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Doing Data Stuff for Money with Moxy Analytics co-founder Serena Roberts
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Running your own data literacy and data consulting shop is no easy task. And helping customers not only build better visualizations and dashboards, but helping them create a better (or new) data culture is even harder. But Serena Roberts and her team at Moxy Analytics has been fighting that good fight for a few years now. Serena and I talk about what Moxy is up to, how to build better data teams, getting over imposter syndrome, and much, much more.
Sponsor: Maryland Institute College of Art
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Transcript
Introduction to MICA's Online Program
00:00:00
Speaker
This episode of the Policyviz Podcast is brought to you by the Maryland Institute College of Art. Virtually everything we interact with today is driven by or generates data. This data explosion has resulted in the need to take raw, unorganized data and not only process it, but also present it in meaningful ways so that it is insightful and actionable.
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Speaker
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00:00:43
Speaker
MICA takes a hands-on, real-world approach with an engaging curriculum. You'll develop career-ready skills while you build a compelling portfolio to impress potential employers. Join their vibrant community of creative professionals as you are mentored by passionate faculty leaders who have built successful careers in data visualization. Discover more at online.mica.edu. That's online.mica.edu. Now accepting applications for the spring, summer, and fall semesters.
00:01:23
Speaker
Welcome
Guest Introduction: Serena Roberts
00:01:24
Speaker
back to the Policy Viz Podcast. I'm your host, John Schwabisch. It is episode three of season 10. I hope you've been enjoying the last couple of episodes of the show. I am excited to bring you this week's episode with Moxie Analytics co-founder, Serena Roberts. We talk about all the work that they do. I found out about Moxie Analytics through my friend, Kevin Flurlage. Kevin and his brother Ken were hired by Moxie several months ago, I think kind of maybe springtime, February, March, April, somewhere in there.
00:01:52
Speaker
and started poking around the Moxie site and found a lot of great stuff. And so reached out to Serena and her co-founder Laura to come on the show and talk about their work, talk about data culture, which of course is an important aspect of data visualization because you can't quite get to data visualization unless you have some kind of data culture and hopefully good data culture. And so Serena and I sat down and talked about their work, talked about how they engage with clients, talked about how they try to help clients develop a better data culture.
00:02:21
Speaker
So I hope you'll enjoy this conversation on this week's episode of the podcast with Moxie analytics co-founder Serena Roberts. Hi Serena. Welcome to the show. Good to see you meet you. I don't know. We trying to figure out whether we've met in person before.
00:02:38
Speaker
I think, but I can't place it. Well, good to see you again. Thanks for coming on the show. I'm excited to have one of the two founders. We can talk about Laura later if we want so she can tune in. Yeah.
Moxie Analytics: An Overview
00:02:54
Speaker
Um, do you want to, um, maybe start talk a little bit about Moxie analytics and what you guys do and, and the work that you're doing now? Cause there's, cause when I look through the website, there's kind of like, I don't know, but maybe six different kind of, I mean, all interrelated, but kind of like six content areas. So, um, we can just start there and then we can, we can chat some more. Yeah.
00:03:14
Speaker
Um, so I, my favorite thing to say about what we do is that we do data stuff for money. So like we're a, you know, a consulting firm in the data space and our website or the way that we organize our, our thoughts and our philosophy and things that we do is really around data culture enablement. And so in order to successfully have this thriving, you know, a data culture.
00:03:44
Speaker
you need a number of different things. It can't just be really awesome data visualizations. It can't just be you're really good at managing your data. It can't just be that you've got the best of the best tool sets. It can't just be that you've got really smart people. It is how all of those things, your strategy and time back to the business value, how all of those things
00:04:07
Speaker
work in concert together towards this utopia of, uh, a data-driven culture. So, so yeah, so we do data stuff for money, John. Um, it's pretty
Diverse Expertise at Moxie
00:04:18
Speaker
good. Yeah. I mean, you know, if you're going to do something for money, might as well be data stuff. Yeah. I actually, when we were in Vegas for the Tableau conference, uh, this year, wasn't it? Yes. Um,
00:04:31
Speaker
And so I made buttons and it said, we, it, well, if you were, if you weren't looking closely at it, it said, we do stuff for money. And then I had a little like little, little data. So yeah, I, I want to say at least one of the, one of the twins's wives was like, really? Like go with that in Vegas.
