In this episode Josh discusses data visualization with Stephanie Evergreen.

Dr. Stephanie Evergreen is best known for bringing a research-based approach to helping researchers better communicate their work through more effective graphs, slides, and reports.
Dr. Evergreen has trained data nerds worldwide through keynote presentations and workshops, for clients including Verizon, Daimler/Mercedes Benz, American Institutes for Research, Rockefeller Foundation, Brookings Institute, and the United Nations.
Both of her books, Effective Data Visualization and Presenting Data Effectively, hit #1 on Amazon bestseller lists.

In today’s episode you will learn:

  • How to cut through all the noise to communicate business insights
  • How to use data to be better at business
  • How to present data to make clearer and more streamlined decisions
  • What is the ROI on good data presentations
  • How easy it is to make high-impact data visualizations

Transcript

Narrator:         Welcome to The Sustainable Business Radio Show podcast where you’ll learn not only how to create a sustainable business but you’ll also learn the secrets of creating extraordinary value within your business and your life. In The Sustainable Business, we focus on what it’s going to take for you to take your successful business and make it economically and personally successful. Your host, Josh Patrick, is going to help us through finding great thought leaders as well as providing insights he’s learned through his 40 years of owning, running, planning and thinking about what it takes to make a successful business sustainable.

Josh:                 Hey, this is Josh Patrick. You’re at The Sustainable Business. Today, my guest is Stephanie Evergreen. Stephanie refers herself as a data visualization geek. She has written like a zillion books on data visualization. The reason I’m asking your on today is one of the big challenges I see with private business owners is that they almost never get their data right. I think it’s because they keep looking at numbers and not have pictures. That’s just my thought. Let’s bring Stephanie out and will start the conversation.

Hey, Stephanie, how are you today?

Stephanie:       Hey, Josh. Thanks for having me. It’s so good to be here.

Josh:                 It’s my pleasure. Let’s start with data visualization. First of all, why don’t we start with the definition of what data visualization actually is?

Stephanie:       Yeah, you kind of actually already defined it for us because you were right in your little intro there. It’s about putting data into pictures. Typically graphs and charts so that people can actually make better sense of it versus say, looking at a spreadsheet of numbers.

Josh:                 What is the science behind visualization versus looking at numbers that makes visualization better?

Stephanie:       Yeah, I think a lot of different visualization folks might say different kinds of research. But I always go back to with the research that we have around how our brains operate. My background is in education. I always learned back when I was becoming a teacher how we teach people and we know from all the research there that people primarily consume information through their vision.

Through their eyes we are built to look at pictures and we have five senses. We have five ways that information technically can get to our heads, but primarily its vision. You’ve probably heard that anecdotally about how much of our brain processing is dedicated to what our eyes see. We need to have pictures because that’s what people primarily consume.

Josh:                 Okay, so how do you know what data you should make into a picture?

Stephanie:       Yeah, that’s a good question. I think it’s a common question people have because everybody’s trying to be so data driven now that we have so much data people don’t know what to actually work with. So I encourage people to focus on the data that’s going to speak to your business objectives. You should stay focused on your primary strategies, your primary objectives, and collect the data that’s going to directly tell you how you’re doing on those.

Josh:                 Do you want data that’s historic or data that’s predictive?

Stephanie:      Ooh, both. You kind of need the historic in order to be predictive. What I typically see people do is neither of those things. They’ll just show a number with zero context and you’re like, “Well, are we up? Are we down? Are we on track?” People will automatically have those historical and those predictive questions so we need to see that full picture that the big context.

Josh:                 So when you are working with a business and you’re designing a visual data program, I assume that’s something that you guys do.

Stephanie:       Well, we help people figure out how to visualize their data. Yes.

Josh:                 Okay. Where do you start and how do you go about doing this?

Stephanie:       Well, we typically ask them to show us what it is they’re currently struggling with. What are their biggest problems because I feel like folks are smart and they’ve already got one things figured out so they bring us in to help make tweaks.

