The Year in Data: 8 Stunning Data Visualization Examples that Defined 2020 with Alli Torban

[00:00:01] CK: Hello! Ho! Ho! Lea Pica here. Today's guest is a data visualization renegade who's here to help us close out one hell of a year in data. Stay tuned to find out which viz is naughty or nice on the Present Beyond Measure Show, episode 63.

[00:00:16] ANNOUNCER: Welcome to the Present Beyond Measure Show, a podcast at the intersection of analytics, data visualization and presentation awesomeness. You'll learn the best tips, tools and techniques for creating analytics visualizations and presentations that inspire data-driven decisions and move you forward. If you're ready to get your insights understood and acted upon you're in the right place. And now your host, Lea Pica.

[00:00:44] LP: Hello, listeners. Welcome to the 63rd episode of the Present Beyond Measure Show, the only podcast at the intersection of presentation, data visualization, storytelling and analytics. This is the place to be if you're ready to make maximum impact and create credibility through thoughtfully presented insights and ideas.

And today you are here because you are either dreading the now virtual company Christmas party with lamp head Zoom backgrounds or maybe you just really want to hear what the best and the worst of 2020 had to offer us in dataviz. So this is the final episode of the year 2020, 2020, 20. Oh! It's a weird echo in here. So, yes, it's been quite a year, right? And I’m still hoping everyone is hanging in there navigating this very different holiday season and adjusting to elements that may become part of our new normal for a bit or for a long bit. But since we're still stuck at home for a while, it seems, I have an amazing guest lineup slated for you in the new year to keep you from getting so bored that you start building dashboards from flung spaghetti and un-vacuumed pet hair. Scary what's happening out there guys.

Now you may have heard that I have this itty-bitty little free 30-second online assessment that will help you identify the number one silent killer of your data presentation success. If you haven't taken it yet, what are you waiting for? After delivering and observing hundreds of corporate data presentations over the last two decades, I’ve seen that most practitioners fall prey to one of four sneaky, silent blind spots in their process for delivering insights during business meetings. This assessment will help you identify your biggest blind spot and give you a free customized report with strategies for overcoming it. So I invite you to check that out at leapica.com/assessment.

So what am I? Can you guess? Okay, yes. I’m excited for today's guest, as usual. And I’m extra excited because we're doing something a little different this time. Today I’m bringing on a fellow radio star from a super popular dataviz podcast to look at our top picks for the most impactful data visualizations inspired by the extraordinary series of events of the year 2020. This episode is not like the rest, and I think we're kicking off a new holiday tradition that will have you ho-ho-hoping for more. Just go with it.

[INTERVIEW]

[00:03:39] LP: Hey everybody. Today's guest on my show is an information design consultant in Washington, D.C. and a leading voice in the field of data visualization on her kick-ass podcast, Data Vis Today, which has been downloaded over a hundred thousand times. Her work has been featured in the likes of Washingtonian Magazine and Nathan Yau's FlowingData. Amazing! And she's been published three times in the Data Visualization Society Journal. She was the keynote speaker at the esteemed astronomy data conference Data2Dome last year. You must have said hi to my mom. And currently she consults with companies big and small to solve their information design challenges.

Please help me welcome, finally, the latest guest in my superstar women in analytics spotlight, Alli Torban. What's up?

[00:04:30] AT: Hi, Lea. I’m so happy we can finally get together and meeting of the podcasts.

[00:04:35] LP: I know. Years in the making. So today is a special show where we are actually doing a double podcast swap at the same time. So, Alli, how would you like me to say hello to your audience?

[00:04:50] AT: Well, Lea Pica, I have been listening to your presentation podcast for so long. You're like the OG data podcaster.

[00:04:59] LP: That's funny.

[00:05:00] AT: Was it 2016 that you started?

[00:05:02] LP: 2015.

[00:05:02] AT: 2015. Wow. I know. I was scrolling back. And it's amazing that you've been going this long. You have such a beautiful radio voice too.

[00:05:11] LP: Oh, thank you.

[00:05:14] AT: Well, Lea is a data storyteller, virtual trainer, keynote speaker. And Lea, can you tell us a little bit about how you got into this line of business? Because you're just kind of taking over the data analytics field, and I’ve always wondered how you ended up here.

[00:05:28] LP: Presentation domination. It's so funny. I’ve never been able to get asked that question on my show. So I’m excited you asked.

[00:05:34] AT: I know.

[00:05:37] LP: Well, what's funny is that I have a musical theater background going back to age three. So I started my street cred pretty early. But in college and trying to get a job I realized that that line of work was maybe not going to support my lifestyle the way I envisioned. So I joined the corporate ranks. I happened to love computers. And I got into data. Loved website analytics and noticed that we kept being asked to present information to these important people. It was an audience like a musical or a play, but not nearly as excited to see you or hear what you had to say or easy to keep engaged because I hadn't learned yet how to sing my way through a quarterly business review.

So eventually when I noticed again and again that no one was taking any action, people were falling asleep, and this was really frustrating to me. I accidentally happened on the book Presentation Zen by Garr Reynolds, and it completely changed my life obviously. So I realized there was an entire discipline, an art and a science around presenting information to the human brain and the human heart and that was the key to inspiring action.

So once I applied all of that, I was able to start making an impact in my organization and then people started asking me to help them with their presentations. Then companies started asking me to speak about creating impact in their organizations. And it led to the journey that kicked off the podcast and a workshop and speaking engagement career that has just been the greatest rollercoaster ride of my life other than motherhood. So that's in a nutshell.

[00:07:21] AT: Yeah. It seems like speaking is such a road to opening up doors.

[00:07:24] LP: Oh my gosh! One thing I want to help people do, this is something, if your listeners or mine are thinking about, is I really want to help people cultivate their voice especially in the industry field because it is the fast track to creating credibility both inside your organization and outside especially if you're really passionate. I don't think there should be any obstacle for people owning their voices and sharing their subject matter expertise at scale when they have something to offer. So that is –

[00:07:55] AT: Making connections too, because I feel like that was a huge benefit of me starting the podcast. It's just like all the connections that you're able to make.

[00:08:02] LP: Hasn't the podcast been the meet your hero fast track?

[00:08:06] AT: Yes.

[00:08:08] LP: Every time, I have to like pinch myself and then I’m like, “Play it cool, Lea. Play it cool.”

[00:08:14] AT: I know. You have had some cool guests. When I had Alberto Cairo on, it was like the database king. I was just like shaking.

