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Before & After: Inside the New Book from the Storytelling with Data Team
504 Plays1 day ago
In this episode, I’m joined by Cole Nussbaumer Knaflic and Mike Cisneros from Storytelling with Data to talk about their new book, Before & After. We dig into where the examples came from, how they selected and refined real client work, and why the book focuses so heavily on process rather than rules or templates. We also reflect on how the data visualization field has evolved over the past decade—from best practices and chart types to iteration, audience empathy, and real-world constraints. Along the way, we talk about teaching data viz, common pitfalls, and why there’s no such thing as a true “201 course”—only practice.
Keywords: ddata visualization, storytelling with data, data storytelling, before and after charts, visualization process, data communication, chart design, visual analytics, design iteration, audience-focused data, PolicyViz Podcast, Cole Nussbaumer Knaflic, Mike Cisneros
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Email: jon@policyviz.com
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Transcript
Celebrating 300 Episodes of Policy Viz
00:00:12
Speaker
Welcome back to the Policy Viz Podcast. I'm your host, John Schwabish. Folks, this marks the 300th episode of the Policy Viz Podcast.
00:00:23
Speaker
Thanks so much for tuning in. Thanks so much for listening. Thanks so much for your support over these last, yes, wait for 12 years. As I've interviewed folks and talked about all sorts of things related to data communication from presentation skills and design to data visualization tools, techniques, books, all the things that can help you be a better data communicator.
00:00:48
Speaker
I'll also say I'm happy to get a lot of free books along the way. um i have learned a lot over these last 12 years. I have made lots of new friends. I've been able to talk with so many interesting people in so many different walks of life. And I just want to say thank you for supporting me and my guests for listening to the show and and tuning in. I also be remiss if I didn't thank some individual people who have helped me build this show over the last several years. Ken Skaggs is my audio editor, does great work there. Sharon Skotsky-Ramirez helped me for a long time on the social media and the production side.
00:01:23
Speaker
And my friend Nyan Bula, who used to lead the band, the NRIs, provides the intro and outro music.
Introducing Guests and New Book Discussion
00:01:30
Speaker
Now, I thought about taking this opportunity of having the 300th episode to just be me and talk about a few things, do some reflections, looking ahead. But then I figured, meh, I'll just stick with my basic format, which is an interview show. And what better way to mark the 300th episode? than to have my good friend Cole Nussbaum or Nafleck on the show because Cole was the guest on what I'm going to say is the negative first episode because I was very early on sort of dabbling in the audio format.
00:02:06
Speaker
of Maybe instead of doing blog posts doing some audio things and so I interviewed Cole as one of the first two people Before actually saying I should just do this as a podcast So on this week's episode of the show I am glad to be joined by Cole as well as Mike Cisneros two of the three authors of the new book storytelling with data before and after practical makeovers for powerful data stories and we talk about the writing of the book and where the content came from, how they approach redesigning and remaking visualizations.
Importance of Storytelling in Data Visualization
00:02:39
Speaker
And we talk about all the good stuff that's necessary to be a good storyteller with data. And hopefully over the last 12 years, over the last 300 episodes, I've been a good storyteller to help you figure out how to improve the way you communicate your work through data, through graphs, charts, diagrams, slides, videos,
00:03:01
Speaker
diagrams, whatever it might be. i hope you've enjoyed the show and thank you so much for tuning in each and every other week. So with no further ado, let's get over to this week's episode of the show. I am joined by Cole Nussbaum or Nathlick and Mike Cisneros from Storytelling with Data to talk about their new book before
Team Dynamics and Project Contributions
00:03:20
Speaker
and after. Here it is only on the PolicyViz podcast.
00:03:27
Speaker
I've got part of the storytelling with data team. Okay. Hi. You're not going to make me do percentages on the fly. What share do I have here? I only have, we got what? Two thirds of the author group for the new book. Yes.
00:03:44
Speaker
And seeing alex what? Roughly a quarter of the storytelling with data team. team All right. Nice. Maybe exactly a quarter. Yeah, based on, as as we're recording this, we've just had our holiday party. So we were keeping track of the eight people involved at any given time. So yes, one quarter.
00:04:02
Speaker
And this doesn't include, Cole, your kids. So I'm assuming every once in a while have to chip in. so i mean they Yeah, they'll like count swag or help brainstorm dragon ideas and that sort of thing. But no, they do not count toward the eight. don't yeah.
