Eva Murray, Technology Evangelist and Tableau Zen Master, is a leader in the data visualization community, running the popular global social data project #MakeoverMonday and the speaker platform ‘The Maple Square’.
Eva is passionate about helping people understand, work with and fall in love with data by giving them a platform for learning about data analysis and visualisation and for connecting with like-minded people.
Eva is an international speaker on the topics of data visualization, data culture and data communities, has published two books (#MakeoverMonday and Empowered by Data) and is a driving force for women’s empowerment in the technology industry.
Outside of the data world, Eva combines hours of indoor cycling with watching interesting series on Netflix, has found a passion for baking sourdough bread, loves to cook and uses running and hiking as a way to explore beautiful places close to home.
Eva and I chat about her book, her work with the Makeover Monday community, and much more!
Makeover Monday | Project | Book
Episode #188: Chantilly Jaggernauth
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Welcome back to the PolicyViz Podcast. I am your host, Jon Schwabish. Now last week’s show, we talked about this idea of how do we collect and manage and think carefully about the data that we are using, in our data visualization projects. On this week’s episode of the show, we are going to talk about how we build a culture of data and data visualization in our organizations. And to help us learn more about this particular aspect of the data ecosystem.
Jon Schwabish: I am excited to have Eva Murray, join me on the show Eva is one of the organizers of the Makeover Monday project, which if you’re listening to this podcast you probably know about, if you don’t know about it, you should definitely check it out. There’ll be a link in the show notes. It’s a project in which contributors create a new visualizations primarily tableau, out of data that are provided. And then the community provides feedback and critique and ways to evolve and grow.
But in Eva’s new book, she talks about building a culture around data and around Data Visualization, based on of course, Makeover Monday, but extending to I think, more importantly, into the organizations and the groups in which we all work. And so it covers things like providing feedback, it covers things like how to build out templates, and how to build out methods and groups and organizations within our current, maybe workforce, or jobs or organizations, I found it to be a really easy read, I found to be a great book, I think something that is becoming more and more important as the value of data visualization has been demonstrated time. And again, people are now starting to look I think a little more carefully at the entire data ecosystem within organizations. So I hope you’ll enjoy this week’s episode of the podcast. And here is my chat with Eva Murray.
Hi, Eva, welcome to the podcast. Great to chat with you. And in a rare occasion for me, good to see you as we’re recording on zoom. So this is more fun than just audio. So Hi.
Eva Murray: Good to see you, Jon. Thanks for having me.
JS: Yeah, this is so much fun. Like I said, I usually do this audio only, but with some technologies. Now we use on my side, this is like, it’s almost like a real conversation of talking to someone I can see your face.
EM: Yes. And I have to admit this zoom fatigue aside, I really enjoy when I get to see people on video, because otherwise you just see the same people all over again, every day, nonstop day.
JS: Every day. It’s the same people and I love my family. But it’s the same people every day.
EM: It is Yeah.
JS: Well, thanks for coming on the show, you have this great new book empowered by Data. And I want to get into that and talk about how people and their organizations, their groups can build better Data Ecosystem. So maybe we can start by maybe having you talk a little bit about yourself and your background. And then we can just dive right into the book.
EM: Sure. Happy to do that. Where do you want me to start? How far back do we go?
JS: That’s a good question. We don’t need to go all the way back. Maybe we should go back to university. So because I find on this show, having interviewed a lot of people that no one comes to Data Visualization from the same background, everybody just sort of gravitates to, it’s for everything. So what was your background? And your, like core interests in university?
