168: Dashboards: The Inside Track on Data Visualization

ABOUT THIS EPISODE

Contact info:

Jack Tompkins

Website: https://www.pineapplecf.com

LinkedIn: https://www.linkedin.com/in/jack-tompkins

YouTube: https://www.youtube.com/channel/UCalnj5yLU0ZH9y_tVl1J4ng

Bio:

Jack is the owner of Pineapple Consulting Firm, based out of Charlotte, NC and absolutely loves helping businesses become data-driven!

Originally from Connecticut, Jack spent years after college in Corporate America with roles ranging from analyst to partnership manager, but moved down to Charlotte and started his company, Pineapple Consulting Firm.

Now he and his team help businesses become more data-driven by creating KPI (Key Performance Indicator) dashboards with visual representations of their performance along with analytical support to fully tell the story of their business.

This is profit from the inside with Joel Block insights to give your business the inside track. And now here's your host, Joel Block. We have three different sets of data from three different vendors. Why don't they talk to each other? I just want good data that I can read, and it would be even better if I could see it so we can strategize and benefit from our investment in all of this stuff. What can we do? How do we do it? Answer those questions, Jack Tompkins, Jack welcomer the show. Thanks so much, Joel. Good questions. Looking forward to these people who run middle size companies have all this stuff happening around them all the time and the only way they can make sense of it and be competitive is, you know, to look at, you know, their data, in whatever way that is. So why is it that they they buy this thing, that thing, and the benders all telement's going to work and it doesn't work. What's really going on behind the scenes? Yeah, it's all too common. And if it's three different systems of three different vendors or whatever it is, the data very rarely effectively talks to each other and as a super, super common problems. If you're listening and you're thinking, Oh man, I'm in that boat. Don't worry, you're not alone in that boat by any means. But it happens all the time because you don't have something that can clearly identify to get a little bit into the weeds, clear identify a an entry or a row or metric in one system that clearly ties to the other. And so there's a lot of date engineering and Apis and all that fat, fun fancy stuff that can link everything together. Sometimes it can be challenging. Sometimes it can be easy, as in the very simplest terms of orted kind of put it into excel just like a v look up and say, Oh, it was this, now it's this. So there are ways to get things to talk to each other. It takes a little bit of creativity, though. You know, they keep telling us, and I don't know who they is, they keep telling us that the world is getting similar, computers are getting a little easier to use, and you know we should be able to you know, there's Apis and there's that here and there there's all these humer things that are supposed to work together and talk to each other and make our life easier. And every time we turn around seems like it's even get it harder and you got to rely on more and more people for help. So where are we going with all this? Yeah, it's a good point, because technology is supposed to your best friend, right, but I guarantee it's one of the bigger headaches we sort we start all have a love hate doing exactly. Yes, yeah, I do think it's going in the right direction. It's it's never going to be as fast as we want, but Zapp here's a good example. Right, Zapier, however you want to say it, because they are good at linking two systems together and finding some tie so that you can bring multiple sets of data into one place. Is it perfect? No, not by any means. And does it work for every application? No, not at all, but those types of things are becoming much, much more common, and that I mean safe. Here's got. If you just Google's happier. I think there's like five things that are ads that come up before it trying to get you to go with them instead. So there are a lot of those options that are growing. The big question of how do I get the two systems to talk to each other? It's getting solved, although slowly. I do think there's always going to be some sort I don't want to say a manual component to it, but some sort of a human component to it to match the things up or, at the very least, quality check everything all right. So let's let's get past that, because it's you know, it's something they could, you know, pull our stuff out by bar her out. But let's just assume that the systems are talking and everything that's going fine. What are the one of the...