[00:08:20] LP: You’re like, “Hah-hah-hah.” Yeah. I get it. I had that moment with him. And Nancy Duarte was a big one last year just from – What an impact. Tremendous impact her work has had on so many of us, right. But you know what you realize is you, me, anyone else who feels the same way, someone out there feels that way about us. We're just goobs. We're just humans who are messy and everyone's a human being.

[00:08:47] AT: Up against the wall.

[00:08:50] LP: Yeah.

[00:08:50] AT: That might not make sense to the podcast listeners, right? I’m up against the blank wall.

[00:08:54] LP: We haven't found that perfect Zoom background yet or in front of a Trevi Fountain or something, or the Northern Lights.

[00:09:00] LP: So happy that we're able to explode the podcasts today. Kind of get a feel for what happened in 2020 and what we're looking forward to in 2021.

[00:09:09] LP: I agree. This is such a unique episode and I’m so excited that this is what we're kicking the year off with, because a lot of times we just ask people, “What did you present recently?” But this time we're talking about the year 2020, a year that was nothing short of extraordinary. It will no doubt live in infamy for generations to come, but it's a year where data really played a starring role in helping the world make sense of the sweeping changes to our way of life, and that was positive and otherwise. And I think in terms of date of viz, it was outstanding. And that's what I’m so excited to look at with you.

[00:09:47] AT: Yeah. It seemed like it has really seeped into the general audience. Everybody is used to seeing a chart multiple times a day now. It’s like everyone's joined our world.

[00:09:58] LP: Right. And something that is to be so mindful of, and this is especially where following Alberto Cairo is critical right now, is finding the truth in that art that we're seeing out there. Learning to be a discerning consumer of data especially in the media where agendas and bias can be an unseen part of that visualization, right? So I'll definitely make sure to put a link to his podcast on both our show for sure.

[00:10:27] AT: Yeah. It's important to have a healthy dose of skepticism when you're looking at charts. And I hope that even though charts have become more popular with people, I hope that will help them further understand that not every chart is to be fully trusted.

[00:10:42] LP: That's right. First step is get excited. So glad people are getting excited about seeing how data can take different forms and especially in storytelling mechanics. Next step, get informed about how to trust that. What you're seeing, right?

So we're going to do something new. We're going to actually take this visual and we're going to take a look at what some of our favorite data viz in 2020 looked like in terms of four of the most important topics that hit this year hard, right?

Okay. So I know Alli can see my screen. Hopefully you can too. So the first topic, somewhat little-known topic under people's radar right now. Just kidding. It's around coronavirus. So I don't think there's been any other topic in the news media that has had more media coverage and more visualizations, but what we're going to do is for each of these four topics, show each of our most memorable visualizations or stories that we saw that really made us think. And that's the whole point of viz, right?

So, Ali, you brought to my attention a Washington Post article by Harry Stevens; Why Outbreaks Like Coronavirus Spread Exponentially and How to Flatten the Curve? So take us through this one.

[00:12:03] AT: So this came out March 14th, 2020. And for me it was probably similar all across the U.S. But I mean mid-March was the time. We all shut down. And we kept hearing, “Flatten the curve. Flatten the curve. Flatten the curve.” And I’m a math major. So I mean I understand modeling and everything, but even I was just like, “I don't really know what that means.”

[00:12:25] LP: Yeah.  Yup.

[00:12:27] AT: Even though you would see charts of like okay, “Here's a curve and then here's a flatter curve.” You still didn't really get it. So this piece by Harry Stevens just kind of blew my mind and I think brought so many people understanding on what actually flattened the curve meant, and he did that by just showing this simulation of these balls bouncing around. If you scroll down a little bit you can see there's a little bit more. They have –

[00:12:52] LP: So that's the first curve where people were like, “What?”

[00:12:55] AT: Mm-hmm. Yeah. It's a line chart just showing the start rising of the number of cases. And then it's just trying to start to show you one infected person, or in this case just a red ball, how it goes back and forth and just travels around randomly. And when it hits another ball, it infects it. And it shows as that ball hits other balls just how quickly the infection can spread to so many people, exponential growth.

So seeing those balls just move around you quickly understand how this problem can really get out of control. And the really important part is that later in the article he shows here's how this model would play out if we did this measure, if we did that measure, like quarantining. And then it really showed you what flattened the curve meant, because it showed you in real-time these balls are bouncing around, they're getting infected and then it also has an area chart at the top showing you the number of infections that are happening so you can see how, if you take certain precautions like quarantining, the curve of the number of infections gets flattened.

[00:14:09] LP: Right. Right. Yeah. This was absolutely fascinating. Do you have any idea what he used to create something like this?

[00:14:15] AT: I don't. But I think he has been on other interview shows explaining –

[00:14:21] LP: How he did? Yeah.

[00:14:22] AT: Yeah. Yeah. But it's not exactly simulating COVID in particular. It's more just a model of how something like –

[00:14:29] LP: A vector of transmission.

[00:14:31] AT: Yeah. And it was just so amazing that a simulation paired with data visualization can be so powerful and explain something so complex and so important to so many people. I think Washington Post said this was the most read article on their site.

[00:14:48] LP: It made sense. I remember when this came out, because I help people with simple viz, because getting back to basics sometimes is the best way to help a lay audience, like a C-level audience understand business data. But when it comes to events like this where even these four graphs at the bottom where they show the free-for-all attempted quarantine, moderate distancing, extensive distancing, these are views that we are not necessarily trained to understand right away. But when they're executed so well with the right – Like there's a story here. He's showing a progression through a story showing those differences between each stage. And our brains are able to see the differences and make sense of those differences. If I saw just the moderate distancing chart on its own, I may be like, “Okay, I’m not exactly sure what that means,” but it's the relativity between the curves when we're in these other scenarios that for me says, “Oh, I see what this spike looks like in the free-for-all.” Then attempting it with a bit of a lag, then distancing kind of earlier in the process and then just really going more extreme.

[00:16:07] AT: Yeah. And the fact that he already walked us through these charts slowly –

[00:16:11] LP: Right. By the time we got here.

[00:16:13] AT: You saw them basically being built as the simulation went on. So that's a great thing for people to use. If you are going to show complex information, maybe step them through it first so they can really see, “Okay, this is what happens as we step through time.” And then when you put more complex charts together, people understand them.

[00:16:32] LP: Absolutely. And what else he did here other than just showing the curve over time was his simulation created a relatable concept that we could understand where we are dots as people. We don't move the way a curve moves, but we move the way these dots move. We can instantly relate that to human behavior. And seeing that spread or lack of spread, then we can start to make sense of that. So that's what I found to be really powerful for being able to relate that to how the curve unfolded.

