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Let’s Practice Storytelling with Data with Cole Knaflic’s Book



Today’s guest is a woman who has had a formative impact on my journey and whose latest book is my new desktop Bible for data presentation.

Cole Nussbaumer Knaflic is the CEO and Founder of Storytelling with Data, a company providing workshops and presentations that teach the basics of data visualization and how to tell compelling stories with data through theory, practical application, and clearly articulated and demonstrated lessons.

She is the author of Storytelling with Data: A Data Visualization Guide for Business Professionals and her newest book, Storytelling with Data: Let’s Practice.

She is also the host of the Storytelling With Data podcast and this year, her company launched a Storytelling with Data community, an online community where you can practice in a low risk setting.

The community is highly engaging and members have the opportunity to give and receive feedback and engage in conversations with others.

In this episode, Cole shares the wisdom of her book which is packed with real-world data examples, business scenarios, and brainstorming exercises.

In This Episode, You’ll Learn…

  • How Cole’s passion for making meaning out of data came to be.
  • All about Cole’s latest book, Storytelling with Data: Let’s Practice.
  • The five-phase SWD storytelling model to nail your data stories every time
  • How to apply classical narrative structure in a business context
  • How to help your audience with transitions between the data they are familiar with and the data they need to know.

How to Keep Up with Cole:

People, Blogs, and Resources Mentioned:

Thanks for Listening!

Thanks so much for joining me. Have some feedback you’d like to share, or a question for Cole? Leave a note in the comments below, and we’ll get back to you!

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And finally, don’t forget to subscribe to the show on iTunes to get automatic updates and never miss a show.

A very, very special thank you to Cole for joining me this week. And as always, viz responsibly, my friends.

Do you have a burning question for Cole about how to turn your data into an impactful and actionable story?

Lea Pica: Happy days of holly. Lea Pica here. Today's guest is one of my data storytelling idols and she's back on the show to help you practice to make perfect. Let's find out who's closing out the year on the Present Beyond Measure Show, Episode 52.

Lea Pica: Hey guys, welcome to the 52nd episode of the Present Beyond Measure Show and the final show for 2019. Ehrmagerd, but don't worry, it's not over.

Lea Pica: I have another one really closely queued up for January. You're gonna love it and you won't have to wait for long. This is the only podcast at the intersection of presentation, data visualization, and digital analytics and marketing. This is the place to be if you're ready to make maximum impact and create credibility and indispensability through your thoughtfully presented insights. So I'm really excited because I just signed on to be a speaker at the Observe Point Virtual Analytics Summit in January of 2020. I participated in this summit a few years ago and had an absolute blast. And I have to say it's a really quality event. They get some incredible speakers in their lineup. And also, it's completely remote. No need to book travel. No need to stand on line waiting for those cookies at the end during the networking break. So you don't want to miss it. It's totally free. And you can find all of the information at the link. I will be speaking about my three pillars of presentation and enlightenment. So you don't want to miss it. Can't wait to see you there.

Lea Pica: So I just want to dive right in because this interview was mind-blowing. This is one of the people that has had a formative impact on my own journey as a teacher and trainer of data storytelling. And it was really exciting to have her back on the show talking all about her latest book, which has become my new desktop Bible for data presentation. Let's not waste another moment. Let's dive in.

Lea Pica: All right, guys. I'm so excited to finish off the year with one more incredible guest. She has a big thing for turning data into pictures and stories. And she's the author of the wildly popular blog and bestselling book Storytelling with Data, A Data Visualization Guide for Business Professionals. It's a book that I recommend to every single person I speak to, students and everything. So for nearly a decade, she and her team have delivered interactive learning sessions, sought after by data-minded individuals, companies and organizations all over the world. And she is a returning guest, having first appeared on this show in episode twenty-three. She has her own podcast, Storytelling with Data Podcast. She has an awesome monthly challenge, which you should absolutely check out and participate in. And she's here today because she's graciously returned to discuss her new practice book and my new desktop Bible. This thing is no joke, bible for a compelling data stories. And it's called Storytelling with Data: Let's practice. So please help me. Welcome back to the show. Cole Nussbaumer Knaflic.

Cole Nussbaumer Knaflic: Hi Lea, thanks for having me back.

Lea Pica: It's my pleasure. All you have to do is watch your book and use it.

Lea Pica: So for anyone who may not have heard the first episode. I discovered you a few years ago through Stephanie Evergreen's online course, and I followed you for years, and I was always drawn to your very simple and practical approach that didn't feel dogmatic or extreme or judgmental. I really resonate with that. And you've made it into many of my workshop keynotes. And, you know, even this book has inspired some new thoughts around work. I've done like a flow graph. I'm just so appreciative of your contribution. But I'd love for you to tell us your audience story. How did his passion for making meaning out of the data company?

Cole Nussbaumer Knaflic: Yeah, it's so for me, it's been an area of interest for a long time. Going back to school, I studied mathematics and business and I've always been really interested where those two things intersect and where you can take numbers and make them meaningful for people. And one fantastic way to do that is to take those numbers and make them visual, right when we turn numbers into pictures and graphs and charts. We make them understandable and accessible in totally new ways. So I started off in banking career-wise doing statistical loss forecasting and really enjoyed the visualization piece of things. So sort of as data visualization was starting to become a thing. And it started out just playing around with different colors and different graphical forms. And what I started to recognize was when I paid more attention to how my graphs looked, people paid more attention to my graphs. So it started being this self-reinforcing cycle.