...main things that you know for the clients that you go with, what kind of KPI to they examining? I mean every business has its help. What are some big ones that people are looking at? Yeah, it's a good question, right. And so the business is always from the clients that I work with. The business always decides on their own Kpis because they know the business much better than I do. But I like to chunk them into three different overarching groups, first being financial, second being marketing, third being what I call operational. So within those groups, again, depending on your business spending, on the business model and all that good stuff, it'll change a lot, but there are some very simple things that are common. I mean I'll say revenue and you know, present to budget and stuff like that. For the financial obviously gets a lot more in depth. For that you go down to revenue by department, revenue by employee, client, etc. Some of those breakdown type things. Marketing, marketing effectiveness is the big ones. So Marketing Roy be something like a conversion rate on a specific email campaign. And then operational is all efficiency based. So how quickly are we doing the thing that we need to do and how effective are we doing it? You know, you may or may not know a lot about this. Maybe you will. When I look at a lot of these indicators, most all of them, like all accounting data, is all historical. I like to look at data that's predictive. The way you're going to gain an advantage. I mean those listen, there's some advantage to be gained by being efficient, but in a certain way. You have to be efficient just to stay in the game. That's not even an advantage. That's it. That's just kind of the anti to stay in the game. The advantage is really about, you know, knowing something's going to happen before your competitors do. Have you seen any great Kpis that followed the bucket of the leading indicators or something like that. Yeah, it's a great point, because in those three buckets there's the lagging and the leading indicators. I'm glad you brought it up, Joel. One of the big ones that I've really liked with some clients as the sale cycle, and I don't mean what's the whole industry doing, I mean to get a potential client to a converted client or I mean obviously a very basic example, but something along those lines. How long we measuring that out for and other different points along the way? Can we sell them along the way? Is there a big sale the end? What does that look like? Because that allows you to anticipate or forecast out your your budget and what you want to do financially. Obviously factors into everything else too in terms of planning, but things like that and then cash flow related metrics have been two big ones that I've seen. You know, if if people are looking at their sales cycle and and they kind of have a sense that they're you know, when a person starts doing something like this, then they're more likely to be one of our customers. Is that the kind of thing that a I can pick up on and then start to manage that process in some way. Depends on the AI, but yeah, I think so. It's not something I do myself for a lot of clients, but I you know, just being in the data world that I live in, that does come up a fair amount and hey, I can be pretty freaking smart. Yeah, what Um? So what are the kinds of things in the sale cycle? What are some of the triggers that you see that you know companies are looking at one of the big things that they're really hooking it too. Yeah, so it's starts on the marketing side and then goes to sales typically. Okay, so actually just uninclient call and we're talking about sort of like email optins, and then getting more specific. If they're coming to US and they want newsletter a vers news letter B and they're in industry X AS OPPOSED TO INDUSTRY WHY? Those are, you know, four different paths that they could go down and...