00:04:54
Speaker
So let's talk about who's on the team. So for those who don't know, when you reference the twins, who you're talking about, because those, I think most, probably most folks in the Tableau community know who you're talking about, but maybe not everybody. So what is the team like these days? Yeah. So, so we're a team of six small, but mighty. Uh, so it's myself and my business partner who like totally bailed on me. She was supposed to do this podcast with me. Um, her name is Laura Madsen and she and I go way back together.
00:05:23
Speaker
Um, we have two other gals, Anna and Ruby. And then our most recent hires are the twins, the Floralage twins, Ken and Ken Floralage. And I'm going to show you, I've got this little bobble head guy. You've got a Ken bobble head. That is pretty cool. Well, if we're Ken or is it Kevin? I don't know. It was a Canada's Kevin. I don't know. You'd be the, yeah, you'd be the judge on that one. Yeah. So we are, we're a small but mighty team of six right now, um, which is exponential for us because when we started
00:05:53
Speaker
2023, it was still just Laura and I. Wow. Yeah, that's really fast. And then the twins. And so I spent a little bit of a rocket ship ride and we're just trying to, you know, hold on to our seats and like still do the right smart things and not screwed up. So that's good.
00:06:13
Speaker
So I know Ken and Kevin's background, but what's the background of the rest of the team? And, and I always find it interesting how people come to, I mean, I know you're not just doing data visualization, but how they come
Serena's Journey into Analytics
00:06:25
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to sort of the data space. Um, so, so what is that small but mighty team we're assuming is going to be a variety of backgrounds. It is a variety. Um, so Anna, uh, she's a geophysicist data pro.
00:06:40
Speaker
Well, so yes, uh, she's phenomenal. Uh, we have a nurse, a former nurse, like direct patient care, uh, term data pro. And, uh, so Laura, uh, she, she actually spent most of her career in, you know, the BI analytics space for, she went to college for applied psychology at UW stealth. Um,
00:07:09
Speaker
So she's probably got the most like, uh, logical path. Although for some people, you might think like applied psychology, like how does that, right? But it's like, it's statistics, it's data, right? Um, so to me, that's a logical, logical path. Um, I, I went to school for entrepreneurship. So until I actually started Moxie, it really wasn't using my degree that much. And I completely fell into the world of data and analytics. I.
00:07:39
Speaker
was like 20. I've held was I almost like 24. Something like that. Yeah. Um, single mom just needed a job. Yeah. And I started at this very small boutique consulting firm. It's called Lancet data sciences. Um, amazing crew of people back then. And so I started out in a sales and marketing and I was employee number 18. And when you're an employee, number 18,
00:08:08
Speaker
at a company you do. Pretty sure I cleaned the toilet once. It happened. Yeah, so you just kind of did whatever you needed to do and literally before that I didn't
00:08:21
Speaker
even know that this was a thing, that this was a field that existed. Right. And so just, I spent a decade there. And in that decade, you know, became, you know, somewhat of an expert, right? Like, for a long time, I didn't feel like I belonged in this space. And that was probably just me fighting with my Pfizer syndrome. But yeah, so that's, that's why I got my start into data and analytics from that consulting firm. I spent some time
00:08:51
Speaker
Um, on the client side, as we in consulting, like, like to say, um, I worked in the financial sector for a little while in education. Um, and then, and then finally just kind of got sick of like grind and the bullshit and, um, and decided to try and create what I couldn't find out in the corporate world for myself. And then icing on the cake is to be able to extend that out to.
00:09:20
Speaker
to other people to enjoy. So I want to ask some questions about the folks that you work with, but I want to come back. You mentioned this kind of imposter syndrome, and I think we all have that either from time to time or, you know, people have it. It's like just kind of part of their identity. And at least within your experience, within this kind of data space,
00:09:40
Speaker
what helped you sort of overcome that and say, yeah, I actually do know what I'm doing and I can go that next step, which is like a really courageous step to like start your own business is maybe like the most courageous step, right? Is like, not just to say, I know what I'm doing and I can do this job that I'm in working for someone, but like I'm courageous enough or I can go out on my own and do this, like owning my own business. So
00:10:04
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you know, if you were to think about your younger self with someone out there listening to this as your younger self, like what were the keys for your success?