00:04:18
Speaker
It's probably good. That's probably a good rule of thumb just, you know, for, you know, labor laws and whatever. um Well, good to see you both. um It's been a while. Excited about the new book, Before and After.
00:04:29
Speaker
Why don't we do intros just so folks, I mean, you know, and I think everybody knows storytelling with data, but we'll just we'll just do that and then we can talk about the about this book. um So Mike, you want to want to kick us off? Sure, I'm Mike Cisneros. I am a data storyteller at Storytelling with Data, which as I often say, sounds like a mouthful when you say it all in a row like that.
00:04:49
Speaker
But what it means is that I get to work with Cole and bring the lessons that we have been teaching to people over the course of more than a decade. to people all around the world, vette through workshops or through books or through other writing, through podcasts, whatever it is. Because one of the things that was always exciting to me in my pre-SWD life as a data analyst was getting to show people how effective it can be
00:05:20
Speaker
when you are telling your stories, visualizing your data in a way that connects better with your audience. And this was Cole's whole thing. She was one of the first people that I remember reading who would talk about this on a regular basis. It was extremely accessible from my perspective.
00:05:36
Speaker
And so getting to carry that banner forward on behalf of her and of the company is something that I've been fortunate to do over the past six, seven years. Haha.
00:05:46
Speaker
Sorry about that parents. Uh, Cole?
Approach to Effective Data Communication
00:05:51
Speaker
ah Cole Nussbaum or Naflik. And I characterize what we do at Storytelling with Data as teaching people how to make graphs that make sense, but really going also beyond the graph and thinking about your audience and the journey you want to take them on and how you can weave the data that you want to communicate into that in a way that gets people's attention and builds their understanding in a new way and ideally helps them want to act more smartly or have a better decision than they otherwise would have. and As Mike mentioned, we do this through a lot of different resources, team trainings, public workshops, podcasts, online community, books, which we'll talk more about today.
00:06:39
Speaker
Yeah.
Real-world Examples from Client Workshops
00:06:40
Speaker
Great. So the new book is out, Cole, Mike and Alex coauthors who's, who's not here. um So there's about, I think like 20 separate chapters going through these different examples. um Let's start with where the examples came from. My recollection, if I remember correctly, is that you all put out like a public or no, wait, did you publicly look search for people or you, this was all just internal like client stuff. Like we've got, we've got a huge library of stuff that we can pull from.
00:07:09
Speaker
Yeah, so I mentioned one of our main work streams is team trainings, workshops, where we'll go in, we'll spend most typically half a day with a client or a day with a client, and we always solicit examples from them ahead of time. And what we say is, this can be any example where you needed to communicate something. Oftentimes it's data because people are coming to us for that piece of things, but sometimes it's a slide or a report or an email. It can take a variety of forms. And then what we do is we use this to get a better understanding of the challenges specific to the client that they might be facing, also understand where we might go deeper or less deep into some of our standard content. And then we typically pick a handful of the examples shared and use those actually to illustrate the lessons that we teach, which is a really powerful thing because I've found that sometimes people, when you teach them something and show it through an example that you've made up for this purpose, it's easy for people to say, oh Yeah, that works there, but that's not going to work in my scenario. And so when you show the lessons through their examples and their colleagues' examples, it takes away that argument and I think really opens people's eyes to the possibility of what could be that might look very different from how things are typically done.
Unique Challenges in Data Visualization
00:08:32
Speaker
And so what this means is we had a ton of content over the past 15 years or so that we've been doing this to pull from. And really, that was the one of the impetuses of the book was to be able to take this magic that we are able to cultivate for people in a workshop setting and make that more widely available. Mm So Mike, tell me a little bit about this process. So you have this huge library.
00:09:00
Speaker
Now you have to go back and pull out like what your favorite redesigns or like the ones that you, like you and Alex and others like remember. And then like, so, so then what's the process of redesigning it and then writing each chapter?
00:09:16
Speaker
It's an excellent question because it, if only it could have been our favorites from over the years, because You love all of your children equally, of course, but there are some redesigns, some makeovers or before and afters, as sometimes we call them nowadays, given the the title of the book, that spoke to us as the people who were working on them, that there was something really interesting, a unique challenge, a particular thing the client was trying to communicate that doesn't always come up
00:09:48
Speaker
in the examples that we get, but definitely comes up in business on a regular basis. And you think, oh, I haven't ever gotten the chance to show people how to solve this problem in some of my other workshops. So those tend to stick in your mind and you think, oh, this would be a great teaching example for something beyond teaching the fundamental lessons that we often include in our workshops. So we went back, Alex and I, Cole, ah all of our other storytellers, Simon, Amy, Elizabeth was on the team at the time when we started thinking about this many years ago. And we all took from our history, from our...