Cole Nussbaumer Knaflic: Fast forward from banking. I worked at Google for a number of years on the people analytics team and so had this passion around churning numbers into pictures and stories. And at Google had the opportunity to develop a course on visualizing data and travel to our offices around the world teaching people these courses. And word started to spread. I spoke at a couple of conferences and people started reaching out saying, hey, we heard you do this. Can you come to do this for us as well? How to turn our data into pictures. And fast forward over the course of the last decade. And what started as a passion project has turned into a company where we were small but mighty.

Cole Nussbaumer Knaflic: We have a team of data, storytellers who deliver workshops and presentations to people all around the world. And the goal really is to help people and organizations make graphs that make sense and then weave those into stories that can inspire action.

Lea Pica: That is amazing. It's so incredible how every great mission starts with like a small spark of an idea of doing something different. And now you've turned it into a movement. You know, you have such a passionate following and especially through your challenges and whatnot. And I think what really sets you apart is how you involve the community in there in honing their own practice and skills.

Cole Nussbaumer Knaflic: I feel like, we have so much to learn from each other. Right. This is a space where there are no experts. Everyone, even people who've been doing this for a long time can get increasingly nuanced in how we look at data or how we show that data to others or the words and the understanding that we help build around it. So I think there's a ton of benefit that comes from talking with other people. And one of the things that become really interesting. So we spend a lot of our time doing workshops where we'll go into organizations, spend half a day or a day with a team and they'll share examples ahead of time. And we use that as the basis of some of the hands-on exercises. We go through makeovers that we can highlight some of the lessons and show them applied to the group's own work, which tends to be really eye-opening. But one of the interesting things for us is seeing all these different examples across all these different industries. And pretty much everybody struggles with the same sort of idea.

Cole Nussbaumer Knaflic: And so there's value in being able to turn that into things to share back because there's also an interesting thing I think that happens when we try to practice on something that's outside of our day today because when I'm in the data that I'm working with every day, I'm naturally making assumptions. And I have a lot of tacit knowledge and I may not even think through some of the decisions that go into that, whereas if it's new data from a new space, it just opens up our minds. I think to think about things more openly or try something new or recognize when we need to define something better. And so being able to provide those examples back to folks as discussion points or specific things to be able to try out. And that's really where the practice book comes from. We've got all of these examples from all sorts of different industries. How do we turn that into things that not just people in our workshops get to learn from, but that everybody can learn from?

Lea Pica: Right. And so much of that, so many of those examples, I would imagine, were sourced from the companies that you worked with.

Cole Nussbaumer Knaflic: Yes. So all of the examples from the Practice book are actual real-world examples. We've had to take some steps to cause them, to make them not give away any confidential information, but they're all based on real examples that somebody dealt with and was trying to resolve.

Lea Pica: I really resonate with what you just said about people thinking that they're the challenges they're experiencing are unique to them or they're the only ones that have this problem. I hear that a lot with my workshop students that I'm like, oh, you're so cute. You think you think you're the only one? No, like, there's this challenge is so endemic, you know, across organizations. And I think that what the power is of what you and I are trying to do is actually create a fluency in that language, which so many organizations don't have naturally yet.

Cole Nussbaumer Knaflic: And it's simple things that people can do. Right. And it's a lot of the stuff. I'll preface some of the things that we say at the workshops that this is going to sound obvious. Once we say it right, some of this stuff you don't think about like, you know, how are you using color? How can we be thoughtful and sparing and strategic about that? Or, you know, what sort of stuff has entered its way into your graph or you're visual that maybe actually doesn't need to be there and is distracting from your message. And so it doesn't take highly technical skills to do great work with data. It means being thoughtful. And that's one of the reasons I think this space is so much fun. As you know, everybody is increasingly being asked to do more with data, even in roles that traditionally didn't touch data. And there are things that we can all do to do that better. Right. In a way that's going to be more accessible for our audiences and really designing with the end-user in mind so that we can help move them towards actions or not, just putting data out there for the sake of it, but that we're helping someone understand something new or do something in a better way.

Lea Pica: I completely agree. I also explain that you don't need a Ph.D. in neuroscience or design in order to create effective visuals. And for me, the two keys are awareness and like intentional awareness and simplicity.

Cole Nussbaumer Knaflic: On the awareness piece. And it's an interesting one because I think what happens really easily and what comes most naturally to people, which makes sense is it's easy for me to design a graph for myself or for my project, right, for my data. It's a much harder thing to design that graph for my audience, which is the paradigm shift that we have to make. Right. Because when we're visualizing data for explanatory purposes, it beats because we're trying to help someone else understand something better. And when that's the case, we need to keep that someone else in mind. And yeah, make decisions that are going to help make our data easier for someone else to understand. So if I made a graph, I always know where to look. But to make that clear to someone else, have to take intentional steps. That's where the lessons and the tips and the books and the workshops really come into play.

Lea Pica: Yeah, I love it. So I'm so excited to dive into this book. So this is a follow up to your first best selling book. It's one of my other Bible. And does someone need to read the first one in order to make the most out of this book?