[00:17:03] AT: I totally agree. This was a very, very successful visualization.

[00:17:07] LP: Yeah.  Hats off to this guy. Okay. So the next one, and I saw this back also it's March 22nd of this year. I saw this one. My brain was really trying to make sense of what in the world was going on and this story absolutely captured my attention and imagination. Again, it used a similar technique of relating data into human behavior where it plotted out the potential, the estimated spread of this virus based on traveler behavior using people as dots, tracking actual movement.

So the way that the New York Times executed this is they had these very simple easy to read boxes of what actually happened in the beginning. It seems simple. Stop travel. Stop the virus. Here's why that didn't work. Excellent storytelling technique from the beginning, saying something we expected and showing that it did not turn out as expected. And as you progress down the natural scrolling behavior, which a lot of the viz’s we're seeing are using now. They zoom in into a train station in Wuhan and they start to explain step by step the things that they knew would happen, the Huanan seafood market through the train station.

So as you keep scrolling, they literally walk you through how they've translated the data to different milestones in the story. And as the story progresses, you start to see the people as the number of cases as dots that form. And I couldn't stop scrolling. I had to keep going. It leveraged such a clever way of having this unfold and changing the view all the time. So zooming out and looking at all of China and all the pathways of where people were traveling back to hometowns for Lunar New Year. And then 175,000 people left Wuhan just on that day, which was staggering statistic. And you can see the outpouring here.

As you keep going, the map view changes. You start to see the tracked infected cases and how they spread out. And I was just absolutely in capture this. I felt this was such an ingenious way of telling the story in a way that was easy to grasp and even relating to the travel systems through all of Asia just absolutely incredible. So this is not one to miss for me. I feel like a tremendous amount of effort and thought went into telling this particular story. As I’m paging through, I’m just remembering how incredibly fascinating it was. What are your thoughts, Ali?

[00:19:59] AT: What I really like is when it's zoomed out, it looks like a network diagram yeah laid on a map. But if you zoom in a little bit, you start seeing that it's not a line that's the network diagram. It's a series of dots kind of huddled together. So it really gives you that feeling. Like these are people traveling. These people are infected and they're traveling out to all these cities. And then they're traveling further out to more cities. So you really get that like in that previous version where the people were balls and in here the people are dots. You're not seeing aggregate measures. You're seeing actual people.

[00:20:37] LP: Right. Exactly in the way they're telling the story, what I love how they do is they zoom in on the closest level and then they take steps to start spiraling that zoom outward to Asia. Then they move here to the United States and what the U.S – The steps that U.S. took. I just found this to be absolutely groundbreaking in terms of understanding what data was able to tell us about how things happened. And from a visualization perspective, it embodies all of the best, most effective storytelling mechanics I can think of. If you're not presenting something to someone live, this visualization and these boxes acted as the narrator for me that spoke in such a humanly approachable way that I just got it, all of it.

[00:21:30] AT: Yeah, the scrolly telling technique has been –

[00:21:33] LP: Scrolly telling. I never heard that.

[00:21:34] AT: Yeah. That's what they call it, the scrolly telling, where as you scroll it kind of jumps you around. And I love how they kind of started at the source. And then, of course, every reader or listener is thinking, “Well, how does that affect me?” So they did that. At the end, most of the readers of the New York Times are in the U.S. So they jumped to the United States. So you could see exactly, “Okay. Now that we saw where it started, how was this affecting us?” So this was great.

[00:22:01] LP: Yeah, awesome. Okay. So these are just two examples. But if you're listening to the podcast and you come to visit either of the shows, I would love to see your favorite visualizations as it related to COVID. I think there are so many that would benefit and also a lot to be learned from in terms of doing data viz too. All right. Cool. So we're going to go to our next topic. I love this so much, Ali.

[00:22:27] AT: Yeah, it's great. The scrolling telling is very popular.

[00:22:31] LP: No. I’m saying I just love this data diving.

[00:22:35] AT: Oh! Our database tennis match?

[00:22:37] LP: Yeah.

[00:22:37] AT: Back and forth.

[00:22:38] LP: Yeah, data viz death match. Okay. Cool. All right. So a second big topic that didn't necessarily have a huge new focus on, but it's been a continuing focus for us. And I think as the election is upon us now, that's actually when we're recording right before Election Day, is climate change. This is actually what inspired our episode. So you brought this to my attention. So tell us about the warming stripes visualization.

[00:23:12] AT: Well, I’m pretty sure this won't be new to anybody, because this has been around since 2018, the climate scientist at Hawkins. He wanted to create a graphic that explained how the global temperatures were rising in a way that was really easy for people to understand. So he ended up with this almost barcode-looking visual where one line is one year and it's colored more blue if it was cooler and more red if it was hotter. So you just got these lines stacked up next to each other and you can see it used to be colder around the world and now it's getting hotter. And the amazing part was in 2019 this really went mainstream and you started seeing it. People started wearing it on shirts and having it on billboards and everything. And I really think that it got even more mainstream in 2020 because I started seeing it on face masks.

[00:24:03] LP: Oh wow! Crazy.

[00:24:05] AT: Can you imagine? Can you imagine that having a data visualization that means something so important on your face?

[00:24:12] LP: It became an emblem.

[00:24:13] AT: You wouldn’t have thought about it before 2019. Yeah. You would not have thought about that in 2019 that this would be on someone's face in 2020.

[00:24:19] LP: It is crazy. When something like a visualization becomes an emblem for a movement, that I think is an accomplishment to be recognized.

[00:24:28] AT: Yeah. And I think that this really stood out to me. Seeing it on a face mask, it just like became crystal clear to me that if the world of surface patterns. If you look around you, almost every single thing has a pattern on it, right? And we are missing – As data viz practitioners, we are missing all these opportunities to put our most important message on these things.

So I think at the end of 2020 and hopefully in 2021 and beyond people will realize the amazing baby that data viz and pattern making could have on sharing their message, their really important message. That's why this one was so important to me.

[00:25:13] LP: No. I loved it. Somehow this escaped me, but tell me. So from the years 1850 to 2019, each one of these stripes or bars represents a deviation from average temperature. Why would one be somewhat bluer versus redder?

[00:25:32] AT: I think it's just the actual average temperature.

[00:25:34] LP: Okay. Gotcha.

[00:25:36] AT: So then you've got like the average temperature. This one was however many Celsius and then it just gets hotter and hotter. And then the cool part was he made this site where you could kind of click around and go to Africa, or Asia, and then you can actually go to your country and I think maybe even down to the city level.