00:10:29
Speaker
recollection of the particular examples that stood out to us. And we put together a pretty long list. yeah And yes, we all had favorites, but also we're putting together not just 20 blog posts.
00:10:44
Speaker
We're putting together something that has to work as a full, cohesive, singular unit. And so in doing so, you want to cover lots of different types of visualizations, lots of different challenges, lots of different, I i would even say levels of, oh, here's something that is relatively straightforward to explain. Here's something that's a little more nuanced, but it's something that you're going to run across in your professional life as long as you keep working in data long enough. yeah So we had that range or we wanted to build that range and that's how it ended up whittling down from the dozens and dozens of our favorite examples to the 20 that we ended up selecting for publication.
00:11:30
Speaker
Now, I'm going to guess you're not be able to answer this question, but maybe. did you find that certain people on the team had certain classes or themes of visualizations that they were drawn to, to add or to, or to even window down? Like Mike, were you like, Oh, we're like, I'm the bar chart guy. and No, Mike's the dot plot. Mike's the dot plot guy. Okay. Mike's the dot plot guy. Like, were there like, i mean, you've got this team and everybody has their own, you know, personal thing, personal preferences. You find that there are people who are like,
00:12:03
Speaker
I mean, either by client or by graph type or by what they wanted to write about? At times for sure. Cole describes me as the dot plot guy, because I like to find, i like to find examples where a certain graph type that maybe you didn't expect but is understandable might be the optimal choice in a certain scenario. Or one of the chapters that I was fond of was where a simple bar chart ended up being extraordinarily confusing, which is the opposite of what you would expect if you chose to use a bar chart. And honestly, using it in a way that seems on the face of it pretty straightforward.
00:12:45
Speaker
And I like to discover those particular areas where there is a twist in it for a reader who you might think at the outset, well, this looks pretty good.
00:12:56
Speaker
I don't know why you're using this example in the first place, because yeah this before that you're showing me really looks like an after. I don't know where you're going with this. yeah And I honestly believe that a lot of the examples in our book are that because we can get hung up in the framework of let's do a viz makeover. You can get hung up on the idea that it is all aesthetics based and it isn't.
00:13:20
Speaker
It's all about what is this visual going to do in the context of the messaging we're trying to deliver and in convincing our specific audience of what's going to matter to them and what they should do. And so taking the the before that looks insidiously like an after and showing people, oh, no, here's what you can do in order to make this even stronger. There's nothing inherently wrong with what you have, but the opportunity to make it so much more effective is there. And we wanted to choose examples that let people go from
00:13:53
Speaker
ah from that starting point to a new ending point and show them that it is not incredibly complicated to do that. It's just changing the way you think about what you are doing with your communication.
00:14:05
Speaker
And we experienced that at one point when we tried to put, we
Focus on Process Over Aesthetics
00:14:09
Speaker
had in our minds this idea of like the befores and then the afters and you'd see this like transformation in such a positive way when you went from one to the other and you actually, you don't see that for the most part, or even when you bring it down pairwise to the one before to the after, there are some things. that you can do that with that look really impressive when you see the before and after, but for the most part, they don't. And it's interesting because it's it's actually the process, which is what the majority of the book is about. It's not just the before and after. It's how did you get from one to the other? What were all the considerations that went into it? What constraints were faced in this given scenario? And that's where all of the learning comes in. is It's not just...
00:14:49
Speaker
here's a bunch of before and afters. It's the thought process and the iterations and we show all of the in-betweens that that lead you from one to the other. And so you get through that or the reader gets through that such insight into just the sort of things to be considering or tinkering with as you're working on improving your data communications.
00:15:11
Speaker
It's kind of like the get ready with me of doing data visualization. It's, I'm going to step you through my process and yeah here's how you go. And also there are times when we show avenues that we start down, but then we discard because iteration is such an important part of anything that you do. We don't want to give people the impression that we always know exactly the right route to go from beginning to end. that if we're trying to show you this is how you do this in the real world, this is how you apply the fundamental lessons that we've shown you in all these different scenarios, it's never going to be if you don't feel like it is smooth from beginning to end, you're doing it wrong. It's no, no, you will have to try things. You will have to get feedback. It's okay if there are bumps along the road. That's
00:15:58
Speaker
John, I know you're from D.C. Remember, that was ah a famous quotation from ah the Washington Nationals manager the year they won the World Series was yeah bumpy roads lead to beautiful places. And so that is part of that process of developing something that is going to be effective at the very end.