Cole Nussbaumer Knaflic: No, they're meant to be standalone. And the way I differentiate the two is straight-talking with data. The Origen. Which came out in 2015. It's really the foundation. It goes through the six lessons on how do you put together a graph that makes sense to someone else. How do you start thinking about the story when it comes to how you present that information to someone else? Go through a number of case studies and lots of tips and examples. Let's Practice is a totally different sort of book and book almost feels like the wrong word for it because it's meant to be an experience because I'm a strong word that the way to get good at this stuff is just to do it and practice and try things and to learn from what works and what doesn't work. And so the practice book follows the same key lessons as the original. But each chapter is divided into three sets of exercises. There's practice with coal where I pose an exercise, write a scenario, something you're meant to solve and you run to solve it on your own. But then I also go through my solution as a way of introducing a ton more examples. Tips, tricks, insight into the thought process and more of the sort of corner cases. So if you like, in the first book, everything was very easy, cut and dry, right? The data was always perfect. We could always get our audiences by an immediate, which is not reality. And so there are a lot more nuances that we're able to work in through the various examples in the practice book. So Practice with Call is the first section of exercises and that's followed by practice on your own. So these are similar sorts of canned exercises, but without any prescribed solution. So these will be useful for the individual who wants to just undertake more practicing.

Cole Nussbaumer Knaflic: The manager wanting to assign things to upskill their team or university instructors who are teaching from the content because there's basically no end of exercises you can make out of mixing and matching or subbing in your own data for some of these. And then the final exercise section within each chapter is practice at work, which is OK, you've done this in theory, you've done it with some canned examples. Now let's take a project. You are facing in your day to day and break it into its component pieces. All right. When should you get feedback? Who should you get it from? How should you do that? How do you set good goals around this stuff? How do you shift a culture at an organization for allowing time and patience for doing some of this stuff and really takes the practical application on the job? So each chapter starts off with a recap. And actually, I worked with Catherine Madden, an illustrator who's based in San Francisco, and she's fantastic. Illustrations are amazing and right to get to work with someone else on some of these things. Catherine has a superpower for being able to take words and concepts and make them visual. And so I basically gave her an outline of each of the chapters from the first book. And so let's practice each chapter starts off with a little bit of context. And then her two pages illustrated the spread of the main lessons from the first book. So for someone diving in, they'll get a refresher upfront if they've already read the first book or an overview if they haven't. And from there can dive straight into the exercises and we'll get all the content that's needed from the practice with call exercises.

Lea Pica: Beautiful. Wow. It is packed with amazingness and I can see what you mean. It feels very different than a traditional book just walking you through a lot of theory. It really is about the application. So I created in my questions kind of in the form of this five-step structure that you have for your process. So I'm going to follow that for this interview. And the first one is about understanding the context and that might be the request that you get or something you're finding in your own data. One of the first tools I saw and I loved was this big idea worksheet.

Lea Pica: I was wondering if you could tell us more about that.

Cole Nussbaumer Knaflic: Yeah, absolutely. So this was actually inspired by something that Nancy Duarte wrote about in her book Resonate. And she goes through the big idea worksheet. And it's something that I've adapted and that we've been using in our workshops pretty much since what feels like the beginning of time now. It's a very simple thing.

Cole Nussbaumer Knaflic: It's one sheet that asks you a few questions about what you're doing. Right. Who's your audience? What do they care about? What motivates them both in terms of know the things that they're inspired by and the things that they're scared of? And what action are you trying to incite? And so break it up into these component pieces, right. Who's your audience? What do they care about? What do you need them to do? And then at the bottom of the big idea worksheet is your box where you're meant to fill in the big idea, which is a single sentence that articulates your point of view. It conveys what's at stake and it's not what's at stake for you, but rather what's at stake for your audience. And it's a complete and single sentence. So in our workshops, we have people work their way through this worksheet for a specific project that they're working on currently. And so people spend five or ten minutes filling it out. And then partner up and they spend another 10 minutes or so reading their big ideas to each other and going through the Q&A that ensues and helping each other refine. And it's always a very interesting exercise and coached people to pick somebody who has no idea we're going to talk about because actually, that lack of knowledge can be helpful when it comes to them feeling free to ask all sorts of questions to really get at an understanding because it's very easy to create and what you think is an awesome sentence. Right. And I've done this before. And then you say it out loud to someone else and you're met with like, I don't know anything about sort of phase or a barrage of questions that you weren't anticipating.

Cole Nussbaumer Knaflic: And it takes going through that to realize. I think it helps point out that the words that we say that we're totally clear for us may sound like they're spoken in another language to someone else. And so this practice of both pausing and thinking about our audience and what we need to communicate to them, but then also running through that with someone else. Right. Because if we think of the spectrum of familiarity someone has with what you're going to be talking about, you know, you're at one end of that spectrum. You're intimately familiar with what you want to get across. You're your partner without any context is on the complete opposite end of that spectrum. And the whole point is your audience probably isn't over there with the person who has no context, but they're also not right there with you. And so by getting out of your head, having this back and forth with someone who's less familiar, it can be really helpful for getting at the gist of what we need to get across, because then that becomes like your guiding North Star as you plan your content. You can ask yourself after you've taken the time to do this for any bit of content you are debating do I include, do I not? You can ask yourself, does this help me get my big idea across? And so taking this little bit of time upfront helps us form more targeted communications.

Lea Pica: I love that it sounds so close to a similar tool that I pulled from TED that I use in my workshops, which is called the through-line. So every single TED talk has to have a single sentence that encapsulates every single idea and every idea presented in that talk must hook onto it as if it's like a clothing line. That's why I love the visual of that. So I think that's I think that's probably the first thing that's really missing from so many of our presentations is, you know, especially in the digital marketing field, which, you know, is what I who I cater to a lot of times we're asked for these FYI check, read out check-ins sort of things where they just kind of want an update across every channel and you touch on every channel and you pretty much say nothing really new is happening.