Building a Data Culture
00:10:12
Speaker
Um, so I think I've, I like, I've always had a pretty high level of risk tolerance. Like just that is my, my general nature. Yeah. I, if I had a super power, it would be being able to pick things up quickly. Right. Like I'm the type of person who,
00:10:33
Speaker
If I don't know how to do something, I will go, you know, watch a YouTube video. I mean, I don't know what people did before that, but I will watch a YouTube video on how to like, you know, tile a bathroom. And then I'll be like, I'm an expert now. And I'm probably not. I'm probably not an expert, but I have enough confidence in my ability. Um,
00:11:00
Speaker
And also a high enough level of risk tolerance to be like, if I totally mess this up and need to retile my bathroom, like worst case scenario, I'm okay with that. Yeah. I think that was just kind of like base level for all of the things that I've done in my life that I've worked out. Well, it's just like being okay with taking that, that level of risk. Um, when I did make that leap to start Moxie, um, my, it was actually, it was,
00:11:29
Speaker
predicated on a conversation that I had with my husband because I was like, I'm working a job that was like 50, 60 hours a week. It wasn't what I had signed up for. I wasn't being the kind of mom or wife that I had wanted to be. And my husband, I love him. Okay, I'll just practice. I do love my husband and he will speak.
00:11:55
Speaker
Just a pause here in the podcast and just let that all sink in for everybody. Okay. So he came to me and he's like, you know, I knew
00:12:06
Speaker
that you were kind of a bitch when I married you. Like, that was one of the things. Like, that was a, that was a plus, right? And he needed that in my life. Like, this is next level. Like, you need to, you need to do something about, about this. And so it was like the conversation between he and I about, well, you know, we have health insurance through my job. Like, I mean, the money then you do at this point. And like, how can we, I feel like, how can we, I feel like I couldn't
00:12:36
Speaker
didn't have any of her choices and I was just stuck there. And so we really were just kind of like, well, what is the worst thing that could happen if I just put my job to work without anything lined up, without any knowing what I'm going to do, what would be the worst thing that would happen? And he was like, well, we'd probably have to sell our house and everything we own and buy an RV and then, you know,
00:13:04
Speaker
And we're both just kind of like, you know what, that actually doesn't sound terrible. Now, John is actually almost like a bucket list thing. Right to do that now. Right. Just like, yeah. Yeah. Yeah. All right. That's good. That worst case scenario. Let's like, let's do it. If that's the worst that's going to happen to us, then like, you know, I'm all in and plus I thought Laura,
00:13:30
Speaker
Um, and not doing it alone. And that's a huge, huge thing. She actually quit her job before, like I almost like a full year before I did. And it was doing her own thing by herself before we started Moxie together. So I'm not sure that I would have done it all by myself like that. Right. But to have someone you can lean on and trust and just another brain. I mean, like so much of this stuff is like.
00:14:00
Speaker
trial and error, right? You don't know what's going to work, what's not going to work. And so just to have that second person too, is this a crazy idea? Like isn't this kind of crazy idea or like a bad, a crazy idea? And so I'm going to pick you up and say, Hey, that didn't work, but like, dust yourself off and we're going to try something else. Right. Right. Yeah. No, I think it did. I mean, I think part of it is.
00:14:25
Speaker
the ability or the willingness to just learn new things, which I think is definitely part of this data world, data viz world data, you know, like learn new tools, learn, you know, whatever tool it is, pick those up, and then to try something and to have the courage to go out and recognize that.
00:14:41
Speaker
you know, maybe the worst case scenario is not so terrible. And of course you had your spouse to lean on and other people may or may not, but they might have their parents or a sibling or, you know, another spouse or friend to lean on. So, I mean, I think it's, it's everybody's experience just, just a little different.
00:14:56
Speaker
Um, so you mentioned, uh, at the start that, um, you work with lots of clients on their data culture. And I know
Challenges in Data Culture
00:15:03
Speaker
on the website, it talks a lot about data literacy. What are some of the big challenges or I guess challenges be the way to phrase it. What are the big challenges you see when, when a client calls you to help them on that? I think primarily my interest to be on the data culture. Cause it's such an interesting part of this world, as you mentioned is how people.
00:15:22
Speaker
evolve and improve and develop that culture within their organization. So what does that sort of engagement look like with Moxie? Yeah. Well, so we almost never get clients that come to us and say, Hey, I want to hire you to help me build a data culture. Right. It's usually something else. Sometimes it is like, Oh, we need a literacy program or a champion program or whatever, whatever you want to call it. Um,
00:15:51
Speaker
But if you peel back the layers of that onion, what people are trying to do when they build a data literacy program, when they try to build these really great dashboards, when they invest in tools like Snowflake and Alterix and Tableau and all these things. They're trying to create an enterprise-wide culture of people who know how to access
00:16:21
Speaker
you know, leverage, you read, write, understand, speak data, and can use that to make good business decisions and inform good business decisions. And like that to me is data culture. And it can't be the thing that you directly focus on, right?