00:16:16
Speaker
Well, I'll just say for the Nats, it is a bumpy road right now, but that's a whole other podcast polar conversation. um I want to take a little detour here for a moment because Cole, it's the 10th anniversary of your first book, Storytelling with Data. I have a hard copy you sent me over here somewhere. I have one. Look, I prepared.
Evolution of Data Visualization Books
00:16:33
Speaker
Oh, there you go. Okay. Yeah. Hard copy. Lovely.
00:16:35
Speaker
um Congrats, by the way, on 10 years. um So I think the question I want to ask you is, It feels like these two books in some ways kind of are good demonstrations of the evolution in the data viz field, at least in the book world. We're like storytelling with data, you know, um boy, going to forget. Visualize This maybe was Nathan Yao's first book, you yeah Alberto's first books. my books, um kind of went in like best practices, graph types, like, you know, do this, don't do this. Maybe we're all a little less dogmatic than we were 10 years ago. And now the seems like more of the books now, including before and after are more about process. First, do you agree with that? But secondly, do you, if you do, do you think that's a maturation of the field or what is that about?
00:17:29
Speaker
Absolutely. I think that it is exactly that because when when the first books you mentioned were coming out, there wasn't a lot out there. And so it makes sense that we start with the building blocks. We start with the the foundational lessons, the the things that everybody should be thinking about and exploring as they are communicating with data. Because the I think the timing of my first book coming out was very fortuitous in terms of you know I had started a blog and that was when there weren't many blogs out there and so you could actually get attention and so that was a great way to start writing about some of these ideas and doing that enough plus teaching enough to then be able to have content for a book.
00:18:14
Speaker
And the field was definitely maturing at the same time and kind of becoming a field at that point. and i mean, I think when I started doing research when I was back at Google and starting to develop training on this, really the only books out there were, you know, there were Tufties books, Stephen Few. I got really into Colin Ware. His stuff's a little more academic, but like visual perception sort of things and drew a a lot from... those worlds, I guess, because there wasn't any there wasn't a lot else out there. There weren't very many people blogging. There were only a handful of books. Everybody had read the same handful of books. And so i think taking those then plus the real world, you know, here's a graph we see in the wild, or here's a graph from a client and being able to
00:19:01
Speaker
teach through example at that foundational level. Because i think that's one of the things that I really realized when I go back to the first book is just how simple and straightforward everything is, which makes sense when you're teaching basic concepts, but also doesn't match reality. you know In reality, there are all these corner cases and you're always faced with constraints and you have a boss who says, i hate pie charts. And you have another one who's you know who you have 10 minutes with if you're lucky. And so all of these real world the messiness that comes in with that. And I think that's the evolution that we've seen in the books that are out there is more, how do you deal with the not straightforward case? And what can that look like? And how do we advance our thinking in ways that will help us be successful across different situations?
00:19:48
Speaker
ah Detour on a detour. ah Do you find fewer people with the i hate pie charts thing? I mean, I found fewer and fewer students who,
00:19:59
Speaker
particularly students when i'm teaching at the university level, they they haven't heard of Tufti, they haven't heard of you. They don't have this disdain for pie charts, which you know a lot potential reasons are. I think it's become kind of a, people people like it for the shock value still. So i see I see it played that way on social media. Although I will say between the Storytelling with Data 10 years ago and the 10th anniversary edition, the pie chart section is actually one part that I did fully rewrite. where the i went back because i was like wait i know know i know i've given talks called like death the pie charts but like know what pie charts are evil did i have a blog post like no that was like a subsection in the book was titled pie charts are evil and so uh in the 10th anniversary edition that subsection has been retitled to pie charts aren't evil just often misunderstood or often misused oh yeah verbatim but But in response to new research that came out in the meantime, which is no longer so new, but Robert Kassara and Drew Scow, their pair of pie chart studies. there have been some things like that that have come up over the years. But for the most part, the lessons still apply. And I think that really is the nice um dovetailing of before and after. you know You've got storytelling with data for the foundational lessons and then before and after for all of the real world application. Yeah. um Mike, do you have, ah we'll finish this detour on a detour and then come back in second. But like, do you have either in your own practice or when you're teaching, do you have a newer, a new version of a graph that's the never pie charts, but there's like a never something?