Cole Nussbaumer Knaflic: Well, and that's the thing. Right. And there is a need for those sorts of things, because for me, you know, regular dashboards, regular reporting's right all at the same bucket. And that doesn't mean no, we don't do that. That's serving a different purpose. Right. But it does mean you could think about maybe you put a cover on the front or a couple of pages up front that says, hey, all the regular stuff's there for the most part and there's nothing new. But you can go through it or we can go through with you to your heart's content. But here, pulled out upfront, applying the lessons that we cover in the workshops and the books are the things you do need to pay attention to this time, because I think they do want a story.

Lea Pica: I'm not sure. You know, I think a lot of times they think stakeholders may say, well, I want to know everything is hunky-dory. I want to know that, you know, all systems go. And yet that thing that drives our human side is where's that conflict? Where are you know, where's the thing that problem we can solve?

Cole Nussbaumer Knaflic: It takes developing trust in order to do that. That's right. One nice step in-between where people don't feel like you've taken anything away. Right. Because if you would take that scenario, you say, well, I'm going to take away the regular stuff and instead met you a story about the things that are important this time. Audiences will or stakeholders will not be happy with that because it feels like you've taken something away and maybe they don't yet trust. So the one way to deal with that can leave the regular stuff there, but start to pull the stories out upfront. And when it happens is over time, as you are able to convince your audience through showing them that you're focusing on the right things. Then you can start weaning them off of all of that detail. So it never feels like you're taking something away. It only feels like you're adding value. And this is actually something interesting that we see when we think about the, you know, the steps of the process that you were talking about with de-cluttering. Specific de-cluttering, I think is one of the most simple but potentially most powerful lessons when it comes to communicating effectively. Right. Think about the stuff that doesn't need to be there and steps to strip it away. But we find an interesting thing happens when people only declutter, right.

Cole Nussbaumer Knaflic: So if I'm an analyst, I go to a workshop and I. All right. De-cluttering. I'm going to declutter all my graphs. But what happens is or what we've seen in practice is when you just de-clutter, people feel like you've taken away. But not added anything in its place. Right. So you need to take it to the next step and not just up with de-cluttering, but also think about how do you focus attention? What is the takeaway and make those things clear. So when you make those things clear. An interesting shift happens in the conversation where the conversation is no longer about the data necessarily, but more about what's the data telling us. What does this mean in terms of the context? What do we do next? And for me, that's probably the most interesting thing that happens when we are thoughtful about how we communicate our data and what it means for our audience. And what they need to do is we can actually completely change the conversation that happens where we're no longer met with know requests for a bunch more data. Rather, we're able to facilitate conversations focused on the right sort of things, using data as inputs to that, but really getting people to focus on what the numbers mean and what to do with that.

Lea Pica: It's so funny that you say that and we can jump to the Eliminate Clutter and Focus Attention section, which I head. When I walk people through, the name I have for it is the detox. So getting rid of the stuff you don't need and then you're right, putting back the emphasis. And it's so funny when you take away a lot of the extraneous garbage, but you leave color there, it still feels safe because it's visually engaging in some way. And then you switch it to that gray to send that data to the backdrop so you can create a kind of canvas for your story. It's like watching everyone slump a little and then like. And then as soon as you put the color back to emphasize one key point, they're like doing the most incredible thing to watch when they see color being used intentionally for probably one of the first times.

Cole Nussbaumer Knaflic: Yeah, I think color used sparingly and intentionally is one of our strongest tools for being able to direct the audience's attention to where we want them to look. So you can think about if there's a takeaway you want your audience to focus on or something. You want to make sure your audience sees it. Use color sparingly just there and put words around it to make that clear. Think for me, that's often the lowest hanging fruit when it comes to the minimum amount of work you can do for the maximum amount of benefit is think about how you use your color and how you use your words. So color used sparingly to direct attention and words either spoken out loud or written down, or a combination of those two that make why you want your audience to look there, clear.

Lea Pica: Right. Exactly. Now, since we're in this area, you know, you reference Gestalt principles and very attentive attributes for eliminating clutter and also focusing attention. And there's no question I've seen that these are super fundamental tools for communication, but I think a lot of practitioners aren't yet aware of them. So what are some of the basic principles or techniques that U.S. designers aren't using to their advantage, which are simple?

Cole Nussbaumer Knaflic: I think the symbol for me is or one thing that people can be thoughtful about is when you're showing words with data together, which we often are and should be. I hate this idea that data should speak for itself because it doesn't write or it says every single different person is true separable. So we need to put words around our data both to aid and understanding when we think about effective titling, but then also if there's a takeaway or a conclusion to make sure that's clear. But when you put words together with data, oftentimes these things end up divorced from each other. We have a graph on one side and some bullets on the other side or, you know, text at the top and then the graph. And one simple thing we can do is when we show text and data together is connect those things for our audience visually, which comes back to the Gestalt principles. But you don't need to know the Gestalt principles to him to be able to do this right. It's thinking about how do you physically, visually connect these things for people? So you can think about on the topic of color. You could make the text that describes a certain data point, the same color as that data point.

Cole Nussbaumer Knaflic: Or we can use where we place the text, right. Put the data or sees me put the text close to the data. It describes or you can think about using the connection. I draw a line from the text to the data that it describes. Anything you do that can make that connection easy because that means when the audience reads the words, they know where to look in the data for evidence. And when they look in the data, they know where to look for additional context or, you know, answers to that question of why. And these are simple things that you can do that you don't have to know. The underlying theory seems to think about how you know them. The connections that I make in my head, because I know the scenario, how can I help make those in a tangible way for someone else? The best way to test that is just to create your visual on your graph, your presentation and sit with someone else who's never seen it before and have them talk you through their thought process of what are they? Pay attention to questions. Do they have what observations do they make? It can be really useful for seeing how someone else might interact with what you're putting together and make adjustments if needed.