00:16:41
Speaker
Like I'm not going to come in, I'm going to build you a data culture today. Right. Right. Right. There's so many pieces of it. Um, and it's such an ambiguous thing to sort of measure that like, it's almost never the direct goal. Right. When I write a contract, right. It's never like, I'm going to build you a data culture. Right. All these things that, that, uh, that are in service of that. So, and when it comes to the things that I see are getting, um, in the way of people.
00:17:11
Speaker
meeting that goal or succeeding in these efforts. What comes to mind first is government governance. Laura would be great to have here because she's our resident queen of data governance and data management. Because on the one hand, yes, you need and want people to be using data as this asset that you've invested in.
00:17:42
Speaker
But if you don't have the guardrails and like the education in place, those people are going to do some really stupid stuff with it. It's like driving, right? Like think about all you have to do, you know, to go through to get your, even just your provisional license these days, or at least in Minnesota, that's how they do it. And then we have roads and those roads are maintained and there's, you know,
00:18:08
Speaker
white lines and yellow lines and like there's guard rails to try and make it so.
00:18:14
Speaker
The people on the road are driving safely. It's a great analogy because like, well, if nobody drove on the roads, well, we wouldn't need cars and we wouldn't need roads. We want people to, we want people to be using that infrastructure because it supports a lot of the commerce that our society lives on these days. But without all of those,
00:18:42
Speaker
all those guardrails, it would be chaos. Right. So, so we see some organizations will invest in like data literacy programs, um, or like self-service initiatives where they're like, we just want everybody to have access to all this stuff. Yeah. And then they don't put the, you know, any kind of governance or guard guardrails around. So in that case, it just kind of becomes like, what a free for all. And there's no, yeah. I think you'll have people summing averages and not like not
00:19:13
Speaker
And, you know, connecting the dots between the thing that they're building and like the business decisions and business value. It's just
Data Governance Importance
00:19:21
Speaker
like, here's a chart and build it. Cool. So the lack of the government's piece is one. And then I think, I think accessibility is probably number two and I am, I
00:19:38
Speaker
I, accessibility in like the, you know, the, in the sense that, you know, everybody should be not just regular, like fully sighted able-bodied people like me. So that is important too. But when I say accessibility, I mean like being able to find stuff. I mean, like how many table of server cloud or server cloud environments you go, you go to two and you're just like, I have.
00:20:03
Speaker
No idea how this stuff is organized. I don't know where to go to find this. And that's not tableau specific by any means. So it's like, just think, how do you make this stuff accessible to people? You know, push it to them, you know, when and where they need it, sort of like a meeting, meeting them where they are kind of, kind of thing, or making it really intuitive and logical for them to go to some kind of a repository and, and find, find that.
00:20:34
Speaker
So that's one and two. I could probably call out a third being. Just people not following some of the basic design practices, you know, like all too often you see like Tableau can do some really amazing things and then they just go and build a grid. Yeah. Right? Yeah.
00:21:00
Speaker
Like they connect it to some CSV file and then they just recreate that CSV file. Yeah. Yeah. Right. Here's a table. I made another table. Yeah. Not sure that was worth an investment. Right. Right.
00:21:16
Speaker
This is a very broad question, but like having identified those three pieces, plus I'm sure many more, I'll hone in on this question a little bit. Where do you start? So you come into an organization and let's just say they are in kind of that wild, wild West current state. Where do you start to say, Hey, we need to build in, for example, a data governance structure. We need to make things available for everybody. We need to get best practices sort of.
00:21:42
Speaker
organizationally wide. Like where do you start in that? Because I think what I'm hearing from you is it's not just a technology problem and it's not just a personnel problem, but it's a, as you said, it's a cultural management problem with, which is human beings, which is way more difficult. So I think the applied psychology degree probably comes in handy here, but like, yeah. So where do those conversations start?
00:22:05
Speaker
You so, you know, I'd love to see that there's like, Oh, like there's this common path. Yeah. There just really isn't everybody is on such a different journey on such different paths. Um, I will say that one, one common thing that we see is that every organization comes in and they think that they are the ones that are like behind the eight ball, that everybody else is doing all of this cool stuff, better, faster, smarter than they are.