00:21:38
Speaker
Off the top of my head, I wouldn't say that there is any verboten graph type. I talk about pies, I talk about donuts as essentially the same, any food based chart really could be, you know put in the same similar category.
00:21:56
Speaker
But when you think about, we talked a few minutes ago about when Cole started writing, there weren't that many people writing about
Growth of the Data Visualization Community
00:22:05
Speaker
this. And so I wasn't part of the writing community then. I was part of the reading community then, the practitioner community. But I think that means that it was a smaller community. It was those of us who were seeking out people who were talking and writing about this. And so for us who maybe have been thinking about this in a larger portion of our days for a longer string of days, maybe for us, yeah, the pie chart discussion, maybe that's a little played out.
00:22:31
Speaker
yeah But I teach workshops to people all of the time who don't think about this every day, all day. And there are new people entering the workforce all of the time or new people who realize, oh, this has to be a part of my day-to-day business. And so the simpler things, the more foundational things are still very resonant with the people that I talk to. it's a The pyramid base continues to get wider of people who are involved in learning. so I do think there is more acceptance of pies because there aren't such a large percentage of
00:23:09
Speaker
didactic data visualization. i am a data viz person. There's not as many of those in my day-to-day experience. So I i do explain, well, the 100% stacked bar is a great alternative here because it's like a linear version of a pie, sort of the same thing.
00:23:29
Speaker
And when you just demonstrate, again, that's that iteration coming back. Yeah. So, yeah so no, I don't think that there's, there's that there's no new pie charts. I've got one to put on the foreboding list. Can I add one to the foreboding list or I'll show it and then I'll describe it for those who are listening. So, okay. So i don't know if you can see that very well. Is it the vertical line chart? Yeah, so I'm showing an example from chapter two of before and after, and it is survey data that is being shown in, yeah, this weird like vertical line chart situation. And I bring that up because we see that a version of that graph so often from our clients that at some point it must have been ah introduced into survey data land because we've seen different variations of that from all sorts of different clients over the years. So when it's categories that you're trying to compare, rarely is a line chart going to be a good choice. Every once a while a slope graph will do it, but yeah not in that instance.
00:24:31
Speaker
it is It is kind of interesting on like the verboten graph because when i i have the same thing. When I teach, it's not like I'm like, here's a whole bunch of rules that you need to follow because you know it's a little art, little science, so how do you have rules? But then people are like, well, what about pie charts that sum to 100%? I'm like, well, i okay, I guess that's a rule, but like also like isn't I feel like that's just common sense. But like math, yes, math. Yeah, right? But also like I guess that puts a lot of onus on people following common sense, which...
00:24:59
Speaker
maybe humans are not very good at to begin with. So maybe that, maybe that would throw, I would say more generally, like more specifically for me, it's dual axis charts, like those, those line charts with two axes. But again, like there's always an exception to that rule, right? Like Fahrenheit and Celsius, sort of the classic example, but that being said, I i think I'm, I'm, I'm with you. Okay. Okay.
00:25:23
Speaker
Detour, detour. Let's come all the way back to the book. Where are we going back to? Okay. Yeah. um Okay. So I wanted to ask, I guess, two questions because we've got these 20 different chapters, these kind of 20. Well, I don't even want to say 20 different before and afters, right? Because there's the steps within. Yeah. yeah But the steps within each chapter, right? um But I want to ask like,
00:25:45
Speaker
do they fall into themes or into categories? um ah Good question. And I guess sort of a related question, like, do you think people should read this cover to cover or is this a kind of book where it's like, I'm having this problem. mean, you always want people to read cover to cover, but you know, would you say, Oh, I'm having this problem. I have a bar chart. I know it's not, I, even I can't read it as a creator. Like, should I go to chapter seven?
00:26:13
Speaker
there's kind of a bunch of questions there embedded, but it's really about the kind of the overarching theme and organization of the book. You can imagine, John, that we had a lot of discussion about how to organize the the book. And it did go through a number of iterations. but i think And one of those that early on was in theme, like with there being clear different topics and then subchapters within that. Right.