[00:25:51] LP: Yeah. So, Africa, that's definitely more extreme. You can see much bolder differences here in terms of those colors.

[00:26:00] AT: You can download the image. Make it your background. A lot of people are doing that, making it like a Twitter background.

[00:26:06] LP: Yeah. And North America, pretty interesting too, there's a lot of back and forth between. Whereas before, I think in global, we saw much more blue going over to more red. What would be one area – I guess, maybe, let's see South America. All of South America. Yeah, so similar to North America. Just very extreme blocks. Some pretty deep red blocks. Yeah, very simple and brilliant, but amazing how impactful and memorable that can be.

[00:26:38] AT: I know. Just lines. Colored lines.

[00:26:39] LP: Colored lines. But you know what it means. You know what it means.

[00:26:44] AT: Yes.

[00:26:44] LP: Very cool. So actually the one that I found is kind of leveraging some of the same visual cues to generate that alert like, “Oh crap! Where are we going?” But leveraged animation in such a creative way. So rather than having one view showing all of the time available and how it changed, he animated a series of views where each view was one year and showed a distribution of deviation from average temperatures over every country. So you can see here we have all major countries. And the bubbles represent whether it went way above average temperature or below. And the animation, I'll animate now. So we're like, “Okay. Not so bad.” There's almost like a heartbeat happening here like, “Okay, I think it's a little red, a little blue. Doesn’t seem so bad.”

And as the years start to get closer to the last 30 years or so, that's when all of a sudden you feel like your pulse is accelerating a bit right around here where all of a sudden you're seeing a lot of pulsating reds and oranges. And it gets to a point where there's not a single country on here that's not above average in temperature.

[00:28:08] AT: Yeah. The difference from the warming stripes that you see, “Okay, just one place. Oh, here's just North America, or here's the world,” and you can kind of see one view of that. But this one is showing a whole bunch of countries and you're seeing across the board it's all red. You just can't be like, “Oh, I’m fine,” and everyone else is –

[00:28:28] LP: Maybe it's just the Pacific.

[00:28:31] AT: Yeah. You can't make excuses anymore. That's the beauty of this one, is that it's just so in your face about how widespread it is.

[00:28:38] LP: Exactly. And I think that the pulsating nature of this especially as it starts to get to the later years like, say, around here, I'll play it again, is I actually felt my nervous system accelerating along with this. I was like, “Oh, wait. What? Oh! Oh! Oh!”

[00:28:54] AT: How bad is this going to be?

[00:28:57] LP: And that, I think, when you're leveraging the exact psychological triggers like an acceleration of something towards something people don't want or something people do want, that is when I think you've really hit the nail on the head on persuasiveness.

[00:29:15] AT: I totally agree.

[00:29:17] LP: Right. So that was my favorite one for climate change. When I say favorite, I mean most powerful but not favorite story. All right. Cool. So the next topic of the year, definitely one of the sadder, more polarizing in a way I don't think people expected. But this was the racial inequality, Black Lives Matter, George Floyd movement that happened. And what I have to say is that, for me personally, that event absolutely catalyzed an awareness around racial inequality and prejudice and police brutality in a way that was sorely needed. So I’m happy that we get to include looking at some of these visualizations today. So you brought to me a duration of protests that create change.

[00:30:09] AT: This is an Instagram post by Mona Chalabi, and she's a data journalist at The Guardian. And her Instagram is huge. And she –

[00:30:21] LP: I see that.

[00:30:21] AT: Yeah. She has 500,000 followers. I mean, it's insane. She's the most followed data viz person I know.

[00:30:27] LP: Cool.

[00:30:28] AT: And one of the great things about her approach is that she doesn't think that there should be any kind of barrier to understanding information. So she actually hand draws most of her charts so that it feels a little bit more approachable. And she utilizes the medium of Instagram really well. So in this chart it says duration of protests that create change. So what she did was she just created a simple bar chart showing how long protests lasted. So starting from protesting George Floyd's murder all the way down to Montgomery bus boycott. And the Y-axis is just showing the number of days that the protest lasted. And as you click through –

[00:31:12] LP: So just before I click through, each of these graphics, these picture cutouts represent a different event in the racism movement?

[00:31:25] AT: Yeah, different –

[00:31:26] LP: Other racism movement.

[00:31:27] AT: Protesting events. Yeah. Yeah. So the Montgomery bus boycott, the protesting George Floyd's murder. And then she has three other ones there also. So one, two, three, six, six categories. Yeah. So you can see George at that time, protesting George Floyd's murder, had lasted around 20 days so far. Then she instead of putting the bar chart all in one view, in one picture, she makes you click to go to the next page and then it shows a little bit more of the bar chart. And you see the Birmingham movement lasted around 35 days. Then you got to click again and click again. And then you see the Greensboro sit-ins, which is about 100 – What is that 80 days? And then you got to click again. And you see the Chicago Freedom Movement, the Freedom Riders lasted around 230 days. And then you have to click again and again and again until the very end.

[00:32:20] LP: Still demanding.

[00:32:22] AT: Yes. Montgomery bus boycott ended. This is the last slide, and it was what? 380 days that people were protesting. So it just gave amazing context. That's a great part about data viz, it gives you context, but she just didn't present you with the bar chart. She made you actually feel time a little bit more by making you click over and over and over and over again. This is on Instagram. People are just scrolling looking at random pictures. And the fact that she can get you to engage and really understand and feel this information, I thought this was very successful.

[00:32:57] LP: That is incredible, because you don't think of Instagram – I mean in terms of data viz, you might think of Instagram as something where you see incredible radial or very complex advanced chart types.

[00:33:10] AT: Data art.

[00:33:11] LP: Alongside cats and food photos. But it's amazing that you use this sort of page turning effect that Instagram allows for to essentially show one data viz, but not all at once. And for me that's one of my favorite tips of data presentation of all time, is don't show it all at once. Break it up into views and build that story as you go. Keep adding on to that view to create that bigger picture or to zoom in or to create that turn of events that keeps people paying attention.

[00:33:44] AT: Totally.

[00:33:45] LP: Wow! That is really cool. I’m definitely going to follow her and I'll make sure that she's on this page too.

[BREAK]

[00:33:52] LP: There's never been a more important time for presenting data accurately, confidently and impactfully to your stakeholders and clients. If you're a leader or agency owner whose team is responsible for driving database decisions and keeping satisfied clients and if you've tried other data storytelling courses, trainings or instructors in the past who miss the mark, I get it. With over seven years of experience training data and digital practitioners in the unique art and science of presenting data, who knows the unique challenges of this field? Having been in it myself for 12 years, I’m ready to help. I offer both live, virtual and online course solutions with ongoing learning support options that suit your specific organization's needs. Visit leapica.com/workshops to schedule your strategy session with me and we'll get started on your custom training solution today. That's leapica.com/workshops.