Lea Pica: Right. What are they seeing first and what is it meaning? Or are they confused in any way? These are amazing questions. And I think that sort of practice can actually really facilitate the adoption of a new way of doing these things because I encounter the same friction with my students where they say this is great and I don't know how I'm going to get my stakeholders to adapt to seeing data in this new way. But I think engaging them and involving them in that process as a collaboration rather than this is what we're doing now. Take it or leave it.

Lea Pica: Yeah, I think that could be powerful.

Cole Nussbaumer Knaflic: Yeah. You want to avoid anything that makes this sort of us vs. them mentality. Right. Which is not a successful way. Another approach there can anchor your audience in something they're familiar with or the thing that they're used to and then transition from there to a new view and make it really clear how the two relate to each other. Because then again, similar to what we talked about before, you're not taking anything away, rather adding new value through potentially a different view or a different way of looking at things.

Lea Pica: Do you have an example of a case where you in a sort of transition like that anchored in familiarity?

Cole Nussbaumer Knaflic: Yeah. Let's I'm going to totally make up a simple example for a is that you've been able to talk through it easily, but you could imagine. So one challenge that people will sometimes vocalize to me is I don't want to use pie charts. I understand they're difficult, but I have this audience member or younger audiences and they love their pie charts and they want to see everything as a pie chart. Say, OK, well, don't just go and say, I went to this workshop or I read this book and I learned we shouldn't use pie charts. I'm not gonna use a pie chart, which isn't the case, by the way, but that's not a way to win anybody over.

Cole Nussbaumer Knaflic: When we think of influencing. So one way to do it could be OK. Let's look at the pie chart. Let's start there. And now let's see what happens if we actually unwind this and transition it into a bar chart. So notice now we can see we lose that percentage of the whole, which is what you get through the pie. But now we can start comparing segments to each other. So it may not even be taking anything away, but rather showing the benefit of how when you look at data through different views, it actually enables you to see different things. Or I can think of a scenario that there was one I was working with a pharmaceutical company. They were communicating with physicians. So it was communications that were going through the sales reps to the physicians. And they'd been showing the results of this study in what to an outsider, me coming and seemed like a really complicated way to show things. But they were convinced that, no, the physicians you know, we've been using this for so long, everybody knows how to do this. The sales reps are equipped at talking through it. If we tried to get them on something new now, you know, there will be anarchy.

Cole Nussbaumer Knaflic: And so what we did, in that case, was something similar. Was said, OK, let's take how we're showing it now. And now let's decompose it, decouple it and go through sort of step by step how you can see some of these relationships when you show them maybe one at a time or a couple at a time. And so they basically started with the complicated thing as the first view of the data. What people had been used to and then provided all of these alternate views as a way of getting to make specific comparisons out of that big complicated view. And what you can find sometimes is if you're trying to transition away from something, then you can do that for a couple of months or whatever the iterative process is, whatever the cycle is. And then over time, you can start stripping some of the historical stuff away, because now you've transitioned people into a new view. It's something to think about. France also, you also always worth thinking about if you're wanting to change something. Is it a fight worth fighting? Sometimes it isn't. Sometimes it is not.

Lea Pica: No. I mean, any change, even if it's good, is psychologically taxing, right? So making things gradual. I like small, gradual shifts in, you know, including logos or the way that people see certain tables and things like that. I agree. Even though I'm a person who's often made dramatic shifts because I just want to leave the old way. It's really not the way for a lot of people. So I can appreciate that.

Lea Pica: So back to moving back a step to choosing an effective visual. This is also a huge place that. Like a fun sandbox for practice, but it's also probably a really important place for people to hone their skills. So I'm always curious, what is a chart that you just wish people would stop using or if there is like for a certain scenario and maybe a chart they'd that you wish they'd use instead of or you wish they were aware of?

Cole Nussbaumer Knaflic: I'm going to reframe that a little bit and I'll come back and answer that more specifically. But for me, I should caveat. Right. I've written posts called things like Death to Pie chart more about being provocative and grabbing attention than, you know, pie charts are not evil.

Cole Nussbaumer Knaflic: There is no graph that is inherently evil. And in fact, pretty much every graph has its perfect use case. The challenge is just you veer too far from that perfect use case and things get pretty confusing pretty quickly. Now, that said, there are some things that you should try to avoid because they hinder the interpretation of data or cause us to easily misinterpret the data. So examples of this. You should never curve a bar chart that has no theories in it, because as soon as you do this, you're elongating some. And it just invalidates the comparison. Steve Wexler has a great post on his blog, Data Revelations. It's called Something About Spooning Skyscrapers. He basically shows sort of the circular version of this bar chart and then which was skyscrapers for one of the examples he uses and then unwinds it and shows. Yeah. Why? Why? That's not a good idea. I think coming back to your specific question, one visual I wish I wouldn't see is the gauge right adopter. Yep. Range. And for similar reasons, because we often when I see people using those and they're surging in popularity around the time that dashboards started becoming popular. But I don't see many anymore. But they do unanimously make me cringe because oftentimes, you know, we're showing or showing some sort of measure than we're showing it compared to an average or we're showing it compared to some past point in time.