The tweaks are simple that end up having really big impacts because we got ourselves focused on answering those key business objective questions. So whatever metrics folks are using to monitor their performance and to see if they’re making progress and having success that’s where we begin. We typically start by asking them to tell us, what is the point of the graph that you are struggling with here? What is it that you’re really trying to say?

Once we know what people’s insights are about that data then we can figure out exactly how to make it look? I think people don’t start by framing what we’re looking at here with their insight. It’ll just be some kind of generic framing like revenue. We need more help than that. We need to see a title of something clear like revenue has gone down, revenue has gone down significantly. Those kinds of free things will help us make the right business decisions and also tell us how the [inaudible 00:04:59].

Josh:                 You just gave an example of the historic number. Frankly, historic number is never going to tell us what we should do tomorrow. It just tells us what happened yesterday. It tells us whether it’s a good or a bad thing.

Stephanie:       Sure.

Josh:                 So how do I take my data and visualize it so it helps me become a predictive item for my business?

Stephanie:       Sure. There’s probably going to have to be some work on the back end with the data science team who’s going to use the historical data that we’ve had and build some data models that will help us predict where this thing is heading. That’s a very tricky business. That’s why those people get paid a lot of money because a lot of factors go into what performance could look like in the future, not just our own personal business history.

Josh:                 Now we’re looking at again a model of what it could be. I’m more concerned. I want people listening to this podcast, to be more concerned about what is going to happen when I say predictive. I don’t mean it might happen. I mean this is what what’s going to happen over the next 90 days.

Stephanie:       Yeah.

Josh:                 So how do I set up a dashboard with data visualization that’s going to help me with that?

Stephanie:       Well, typically, what we would see in a dashboard that’s showing future stuff would be some history. Here’s where it’s been and then range of possibility for what’s going to happen in the future. It might look like a solid line for where we’ve been and then dashed lines that show the future possibilities or maybe just like some people call it the cone of uncertainty sort of like how you would see in a hurricane map. There’s a shaded region that shows where it could end up anywhere in this range. That’s what we would typically see.

Josh:                 How does that help make it easier for somebody to run their business?

Stephanie:       Well, it’ll at least let you know what you’re on track to be between and that will help you decide, “Okay, do we need to make some major interventions right now because this is only wanted to be?” I would also expect I mean I would hope that graph that shows with the future would also include your targets, your goals, your aims. So that you can make determinations like, “Okay, well, the target is not even in the predicted range of uncertainty so we’re going to have to make some movements, or it is and we’re going to be fine so just maintain the status quo.”

Josh:                 Let me give you some predictive things that we always ask our customers or clients to monitor because it always shows what’s going to happen in the future. One of those is face to face sales calls by their sales team.

Stephanie:       Okay.

Josh:                 So how would you visualize that and have that be meaningful to a business owner?

Stephanie:       Well, tell me a little bit more about what that data looks like. What kind of numbers are we talking about?

Josh:                 This between zero and how many calls they can make in a week?

Stephanie:       Gotcha. I would hope to show something like the average number of calls looks like the highest return on investment means we’re going to end up at this number of calls. You’re actually at this number of calls. I would want to see three pieces of data on there.

Now, whether you show those things historically, or whether you show them just this past week, or we were this last month is up to the business decision that you would be making about what comparisons are going to be most meaningful for you, but that’s what I think is going to be most helpful for folks. What the average person is doing, what the most ideal person is doing and what you’re doing.

Josh:                 Okay, I guess I’m trying a little blank here. If I know I need to have my sales people making one call per day on the customer and that’s going to make my business healthy if they call you on the right customer because they could be calling one person per day, but not somebody we need to do business.

Stephanie:       Not the right person, yeah.

Josh:                 Not the right person. I’m not sure why I need to visualize that data because it’s in my head.

Stephanie:       Well, if it’s just one salesperson on your team and they have to make one phone call a day. It’s going to be a pretty simple like they did or they didn’t.

Josh:                 Not one phone call, one face to face meeting—

Stephanie:       Sure.

Josh:                 You have to make more than one phone call, obviously to get one face to face meeting.