00:22:35
Speaker
And in my opinion, that is almost never the case. Right, right. Everybody is much, much earlier on in their journey. I think despite, you know, some, you know, cool AI, you know, predicting, you know, somebody, you know, somebody that's doing over here. Yeah. Um, but like, number one, it's like, we just, we're going to meet people where they are from a,
00:23:03
Speaker
From like, from a selling perspective, we do know that it is easier to sell like dashboard projects simply because I can say to you, um, I'll build you a dashboard. Right. You're going to generally know like what I'm, you know, what I'm talking about, right? What you're going to walk away with at the end of that engagement.
Initiating Data Culture Change
00:23:25
Speaker
Um, if we say something like, I'm gonna like build you a data governance framework.
00:23:31
Speaker
Yeah, it's more amorphous. Yeah. Yeah. So that needs much more explanation. So, um, so we do see, uh, we are getting our foot in the door, particularly because now we've got, you know, the table, you know, we're getting our foot in the door, like let's build you a dashboard. And then that will lead to things like, Hey, um,
00:24:00
Speaker
Here are some best practice things that you should be thinking about implementing. Here is some templates that you can use to help drive standardization across your enterprise. Here's some checklists that you should run through before you pick stuff up to production. Oh, by the way, you should have production in that environment. Looking for opportunities where we can
00:24:29
Speaker
give that kind of best practice of advice and guidance. And then after a while, it's just like we have built that relationship where we're seen as someone who can give that kind of advisory expertise. So when they are ready for, hey, we want to do this big thing, right? We do want to build a data governance program. We do want to have a data champion program. We do need help.
00:24:58
Speaker
you know, getting buy-in from our leadership and the change management aspect of this difficult work, that we've got a good footing in place. It does help that Laura
00:25:12
Speaker
literally wrote a book on data governance. So she's already kind of like seated herself as that expert. Right. So this may not have an answer either, but have you found that it is a better strategy for you to work with the analyst level so that it's kind of bottom up to have this cultural change? Or is it better to work with the top C level management style and sort of like driven top down?
00:25:41
Speaker
Or again, is it sort of like, it more of like the great, it depends. I mean, yeah, as a consultant, every answer I give is it depends. Right. Sure. Yeah. But, um, we've done it both ways. We've done it both ways. And, uh, I gave a presentation a while back on like how to kick certain data culture. And one of the, I think there was five, it was like five, like, you know, myths about kick starting a data culture.
00:26:08
Speaker
And one of them was that you need to wait for C-suite sponsorship. And in my opinion, that is just not true, right? If you have even mid level, like if you have an analytics function, whether it's a center of excellence or just, you know, whatever, right? Even if it's a siloed analytics function inside your organization that has appetite for that kind of thing.
00:26:36
Speaker
Um, there are some things that you can do from, you know, maybe not necessarily like ground level. Right. But, you know, that sort of middle of the organization, there are definitely some things that you can do in a shorter period of time on, you know, you know, with a little, little budget to show what is possible and take that, you know, what you've done.
00:27:03
Speaker
And you use that to make a really strong case to your leadership of like, look at what we did. This is what we spent, this is how long it took and here's the impact of that. You know, the top down approaches where, you know, where that is starting at the C-suite that has its challenges too, because it, you know, that can always just feel like it's another freaking thing that I'm being told to do, right? Eat it from on high that now I'll do this training and blah, blah, blah, blah, blah.
00:27:32
Speaker
Right. One more training. I have to pretend to watch four hours of videos on. Yeah. So there is no, like sort of one size fits all approach to it. And we really do try to come at it.
00:27:46
Speaker
the right way in each unique case. Yeah. Um, I want to ask about the, the third point you made earlier about following design best practices. Um, probably folks on this show know that I have like a little side interest and project on, on database style guides. And so I was wondering how you work with your clients on, on promoting those best practices. Do you give them readings? Do you do a training? Do you.
00:28:14
Speaker
the build style guides for them. Like what are your steps that you, or I don't know, steps is not the right word. Cause that suggests it's linear, which I'm guessing it's not, but like, what are the, what are the tools and things that you do to sort of help people follow those best practices? Um, all of the above. Okay. So we actually just published a, an ebook. It took me embarrassing to say. Um, it took me like a year to complete this, this database best practices ebook.