00:26:41
Speaker
And then we thought of it more as a a reader where at the beginning, there are more of the basic, more of these simple changes, the less challenging things that you would need to overcome. And we got into some of the more sophisticated makeovers towards the end. But throughout, there are examples where We will do a full like if you are presenting this, this might be a live presentation. There are some where you're changing just specific aspects of a single slide and.
00:27:19
Speaker
there's There's variation throughout, but I would say it gradually gets more and more sophisticated and complex as you go through the book, which I think parallels your own development as a practitioner and somebody who's applying these lessons. You would feel more comfortable doing them you know one at a time or a couple at a time. And then eventually you gain the confidence to use your entire toolkit as necessary on some of the more challenging examples or Cole mentioned this before is it's not just limited to a graph. We're not just limited to a presentation slide deck. It's sometimes it's an email. Sometimes it's an infographic. Sometimes it's a combination of things. And we wanted to show how you could apply a lot of these lessons to those as well.
00:28:06
Speaker
Well, just back on the themes, we abandoned that because it ended up feeling too forced and it it wasn't flowing in the way it needed to flow. So we went through few different reorganizations of content and how we were approaching things. because it didn't it didn't all start with the examples. we We kind of approached it in a few different ways. We had the structure that we thought we were going to go down for a bit. We had examples. We also had just topics that we knew we wanted to cover or certain tips that we knew we wanted to share. And it became this triangulation of, right, where do we have an example that'll show this one thing? Or we have this example that we really know we want to use. What lessons can we highlight through that? And so we abandoned the thematic approach, I don't know, a while before ah finishing writing. And then even after finishing writing and as we were finishing writing, we were reorganizing things and went through several rounds of that. But as Mike mentioned, the general um progression now goes from more straightforward, more simple to more robust, more comprehensive, more nuanced as you move through the chapters of the book. But they are each written, they could be read as a standalone where you can flip through and just choose your chapter and you're going to get lessons. Each chapter starts off by outlining key lessons, shows the before with a little bit of prelude of what's going on in the scenario, takes you through the process of teaching those lessons that were outlined at the beginning through the given example. And then there's a recap at the end where you see the lesson lessons fleshed out with more detail.
Flexible Reading Experience of the Book
00:29:39
Speaker
And so you've got a nice container for each of the chapters. You certainly can read it through cover to cover, but it's not necessary. Okay. Yeah. I mean, I haven't i haven't obviously read all the way through yet, but so a person who has just starting with DataViz could read storytelling with data, get the basics, come in here and read it cover to cover. That new person probably would benefit from that. But someone who's been doing this for a while could start in the middle of the book or just find the things that they are
00:30:08
Speaker
And there is some prelude in the introduction of before and after is like the crash course on storytelling with data. So if you don't want to add two books to your wishlist, but just one, start with before and after because yeah you can you can get some of all of it there.
00:30:23
Speaker
so So when you think about this sort of progression, I'm guessing like at the for the intro folks, it's some of the things that we've been talking about, right? Like, you know,
00:30:34
Speaker
you know, bar charts and, you know, line charts, you know, using color well, using font, you know, line anything, you know, the sort of the the sort of basics of of design and layout and different chart types.
00:30:45
Speaker
when you think about the later chapters, what are some of those like core next level skills that you find people are lacking or haven't, I mean, I don't want to say lacking because that's not quite fair, but you haven't developed as as strongly as some of, some of these other, you know, skills like color and font, that sort of thing.
00:31:06
Speaker
I think the biggest opportunity, and I'll share mine and then Mike, I'll turn it over to you. Biggest opportunity for improvement just generally is for people to really be communicating with their audience front and center throughout the process from what data they're looking at in the first place to what they do to it, how they show it, how they communicate it. I think when we see data viz and communications fail, often it's because that wasn't taken into account where I was making a graph for myself or for my data and you know who cares about, you know if if somebody else can't understand it, that's on them. When really, ah no, we can take a more empathetic approach to how we communicate and really think about how do we make this work for our audience? Because you make totally different choices in some situations when that's the case. And it allows us to communicate more thoughtfully in a way that's going to be more effective, even though the way that looks may play out totally differently across different scenarios and different audiences.
00:32:09
Speaker
Like you have that next level yeah strategy that people need? Part of it is letting not letting the data itself determine the way in which you show the data, because there are often multiple stories or multiple messages with multiple audiences that need to be considered.