EM: Yeah. So at university, I did a double degree in the Bachelor of Science in Psychology, and Bachelor of Commerce and Commercial Law, accounting and HR. And while I was doing Psychology, funnily enough, we did learn about Visual Perception about Gestalt principles, and those kind of things. And back then, I didn’t connect it to Data at all, like, I just —
EM: There was no Data Visualization on my radar. But going then into Database a few years later, I’m like, Oh, yeah. I learned this stuff. And I always thought it was really interesting. So yeah, so that was my university background. And I from there, went into consulting, I worked at Deloitte in New Zealand for a couple of years. And that’s really where I started heading to work with Data. Because you know, you need to analyze Data, and if you want to figure out what’s maybe going on an organization that you’re providing advice to, yeah, that’s where it kind of started, I went to a training course, for QlikView at the time. And that’s like, Oh, this is really, really cool. And shortly after, actually, I left the line to move to Australia, and joined a large Australian bank. And there I was exposed to Tableau for the first time and things really kind of fell into place. And I really enjoyed using the tool and that’s where I met the community and it all kind of started from there. So finding people who like oh, yeah, we enjoy doing this stuff so much. We actually meet up after work over BN pizza and talk about Data, I am like, what the hell. But I was like, this is for me sign me up. And that’s where I realized that actually what I really enjoy is working with Data.
JS: Yeah, yeah, it’s the combination of like a job and a hobby simultaneously that gets people really going.
JS: So let’s talk about Makeover Monday just briefly, because I want to, maybe you can talk about the project itself, and how you got involved in it. But then also, let’s talk about how that informed the especially the beginning part of the book, because the beginning part of the book really focuses on Makeover Monday before it sort of branches out a little bit?
EM: Yeah, so I got involved to Makeover Monday, exactly Four years ago, yeah, this is my fifth year, I’m still Co-hosting it. And he asked me to join him as a Co-host. And we’ve been running it together. And then he took a bit of a break last year, and now he’s back on board. And it’s the Global Social Data Projects, where every week we share a Data Visualization and Data Set, for people to then create a better Visualization of the same Data, with the idea being, hey, let’s look at something that already exists and see what we can improve. What are some things we think are great, what are some things that, you know, could be changed. And how can we tell a better story list the same Data, using whatever tool people want. And it’s been a real, real fun project to be involved in and to run and to get new people involved in the community has grown immensely over the years. And along the way, there have been, you know, a few cool events, and one of them was at Tableau conference 2018, we had Adam Grant, as a as a keynote speaker. And he spoke about givers and takers in organizations and in life. And we were actually nominated as the most giving people in the community, which is not the point I’m trying to make here. But what’s really nice, I did finish to speak to him afterwards and connected with Adam. And he invited me to speak about this community idea at the people analytics conference at Wharton Business School in 2019.
So I went to Philadelphia and I spoke, and while I was on the stage, I am like, I should write a book about this community. Because I’ll Makeover Monday book was very much about Database best practices. But I felt that there are so many things I’ve learned through running Makeover Monday, it could really work as a book. So that’s where the idea started. And then I needed a few months to think on it. And then, you know, put together a proposal, put it forward, it was accepted and wrote the book, which then was published in November, just last year.
JS: Yeah. Yeah, that’s great. I mean, I think that’s the perfect sort of inspiration for this book. Because I think the community while it’s disperse all across the world, and I would guess that it’s mostly individuals doing it’s not necessarily organizations or groups doing it.
JS: But it does speak to. How does an organization be more productive and more responsible, I think at the end with their Data. So, maybe you can walk folks through the book, in case they haven’t seen it, I found it to be a really easy read. So for those of you who haven’t seen it, like, it’s one of those books, you can literally sit down with and read kind of straight through with lots of flags that I haven’t noticed. But then you can just walk us through it, and and then I have a couple of specific things I want to talk about that have been challenges I have seen in places I have worked in, also in places I’ve worked, you know, worked with?