[INTERVIEW CONTINUED]

[00:34:55] LP: So this data viz for me in the race conversation I actually came across before this year. And I want to say that it had the permanent effect that it should have had, but it didn't. But George Floyd and Watching 13th, the documentary, reinforced what I should have really taken away from this. So for me, this was just kind of a blog post that I think went a little bit viral was the most sobering thing about something called the racial dot map.

So 2010 census data was used to create a map, a demographic map of the United States that could go really, really in, like zoomed in at the house level. That's the power of the census. And then they use different colored dots for people of different races. So what you were able to see, she had some initial views. She didn't create any sort of special visualization for this. And all she did was take screenshots. But the way that she told her journey through her own understanding of this map I found to be absolutely compelling and a little chilling.

So she's walking us through and see, “Okay, I’m exploring this data,” the racial dot map, “and here's Chicago. You can see lots of interesting places.” In particular, to know, blue dots are white people, green for black, orange for Hispanic, red for Asian and brown for Native Americans. That's just how the map was decided. So this one was Chicago. This one is LA. This one, Washington, D.C. There you are. And then she has this surprising turn of events where she started zooming in on some very rural areas that had a lot of blue, but then extremely densely concentrated green with some orange. And when she decided to find the same location on a Google map, she found correctional facilities, prisons.

And I’m telling you every hair stood up on my skin when she made that connection here, because it's such a strange looking thing on this map. And then you see this. And when I saw this, it was not on my radar around the extreme racial disparity in the prison system. And that's what led me to watch 13th. And she kept scanning ruler areas and kept finding them again and again most interestingly in areas that are predominantly blue, which is another issue around this where I read that a lot of correctional facilities are in predominantly white areas. And it is challenging to hire diverse correctional staff. And that can be creating issues on its own. So she just found them over and over again, these very strangely demarcated areas in areas of blue. There's another one.

[00:38:04] AT: Yeah. They look exactly the shape of buildings. That’s so strange.

[00:38:07] LP: That's exactly –

[00:38:08] AT: Yeah. All the other dots are organically placed like normal people. But then there's these almost cookie cutter squares where the colors are completely different. That's very stark.

[00:38:19] LP: That's right. The closing thought she had in this post, I want to say here, because for me it encapsulates a blind spot that I have had so much and I want to unveil for myself and others. She says, “When activists talk about the criminalization of the African-American male and the need for prison reform, this is what they're talking about, an imprisoned population so racially imbalanced that you can find the locations of correctional facilities on a map that shows only demography and nothing else.”

[00:38:53] AT: Crazy. And this is by someone named Libby Anne, right?

[00:38:56] LP: Yes. She has a blog called Love, Joy and Feminism. So not what you would maybe expect here, but this visualization did make it out into the mainstream media for being such a compelling story. And I think there's a lot to take away from it in terms of the message, but also how she went about it.

[00:39:15] AT: Yeah. Yeah. This is very moving, and it's amazing how you can take – Because I think this started out – I don't know if the article says, but the maps look familiar. I think this might be from just a Washington Post article that they created the dataset or they had the dataset and they put it together and then she found this story herself as she was looking through it. That's amazing.

[00:39:38] LP: Exactly. That's what I found so powerful, that this was an accidental find. She didn't have a particular agenda or message in mind saying, “I’m going to find a story here about racial inequality. I’m just going to poke around,” and here it was right in front of her. Really powerful data.

All right. So the final topic that we're going over today, we are in the midst of the pressure cooker right now of this. And by the time this airs, it may be decided. Not sure.

[00:40:14] AT: We'll see.

[00:40:15] LP: Not sure about that, but we’ll see. So it is the 2020 Election. Oh my gosh! What an incredibly hot topic. So let's bring up the visualization you had in mind. You brought up something from 538. So take us through what we're looking at.

[00:40:32] AT: Okay. So 538, very popular in terms of elections and modeling and data viz. And one cool thing that they did for this year was they did this election snake almost. And normally when you're seeing election results, you see a basic choropleth map. You have the states and then they're colored blue or they're colored red. And the problem with a choropleth map like that is that something like Texas or some state from the Midwest, it looks really big, or you see a lot of blue or you see a lot of red just because of the land area, but it doesn't really give you any information about how many electoral votes, or is this person actually winning?

So if you scroll down a little bit, they did this thing, I think it's called the road to –

[00:41:18] LP: The winding path to victory?

[00:41:19] AT: The winding path to victory. And I love this kind of visual metaphor that they're using, the winding path to victory. So it looks like a snake. It’s like this back and forth coils or maybe like a really windy road. And the segments are the states and the length of this segment is how many electoral votes that state has. So Texas is really long. And the color of the segment is which way it's leaning? Like is it going to be more republican or is it more democrat?

And what I really love about this is that it's so approachable. This winding path to victory, everybody understands what that means. Everybody understands a road, right? So this visual metaphor is very approachable and people don't feel this instant chart phobia when they see like a map and a bunch of information about electoral votes and everything. This is just a very simple way to see, “Okay. Well, Texas is really big. This is really important on what color it is.” Or, “Here's this tiny little segment. It's probably not as important what color that one is.” So it communicates the information in a very unique and approachable way, and that's why I really, really enjoyed this 538 graphic.

[00:42:35] LP: Yeah. So what I would love for you to help me make sure I understand, because with graphs like this, I know for me, if I’m not immediately fluent in the construct that it's built in. Especially around something with the electoral college I feel is something so obscure for most people, like esoteric. And everyone hopes that people get elected based on a majority vote, right? But that's not how this works, and that's why there are battleground states and such.

So for me, I look at this and I’m in Pennsylvania. Everywhere I hear is that Pennsylvania is a very, very important state in this election. So when it comes across 270 electoral votes, the darker states, what does it mean if they have a darker color?

[00:43:23] AT: My understanding is that it's more leaning a particular way.

[00:43:27] LP: Gotcha. Okay.

[00:43:28] AT: It's less of a battleground. Is pennsylvania more in the middle?

[00:43:32] LP: It's leaning democrat, but it's definitely on the lighter side. So margin of victory is that legend. That's the coolest legend I’ve ever seen.

[00:43:38] AT: Oh, yeah. Yeah, that is cool. It’s a little example of the road. It’s tiny road colored.

