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Episode #40: Zach Gemignani
144 Plays9 years ago
Welcome back to The PolicyViz Podcast. This week, I’m pleased to chat with Zach Gemignani, CEO and Founder of Juice Analytics. Juice, a sponsor of the show, helps their customers analyze, visualize, and deliver their data. Their experiences with different clients demonstrates...
The post Episode #40: Zach Gemignani appeared first on PolicyViz.
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Transcript
Introduction to Boku and OpenVizConf
00:00:00
Speaker
This episode of the PolicyViz podcast is sponsored by Boku. Boku helps businesses make sense of their data and transform it into interactive, engaging, and informative experiences online. Boku also brings you OpenVizConf, a two-day conference about the practice of data visualization on the open web.
00:00:18
Speaker
OpenVizConf is taking place in Boston on April 25 and 26 at the New England Aquarium IMAX. To learn more about Boku, visit them at B-O-C-O-U-P dot com.
Meet the Host and Guest
00:00:41
Speaker
Welcome back to the Policy Viz Podcast. I'm your host, John Schwabisch. Spring has sprung here in DC, and that means more discussions about data and data tools. And I'm very excited this week to welcome co-founder and CEO of Juice Analytics, Zach Jimignani. Zach, thanks for coming on the show. And of course, thanks for sponsoring the show for the last few weeks. It's been great.
00:01:03
Speaker
Absolutely, John, happy to be here with you.
Origin of Juice Analytics
00:01:06
Speaker
We have a lot to talk about, the sorts of things that you're doing at Juice, the sorts of products you're building and how you're helping customers and clients work with their data. But I want to start first by asking you a little bit about your background and the background of the company.
00:01:19
Speaker
Well, John, let me kind of take you back to starting Juice. And we actually started Juice almost 10 years ago. I started the company with my brother, Chris. He's the co-founder and our tech lead at Juice.
00:01:34
Speaker
really wanted to do something together focused on data and analytics. And when we found the time to do it, we got together came up with the name juice, because we were looking to help people extract value from data. So that's, that's where we got the company started and start out in my basement, one of those standard startup stories. And at the beginning, we were really focused
00:01:59
Speaker
more broadly on analytics and helping our consulting clients understand data, find insights from that data. But the thing that we found after a little bit of that time working with our clients was that the thing we really got excited about John was the way that we communicated data.
00:02:17
Speaker
The piece of it energized us was finding creative and new ways to visually present the data that we had analyzed and put it in ways that our clients and executives could really understand what they were looking at.
Building Customer Relationships with Data Products
00:02:30
Speaker
And when you're working with clients today, are most of the solutions they're looking for learning how to communicate better internally or is it externally or is it both? We work with clients in a lot of different industries. And one of the things that has changed for Juice over the years is that at the beginning, we did do a lot of work with clients, helping them build internal dashboards, explore their own data, find operational improvement areas internally.
00:02:57
Speaker
But the area that we've gravitated toward over time has been these use cases where clients have valuable data and they're looking to take that data and package it up and deliver it to their customers. So deliver it externally, whether that's in the form of interactive reporting or what we call data products.
00:03:19
Speaker
our clients feel like they have this chance to build better relationships with their customers by delivering data in ways that those customers can really make sense of it and take action on it. So walk us through an example. Customer calls you up and they say, we need help. We have all these data. We're not exactly sure how to talk about it and analyze it. Can you come over and help us?
What is Juicebox?
00:03:40
Speaker
So walk us through sort of an example of what you guys do when you walk into an organization.
00:03:44
Speaker
Sure. So we have a technology platform that we've developed over the last couple of years called Juicebox. And Juicebox is our toolkit for building the kinds of data applications, highly visual, interactive data applications that we deliver for customers. If a company comes to us and they're saying they have a challenge with the data they have and delivering that data to their customers, or they see an opportunity with that data, what we do is help them think through
00:04:13
Speaker
who that end user is that should be looking at that data and what actions they should be taking or could be taking on that data. And then what we're able to do with Juicebox is design these applications that are going to take our client's data, package that data up, and then deliver it as a solution externally to those customers. So just to give you
00:04:37
Speaker
One example, we're working with a large company in the healthcare space that's based in Atlanta that delivers a whole series of different services solutions to hospitals. They're delivering all these solutions. They need to do a lot of reporting back to those customers to demonstrate the value that they've delivered to those customers.