EM: Yeah, um, thank you, it’s great to hear that it’s an easy read. It was a fun writing exercise. And I guess one thing I always underestimate when it comes to writing books is just how much reading you have to do, because you have to proofread so many times, basically. So the book the way I’ve structured it is, first, let’s, you know, we’re talking about why would you want to build a community? Why do you want to become data driven? What’s in it for the organization? And what could it look like? And then I share a little bit about Makeover Monday, because it’s such a great example, I think of how it can look. And it’s also something I can talk about so easily because we’re not a business, we don’t charge everyone is voluntarily participating. So there is nothing to hide, really. And you know, it’s all out in the open. So I share a bit of detail around that and, and then it’s about Okay, let’s get down to business. What do you get out of building this community and looking at the individual, the organization, but also our industry and our analytics industry. Because I think analytics industry benefits as well from people being more skilled and more connected.
And then I used a lot of examples from individuals but also community so individuals that were part of communities but also who were leading communities and organizations to address things like okay, we’ve got this idea of, yes, we want to do this, but also what are some potential risks or challenges because I want everyone t to be very realistic going into this. And community is all about people, you’re going to deal with people and personalities. And that’s going to come with challenges. So let’s address them upfront. We’re all aware, and then we can go from there.
EM: And then a bit of a process for how can you think about and plan this community. How can you come up with a plan of what it could look like, and I share a lot of templates along the way, so that people can say, Oh, this would be an example for a community meet up, or maybe a half day internal conference we can run and what do you need for it. And, you know, how could you structure the day, like, example agenda’s. Because I want to make this as practical as possible for people, I want them to pick up the book and say, Oh, I could start some of this stuff literally tomorrow. And then just some tips for Okay, how could you actually get started. My advice for the steps you can take to make sure that you get some quick results, but also the longer term success. And I’ve also shared a quite honest lessons learned, from my own perspective, and from some other people who was like, oh, that didn’t quite work. So don’t do it that way.
EM: Because, you know, I want to try and save people some pain, but also make it very obvious what I learned from that, because people have to make their own mistakes, but hopefully, they will make fewer or, you know, more informed mistakes there. And then I give them a bit of a roadmap for the future, you know, what should. Where could they aim to, to go from there?
JS: Right. So, because in an organization is just inherently different than Makeover Monday, which is just everybody working on their own and having a dialogue, but it’s certainly different when you’re in an organization. So you had mentioned, it’s about people, and it’s about personalities? So how do you think about that aspect within an organization, and you spend some time in the book talking about the hierarchy and the culture of a hierarchy within an organization? So when it comes to the Data Culture, you know, what do you think? Or what are your recommendations for people in groups to sort of try to break that hierarchy down and address those, maybe those personality conflicts?
EM: Yeah, one thought that comes to mind here is data as data. And I know that everyone always thinks, and this is not a criticism, but everyone always thinks they’re so unique, their situation is so unique in the organization. But many, many organizations have the same challenges. And many people in those organizations have the same challenges. And I think data can be a really good level playing field. Because if we’re all using it, you know, we all have to ask ourselves certain questions and come with certain skills to use the data. And I’d say, I mean, flattening those hierarchies, it requires, I would say, beyond, you know, the data side requires communication and transparency.
EM: And so much comes down to communication. And a good way to get some skeptics on board would probably be, hey, here’s some examples of what’s worked in our industry, or in other organizations that are similar to us, but also maybe internally already, for some individuals. And I would hope that leadership has the, you know, the vision to see, okay, we can apply this to our situation, but coming up with some examples, and that could be tested in, you know, small pilot groups, maybe internally. Because I’m sure people will find a few people willing to invest a bit of time to say, hey, could we test this out? And could we come up with an example of, hey, this is what we’ve solved internally, for example, we have this big dashboard that we’re all using in this department, and we just wanted to run faster, or to look a bit different, hey, let’s sit down, let’s work it out. Let’s just mock something up and present that and show them hey, this is what we can do, if you give us an hour each week to just put our heads together. And I think those examples can be really powerful. But also not shying away from actually just reaching out to other people in the industry, because I’ve found that the data industry is very giving one people are quite happy to share some examples and some tips and their own lessons learned. But also to maybe just pick up the phone and talk to someone say, yep, this is what we’re doing. And this is why it works for us.