00:28:42
Speaker
It's, um, out on our website for free download. It's like, I think it's like 30 pages or something like that. And it's just got like my top, I think there's 10, um, database best practices. It's
Data Visualization and Branding
00:28:54
Speaker
really focused on actually going from good to great. You know, although I've seen a lot of really terrible data visualizations out there, I think most people understand generally, um, how to make an okay chart for a good enough.
00:29:10
Speaker
Sure. You just insert thing. Right. And yeah. Yeah. Especially when you've got like the little, you know, click ready. Yeah. Right. Show me tab or whatever. Right. Yeah. Yeah. So how to take, you know, how to take it up a notch on there. That's what that, that ebook is really focused on. Um, but, you know, so we also build people templates and, you know, whether we're doing that in Tableau or Power BI.
00:29:39
Speaker
Um, you know, the tools can lend themselves like bone to pick with Tableau is that like creating those templates is harder than it is to do other applications, right? Like, you know, you can be an absolute pro at containers.
00:29:57
Speaker
and still want to kill yourself. Messing around with that for a couple hours. But yeah, yeah, you know, helping people figure out like,
00:30:11
Speaker
You know, so one of the things is like, Oh, I've, we've got our style guide for our brand as a company. And we want to infuse that into our style guide, you know, into, into our dashboards. We want to use brand colors in every bar chart needs to be colored by these colors. And it's just like, please don't, please don't do that. You can have splat like splashes of those kinds of colors in there.
00:30:41
Speaker
as long as you're using them in some sort of logical and consistent format, but more often than not, what that does is it just confuses our attention as you very well know, right? It's like, I see this orange here and this blue here and it's over here and it's over here and it's over here. And at the end of the day, if it means everything, it means nothing. And so, just as an example, we might say, okay, well, let's,
00:31:11
Speaker
Let's just keep some of that color in the header and that can be consistent across every dashboard. Your bar charts and things like, why don't we just use a grayscale? Pick one of those colors and then use a gradient, a washed out version on a gradient, something like that.
00:31:33
Speaker
Yeah, it does seem that people, they try to take their branding styles and apply them to database, which either like generally I have found like the colors are too saturated or like their colors are like red, white, and blue. Well, white doesn't work in a, like when you draw a line and white on a white, but like it just doesn't work. And so that frustration, so I know you have more to say on the, on the thing, but I want to, I want to make sure we, to on the color point, just to drill into this a little bit. So like.
00:32:01
Speaker
Yeah, I mean, yeah, it's a huge one. So like, do you get a lot of pushback on that? Like, no, our brand guidelines are, you know, red, white, and blue. And that's all we can use. Like, how do you work your way around that? Sometimes, but at the end of the day, um, we give the advice that we use. It may not be the advice or the recommendations that clients want to hear, but that doesn't like, we're not
00:32:25
Speaker
the people who are just going to tell you what you, what you want. So clients get to decide there. It's their money. It's their dashboard. If they're going to die on that Hill, fine. Right. But we did our job by saying here's what you should do instead. Right. Right. Yeah. Um, color is in my opinion, one of the easiest ways that a dashboard can go completely sideways. Yeah. Yeah. Yeah. The brand colors are too saturated. And what gets me John is that like,
00:32:56
Speaker
99% of these dashboards are internal. Everybody knows what's opening. It's in your company. It's on your... It's a company. It's okay. Just slow down a little bit. Your brain does not need to be everywhere.
00:33:16
Speaker
Yeah, that's a really good point. I mean, but, but I do, I often run into people who are like, you know, they lose sight of like the graph or the point because it's not in the blue color that they expect it to be in. And you're like, Hey, yeah, it's, you know, sometimes just like a wire framing. I had this yesterday. I asked, I'm working with a group that's building a website for one of my projects.
00:33:37
Speaker
And I was like, they were showing me the wireframes and I did this exact same thing that I tell people not to do where I was like, are these the colors we're going to use? Cause those aren't the, they're like, no, no, these are the wireframes. It's all gray for a reason. I'm like, right, right. Um, I think people kind of get stuck on some of these things that they expect and lose sight of the bigger picture or the actual like point. Yeah. Well, and that goes, I think that goes back to why doing requirements gathering is so important. Part of that requirements gathering, you should know.
00:34:07
Speaker
what your use case or use cases are. Right. And so if, if you tie all of your design decisions back to the use case, like what is the goal? What are we doing here? What's the point? Right. And are you spending time arguing about the color of a particular graph based on branding colors? And you haven't stopped to ask the question, like, does this impact the goal of this, of this chart, of this dashboard report?