00:04:58
Speaker
and help them understand the impact that they're making. And what we're doing with this client of ours is taking all of that reporting, which is currently done in Excel and PowerPoint and takes a lot of effort and ultimately turns into giant PowerPoint documents that their clients don't want to look at. We're taking all of that reporting and turning it into juice box applications that when they deliver that to those customers, they understand they can interact with that data in a
Designing for End Users
00:05:24
Speaker
new way. They can understand exactly why that data is useful.
00:05:28
Speaker
and what impact our client is making on their business. Right. So let's talk a little bit about Juicebox. So Juicebox is an interactive data platform that your customers can use to work with their data in sort of, it seems like more visual ways. So can you talk a little bit about sort of, not necessarily the technology behind it, but the use cases. So you talked about Excel and PowerPoint. People use those because they're familiar with the Office suite and they're sort of easy to use. So does Juicebox allow people to work with data in easier ways? Not just in terms of, oh, here's some output and I can interact with it, but
00:05:58
Speaker
There's drop and drag technologies. They can move data in from different sources. And why then do they go to a tool set like Juicebox as opposed to something like, you know, Tableau or even something a little more custom where maybe they need to code or something like a Hydrox or JavaScript.
00:06:15
Speaker
Yeah, they can certainly build something themselves. So the distinction that we like to make is that there are a ton of great tools out there now. Like Tableau is, of course, a great example of tools that are designed for analysts to be able to be great at their job. So Tableau is
00:06:34
Speaker
a lot of ways kind of a super powered version of Excel. It's going to give the people who are deep in the data a powerful tool to be able to explore information, find insights, create dashboards and give that to the management within their organization.
00:06:49
Speaker
The thing that we are really, I think, obsessed with and focused on in a way that there's really no other tool out there is focused on the actual end user of that data. So the actual person who hands up looking at that data is not an analyst. They're not used to looking at the data. They don't necessarily know what the metrics mean. They don't live inside of a spreadsheet on a day-to-day basis.
00:07:14
Speaker
So what we've really set out to do is create a technology and an ability to build data applications that are ultimately for those end users. So when we focus on really trying to create a great experience for the end user, it changes what the features and capabilities that Juicebox has relative to almost anything else in the market. So we focus a lot on guiding users through the data in a very prescriptive way.
00:07:43
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walking users from a starting point and an overview of the information all the way through to views of the data that they can actually do something with.
00:07:54
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We focus a lot on wrapping that data and the visualizations in context and providing guidance when people are using this and they're not familiar with the tool or they're not an analyst, they can still understand what they're seeing. And we also have a lot of features in Juicebox that are pretty unique around sharing
00:08:13
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And making that data social so for us it's really important that visualization that we all want to do well and present well is really the starting point for a conversation about data it's a way to get people to understand what's in the data where the insights are.
00:08:32
Speaker
But in most organizations, finding that insight is really just the beginning. After that, you have to take that insight to your boss or your colleagues and discuss what you're going to do about it. You might want to create an action plan around the data that you've seen and decide
00:08:50
Speaker
What are you actually going to do to change something in your organization based on that data? So there's a whole set of steps that need to exist in our view beyond just making nice visualizations all the way through to get people to actually do something with the data that they're looking at.
00:09:06
Speaker
It's a long answer, but essentially to say Juicebox is focused on that end user and getting them to do something. And I think a lot of these other tools are focused more on the analyst themselves. Yeah, that's really interesting. And I'm curious, because it is an interactive tool in which a user can click on this part and things highlight and move around,
00:09:27
Speaker
Where does the sort of annotation, I hesitate to use storytelling for this, but in terms of, you know, you see a lot of times, and especially in static graphs where there's a little explanation of maybe the content, but also how to read the graph. How do the creators sort of think about, oh, okay, I need to make this graph, this dashboard, this visualization for a person who's not familiar with the data. And so I need to walk them through not just the content, but also how to sort of maybe read this as a,
00:09:54
Speaker
scatterplot that maybe the person who's going to get this doesn't really know how to read a scatterplot.
Guiding Users and Providing Insights
00:09:59
Speaker
Yeah. There's a couple of ways that we think about that. I'll share an analogy that we use a lot around here at Juice where we feel like we want to be able to be a Safari guide for those end users. We want to be able to create tools that are able to take those end users
00:10:16
Speaker
through the jungle that is the data. Take them to interesting places where they're going to be able to find insights. Provide as a guide, you explain what you're looking at and what might be interesting about it. And then take them to the next step. So you're trying to provide this kind of guided path. And this is what we do in Juicebox is take people through a step-by-step
00:10:41
Speaker
process of walking them through useful ways and a kind of structured analysis within the data. So we will wrap around those visualizations a lot of text and content and explanation so that they understand what they're looking at.
