal, for example, you could state a statistic, and it could be really big, huge, it can be a huge statistic. And, and people can't get their head around huge statistics. And so you could connect it to something relatable, like you could say, like, I could say, That's like going to the moon eight times is going from the, from the Earth to the Moon, and back eight times. That's how big this number is. It's like, well, I've not been to the moon, have you been to the moon, I'm not been to the moon, what you what you could say, if you were to drive your car there, at the speed limit, it would take you 42 days, 24 hours a day, that's a more consumable number. So what you could do is take the scale of a number and apply something to it that makes it more relatable and comprehensible. And that adds just the right amount of lift and connection to the data to make it stick. The other thing you can do is instead of just throwing a chart up there, like a bar chart or a line chart, just throw the whole chart up there. Instead, you could say, q1, we were amazing. Ah, q2, we faltered q3. What the heck were you guys doing? Guess what? And then you click q4 You guys nailed it. Oh, my gosh, you did the despite fantastic recovery. And it's so different. Otherwise, you could just you could put all four of those bars up on a chart. people be like, Yeah, but if you create suspense by revealing it over time, it makes the data have suspense in it. And suspense is an emotional reaction. So it's just stuff like that, like that whole fourth section of the book has all these different ways that you can state data, it's not about manipulating it whatsoever, you can state data in a way that makes people feel something about the data.

You do spend a good bit of time in your your book talking about how to use data to tell stories to engage our senses. And what advice would you give us for really being able to do that effectively?

I mean, some of it is very similar to what, what I was talking about is the ebb and flow of how you humanize the data. Like for example, a lot of people forget, when we're digging through data that humans probably created that data like we are being tracked, like you can't even date somebody without data being collected about it can't even walk down the street without data being collected. And so there's massive and massive amounts of data. And sometimes when we're in business, we get, we get disconnected from the humans that generated the data. Like you could be just like sales numbers are down, well, well, that doesn't mean your sales teams incompetent, maybe you put in some new policy that's making them ineffective, like, go and talk to the people generating that data, to see if there's some way you can turn the trajectory of the data and or direction you want it to go. You could show pictures of the people generating the data. So often we talk about, you know, our customers are we talk about the poor, or we talk about people that really literally took a survey, but we don't know what they look like, or, or you know, somebody who has specific types of, you know, ailments that we track and try to solve. It's just like, it just makes us realize, oh, wow, that's right, that's right. Behind this number is a human that generated a statistic that made this number true. And so that's just one of the other examples in the book.

The idea of big data. So data just keeps growing at an exponential rate. Right. Right. And, you know, there's really sophisticated, you know, methods of analyzing data. And that's actually one of the things that caught my attention about your book, because it almost seems to me like there's an overemphasis on esoteric analysis of data, then results in things that are very difficult to explain. and higher education tends to emphasize, at least from my perspective in business, think there might be a heavy emphasis on things like the technical technicalities of econometrics and stochastic processes and you know, but but the real challenge is if you know, if you want to take the data and be able to make better decisions, and lead, you really have to be able to influence people and communicate with them. From what I see, you know, a lot of effort goes into capturing this data, cleansing it harmonizing the analyzing it. And then a little bit goes into figuring out how to tell a story with it. And so I wonder, do you think people are getting better than or do you think some of this, like artificial intelligence and machine learning and this sort of thing might actually be taking us in the other direction?

That's, that's a good question. Here's my take. I think that people who just analyze to prepare, analyze, visualize the data, if that's their only role, is to just prepare it for someone else. That role can be replaced by a I like even a tool like Tableau will say, you put your sales data in there, and it would say, it could tell you, Jim had a lower q3 this year than last year, like it'll suggest and prompt potential findings, even like, it won't just flip you the chart, it'll flip you the chart and give it a rough cut of what you may want to look at. That's AI, right. So if that kind of stuff, like put the data in and cough out a potential finding from the data that could replace a lot of roles in data. So if people aren't willing to take the next step and say, Oh, well, AI suggested q3 over q3 was low, I knew that. The big interesting thing, because a human is looking at this and not AI is this other anomaly that this system wouldn't know was an anomaly unless it knew our strategy, right? So you can see how you move from just analyzing the data to becoming a strategic adviser around the data, those are two completely massive gaps in skill. And so I think that people need to realize AI is going to be a real thing. And AI can take it so far. And we need to become communicators of the data, and synthesizers have multiple resources of data, like the company strategy, like, I don't know how you would even put that into Tableau. Like, like, you know, like, it's like, okay, that's fine. Like it could be, yeah, we needed to be down in q3, because we just are moving from a product based organization to a subscription based one, I was completely expecting q3 to be low right now. So it should have coughed up a different set of answers for you from that same data. So it takes a human right now, still, but AI is taking it pretty far.

That's a good answer. So Nancy, we have the Walton College, over 6500 students, and graduate about 1400 undergraduates this year, and a few 100 graduate students as well, what advice would you give them in terms of, and it doesn't just have to be about explaining data, through story could be about anything that because I know, you, you're you also are an expert on telling stories in general, and communicating. So what advice would you give them?

That's a great question. You know, the number one skills gap right now in the world by millions and millions, his soft skills, and in soft skills has things like influence, and they're finding that people don't know how to communicate, they, they just don't how to communicate. And in the workplace, they're not coming out of university, knowing that well, and then the programs are within companies aren't that strong. And so that's why we're, we have this great body of work. And we have a really big training organization to try to solve that, if you think about, so if they work on their communication skills, they will show up stronger than different than better than the other people that are competing for some of the same jobs. The other thing that I feel really passionate about which all my Bodies of Work focus on is the spoken word, too. So if you think about the spoken word, it, it makes the invisible visible, it starts movements, it takes the can make something out of nothing. And it's just such a beautiful thing when your heart races and you hear someone and you see them, and you can feel them in the room and you're lit up by their passion, and you'd follow them anywhere. That kind of ability is rare. And I really think that if if young people could really really understand its power and adopt a discipline and being a student of that kind of influence. It'll really shape not only their own careers, but hopefully a bright future of human flourishing in the world.

Well, Nancy, thank you so much. For all the work you put into writing data story. It really is helpful and I know you're Ted talk that I mentioned, goes back to 2011. But I think it's still terrific. I would encourage the listeners to to watch that as well. But I really appreciate you taking time to visit with me. Thank you so much.

Thank you.