Stephanie:       Certainly, so yeah. I think it’s much harder to keep track of all that stuff in your head when your data set gets bigger. So if you’ve now got a team of 50 sales people, you’re not going to be able to keep 50 metrics in your head and know where every single person is at in terms of that face to face meeting.

That’s where it brings together the bigger picture into a visual. We’ll take all that weight out of your head and put it on your screen so that your head doesn’t have to keep all the information and your head is freed up to do more important things.

Josh: It sounds to me like data visualization might be something that is really more of a larger company activity than a company with, say, 10 employees.

Stephanie:       I don’t think so because I do believe I mean I have a one person business here and I have all kinds of data coming and going—the expenses every month, my revenue every month. Anytime you’re trying to sell your work or partner with another company, they’re going to be asking for evidence that you are a good company to work with.

It’s usually going to be data. We’re going to have to sell ourselves in a way that makes us look good so that data needs to also look good because people judge the way that they judge our own integrity. They judge our professional— whether we would be good partners with them based off of how that stuff looks especially because we’re primarily drawn to look at pictures.

If we’re just using some default tables which they’re not going to be able to even get through or some default pie charts from Excel it’s going to reflect poorly on us. I think every business who’s got any kind of numbers whenever we need to be communicating that with others or even using it for own internal decision making it should be graphed.

Josh:                 When I think about data visualization, I would think about an Excel graph. How do you recommend people set up their data so can be visualized?

Stephanie:       You know, I do work primarily in Excel to do my data visualization because I think we should use the tools that we already have and just be the masters of them. It’s really just about knowing how to tweak with default stuff Microsoft gives you so that the ultimate visualization you produce is awesome and high impact.

That isn’t always easy inside Excel because it doesn’t have incredibly user friendly language on stuff so you don’t really know what the buttons are going to do or what these menu options mean. That’s what we’ve been building in Evergreen data is the interpretation of how to use Excel to make awesome charts.

Josh:                 So I’m running a business. I’m a construction company, for example. My skill is banging nails. It’s not working with a computer. The last thing in the world I want to do is actually spend a lot of time learning how to make Excel work properly.

Stephanie:       Yeah.

Josh:                 What to somebody like that do?

Stephanie:       Well, you probably would buy my book because the book tells you exactly what buttons you have to push. Every one of the graphs that’s in there has a little rating next to it that tells you how hard it’s going to be to make this graph. If you’re like, I do not have a lot of time, I don’t want to have to put a lot of time into this.

This chart needs to be done for my vendor tomorrow then you can pick one that is going to be like a level one or level two something super easy. Maybe a graph that’s already kind of there in Excel [inaudible 00:12:15] small tweaks to clean it up so the point is really sharp. It can be as simple as that. Going back to something that we mentioned earlier, the very easiest thing to do is just to put your insights in the title even if you kept the default graph from Excel because you don’t have time or you don’t want to mess with it. All you did was use the chart title space to tell people your insight. It’ll take you so far.

Josh:                 For somebody to put together graphs that are meaningful in their business, how long is it going to take for them to do that?

Stephanie:       It depends on the complexity for sure. In the book, we’ve got a range from one to 10. One is like you’re going to be there less than five minutes. A 10 is like the first time you do this it might take you a half an hour, but the more that you do it the faster you are. There are all kinds of efficiency checks that we can build in.

Like anything, there’s going to be a learning curve the first time that you do it and then you get faster and faster. Josh: Now, we just moved over to QuickBooks Online which seems to have like a ton of graphs in it, graphical ways of looking at things. Can I just use that or do I have to move that in Excel and then build other visualizations off that to be useful?

Stephanie:       Well, I haven’t seen QuickBooks personally, but I do know that– data visualization is becoming so popular. A lot of companies have been trying to build it into their programs like Survey Monkey will automatically generate you graphs. I think Salesforce is recent acquisition of Tableau which is a data visualization company means that we’re going to start seeing more data visualization built into the back end of Salesforce as well.