...maybe they're in both industries or maybe they'll on both newslet or something like that. So it kind of starts there and then there are different paths from that. Let Yeah, let me ask if companies are building email list, how many of them are looking at the net growth of those as as a predictor, because to me that is very predictive. Yeah, I haven't dealt one that doesn't deal with it as a predictor, so I would say at this point in my career. A hundred percent of them use it as a predictive and a gay. Yeah, yeah, but, you know, for I don't know. I I'm surrounded by a lot of people who who that comes to them as a surprise and they they are familiar with that, you know. So to me that's that's highly predictive. It is if you're you know. I mean I'd be predictive what's going to happen in two weeks, but it certainly is prettict of what's going to happen in two years. And if your database is not growing and you sell in the your database, then you're going to burn out your database. The database is going to die. That's that's what happened at basis over time. Yes, it just stops being fertile. So I'd like to I'd like to uncover a few more of these because I think these are very exciting. These are the kinds of things that really give clients and listeners of our show and advantage is when they understand you know how to predict their future, because people are really they think it's magic. It's not magic. There are things all around us that are very predictive, that they're like towels, and you know in poker there are towels, but in the real world, you know there are tels and we call those Kpis, you know, and that's a towel. So I'd like to try to scratch around and you know, the funny thing is you probably know a lot of them, but but you kind of take them for granted. They're hard to pull out of the hat when you need it right. Right. It's very true they're all that deer point, that they're all leading to a data driven approach, though, which obviously I'm a huge fan of. So yeah, let's talk about some other ones. So leading indicators. Honestly, I'M gonna go away from financial because all those sales cycle you could you could consider some what financial. It's more operational, but financials, they're really the result of everything else that you do. In my opinion, right, their historical and in most cases there are, they're right, and operational things are about efficiency. My senses that most of these things are outside of our external to us at a lot of cases they're not. Hey, they're not things that are happening in the business that we control. We only control one part of the machine, but the things are happening outside of the machine. You know. Let's think about some of those and I'll need for example, if you are a travel company, you might study luggage, luggage companies, because with luggage company starts telling luggage that probably needs people are getting ready to travel. So I'm looking for those kinds of relationship because that's kind of what I want to train people to think about, is the relationship between something that's unrelated but but very much related, not obviously related but it's not inside their business, that is a predictor of what's going to happen to them in the future. And I just wonder to the to the extent how many people are tracking this kind of stuff. It's a very good point. I mean old's talk topically. For second, gas prices and, as we record, are through the roof and they have been for months at this point. But that probably leads to more bike sales. Right, bicycle sales, or motorcycle for that matter, something that's more fuel efficient. Electric carcialsn't wouldn't you think? But I'm not noticing that behavior is really changing very much. I noticed there's a lot of complaining right but I'm not noticing that people's behavior is changing very much. Are you noticing them in your part of the country? And I haven't really dove into the data, so I feel slightly guilty just giving a gut driven answer. But I know more people are making decisions, at least where I am in North Carolina, to I'll say, a void or at least reduce...

...the amount that they're driving, and so maybe that's public transportation, maybe that's just doing zoom calls instead, kind of thing. I've had those sort of anecdotal conversations. I would love to get some numbers from electric vehicles or bicycle sales or something like that to see if it's actually happening. But I think the Coveyat with that and a larger sense of data is that we're dealing with somewhat of a small sample size because gaspers have been high for a while, but we're not talking five years, we're not talking even a year at this point. They've been slowly increasing then obviously jumped up quite a bit earlier in two thousand and twenty two. But a lot of people need a whole lot of time to make a decision, a big decision like that, to switch from driving to work every day to bicycling to work every day kind of thing. So were small sample size. Yeah, it hasn't been long enough to really this this big spike here in the last thirty or forty five days. It's not long enough to be able to really kind of look at it. But isn't that what big data does? They look at all millions of data points from all different kinds of things and then they draw conclusions. So I don't know. That's a good one, though, you know, is the idea of gas prices and bicycle sales. I mean they're probably, you know, is one goes up, you know the other one goes up. So there they go in the same direction. By sycle sales probably go up as gas prices go up. I don't know, and that's an interesting question. I do know that mass transit has been decimated by the pandemic right and with people staying, you know, working at home, people are not taking mass trans and as much. So we have this hardscape that's built into the into the society and it's not going that great. I mean they're not. People aren't using it right. And that's to your point about the big date of taking four five factors together. Yes, gaspers are up, pandemic still looms and it's someone active and some places still then you've got all the stuff. I did talk with the Pike manufacturer at the beginning of Covid and, I think, to get a very simple parton. I have no idea what the part was, but it was like a four hundred and sixty two day wait to get the part from China or something. So Big Daya comes in and says, okay, we've got gas prices, we've got a pandemic, we've got labor shortage, we've got parts from coming in from China and delays there and all the stuff that goes into somebody purchasing a bicycle. What's the actual und result? I don't know off that on my head, but that is a great big data example, you know, I it's sort of makes you think of when we were kids and we had to do Algebra equations, which I was never very good at, but I remember solving for, you know, for x was never very hard solving for x and Y, and when equation was it was more than twice as hard and if you have three of them in there it almost gets impossible. So when you've got ten or twenty or fifty different variables, you know, and now it's real. Now those algebraic equations that we deal with this kids, we can kind of see that there were kind of real, not real for me. I don't do them, but the guy got maybe guys like you do them. But you know, there's there's all these different premutations and you almost can't figure it out. I mean it's it's remarkable, it is it's it's a fun I'll say it's a fun data problem to have, and I say fun very loosely, knowing that it's something that I would enjoy doing. Most people may not. But the reason I love that for business is because all the numbers in the world can tell you a whole bunch of different things. But that's not to get rid of your gut instinct and that's not to get rid of hey like that's happening, but we just lost three people and we might not be able to staff for that or something like that. So there's there will always be the combination of the sea, sweet leader saying, Hey, this makes sense, but we have this real life thing going on sort of that that gut instinct, if you will, that always balances out the date. I think it's...