Cole Nussbaumer Knaflic: And it's on this radial sort of axis, which makes it harder. And so, again, unwinding and thinking about really what do we want to enable our audience to do with the graph and then trying to find a visual that's going to facilitate that in an easy way. And oftentimes that means iterating and looking at our data one way and looking at adding another way. The think one myth that I sometimes hear people vocalize is this idea that there is a perfect graph for a given set of data, which is simply not true. Any data can be graphed. A ton of different ways and different views of the data will allow you to more or less easily see different things. And by iterating through different views, we actually get to know our data better when we think about the Explorer exploration process and then we can be thoughtful about what do we want our audience to see and then how do we choose a view that's going to help make that easy.

Lea Pica: Yes. That is fascinating. You know, we are kind of shown like this is the perfect graph for this particular message. But what I really appreciated about your book is how many times of iteration you bring people through one table like, you know, let's makeover this table. We could see it this way. We could see it that way. I was like, wow. I would have never thought of plotting it out that way. And you're right. You do really see something unique in each of those views.

Cole Nussbaumer Knaflic: Yeah. And even just if you don't want to take the time to do that in your tool, drawing it right. Scouting's to see if it will work. I love sketching because it's fast, right. You can be quick and dirty. You don't have to plot everything exactly right. We don't develop an attachment to what we've done the way we do. And we've taken time to build something. Right. I've just taken a ton of time to build something super sexy. And my tool doesn't work. I have a hard time letting that go versus if I'm iterating on paper, it can be this really easy, fast thing. And I see my kids do this right. They're 6 and 5 and 3 and they draw and they draw prolifically and without any attachment. And Avery, my oldest, will go through multiple iterations on who's drawing this cat and went through all these to get the tail just right. And if the tail should be up or to the side or down. And he's just drawing and recycling and drawing and recycling. And it's this because your brain moves so fast and your hand with a pencil can move just as fast as the computer slows us down when it comes to a lot of that stuff.

Lea Pica: So funny how the apple really doesn't fall far, but I know what you mean and what I'm also finding now. I'm going through an analysis for a date of his competition where I'm finding that by not drawing first, I'm finding myself constrained by the data itself, where I'm having all of these mental visions of what I'd like to see. And I decided today to stop and go to the whiteboard and just straw as if I as if the sky was the limit in terms of what I could do. And I'm finding that is allowing me to create clearer requirements and specs for, you know, do I need to reach out for help. And I now can explain exactly what I'm looking for.

Cole Nussbaumer Knaflic: Well, and you'll find in doing that as well, you may find that it's different data that you need. Right. To do what you're trying to.

Lea Pica: Yes, that's exactly what happened. I realized I was like, I am missing a lot of data. And I went out, found it. And now can get a more holistic view.

Cole Nussbaumer Knaflic: And there's such value in doing that upfront and in a low tech way. And if you're doing something for stakeholders, if it makes sense to involve them in that part of the process, you say, hey, this is rough, but here's what I'm thinking. I speed things up and reduce iterations. Yeah.

Lea Pica: Oh, this is so good. So now is the fun step that, you know, everyone. It's like unwrapping the Christmas present under the tree, which is telling that story. So where does this story actually come in? And what I love is that you really showcase the traditional narrative arc, which is what makes all makes all stories work. But again, it is often missing from how we present and you define it as spoken or written words or both. That tells the story in an order that makes sense and gets people to pay attention to. And I actually recognize it looks like a form of the fray tags dramatic structure, which was great. So I'd love if you could walk us through kind of what those parts look like.

Cole Nussbaumer Knaflic: Yeah, I think the story for me is the concept that has evolved the most. When I look at the first book versus let's practice in terms of when the first book came out, I was still grappling with how do you how do you break this apart? How do you teach it to someone else? And it was between then and let's practice coming out that I encountered the narrative arc and realized like this, this is the way to do it, which is just another word, I think, or descriptor for free to experiment. But the arc is basically you start off, there's a plot, right? Tension is introduced. That tension builds in the form of rising action. It reaches a point of climax. Then there's a falling action and a resolution. And it's interesting because I sometimes get the pushback from folks and particularly highly technical folks who hear the word story and they think like, oh, fluffy fairy tale, Disney. Yeah, exactly. When you think for folks if that's where your brain goes or you could bring us the story, try to widen your perspective. That's actually a very limiting and narrow view. And there are ways that story can be used very strategically when it comes to helping us get our data across in a way that's paid attention to and understood and acted upon it by our audience. And so in the new books, I outline the narrative arc and do a ton more examples of how do you now take a business scenario? And lay it along with this. So I think the typical approach when we think of a business presentation is a much more linear path. Right. Start off. There's our hypothesis or a problem statement.

Cole Nussbaumer Knaflic: What did we set out to solve for in the first place? Then there's the data. Right. How did we get it? Where did we do it? What assumptions did we make? How do we have to clean it? Then the actual analysis. Right, the statistical methodologies we employed. And then the findings or the recommendations. And this is the path that comes most naturally to people because it's the path that we go through us as the analytical process. But I'll put forth the idea that this is a very selfish path, because at no point along the traditional linear path do we ever have to stop and think about our audience. And for me, that's the big transition that comes when we rethink our narrative line from this linear path all along the narrative arc, because, for the shape of the arc to exist, there has to be tension. And it's not the tension that matters to us. It's the tension that matters to our audience. And it's not about making up tension either. If there weren't tension, you'd have nothing to communicate about in the first place. And this is where it really circles back to what we talked about in less than one when it comes back to context and audience, because that tension, you can ground it in what is at stake for your audience. And then the resolution becomes what can your audience do now to resolve that tension that you've brought to light? Mm-hmm. And for me, in a presentation setting, it's less critical that our presentations follow this arc specifically, but more critical that they have those components. Right. That we've thought about. And what that is and. Exactly.