[00:43:43] LP: And what’s interesting, I just noticed they have tool tips, really visual tool tips. So 20 electoral votes in Pennsylvania forecasted vote shares. So it's a tight race. So that's why it's such a light color, but a good number of electoral votes. And that's why the snake is longer, right? That's the number of votes.

[00:44:02] AT: Yeah. And I love how when you hover over it. It shows you the outline of the state as well. So your mind can put everything together. You see a really long snake or a really long segment and then you hover over it and it says California and it also has the outline of the actual state of California. So everything in your mind is working together.

[00:44:19] LP: Lots of visual cues, because when something is so visually unfamiliar to someone, you're grounding people back in visual shapes that can help people connect to the information, right? So even though the snake shape is more accurate than coloring all of California in a chloroplast map. And just in case someone's not aware, a chloralpleth is when you're seeing the actual shapes of states and then each state is colored to sort of represent that state at the state level, right? Yup. So just making sure that people are aware of that. And then there's a tiny one in here, Maine. What family is that?

[00:44:59] AT: A little segment.

[00:45:00] LP: Teeny, tiny one electoral vote, but it’s a little state that could. But what it looks like is on Trump's side there are smaller states with lower electoral votes, right? But there's pretty big states with a pretty even distribution, right? So that's why these states are vital, right? Florida, Georgia, Ohio, Texas.

[00:45:25] AT: Yeah. And something like New York would not necessarily jump out at you on a corporate map, because it's medium to small I would say.

[00:45:33] LP: It’s not that big.

[00:45:34] AT: Yeah. But here on this one, it takes a significant amount of room, because there is a lot of people in New York.

[00:45:38] LP: Right. Exactly. Now this line, there's a line here that says 270 electoral votes. And it goes through Pennsylvania. What I’m trying to figure out is where they're dividing this line, does this mean that there are exactly 270 votes on either side? Do you think that's what that means?

[00:45:57] AT: I’m not sure.

[00:45:59] LP: That's the one question mark I have around this is –

[00:46:02] AT: Yeah. I actually hadn't noticed that.

[00:46:03] LP: Is it a tie if all of these end up getting won the way that they're leaning? But that's okay. I think the really important information is understanding how big these states are in terms of their vote power and where they're leaning, right?

[00:46:17] AT: Mm-hmm. Yeah, definitely.

[00:46:19] LP: This one's definitely you have to check out. Very, very innovative, inventive way. Cool. So for our final viz on this show, I love this graph so much. I don't know how they came up with this, but it's called the Electoral College Decision Tree. Shan Carter and Mike Bostock created this. So here is another way of visualizing the road to victory. And what it does is look at any number of combinations that they could win these states where it's either a landslide and none of the other states matter, or it has to be like a big combination of winning littler states.

So you start at the middle here where things line up and you go to this first node. And if Biden wins Florida, that's what you see come up on the left side. There's a little storytelling gadget there. And I travel to this next node. If Biden wins Florida and Pennsylvania, because that's how long that Pennsylvania node is, then Biden wins. Then it doesn't even matter –

[00:47:26] AT: That’s interesting.

[00:47:28] LP: How powerful is that? This helps you understand that. If you travel to the next node, you can say if Biden wins Florida, but Trump wins Pennsylvania, there isn't a decision yet. If you move to this next node, if Biden wins Florida and Ohio, but Trump wins Pennsylvania, Biden still wins.

So as you are traveling down these nodes, let's say you'd have to go here. This is an interesting scenario. If Biden wins Florida, but Trump wins Pennsylvania, Ohio, and Georgia, and North Carolina, and Arizona and you keep going, and Maine, then Trump wins.

[00:48:08] AT: Wow.

[00:48:09] LP: But if Trump wins these smaller states but at some point encounters Arizona or then Wisconsin and these other states, Biden still wins. So that's what I think is so fascinating about how these nodes play out, because you can literally look at any combination of states one, but still see which ones are ultimately going to matter.

[00:48:32] AT: Yeah. It's almost like choose your own adventure kind of thing.

[00:48:34] LP: That's right. And it's a really interesting way to interact with the results of the election as different states are going to come in and they're saying it's going to take a while to count all the votes and all of that stuff.

[00:48:46] AT: You need to secretly have it up. So when you're talking to people, you're looking like, “Oh, Biden took North Carolina. That means –”

[00:48:54] LP: And everyone's going to be like, “Yay!” And I’m like, “Well, maybe, but –”

[00:48:58] AT: Here are the possible outcomes right now. You can sound like a political analyst with this chart.

[00:49:03] LP: That's exactly right, and these are the kinds of charts that are going to help voters become more engaged with the voting process and even appreciate the power of their vote especially if they're in a swing state. I’m in Pennsylvania and I’m putting a lot of power behind my vote, because it matters, right? So this is such a fascinating way to see how many possibilities can play out especially in a circular form which we can often be told to avoid.

[00:49:31] AT: Yeah. And considering that there are – As you think about it, there are a ton of options. But looking at this chart is a circle like you said, but it doesn't feel that intimidating. It doesn't feel like there's that much information here. It feels like I could scroll over every node and it wouldn't be too bad, but it still has a ton of information.

[00:49:50] LP: It encodes an incredible amount of information. So many probabilities. And I think the key to making this work is that, first, storytelling narration piece that happens right in that upper little left corner that guides you as you're moving along these nodes and seeing things change. You're like, “I get it. I got it within 15 seconds of mousing around.”

[00:50:15] AT: Yeah.  Yeah, getting that instant feedback helps you understand, “Okay, what exactly is happening here?” And you probably see these decision trees all the time, the dendrogram, like a tree diagram, but having it in a circular form, a circular dendogram definitely gives it a new appeal.

[00:50:31] LP: Right. Exactly. Kind of like rivers. Rivers that can go in all sorts of directions depending on the rocks you put in the flow, right? Well, that was awesome. I feel like this is something we might have to do every year. We should make this an annual thing.

[00:50:47] AT: Yes, I agree. Famous tennis.

[00:50:51] LP: Exactly. So, Alli, obviously you have a vast knowledge set. You're like on the cutting edge of what's happening in data viz. So I would love to understand, what's the most underrated way that you have found to make your visualizations more understandable to your audience especially when they're a little out of the box like these?

[00:51:12] AT: Yeah. I think that one thing is – When you start in data viz, you feel like you need to do these kind of out of the box things. And that can lead you. I know it did for me when I first started. It can lead you to creating things that are too complicated, unnecessarily complicated, because you feel like, “Oh, well, I kind of need to keep up. There're all these new and innovative things.” But you can still communicate complex information, but it does not need to be all in one chart. You can break up what you're trying to say in one, two, three charts. And what we were talking about earlier, lead someone into it in sequence charts to really show your information, and that can be very powerful. You do not need to have an interactive circular dendrogram to get your point across.