EM: Reaching out and, and social media makes it so much easier. Because you could just send a direct message to many, many people that you know, wouldn’t ever pick up the phone to because you don’t have the number but they’re there.
JS: Right, yeah. So when you think about within organizations is a better model to go top down or bottom up?
EM: I’d probably start bottom up with just a little bit of prep work and then go back to the top and get the buy and to continue working from the bottom up. So and I guess the public facing communities, those on social media, they’re a good example for that where you get a few people, and then others follow. And they’re like, oh, yeah, this is really cool. And they’re establishing something, they’re building content, or they’re building solutions. And you just need a few of those solutions to then present to senior leadership and say, Hey, we want to do something like this. And this is what we need to realize that.
JS: Yeah, that’s a really interesting point. So when you think about this bottom up approach, which I have found to be mostly, most often the case is you get a few people who are really interested in, we want to learn tableau, or we just want to, you know, do whatever. Do you find that it’s not so much about building the biggest bests, you know, new website, huge infrastructure, but it’s about, you know, I don’t want to simplify too much, but like making a better bar chart, or, you know, making a better dashboard? Like, is it the small wins that can build up? Is that Is that how you sort of see this process really enveloping the whole organization to become, you know, become better with their data?
EM: I would say so, yes. Because I managed to do that, when I was at the bank, I wanted to make the case for, hey, let’s use Tableau more extensively, rather than copy and paste Excel to PowerPoint. And I built two different dashboards. One was a classical P&l, and the other one was very visual. And I presented both to the CFO of the bank, which you know, was a big deal at the time. And the idea was, hey, yes, this is how you always get it.
EM: But he was also an alternative. And I think if you can then to also show, we sat down together, we hashed this out, there were people from different departments like showing that this has momentum, and that people are really willing to do something to drive change, rather than being forced. And I think also, leaders often or managers, there’s often this saying, you know, don’t come to me with problems come to me with solutions. So I think if your first step is, Hey, can we have budget to build this community, that’s kind of coming was the problem. But if you can say, Hey, we got 10 people together last week, and we all discussed how we could improve, you know, these three charts or something and this is what came out of it. And we have this idea. And these are the people, and these are the tools we would use. And this is the requirement we have, which is two hours a week or something like that, then that could be a good way to come up with a solution, as you know, so to speak. And then kind of you go back and forth, you know, you interface from the top to the bottom to back to the top.
JS: I mean, you’ve made a great point. And I would guess that there are people who are listening to this saying, Well, I’m not as brave as, as Eva, I can’t go to my manager and say, you know, here are these two different options. Because my manager is, you know, he is a big jerk, and won’t listen to me. But I think what you’ve hit upon is you don’t necessarily need to be a super brave person, you need to have an interest in improvement and finding like people in your organization, who also want to do that and come together as sort of a crucial group within the organization?
EM: Yes, absolutely. And given that most listeners here would be somewhere along the continuum in the Data Visualization journey, I think, always bring a picture of some sort. So my strategy has always been, and it helps me to be brave, I will come with a very polished PowerPoint. Because if you can make it look good, even if you don’t have all the arguments yet, people see that you’ve thought about it, you’ve made an effort, and you not only have made an effort to make it look good, but to help them understand your point.
EM: And people really appreciate it, when it’s not an ugly Excel spreadsheet, or a really kind of black and white Word document. But maybe just two slides that are so really nicely presented. I think that can make a big impression. And we should use our Data Visualization, skills to think about. How could we make this case and like you say, it’s not so much about being brave, it’s saying, hey, we’ve noticed, these are the challenges, we want to improve them. And we have an idea, and we just want to test it out.
EM: But we need a bit of approval from the top. And you’d be surprised what you get when you actually ask for it because most people never asked for it.