00:10:59
Speaker
So that's kind of one level of it is to really hold users' hands and give them a tour of the data as they walk through it. But the other piece of it, I think, is that the users themselves need to be able to annotate what they're seeing in the data, because no one really understands or can draw insights out of it more than the actual people who understand what's going on on the ground, in their business, on the front lines.
00:11:24
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So we want to let those people also be able to provide annotations on what they're seeing in the very specific data. And we have a feature that we call discussions within Juicebox, which allows people to, when they find something useful, we want them to be able to capture that, write a note about what they're seeing, and then be able to share that specific image and view of the data with their colleagues.
00:11:51
Speaker
I'm also curious about the challenges that you see when you're working with the analysts who are building the deliverable, the visualization, versus the people who are receiving it and where you have to work with the analysts side to get them to understand their audience. A lot of people I work with who are researchers, they want all the subtlety and all the nuance and all the details to be included in everything.
00:12:16
Speaker
where the end user just wants to see the bar chart with the
Bridging Data Analysts and End Users
00:12:20
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four bars. That's all they want. So how do you work with people who want to, or maybe they don't, but they want to have all the detail and all the little nuance in there. But the person at the end of the day just wants to know how they can improve their business with using the data they have in front of them.
00:12:36
Speaker
Yeah, yeah, that's a great point. That is the constant battle is that there's this gulf between the people who understand the data deeply and feel like they want to share all of that data. You know, the people on the front lines or the executives or whoever the audience is really doesn't have the attention span for all of that. So that gap always has to be bridged. Now, what we do to address that is we actually play the role of the designer in when we're building these applications. And this is
00:13:04
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something that I think we've been able to navigate and learn how to navigate over the years of understanding what the most important data is and help narrow that down so that when we design the application we're really only showing the key metrics that are actually key or the
00:13:21
Speaker
The ways of looking at that data are something that somebody will do something about. That's the question I'm always asking in that design process is if you saw that data, if we had that view of the data, what would you do about it? To me, that's the key because often the answer is, well, it would be interesting and I don't know what I would do about it. And I think that's a good indicator that there's not actually, isn't required that it be included in something.
00:13:47
Speaker
Right, yeah. Don't just give everybody the data just because you can. Try to elicit those insights. I'm also curious about the design from the analyst's perspective. So I know Juicebox has a design tip for non-designer sheet, which is great. Talks about core-level design tips all the way to graduate-level design tips and talks about all the different things from color to font to layout and all that sort of things. Again, how do you talk or how do you work with people who
00:14:13
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You know, they are their analysts, their data folks, their statistics folks. How do you get them to think that and appreciate how design is important and can help them tell their story or deliver their analysis? Yeah, well, one of the ways we do that is we take away choice.
00:14:28
Speaker
You know, this is, I think this is one of the great challenges that people have had with Excel. And I think this happens in Tableau and PowerPoint, all sorts of tools that if you give people every possible choice, they're going to feel like they have to make choices all over the place. And some of those choices are not going to be optimal. So in Juicebox,
00:14:47
Speaker
We're making a lot of choices to start with. We're going to make choices about what primary colors we want to use, how we're using fonts. We have a set of really great interactive visualizations, but there are only 15 or 16 of them.
00:15:02
Speaker
And they cover a lot of ground in every kind of situation that we've seen, but we don't need every kind of chart. We don't need 3D pie charts. We've thrown out the things that we know are not useful visual tools. So when we take out a lot of that stuff, then it boils down for the designer and the person who understands the data to
00:15:24
Speaker
What is the story you want to tell with the data? What are the really key metrics and how do I walk my audience through that information? And then the choices we're making are really saying if we know what that story is you want to tell, we've got the tools. We can pull out of our library of visualizations a great visualization to tell each step in that path.
00:15:48
Speaker
But that's really interesting. So do you have people who say, well, I really want to make this flashier and pop? Can I get a 3D exploding pie chart in this thing? Do you have people who say that? Yes. Yes, we find it in that situation.
00:16:05
Speaker
And we do have to push back on that stuff. Ultimately, as I said, we're trying to look out for... We want to have people use our product and sell it to the customers, but we're trying to look out for the end user experience.
Managing User Data Visibility
00:16:21
Speaker
person who gets this juice box application is going to understand it and make sense of it and do something with the data. So I feel like we're on pretty solid ground to push back on requirements or needs that we get from our customers that are not serving the needs of those end users.
00:16:36
Speaker
Another question sort of on Juicebox. When it comes to making things external, so for publishing external, so how does Juicebox work in terms of reading data in and then getting it out to the broader world? Sure. So I don't know how technical we want to go here. I'll probably not get that technical. So Juicebox is a hosted solution.