Lea Pica: Interesting. Okay. And now with this sort of cycle, with the arc, is it something that repeats with it where you kind of clue them into specific insights or issues that you're seeing in the data and you create a full arc and then close it with a recommendation resolution and then move on to the next piece of insight? Or is it something that's generally more following the in the arc, following the entire presentation where the whole meat of the inside. Are all of the insights, whereas the recommendation and resolution come at the very end.

Cole Nussbaumer Knaflic: Yeah. Great question. And I think there is no right way to do this. Right. Just like a lot of the things that we talk about in this space and it's going to very much be context-dependent. So there might be some cases where you do have this over our Ching's structure that ties everybody together, everything together. And you can imagine. Right, maybe there's not just one peak, but there's you know, it's more like a mountain range where you've got different peaks for your different sub storylines. Or there may be cases. Right. If you think of a quarterly business review or something like that, where you may be going through different parts of the business where there's not this overarching structure to pull it together. And in that case, you might have a separate arc for each of those. And so it's not about trying to force anything where it doesn't fit, but rather it's just for me it's another tool that we can be thinking about and potentially incorporating for a greater impact when it comes to making sure our message is heard and understood and acted upon.

Lea Pica: Awesome. This is so good. So how do you apply a framework like this is a tool that has a linear structure like PowerPoint or Google slides?

Cole Nussbaumer Knaflic: I don't know. So for me, it's not the tool, any tool can be used pretty much however you want. So we use PowerPoint and Google primarily, but for us, we use them as sort of empty starting points where we're filling them, we're figuring out what that route looks like. So the fact they're going from one slide to the next isn't a limiting thing. And in fact, it will often use an approach where we build a story with a given graph or with a given dataset where we start by building it piece by piece, which is another way of taking your audience through your data to say start by saying you hear the bones, here's the skeleton of the graph. Here's what we're going to be looking at. On the Y-axis and the x-axis. Now let's layer on the first data point. Here is the text that surrounded this. Now fast forward video. Here's the next data and use that as a way to involve your audience in the story of your data, which for folks who haven't been doing that, it takes some time. But when that time helps facilitate greater understanding and more robust conversation about the data can be time really well spent.

Lea Pica: Right. OK. And then you also talk about the different ways that stakeholders consume information. What I loved is how you contrasted a build for a live presentation like what you just talked about versus something like an email report where it's a self-consumed narrative. So I'd love to hear your thoughts on how to distinguish between those.

Cole Nussbaumer Knaflic: Yeah. And we'll often when we're working with clients or a lot of the examples in the book follow the structure as well where we do both. As we say, if if you're presenting life, it could look like this and step through piece by piece and then we'll end with the final fully annotated version. That is the thing that you would send around, right, if you weren't presenting life or as the follow up if you did present life so that someone consuming it on their own has all of the detail there to be able to walk themselves through the same sort of story that you might go through piece by piece in a live progression. And it tends to be just as nice. I find it to be a nice framing for how to think through things because when we look at our data piece by piece, it helps us decouple things into ways that even if we're not presenting it live, helps us formulate that final takeaway slide or two or whatever it ends up being in a more consumable fashion, which is sort of interesting.

Lea Pica: Cool. Well, there are so many examples of figuring out how to do that. And, you know, that's what I really appreciate because a lot of times I get asked, but I can't do life I can't create live presentation slides because I'm not going to be able to email it afterward. I'm going to kill trees and whatnot. So I think it's amazing how you've given so many different options for recognizing the environments that people will be in when they consume that story.

Cole Nussbaumer Knaflic: Well and that's one of the things I think to be thoughtful of as we are creating our data visualizations and stories as well, is how are we going to be delivering that? Are we there live? We can talk through things so we don't need every bit of detail to be in our content. Or is it being sent around or, you know, introducing more challenges? Is it a webinar sort of situation? Right. How do you deal with each of those things? Because the way to get to successful communication looks a little different for each of those. And so being thoughtful of that as you go in and plan can be helpful.

Lea Pica: Awesome. Well, I have one more question before we move into the wild card question. I want to know what gets you excited about the future of data, storytelling, and presentation.

Cole Nussbaumer Knaflic: I think for me, we're in this new zone when it comes to there is data everywhere, it's being collected about everything. And so increasingly the skills needed to be able to take that data and turn it into information and use it to derive better understanding and motivate smarter actions. I think there's just so much opportunity there and there's a ton of opportunity in work that's already being done that maybe just isn't being communicated as effectively as it could be. So I'm excited about that. Pendulum's sort of swinging in the other direction, which is towards really effective communication that can help motivate people to do good things with data and act in smarter ways.

Lea Pica: You're right. I'm just seeing so much buzz around people wanting to have a more intuitive understanding of the data that we're creating. And I think that is really exciting. It's just this democratization of the investment that they're making in their own businesses. And I think it's helping them understand their customers better as well. So that's just going to benefit everybody. Yeah.

Lea Pica: All right, so this is our final question. Think hard here, imagine this very plausible scenario. You're walking onstage to perform at the L.A. International Piano Competition when you suddenly trip and fall into a vortex that pulls you back to the moment you're about to deliver your first presentation. What are you presenting about? And what would you say to yesterday you?