00:32:33
Speaker
And using the same source material could lead you into a number of different final versions, because each one of those final versions is going to be fit for a specific purpose. And instead of thinking, well, if I have this much data, I should show this much data and it should look it should be in this type of chart because I've you know, I've I've looked through my My matrix of this data plus this need equals this chart. Like there are more things that one can do think about in order to make that communication more effective. And that same source data could be something that you end up using to tell multiple stories to different people because they might all need to be told. They just can't all be told at once.
00:33:22
Speaker
And so thinking through what am I trying to do now and what do I use from my toolkit to make that happen? and also taking into consideration that you can always do something no matter how much time you have available to you, whether you have five minutes or a day, you can always make smart choices about how do I make this message better?
00:33:44
Speaker
But also what you choose to do is going to be different depending on if you have five minutes or a day. So not letting yourself ah pick the one hour solution when you have 10 minutes.
00:33:57
Speaker
To ground some of what Mike said in examples, both of the things he's talking generally about, there are chapters that map to specifically in before and after. So in chapter 17, and both of these are Mike's chapters, so this makes sense, that he dives into some call center data and shows how the same general data can be customized for totally different audiences. Mm-hmm. And I've actually used this example a couple of times lately because I think a secondary insight you get out of this is the way it looking at things this way can help shift people from service provider when it comes to, you know, somebody's coming to you with data, you throw them back the data, they come to you for more data and technology. to get you out of that cycle where you become more of a strategic partner by really thinking through, okay, here's the data, but what does my, you know, the person requesting it, what do they actually need? What do they care about? How can I make this work for them? And to Mike's point, that's going to look different oftentimes for sufficiently different audiences.
00:34:57
Speaker
And then, ah let's see, chapter 19, the lessons get into some different time constraints. So key lessons of chapter 19 are tailor your approach to your available time. With five minutes, use your words wisely. With 15 minutes, declutter and add visual cues. With an hour, iterate, refine, or polish. With more time, build a narrative presentation. Then he goes through a scenario with it's like restaurant franchisee reporting and shows what he would do with each of these time blocks and how you could take it from, you know, what was this kind of just okay looking generic report to depending on the situation, full blown customized presentation to drive behavioral change.
00:35:43
Speaker
um So ah in this theme of like this progression of the of the book itself, but going back to also to what we were talking earlier about doing workshops, what is your reaction when you come into a firm, you teach sort of like the 101 class and like, oh, this was great, but we want you now to teach a 201 class. like what what and And let's ignore, like you know we want you to come and teach us Tableau or something like that. like they They want like the 201 core data viz class. like How do you respond to those requests?
00:36:14
Speaker
Oftentimes the second one that you talk about is getting their examples and doing more hands-on things with the specific scenario. Like it it is the before and after book basically. Yeah.
00:36:25
Speaker
Yeah. mean, I have the same reaction. People ask, oh, can you go do a 201? I'm like, 201 is just doing it. Like you just, you gotta go. People don't want to hear that. No, no, no they I mean, they think there's, i mean, Mike, I think exactly to your point.
00:36:38
Speaker
And I think there's just human nature. People want like data type plus data. don't know, whatever the end audience means I should use this graph. That takes all the fun out of it. It takes the creativity and the thought. Yeah, it the creativity out of it. Yeah. I think for the person who is looking for that, this maybe isn't the right field. I don't know.
00:37:02
Speaker
But there are people who self-select into analytic careers who are looking for those kinds of rubrics. How many graphs should I include on a slide? What is the maximum font size I should use? How many words should I have on a slide? How many slides should there be? yeah Right. like These are things that for many people provide frameworks that they can rely on because they don't want to have to think through all of those choices every time. And I can empathize with that. But when the answer is, i don't know what looks right.
00:37:32
Speaker
Or, you know, in certain situations, more. And in certain situations, less. But not too many. You do this enough and you will understand. And that's not a very... um you can't monetize that advice particularly well. no So we don't often give that specific advice, yeah but, but telling people, well, here's the thought process I go through.
00:37:57
Speaker
And this is, if you start to apply this approach, this will start to become second nature to you, which is a nice way of saying you just have to practice it, but you don't have to practice all of it right away.
00:38:09
Speaker
all of the time. I'm giving you these tools that you can then have and learn and practice when it seems appropriate to do so. And you do the little things first, then when the little things become second nature, then you do the bigger things. yeah And that's much more satisfying than just saying, consult this manual for how many words you can have on your slide. Yeah. Use this template. Yeah. Here's the answer. Right. Just follow. Just follow. Seven. The answer is seven. The answer is seven. Yeah. It's 42. Okay. So everybody knows where they can find you. So storytellingwithdata.com.