JS: Yeah, you know, it’s, it’s interesting, because when I talk to folks, who are in universities and or academics, and I talk about, you know, why don’t you try blogging or you know, talking to podcast or that, you know or, you know, do more on social media, their response is often Well, that doesn’t really get me anywhere in my department, right doesn’t help me get publications, it doesn’t help me get tenure. It, you know, doesn’t help with any of that. And I’m sure that there are places like that out in different sectors where it’s the same sort of attitude that, oh, you spent all this time making this PowerPoint look good. But is that really the best use of our time, but the way you have couched is to say, is to really demonstrate kind of the before and the after, which is essentially what Makeover Monday is?
EM: Yeah. And also what we need to appreciate his other people’s time.
EM: Because that’s what you know, we all have a limited amount of time. If I can use my Visualization skills and say, I’m going to condense all of this information, from my proposal into some very clear bullet points, maybe a chart that shows Hey, this is how much time we’re going to save. If we improve XYZ processes, it’s going to be so much more impactful than asking the manager, who we want approval from, to read something for half an hour that we wrote out in Word, as you know, as a text, and there will be people that are hard to convince, but —
EM: I still think it’s a good use of my time to make an effort. And I’ve had my managers all appreciate it in the last 10 years of my working life. And it also shows that I think it does show that you appreciate someone else’s time and the value of their time. Because it makes it easier for them to make a decision if you present something and all they have to do is say yes or no. Because you have thought of everything they might ask you, or they might need to know, that’s so helpful for them, because they need to make so many decisions every day, that every decision that’s easy to make is going to be a bonus, you know, and not just you get away or come away with, hey, I’ve got the result I wanted. But also you probably have a few brownie points for the future.
JS: Right. Another big topic that comes out in the book, and is also in parent to Makeover Monday is establishing a culture of feedback. And I wonder if you could talk more about how to establish that culture? How to establish you know, respectful way of a useful way of providing feedback and providing critique? Because, you know, not everything is great, you know, some things can be improved. So, so let’s just talk about feedback and critique in general, and how people or organizations can build that culture into this sort of overarching theme that you’ve talked about with Data and Data Visualization?
EM: Yeah, I think feedback is really, really critical for people to improve, the only way we can get better is if someone tells us honestly, quite so good. And I think we’re always afraid of feedback. And I’ll be the first to admit that I find it hard when I get negative feedback. So I always try to avoid it by putting all this extra effort in. So I’m like, I need to do this really well, because then no one can critique it. So I guess that’s how I operate. So Makeover Monday is a really good example there. You know, when I came on board in 2017, and we build out this project, we realize we have so many people now. And the interactions on Twitter are just so limiting. Back then it was, I don’t know, 180 characters. And —
EM: And it was just really hard to give people a response. And it was really time consuming, because you write tweet, after tweet, after tweet. And that just doesn’t end. So much gets lost in these short social media snippets, so many nuances. So what we decided was, hey, what if we spend an hour a week doing a live webinar, and we could give people feedback, literally live with, you know, showing them on the screen, what we’re referring to, and they could just dive into it and take the feedback on board. And we started that. And it’s probably my favorite aspect of Makeover Monday, because I feel it creates the most value for people. We had, we did this for a number of years on BrightTalk, we’ve now moved to YouTube live because it’s more open, no one needs to register, they can chat on the live chat with each other, and we can show our faces. So we continue to do that. And what we learned is, it’s still really hard to give constructive feedback in a way that is clear, concise, doesn’t offend.
We’re trying to give as many people feedback as possible, which means for every visit that we look at, we have to keep it short, which means being very blunt. And I always try and make the point that it’s about the visualization. It’s not a personal attack in any way. And to you know, we always point out the things that we like about this, because much like the experience I currently have was training a puppy, you want to reward the good thing, so people do more of that. But we also want to point out the things that could be improved and why. And I think the Why is so important. Because if I just tell someone to change that it’s not going to teach them anything.