Cole Nussbaumer Knaflic: Interesting. So if I go in the way back Time machine, I am standing in my junior high gymnasium giving a speech to as I'm running for ASV president. And I just remember having the paper in front of me and the shaking hands and the trembling voice. So I would tell myself to breathe. Because. Yeah. Taking a minute and taking a deep breath helps put things in perspective and helps take away that shakiness of voice. And I think just knowing that when we're putting ourselves in places that feel uncomfortable, that when we approach that the right way, there is tremendous growth that can happen. And so not fearing that sort of productive discomfort.

Lea Pica: I love that. One of the mottos I've been trying to live by this year is how can I intentionally go into discomfort? So I don't unintentionally exist in this idea and forcing yourself or not forcing, but encouraging yourself to take every opportunity to see a request to present in any capacity I think should be fully embraced as that dare to be a great chance to grow.

Cole Nussbaumer Knaflic: Yep, absolutely. And actually, in terms of chances to gross, we've talked about the practice book and talked about the fact that practicing is how we get good at this. All right. Nobody starts out and is a masterful Munich hater of data. These are skills. Speak for yourself. I mean, how is this right? Go. Yeah. A lot of ugly stuff to get to the good stuff. But one thing I want to make sure we talk about a little bit before we close is a new resource that we've made available, which is the Storytelling with Data Community. Yeah. So the community is an online community where you can practice in a low-risk setting and give and receive feedback and engage in conversations with others about challenges or successes and discover great work. So as I mentioned before, I think practicing is a way to really get good. And so there are different ways of practicing in the community. You talked about the monthly challenge that we knew. We've just rolled that into the community, which I'm very excited for because historically it was more conversations on Twitter which were limited. So how media you can get there, whereas now we're seeing some of the November was our first month with the challenge entirely in the community.

Cole Nussbaumer Knaflic: And I love seeing the discussion and discourse in forth and people giving feedback and iterating with that feedback. We have the monthly challenge. We also have exercises that are more online with what people will find in the practice book where you are posed and exercise your men to take, you know, 15 minutes of your day and all the data is there. Everything you need is there to spend a little thought time and upload your solution. And when you do so, it unlocks the storytelling with data solution as well as solutions from everybody else who has completed that given exercise. So we have a great way for people to practice and see how others have approached the same exercise. And again, that cycle of feedback so strongly encourages anyone who wants to hone their data visualization and communication skills to check that out. There are details at and that's at But all of our resources are listed on the main site as well.

Lea Pica: And all of the links and resources, including the books, will be listed on the show notes page for this episode. And I actually poked around the community and I was so pleased to see how much engagement your November challenge was getting. I really like people who are so excited to contribute their own thoughts and I think even get feedback. So just a few facilitating that space for people online I think is such a huge contribution.

Cole Nussbaumer Knaflic: Yeah, we're very excited about the level of involvement there. We're in beta testing mode still, so I'm really excited to see what's going to happen when we totally open the gates. Yeah, but place where hopefully everyone in the world can take some time and find valuable resources for continuing to hone their skills.

Lea Pica: Wonderful. Well, Cole, unfortunately, once again, our time has run out. So please let the listeners know where they can keep up with you.

Cole Nussbaumer Knaflic: Yeah. So our Web site has a ton of resources that I'm relatively active on Twitter @storywithdata and you find the good stuff there.

Lea Pica: Sweet. Well, all of the books are available now and I highly suggest running, not walking to get them. And Cole, I just want to thank you again for taking the time. I'm always so happy to share your work because I think that what the approach that you're giving people feels so practical and really so. Powerful. So I thank you for that.

Cole Nussbaumer Knaflic: Awesome. Thanks for having me, Lea.

Lea Pica: YAY, it was so exciting to have Cole back on the show and talk about her incredible book? I really hope that you're going to consider making it a part of your library or it would make an excellent holiday gift for a fellow practitioner as well. I know I'll probably be sending a few copies myself. So to catch all of the links, resources, and links to her book mentioned in this episode, please visit the show notes page at I would love if you could leave me or Cole a comment because I want to hear about the challenges you face when presenting the information. And I'll leave you with today's little bit of presentation inspiration by Cole herself. And that is “put into practice what you've learned. Share it with others. Tell stories with your data that will influence positive change.”.

Lea Pica: My take? Yes.

Lea Pica: The only way to truly master a skill or set of skills is practice. Practice turns into a habit, which then turns into an integrated, mastered skill. There are so many ways to begin participating and practicing and sharing your work with the community. Like the Women in Analytics conference state of his competition and Cole's amazing storytelling with data community and her monthly challenges. And what I hope is that you'll step away from the data that you look at and stare at every single day, and you'll start looking at data sets that speak to something that you're passionate about. And the more we practice and participate, the better. All of our collective skills get as masters of data storytelling.

Lea Pica: That's it for today. And that's it for this year.

Lea Pica: I am so incredibly grateful for the run we had on the show this year. I'd love to give a quick shout out to all of the amazing guests that took the time to hand over an hour of their life to share their wisdom. I want to thank Aaron Moss, Tim Page, Gary Angel, Valerie Kroll, Nir Eyal, Carlos Gill, Alberto Cairo, Nancy Duarte, and of course, Cole and I have so many incredible guests planned for next year as well. But most of all, I want to give the biggest shout out to you, my dear listener. You show up episode after episode. And it is my deepest wish that this show provides lots of valuable insight, lots of super practical tips and little side note of entertainment that makes the day a little more fun. So grateful for you. I am wishing you a nourishing and radiant, abundant holiday, and I'll catch you on the flip side. Namaste and Namago.

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Present Beyond Measure Data Presentation Book - Lea Pica

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