...really cool. You know, that opens up another interesting line of reasoning here, and that is, you know, for me, the it's computers become stronger and smarter and people are giving up some of the mundane tasks that they were doing the computers and they got to do more thinking and analysis. A lot of people are not in a position to do that for whatever reason. How are you seeing people raise their own bar like, like, what are people what are companies doing to help them? What are schools doing to help? What are people doing to help? How are we helping people to not be irrelevant in the future? I mean, because we have a whole a lot of people that are moderately educated. I mean they're basically educated, but basic is kind of not good enough anymore. And what are we doing to make sure we don't leave these people out of the cold in the future? Yeah, I know it's a good question, because the whole thing with technology is supposed to raise the average and raise the whatever lowest criteria rights of the those mundane tasks. Your point, let's let technology handle them and then leave the people to do the quote unquote, smarter work. So I think I mean this is very, very topical and my world focused, but visualizing stuff like that, to actually make something that was technological or data or something like that and then turning it into an image that's easy to understand, whether you're a numbers person, a data person or not, that whole visual of whatever it is, and I pick data dashboards because that's what I do, but it makes it feel less like data and that instance, and so most people are visual learners. I like to say that if you put a giant red x in front of somebody, one hundred percent percent of people will understand what that means. Though, so along with the technology in increasing and kind of changing the face of work, there's the technology that's coming on the side of it that makes the now mundane tasks and everything else easier to understand, and I think that way of thinking is starting to be much more commonplace of Hey, what's happening, what's look at the tech or how do the tech work or, in my case, the data, and then what does it actually look like? So we can understand it. You know what, you know, what kind of comes to mind as you're describing that is, if the programmers can make it almost like a compute, like a game, if they can make it a game that you know, as the as the car is chasing it over and ready to hit the wall, that you do something to prevent it from getting the wall, you know, you know, whatever the metaphor is, and then the person knows how to straighten out the process and pushes a certain number of buttons to get the car back on the road the way it's supposed to go, and then the machine keeps going. I mean if they can make it, you know, like that something that people can relate to, because I'm very concerned that. I'm not talking about uneducated people. I'm talking about people who just have a basic, maybe a high school education and and they don't have high tech skills or they don't have other kinds of professional skills, and I'm very concerned that these people who are, you know, working on an assembly line of whatever they're doing, are going to get passed by. I'm also concerned, by the way, that companies who don't raise the bar themself, you know Amazon to set the bar for consumer products pretty high and we have to do that. You know, we have to set the bar high and we have to you know, we have to raise the bar for each of our companies. Yeah, no, I think you're exactly right and it's I talked with some HR folks a decent amount, and I mean it gets into all sorts of that layer pool and we won't get too deep into that, certainly not my eric of expertise, but it is a it's a very interesting thing and what I hear is it comes down a lot to drive. So if if they're if the employee or the person...