What I have seen with all of those is that it’s a little bit of a slippery slope because it’s going to be very easy to think, “Oh, I got a graph that just right out here. I should use this.” But the software will never be able to do that the thinking for us. The software, well maybe one day with AI, but the software is not going to know our context, our audience, the insights that we see when we look at this data. So inherently, we’ll never be able to visualize it in the best way straight out of the gate. We’re always going to have to do some tweaking to it.

Josh:                 The thought just occurred to me is that I tend to like was called Agile Technologies a lot. An Agile Technologies brings in a whole bunch of tools where you’re actually doing the planning for your day to day work using visualization tools such as combine boards. A combine board, by the way, for those who are listening, says what do you need to do? What are you working on now and what’s done? Then you do a retrospective where you go back and look at what you’ve done over the last period of time and see if you can do it correctly. Will a combine board be a form of data visualization?

Stephanie:       I think so if you know what your description of it. There’s a whole realm of visualization that’s more qualitative nature where we’re talking about things like diagrams. Diagrams are such a huge umbrella I think it would include that. It would include with mind maps. It would include org charts. There are so many different kinds of diagrams out there. I think it all applies and many of the same visualization strategies you would use in quantitative graphing, we would want to use in qualitative graphing as well like the principle of cleaning up the clutter so that the data you’re trying to show are really clear.

Josh:                 We communicate with our clients in mind maps.

Stephanie:       Sure.

Josh:                 The reason I use Mind Maps is that if I send you a 20 page report, you’re not going to read it. If I send you a one page Mind Map, you’re likely to put that on your desk to look at it 1000 times a day.

Stephanie:       Exactly. I think there’s something really handy about a one pager in general especially a one pager that has a visual on it. It’s got [inaudible 00:15:54]. It’s got reach. I encourage people to start thinking about the one pager and how we can put our data in a way that will just be better seen— the one pagers that I have people put up on their office wall or they stick on the desk and refer to 100 times. That’s what we want people to do.

Josh:                 Right? And the whole purpose here I think this is a really important thing. It has to be my first mentor had this great term. He called it Operationally Doable.

Stephanie:       I like it.

Josh:                 And when Operationally Doable means that if you can’t do it easily, it’s not going to be done. If you do it in a complicated manner, it’s not going to be used. I go back to this example a lot is that first time I wrote a business plan it was 1978, probably. I used a program that created a 90 page business plan. I will tell you that nobody read it.     

Stephanie:       Yeah.

Josh:                 Including me after I done I put it up on the shelf and I left it there. When we finally got it down to four pages people would sometimes read it. Then when we started mind mapping and especially computer my mapping program came out because my handwriting is illegible and always has been. It actually started getting used.

Stephanie:       Yeah.

Josh:                 The thing here is that if it’s not going to be used, it doesn’t become a tool for us. It’s a waste of time.

Stephanie:       Yes. I think the more complex we make it like you were saying, the harder it will be for people to dig in and engage with it. So even that one pager I mean I’ve seen people who are like, “You’re right, Stephanie, we should put this into a one pager” and then the one pager they give me it’ll be a paragraph where the line lighting is so squished, you would never want to read it. There are zero margins. People can still take something as lovely as a one pager and make it incredibly complex and difficult to get through.

Josh:                 I’ve seen that happen more than once in my life.

Stephanie:       Yeah.

Josh:                 Absolutely, for sure.

Stephanie:       Yes, always. We’re using the same principles here of white space and reducing unnecessary lines. Little things like that that will apply regardless of the visualization we’re working in quantity or quality or even just a page of paper.

Josh:                 Yeah. What I’m hearing here is that in this is my own personal experience with working with visualization is I think visualization is a more effective tool for predictive stuff than for historic.

Stephanie:       Well, maybe so I’ve seen it used in so many different industries and in so many different contexts. I think the work we do maybe focuses on helping people report out their data versus there’s a whole another realm of data visualization which is exploratory where you’re looking through your data to just see what it looks like.

That’s sort of a different ballpark than the folks I work with who are looking to get data out there so that it will be used. We have so many examples of where this could have been done better, and it would have saved lives and it wasn’t. So whether it’s future, or whether it’s historical, I think we’re looking at using the same kind of techniques and tricks. We’re focused on the same goal which is actually getting the data in front of people so that we can use it.