00:16:56
Speaker
With our customers, we pull data in from their systems into our hosted servers. Then those applications get delivered to our customers' customers as a web application. When it gets delivered as a web application, there's a lot of control that our customers have in terms of who gets to see what data and what features individual users get to see.
00:17:19
Speaker
We have a lot of user management and user permission capabilities because these are externally focused apps. And I think that's another thing that makes Juicebox very different from a tool like Tableau or other tools that build dashboards where it's a little bit closer to everybody sees the same thing. We need to make sure different end users get to see different data. Right. Really interesting. So what's the Juice Analytics team look like? So I know you have two offices, one in Nashville and one in Atlanta. Who makes up the organization?
00:17:48
Speaker
Yeah, sure. So we have a implementation team who are the people who are working with our customers to design and configure and launch these juice box applications. So a good portion of our team is in that role. We base that team out of our Atlanta office.
00:18:06
Speaker
Our core development team is based here in Nashville, where I mentioned my brother is the lead on our technology. So he manages the team that is building the core product that all these solutions are built on top of. In terms of technology, it's a Python-based stack. It's hosted on Amazon Web Services. And there's obviously a lot of JavaScript and D3 kind of stuff going on inside of Juicebox.
00:18:34
Speaker
And then we have Priggle throughout. We have a small marketing team that's based out of Atlanta. And then we have our lead product designers actually based out of Atlanta as well. So we're kind of spread out all over the place, but it's worked out well.
Juice Analytics' Operations and Team
00:18:48
Speaker
And I noticed that you are looking for new folks to join the team. So for those who are listening to the show, what are you looking for?
00:18:57
Speaker
Sure, yeah, we are growing and we're looking to add people. We have this role that we call a solution builder, and it's a person who becomes expert in using Juicebox. They do play a role in actually designing the applications with customers, so they need to have an ability to work closely with customers.
00:19:17
Speaker
but also be able to translate those customer requirements into the visualizations and the stories that they want to tell with that data and stand those things up using JuiceBox. So it's kind of a broad role. I think it's a real fun role because it gives people the opportunity to work with the data, but also think about how that data gets presented. We usually look for people with good data skills, SQL skills. Python is certainly a plus. We're hiring those people both in Atlanta,
00:19:46
Speaker
and here in Nashville. Great. Well, I will link to the jobs page on the website for the
Communicating Data Effectively
00:19:55
Speaker
podcast. We also have your design tip sheet and we have your book, Data Fluency. You want to talk about Data Fluency real quick? Yeah, sure. So Data Fluency was a book that came out about a year ago.
00:20:05
Speaker
We wrote this book in conjunction with Nathan Yao from Flowing Data who got us in touch with his publisher because he wanted to see if we could put together a book that really would speak to helping organizations think about how they can become more fluent in the use of data.
00:20:27
Speaker
put together something that would let managers, executives, and all the types of people who are in organizations that feel like they have a lot of data at their disposal to make smarter decisions, but they're struggling with how do they use that to communicate.
00:20:43
Speaker
We have a framework in Data Fluency that talks about the people who create data solutions and talks about the consumers of data solutions and how you connect those people, and also about the skills that are necessary in order to think about visualizing things and communicating data effectively. It's a whole framework around helping companies be more effective in how they use data to make smarter decisions.
00:21:10
Speaker
Yeah, which is clearly one of the big issues going forward. Everybody has data, everybody wants data, and now people have to figure out how to build their teams and work with it and get it out there. Exactly.
00:21:20
Speaker
Well, Zach, thanks for coming on the show.
Closing Remarks and Feedback Invitation
00:21:22
Speaker
This has been really interesting and I appreciate coming on the show and of course for sponsoring the podcast. Absolutely, John. Thank you. And thanks to everyone out there for listening. Let me know what you think about today's episode. Let me know what you think about telling stories with data in an interactive world. Do you need interactivity? Do you just need annotation? What do you need? So until next time, this has been the PolicyViz Podcast. Thanks so much for listening.
00:21:55
Speaker
This episode of the PolicyViz podcast is sponsored by Boku. Boku helps businesses make sense of their data and transform it into interactive, engaging, and informative experiences online. Boku also brings you OpenVizConf, a two-day conference about the practice of data visualization on the open web.
00:22:14
Speaker
OpenVizConf is taking place in Boston on April 25 and 26 at the New England Aquarium IMAX. To learn more about Boku, visit them at B-O-C-O-U-P dot com.