EM: If I can tell them, hey, you truncated the access here on this bad shot. And that’s misleading, because suddenly, the proportions, you know, don’t compute in our brain. They’re like, oh, yeah, I see that. And then they can, you know, they can remember that. And I do find myself giving very similar feedback week after week, because we have new people coming in. And, you know, sometimes people might just forget. But what I have noticed over the years of doing this feedback process is people who come week after week, they participate. They watch our feedback, even if we don’t manage to get to their Visualization. You see their progress, and this is satisfying for me as the feedback giver to see the progress.
And I guess if I had to sum it up, I would say There’s a huge responsibility on the people who give feedback to be constructive to focus on the task at hand, you know, no personal text, just okay, what needs to be changed and why, but also what’s good to always let’s include some positives. And then for the feedback receiver to, on the one hand, acknowledge the feedback that they’ve actually taken it in, especially now that we’re not in person but also then to do something with it. And I say to people, at the very least, you’re welcome to disagree. You don’t have to change your Visualization. But please let us know that, that you’ve got something out of it. And then what we do expect from people on the project is, they change their Visualization based on whatever they agree with and what they want to do with it, and send a new tweet with a new picture. So we see the change. And sometimes it’s like, oh, my God, they made it so much better than I could even imagine in my head.
EM: And you just see that growth that people are like, oh, and it clicks, and people developed a style of Oh, they’re getting better than developing a unique visual style. And they’ve remember things and it just looks more polished, because they kind of tick all the boxes on the checklist.
EM: You’ve just listed out a bunch of different aspects to feedback and critique on both sides. But it sounds like one of the big aspects to this is the receiver of the critique or the feedback. It’s in common upon them to come back with the next version. And whether that version, may or may not take all your recommendations, which is totally fine. But there is a next version where they have to, or they should or they, it’s advice trying to come up with the right adjective, they should try their hand at incorporating that feedback.
EM: That’s what I would suggest. And I do sometimes see people saying, oh, I’ll remember that for next week. But the next week’s data might be so different that it doesn’t apply.
EM: So I prefer seeing the new verse. And I think in the organizational context, in terms of giving feedback, I mean, you probably don’t get feedback every week, you might. But it’s also, again, important, you know, if your manager, for example, gives you feedback, just do something with it, something that’s visible, and that is also kind of timely, so that, you know if they say, well, actually, you know, make sure to speak up more in meetings, as an example. Try in the next meeting to speak up at least once so that they see oh, yeah, she’s trying he’s trying. It is so satisfying for someone who is giving advice or is coaching people to see them make the effort. Because when I give advice or when I mentor people, the things I say I have a reason for and I do trust that they help people. And they can only experience that feeling of oh, yeah, it’s getting better. If they take it on board and test it at least once or twice.
JS: Yeah. That’s great well on that positive note, and using feedback and growing and evolving, I think that’s great. You have a few months before, I’m sure your publishers are going to come back and ask you for the next book. So I won’t do that now. So I’ll just say congrats on this one. It’s, it’s great, I think gonna be very important for all organizations to have this because it should be noticed not just about the Data Visualization side, like that’s the beginning of it. That’s inspiration, but it really covers the entire data processing system. So Eva, thanks so much for coming on the show. It’s been great, chatting and seeing you which is always a joy.
EM: Thank you absolutely for having me. I’m delighted to be part of the show.
JS: Thanks, everyone, for tuning into this week’s episode of the show. I hope you learned a lot about building a Data Structure within your organization. If you’d like to learn more, I really do recommend checking out Eva’s new book empowered by Data and to look at her website in MakeOver Monday to learn more. So until next time, this has been the PolicyViz Podcast. Thanks so much for listening. A number of people help bring you the PolicyViz Podcast, music is provided by the NRI’s audio editing is provided by Ken Skaggs and each episode is transcribed by Jenni transcription services. If you’d like to help support the podcast, please share it and review it on iTunes, Stitcher, Spotify or wherever you get your podcasts and Policyviz Podcast is ad free and supported by listeners. If you’d like to help support the show financially, please visit our Patreon page at patreon.com/policyviz.