Storytelling with Data Online Community
00:38:43
Speaker
But before I let you go, um i wanted to ask about the storytelling with data community, because my guess is that um this book really
00:38:55
Speaker
you know, hits the, hits the mark with that community, especially because you've been doing these sort of like before and afters for so, for so long, for years now, if I, if I have my time correctly. and So I guess I'd like, and maybe Cole, you could do this, is to, for folks who don't know what the community is, what it is and how they could get, get involved, especially once they have this book and, you know, maybe want to,
00:39:18
Speaker
I don't know. I feel like you've both mentioned like getting feedback from people. And sometimes I have found that people sometimes are kind of maybe embarrassed to show stuff to their colleagues. And they're like, you know, which I think is kind of a culture thing that's sad and organized. I find kind of sad in organizations if you're scared to show your colleagues something that you're working on. yeah But anyway, um so there's this opportunity for people out there to to work with others. So maybe you could tell us about um the community and and and how they can you know pull all this together.
00:39:48
Speaker
Our online Storytelling with Data community, which you can find at community.storytellingwithdata.com or go to our website, you'll find links there, was really built as a space where people can practice and come together who are interested in building skills when it comes to making good graphs and communicating effectively with data. So we have a number of ways to practice in a low-risk environment and exchange feedback. We do a monthly challenge where we give you certain, you know, might be a certain graph type or certain data type or some different things to try to solve. Mike, what's our current one? Do you know off top of your head? Well, the current one as of record, which would be last month's as you hear it, was how do you visualize something when the target is below goal? Yeah, where lower is better. Where lower is better. Lower is better, yeah.
00:40:44
Speaker
So things like that. So there might be a topic like this, and then you can use whatever data you would like, or sometimes we provide some, and it's just, again, meant to be a place for people to practice. So oftentimes people use it to practice a new tool or maybe a technique that they haven't done before. And then as soon as you submit yours, you're able to see and comment on everybody else's participation. We also have an exercise bank that you can go back through and solve any of the exercises. And there, when you submit your solution, it unlocks the solution from the Storytelling with Data team and from anybody else who's done the exercise. There's some great learning in terms of just comparing and contrasting. And the exercises, for the most part, you're provided everything you need, the data, and the scenario, and you're just meant to, you know, if you have five or 10 minutes free to practice something, it can be a nice space to do that. We also, John, to your point of people being sometimes maybe intimidated to share their work in progress at work, If you can anonymize appropriately, we have places where you can get and give feedback on ah people's data of visualizations. And it's just, it's a really constructive place to be able to practice and share things in a way that allows you to get input from others. And also the the process of giving other people feedback is a fantastic way to learn and and solidify approaches and get your language right. So that can be useful for folks as well.
00:42:18
Speaker
Mike, i don't know if there's anything you want to add on any of that. Yeah, did we miss anything? um I would say this is top of mind because I have one scheduled for later on today is we also there's a paid level for people in the community if they choose to, although basically everything is available for free. But one of the things at that paid level is you can do office hours with the storytellers. And I have an office hour coming up. this afternoon. So that is when you want feedback. If you want feedback in a more private environment with somebody on the team, that is a good way to do that. That's how we spend almost all of our office hours is getting feedback on people specifically.
00:42:55
Speaker
That's pretty good. Terrific. Well, thanks you both, Cole, Mike. Great to see you both. Congratulations on the book. Cole, congratulations on the Storytelling with Data re-release.
00:43:06
Speaker
I hope you guys have a great 2026. Same to you, John. Thanks for having us. You as well. Thanks, John. Thanks for tuning in everybody. Thanks for staying with me. 300 episodes. I don't have any sound effects here, but I would ring a bell or something or set off a firework.
00:43:22
Speaker
Thanks so much for tuning into the show and listening and learning. I hope you enjoyed this episode this week. I hope you'll check out Cole, Mike and Alex's book before and after. And I hope you will reach out and let me know how much you're enjoying the show. Ready to review it wherever you get your podcast, subscribe to it on YouTube.
00:43:41
Speaker
iTunes, Spotify, YouTube, wherever you get it. That's all I've got for you. 300 episodes in the can. Very excited. Now I'm going to go take a break. So until next time, this has been the PolicyViz podcast. Thanks so much for listening.