But one cool tip that if you do want to create something like that there is a web-based application called rawgraphs.io. And circular dendrogram is one of the charts that you can create. You just paste your information in there. And we were talking a lot about I want to show my data. I don't want to show an aggregate information. I want to show one person as one dot. You can also do something like that in rawgraphs.io called a bee swarm plot. So that chart type is actually hard to come by. You can't really do it in Tableau very easily. It's certainly not in Excel. So if you want to try something like that, we were talking about how powerful it is to show this data point as one person. Definitely try out a bee swarm plot on rawgraphs.io.

[00:52:45] LP: Cool. I love that tip. May I share my own since I know we’re – Go on both ways.

[00:52:48] AT: Yes. I wanted to ask you. I don't know if this is about presentation, but if you want to share your tip and/or – I wanted to ask you. I am trying to encourage new data viz practitioners. People ask me, “How can I get started?” And I tell them start creating things and sharing them. Speak at conferences. Just start creating and sharing. But a lot of people, myself included, are petrified of speaking in front of other people. So I just love how down you have your presenting skills. So if you were mentoring a young person, can you tell them just one piece of advice how would you get better at presenting information?

[00:53:28] AT: Well, I’m not going to lie. I think one of the fastest ways is to take my courses, which I can provide ways of doing that. And I mean that's half joking. Honestly, having the right guidance in that area. No one figured this out on their own. I actually had clinical stage fright in high school and college having to perform where I would have panic attacks before going on stage. Sometimes my voice would close up. And that started following me into corporate presentations, except I just kept doing it and I started getting guidance for helping me examine what my blocks were. I hated the sound of my voice. So starting a podcast was horrifying. So I started learning to refine my speech patterns. I was wondering why my data points would fall so flat and then I discovered storytelling mechanics.

So one tip I'd love to give actually and making them more understandable, I had this eureka moment when I was working with what I call my online course cohorts. So every quarter I take a small group of people through my online course, but personally, and I get to coach them. And it's a rare set of access that they can have. And I had this moment with them where I realized they kept saying, “How can I make this feel more engaging and understandable?” And I said – Popped into my mind about reading bedtime stories to kids. Bedtime stories are so visually well laid out and they're step by step. I think that's why the coronavirus visual is so powerful to me, because it literally was like paging through a grown-up bedtime story about a very intense topic. But that's what made it work so well, where imagine if you were getting – Don't get in bed with a stakeholder. But imagine you were having story time around a fire with your stakeholders or your clients. How would you be like, “Once upon, a time we had a landing page, and this landing page did this over here. But one day we decided to do a test.” You can see how that might come alive if you're breaking up into that. And bedtime stories is a fantastic mechanism for seeing how very engaging stories play out.

[00:55:46] AT: And it's really great for it to simplify too. Just remember, you're speaking clearly, you're speaking to maybe a young person.

[00:55:52] LP: That's right. Because they say you should be speaking to at all times, whether you're writing or presenting, to a very smart fifth grader. That is the highest level you should be speaking to. That's an 11-year-old, I think. So how can you make some of that data understandable? Well, I'll tell you that when I was judging visualization entries for the Women in Analytics Conference, I did it with my seven-year-old son. And certain ones he was able to understand right away because of how well they stepped through the stories. So it doesn't have to be told in a complex way to lose the beauty of how complex something might be, but the beauty is telling it in a simple way.

[00:56:35] AT: Yeah. That's great. That's great advice. Thank you.

[00:56:38] LP: Sure. It can also help with speaking skills. You'll notice that you'll be more dramatic in your speaking like, “Oh! And who's around the corner?” So you'll use a wider range of vocal tones and intonation. You tend to articulate words more clearly. So just reading bedtime stories in general is an excellent practice as a speaker.

[00:56:58] AT: Not being afraid of pauses too. That's a hard thing. That's a hard one for me. Just pause for a minute.

[00:57:04] LP: And think of those pauses as the page turns in that story. Bedtime stories are so well- designed to pause at a cliffhanger. So you have to turn that page. So just think of your slide transitions as page turns. They want to see what's next.

[00:57:21] AT: That's great.

[00:57:32] LP: So, Alli, in my show, we have come to a segment I call the upgrade. And it's any tool, resource, platform, book something, that the listeners can check out right away and they're either going to love it or it's going to totally level up their game. What do you have for us?

[00:57:49] AT: Well, I think I might have spoiled it earlier. I told you about rawgraphs.io. That's my secret weapon, because sometimes I create visualizations and people be like, “How did you do that?” I’m like, “Oh! Well, rawgraphs.io.” And you can export it as an SVG if you are – I know a lot of people who are in Adobe Illustrator or graphic designers that want to do some more interesting chart types, but Adobe Illustrator doesn't really have a very good in-app charting options. They're kind of hard. So what I'd love to do, my go-to workflow, is to create the chart in rawgraphs.io or Tableau. In rawgraphs.io, I export as SVG and import into Tableau and then I can clean it up and add titles and legends more clearly, add annotations. And something that people don't always know either is that when you create something in Tableau, it is also really hard to create annotations and stuff there. So if you export your dashboard as a PDF, you can import it into illustrator and then all the elements come in as vector elements. So you can completely customize it. It does not come in as an image. It comes in as a vector file. So you can change all the colors if you want to or delete some of the axes if they're redundant. So that is my number one workflow tip, and it's really great.

[00:59:15] LP: That is a baller tip. One of the best, for sure. Awesome. All right. So we've arrived at the final question that I have for you. So this is final question. Think very hard and imagine this very plausible scenario. You're hard at work designing a beautiful new STEM-inspired wallpaper based on the Fibonacci sequence, which you're definitely sending to me, when suddenly you're sucked into a vortex through your screen that pulls you back to the moment you're about to deliver your first presentation. What are you presenting about and what would today you say to yesterday you?

[00:59:55] AT: Oh my gosh! My very first presentation – Well, I think the one that comes to mind is one I did in high school, and it was about interpreting dreams. Yeah, and it was really interesting. But I was so nervous, my voice was very monotone and I was trying to be quiet like as if I’m presenting and no one would notice me.

[01:00:20] LP: Like, “I’m not really a here, guys.”

[01:00:21] AT: Yes, exactly. And then the students had to write a feedback. And someone wrote she has a very nice voice, but she put me to sleep. Oh man! That's not a good presenting.