Josh:                 Give me a couple of examples of where data visualization could have made understanding so much better.

Stephanie:       Sure. Probably the most famous example was from Edward Tufte’s book. He’s one of the godfathers of data visualization. He told the story about the challenger shadow explosion and how it occurred because there was an issue with [inaudible 00:19:25] rings and the scientist they knew about this. They had tried to make this evidence clear to the decision makers that they were not heard and a lot of it had to do with the bad sides and the weak explanation and use of the data the way that it was visualized.

[inaudible 00:19:44] contemporary example with this when it came to the [inaudible 00:19:47] failure where I don’t think if you remember this. It is a couple years ago now but there was an issue where if the keys jingle a certain way the ignition will just shut off even if the car was driving at the highway at 70 miles an hour. This jingle could happen if you just have a lot of weight on your key ring like other keys in a key ring. It causes this.

[inaudible 00:20:07] keep saying, “Oh, this isn’t an issue.” It come a really long time to come figure this out, but in the investigation that occurred afterwards it turns out [inaudible 00:20:17] a long time ago and the slides where the data were presented were this horrible 3D bar charts about kind of different patterns in it and it was like no wonder people just turned away when they saw that because it was so complex [inaudible 00:20:34] even if the data theoretically was simple. So much it has to do with how it was presented.

Josh:                 What you’re talking about here is something new and dear to my heart. We’ll going to have to leave it here and see if I’m correct with this which is simplification.

Stephanie:       Exactly.

Josh:                 We as [inaudible 00:20:53] tend to make simple things really complicated by putting too much information and when you’re going to visualize just by the nature of visualization process you have to simplify what you’re presenting if you’re going to do it right.

Stephanie:       Yeah, it’s hard when you’re smart.

Josh:                 Yeah.

Stephanie:      Because the more you know about the topic, the harder it is to talk about it in a way that your CEO could understand versus your other technical experts.

Josh:                 I advise always this to somebody whether you’re writing or you’re presenting or you’re doing anything for anybody else, if you make it above 5th grade level it’s not going to be understood.

Stephanie:       That’s good advice.

Josh:                 That’s my advice. We’re going to have to leave it here, Stephanie. I happen to look at Amazon before we did this and you’ve got like a zillion books over the Amazon on how do data visualization right. Is that where you want people to go or how do they find you?

Stephanie:      Just the best place to buy a book certainly. My website https://stephanieevergreen.com/ has a blog where a bunch of my ideas are already posted there and that’s free. That’s also a good place to start.

Josh:                 Okay, if somebody wants to work with you personally do they just go to your website?

Stephanie:       Yup, contact info is on there.

Josh:                 Okay and that’s https://stephanieevergreen.com.

Stephanie:       That’s right.

Josh:                 Cool, I have an offer for you also. I have this obsession around Cash flow for private business owners because there have been plenty of times I didn’t have it– I know [inaudible 00:22:15]. You didn’t have it. I actually developed a scenario called success path from having no cash and having excess cash in your business. I made a kind of cool infographic about it. You get it free. It’s really easy. You just go to www.sustainablebusiness.co/cashflow and you click on the button when it comes up and get your infographic.

It’s free and I hope you enjoy it. If you want to talk to me about it, I’m always happy to do that, too. This is Josh Patrick. We’re with Stephanie Evergreen. You’re at The Sustainable Business. Thanks a lot for stopping by. I hope to see you back here really soon.

Narrator:         You’ve been listening to The Sustainable Business podcast where we ask the question, “What would it take for your business to still be around a hundred years from now?” If you like what you’ve heard and want more information, please contact Josh Patrick at 802-846-1264 ext 2, or visit us on our website at www.askjoshpatrick.com, or you can send Josh an email at jpatrick@askjoshpatrick.com.

Thanks for listening. We hope to see you at The Sustainable Business in the near future.

Topics: sustainable business podcast, Sustainable Business, historic data, stephanie evergreen, data presentations, predictive data, data visualization, visual data dashboard, business insights, data based decisions, business data

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