...or whoever is really great on the assembly line, they could be perfectly happy doing that. If they have the drive to learn the additional thing to bring them to the manager position, great, if they want to do two things on the assemble like I don't know what it is, but it comes down to that level of hunger. And I know a lot of folks are. They care less about what degree they have and more what experience they have. So at some point that becomes more important as you get a little older, you know. So let's you know, I mean lessen the what I think the connection is of this whole education discussion, which I know is not in your area of expertise but we're bleeds back in. is well, your visualizing data. Visualizing data is easier for some people, not all people. Some people learn different ways. But you know, I imagine that there are things that people in your world could do to help people that are not necessarily trained in the technlogy to be able to use the technology better. So what kinds of tools are you seeing in there are, yeah, it's so there's there's tools that actually make the dashboards. And I'll say make the dashboards in two different kind of size of my mouth. One is the actual person making the dashboard. So it it's a very creative process, believe it or not, even though it's completely data driven, it's very creative process to make something feel not like data. So anybody can pick it up and say, oh, cool, giant read down Arrow. I guess that section that I'm looking at did bad right. And the actual tools that help make the DASHBOARDS, if you're just starting out, excels a great place to start and then most people go to web based. So the big names are sort of tableaux and POWERBI. Google has a version. It's called Google data studio that I use quite a bit. There is looker. There's a bunch of those web based platforms out there. All of them are similar in function, but not all of them are similar in usability. So there's a lot of I think, like data analytics and data visual zation actually be coming classes that you can take at colleges. Or you to me, or however you say that one the online learning platform. There's a lot of those out there that are teaching folks and even Youtube Channels of here. How do you make this type of visual from data in this specific software? Yeah, are you? Do you are? Do you deal with well that have a hard time reading these DASHBOARDS, even executives of companies? I mean, they're not all Harvard educated people. I mean, you know I mean all this if I'm not over educated. I mean, you know, we all kind of get through our day or whatever it is we do. But do you do find that some people have a hard time and it just doesn't work for them and they need to use it? You find the use the data in a different way? It's an interesting question because the short answer is not really, because it's on the person who makes the dashboard to make it usable for the end user, for the sea sweet executive, for whoever it is, and there's generally a conversation about that and some visuals work better for some people. There's actually, weirdly, a big discussion and the data community about pie charts and well or not their effective at all. People have different opinions on that. So things as nitty gritty as that, it all comes down to who is the dashboard for? Who is the visual for? So they can make it the creator can make it understandable to the end user. Let's talk. Let's talk about the the the I've been on the receiving end of some of these dashboards. I sit on a board of directors and every month we would get a dashboard from the executive director and I have to tell you, as somebody who's background is accounting, a CPA by training, I think the dashboard covered up most of the details that would allow more sophisticated reader to notice a problem, and I think it...