[01:00:37] LP: So cross that strategy off the list.

[01:00:39] AT: Yes. I’m so, “Not a strategy.” So that feedback, plus hearing myself over and over again on the podcast, I realized how much energy is sucked especially when you're talking over a microphone and people can't hear you. It's not as bad, I don't think, when you're in-person. But it's still a little bit. You have to be dynamic. And otherwise people think you're sleeping up there and then you're going to put them to sleep. So I would tell myself to not be afraid to be dynamic. It's a lose-lose if you feel like if your monotone – I don't really know what the thought process is. If you're monotone, people won't notice you. I don't know. You have to be dynamic. You just have to be.

[01:01:22] LP: It's so true, especially now that we've moved to a virtual environment. We no longer have the ability to captivate an audience through just our energy field from being a live human being, but also the motion that our body creates when we're naturally using our hands, because we're sitting behind desks and maybe our arms are hanging.

So I always say keep your arms bent at your desk, which keeps your hands above invisible view and you can still accentuate. But you're absolutely right. It took listening to a recording of myself to understand how comatose I sounded on a recording medium outside of my body. And it was a long road from there. But the way I like to think about it is imagine a friend you haven't seen in two years. You used to be really close. Think about how excited you would be to see them and that tone of like, “Oh my gosh! How are you?” And then take it a notch or two down and you found the perfect level of approachable excitement.

[01:02:22] AT: Mm-hmm. And then when you listen back to it, you're going to think, “I sounded like a crazy person,” but this just sounds like a normal person talking.

[01:02:30] LP: That's right. It's going to feel crazy, but it's not going to sound crazy when you listen. Awesome. Well, that was my last question for you. I don't know if you have anything lingering for me before we wrap.

[01:02:41] AT: I would really like to know what would you say to yourself when you're going to present?

[01:02:46] LP: My gosh! I’ve never been asked this.

[01:02:48] AT: Don’t pass out.

[01:02:49] LP: Yeah, don’t pass out. What I would tell myself is to remember that this is for them and not for me, and that ultimately they want me to succeed, because me succeeding means them learning and growing and transforming. And that's helped me remain in a service mindset. But also not be so terrified that people have rotten tomatoes in their back pocket ready to throw, because they ultimately want you to do well.

[01:03:17] AT: Right. You don't want to sit there and watch someone and have wasted your hour. You're like, “Do well! I want to enjoy myself.”

[01:03:23] LP: Come on! Bring it home.

[01:03:26] AT: Yes, that's great.

[01:03:27] LP: Well, unfortunately, our time has run out but I have a feeling we're going to be making an annual original out of this. So where can my listeners keep up with you?

[01:03:38] AT: My website, alLitorban.com, A-L-L-I T-O-R-B-A-N. And if you have a data vis that you need help on, some infographic, I would love to help you. And also if you are looking to create some sort of cool pattern out of your data that you want everybody to be wearing, email me, because I am very interested in doing more of that. How about you, Lea, where can everyone find out more about you?

[01:04:03] AT: Sure. So my main website is leapica.com. And to get to the podcast specifically, it's leapica.com/podcast. Also the best way to reach out to me is through LinkedIn with a message. Little tip, I love to hear that people come from a podcast appearance or my own. And I absolutely love connecting with people there. And right now the thing I’m most excited about if I can share is I worked all summer building an online assessment that helps data practitioners immediately identify the number one silent killer of their data presentation success. It's based in four specific killers that are most often the habits that we take on and we don't even realize how they might be hindering us. So it's less than 30 seconds. It's completely free and you get a whole personalized report with some strategies for overcoming it. So you can find that at leapica.com/assessment. And what about you? What are you excited about right now?

[01:05:06] AT: I am really excited about tessellating. I’m telling everybody, I’m taking on fewer engagements because I’m just tessellating and chilling. I’ve been creating a lot of patterns and stuff out of data using tessellations, which I’m sure there's a lot of M.C Escher fans out there. I’ve been doing a lot of that. So that kind of feeds into my latest obsession with putting data viz and patterns together.

[01:05:30] LP: Cool. We'll definitely feature some of that on the show notes page as well as all of the links we talked about. So, Alli, I want to thank you so much for coming on my show and simultaneously inviting me on your show.

[01:05:44] AT: Yes. It’s so amazing. Thank you.

[01:05:44] AT: This was incredible. I think the listeners are going to love it. And I can't wait to have you on again.

[01:05:50] AT: Yes. We are definitely going to make a date about it every year.

[01:05:54] LP: Exactly. Thank you.

[OUTRO]

[01:06:04] LP: Wow! That was so eye-opening. And I hope this journey through the viz of 2020 was something that you found as inspiring, illuminating and jaw-dropping as we did. If you loved this episode theme, please show us that love by sharing with others on social media and let us know that you'd love for us to do this again next year, which we probably will anyway, but we'd love to hear about it. And hopefully things and data will be a bit less exciting.

To catch all of the links to see all of the visualizations and the original sources and the tools, please visit the show notes page at leapica.com/063. I would love if you would leave us comments about what you thought about these visualizations and we'd love to hear about the biggest viz for you, most interesting, most terrible, whatever. We'd love to see what viz’s caught your attention this year. And please, if you love this show, if you like what you've heard today, if you're listening in iTunes Podcast right now, hop on over to that button to hit subscribe and please take a second to leave a rating and a review, because ratings and reviews help my podcast get seen by other practitioners like you and they let me know that I am on the right track with the content that you love.

And I’m going to leave you today with the last bit of inspiration this year. Still going a bit bigger than just presentation inspiration, but one day soon hopefully we can switch back. But the theme I want to leave you this year with comes from Helen Keller, and that is, “Character cannot be developed in ease and quiet. Only through experience of trial and suffering can the soul be strengthened, vision-cleared, ambition-inspired and success-achieved.” My take, while it probably feels for many of you, I know for me too, that the muscle holding strong for so long is beginning to weaken. Now is the ultimate time to check in with how we make the most of this extraordinary time.

So when that new year's ball drops, take a moment to reflect and ask yourself, “What's the career in life I want to create for myself? What does that look like and feel like every day? And how can I take a step towards that every single day?” How did the lessons of 2020 help me see that with more clarity?”

All right, my dear listeners, don't forget to take my new assessment and find out what's stopping you from getting the glory and recognition and rewards you deserve from presenting data impactfully. Visit leapica.com/assessment to get your personalized action report today. We at Lea Pica productions are wishing you and your family the most connection, support and health possible for this holiday. That's it for today, and that's it for 2020. See you on the flip side. Namaste.

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