00:34:35
Speaker
Right. Right. Or does it, does it impact it positively or negatively? Like it doesn't matter. Right. Right. Right. So, or not everything needs to be a fricking chart. Like it's okay to use words and just, yeah.
00:34:51
Speaker
Yeah, Lord. Yeah. So just before we finish up, um, what would you say to someone who says, listen to this interview is like, yeah, we need help.
Moxie's Educational Approach
00:35:04
Speaker
So aside from obviously like reaching out to you, aside from the folks who were like, I need help building a dashboard, but let's say there is someone who's they're in their organization right now. They're listening to this and like, yeah, we are in this either we're in this early stage or we're stuck. Like when they reach out to you, like, what should they say? Like, what are the things that you look for?
00:35:21
Speaker
That are sort of the key things that get you saying like, yeah, I want to, this, this sounds like a project that we can do that, that we can help this firm, this organization, this person. So, I mean, there, there is like a certain amount of like, how do we educate our clients to be better clients? Like even from the outset, I think we're getting that, right? Yeah. Yeah. Absolutely. How do we, before our clients prospects even reach out to us, how can we make sure that they're talking in the same language that we are?
00:35:50
Speaker
Right? And check the box that were philosophically aligned. And that's one of the reasons why we put together all of the eBooks that we have. So we have a section on our website. It's called free stuff.
00:36:05
Speaker
Good tab, good tab name. Yeah. And I think we have like seven eBooks out there right now and they are everything on the database best practices that we talked about. Um, but there is also like how to kickstart your data culture. There is also the pillars of data governance. There's also how to prove, um, your return on an, on investment, like as an analytics function, um, part of the reason we put that stuff out there is, you know, yes, position ourselves as experts.
00:36:34
Speaker
in these subjects, but also to be really transparent about the way that we think about these things. Because sometimes it can be quite different than some of the other mainstream thinking. Like Laura wrote a book called Disrupting Data Governance. And the first sentence is like, I hate data governance. It sucks, or something like that. So we're really transparent about how we think about these things.
00:37:05
Speaker
in part because we don't want people to come, come to us and say, well, we think about this differently. And, you know, maybe we're not a good fit. It also helps, helps our clients with, you know, sometimes they don't really understand the real problem. So they might go out and read something there and then have an epiphany moment, or at least we're speaking in
00:37:27
Speaker
You know, some of that same language, we're using some of the same terms. So that helps us start out on the right foot with each, each engagement. Not that everybody goes out to our resection website before reaching out to us. Um, but it, it sure is a good place to start at least evaluate whether, whether we're for, for them.
00:37:49
Speaker
Right.
Engage with Moxie Resources
00:37:51
Speaker
Yeah. Well, that's great. Well, there is, um, so the site is moxieanalytics.com. There is a whole tab. I'm looking at it right now. It literally says free stuff on it. Um, and there's a blog and there's a whole section on Ken and Kevin and, uh, lots of other stuffs for folks to check out. So, so I'd encourage everybody to check that out. It's in the show notes and links to all the other stuff that we've talked about. Serena, thanks so much for coming on the show. This is, this is really interesting. But was fun.
00:38:19
Speaker
Yeah. All right. Well, take care. Thanks again. I appreciate it. Bye.
00:38:24
Speaker
And thanks, everyone, for tuning in to this week's show. I hope you enjoyed that interview. I do hope you'll check out the Moxie Analytics site. There's a lot of really cool free stuff, free e-books on their site that you should check out. And of course, if you have dashboard questions, you have Tableau questions, you have other data governance questions or data culture questions, you should reach out to them. I've put their contact information and some other great resources on the show notes for this episode of the podcast. So until next time, this has been the policy of this podcast. Thanks so much for listening.
00:38:55
Speaker
A number of people help bring you the policy of this podcast. Music is provided by the NRIs. Audio editing is provided by Ken Skaggs. Design and promotion is created with assistance from Sharon Satsuki-Ramirez. And each episode is transcribed by Jenny Transcription Services. If you'd like to help support the podcast, please share it and review it on iTunes, Stitcher, Spotify, YouTube, or wherever you get your podcasts.
00:39:16
Speaker
The Policy Vis podcast is ad-free and supported by listeners. If you'd like to help support the show financially, please visit our PayPal page or our Patreon page at patreon.com slash policyvis.