...was. You know that you can use these tools to highlight problems and two shroud problems, and I think you know a lot of users are not aware of that and they really need to be very careful. So there you know, there has to be a claverer process. You can't just have one person design the thing and say here's the day that you're going to get. You know how the companies go through a process of figuring out what data is the right data to share with their with their audiences. Very good question. Yes, there's typically a few different layers. So there's because, to your point, you can hide a lot with dashboards and you can also show a lot with dashboards. So a few different layers. They're the first one, I'll call like the top one, is generally the sea sweet level. It's quick glance. I've got ten seconds before my next meeting. Let me pull up a dashboard. Boom, boom, boom. Done. I get the overall story and then you get into different departments or different levels from there. So the accountant or the CFO or somebody the finance organization well obviously have a bunch more financial details that they probably don't really care about marketing metrics at all, but they'll get into the nitty gritty of the income statement and that'll still be displayed visually, still be displayed. It was easy to read and easy to translate from the account to the marketing person. Or whoever else it is. On the flip side, on the marketing side, they'll have a very specific dashboard for them and it kind of goes like that. So each department will have its own main views, main things that they want to look at, getting all the way down to ace like and from a marketing perspective, a specific campaign, specific time of day that the email sent or something like that. Obviously the EEO probably doesn't care that much about that. So the more you go down that layer path, the more specific to dashboard. Is still always a visually appealing still always easy to read and translate, though. How many? How many people are using excel to build these kinds of models? I mean, you know, I mean maybe they have a fantasy computer system, but but the pie charts and graphs are not that bad at excel, I mean does a pretty good job. So how many people are using it? Yeah, I mean if my client base, I think about thirty percent, maybe thirty five percent, are still in excel. Even pretty good sized companies are using excel. Yeah, Yep, all the time. And get back and getting back to the original question of how do we get the two day too systems to talk to each other? The ultimate failsafe is dump everything into excel and build it in there. Yeah, that's listen, it works. It's not glamorous, it's not it's not the most, you know, perfect way to do it, but it's certainly worse and it very much does. I am an excel junkie. I absolutely love Excel. That is my home base for everything and sometimes it does make sense and you can make some very, very pretty looking dashboards and excel probably not going to be web based or anything like that, and have some of the sophistication or automation that others do. But at the end of the day it is very difficult to get rid of Excel. Yeah, yeah, well, especially we have multiple, multiple systems, and I guess if you have a single system, the reason people buy multiple systems because so companies just don't make things that work in every single department or solve all the different problems, so they're forced to go with different vendors for different things. And the computer world is still pretty complicated. It hasn't really simplified as much as we need it to, has it? No, not at all. The more sophisticated it gets, the more complicated it gets, and it's in theory simpler, but it just it doesn't always work that way. Yeah, they're theory and practice. I have not yet collided in this particular case. That is a very good way to say it. Yes, yeah, that's for sure. So what do you what do you think is the feature of data? I mean, where's this industry going? It is becoming bigger and bigger. I so. I started my coming about two years ago and I had to for the most part, I had...

...to explain, Hey, this is what a data dashboard is. It's just wasn't a thing in the small to medium sized business world, at least not a mainstream thing. Now, two years later, people come to me and say, Hey, can I get a dashboard that does X, Y and Z and links to these sources? And that's not because they know me, it's because that whole world is just growing and involving and there's much more education out there. So we're we're people mostly learning about it magazines, I mean where these people mostly the conferences where they were to hear and about it. I think it's more just as you scroll through whatever news feed is your favorite, there's going to be a data topic in there. Even if you're not like checking all the vodkas on Google. So it learns what you want and data is not in there, it will find its way in there. Covid actually did a lot in terms of getting data, getting people to understand data, because there's I mean there's always the question of okay, is this the right data? What context does this have? Can we do more with it? Whereas this from what timeframe? All this other stuff that people really needed to know, and so that actually helped a lot with the overall education level of data. Yeah, well, covid really it really change a lot of things. I mean that, you know, many of us were probably using dashboards a long time ago, but covid accelerated it. Many of US reason zoom year four years ago, a long time ago, but covid really accelerated it and normalized it and and maybe as things become more more widespreadly become more normalized. Yeah, I think that's exactly right. The more common place it is, easier it is to get started, the easier is to understand and all all good stuff. Well, listen, you know, the promise of our show is delivered the inside track on you know, whatever it is the best, the fastest, smartest way to get thing done and and you've really delivered on that. As far as data visualization, you know this whole concept of dashboards in the rest and whenever somebody lives up to the promise of the show, we always refer to that person as an advantage player, and you've lived up to the promise and that makes you an advantage players. So thank you very much for sharing what you know, for telling our Audia is what it is. Will have your information, your contacting Phoe in the show notes and we appreciate being part of the show. Thanks so much. Shows as great as a super fun conversation. Excellent. You've been listening to profit from the inside with Joe Block for more insights and to learn more. Is it Joel Blockcom? How about a shout out and a huge thanks to our podcast show producer David Wolf and the team at Auto Vida Studios. Profit from the inside wouldn't be possible without these wonderful professionals. To learn more or to find out how you can launch and produce your own podcast show, reach out to wwwacom. That's Audi v IACOM.

In-Stream Audio Search

NEW

Search across all episodes within this podcast

Episodes (167)