How FP&A Teams can Enhance Visuals, and Improve Dashboards Practical Tips from Zebra BI CEO Andrej Lapajne
In this episode of FP&A Tomorrow, host Paul Barnhurst welcomes Andrej Lapajne, the CEO and founder of Zebra BI. Andrej shares his thoughts on the evolving role of data visualization in financial planning and analysis, the importance of clear communication through standardized visuals, and how automation is transforming the way we analyze and present financial data. Later in the episode, Paul and Andrej discuss the challenges of data modeling, how AI is shaping business intelligence, and why effective data storytelling is crucial for making impactful business decisions.
Andrej Lapajne is the CEO and founder of Zebra BI, a company dedicated to revolutionizing the way businesses communicate financial insights. With over 20 years of experience in business intelligence and data visualization, Andrej has helped organizations across industries implement better reporting systems. He is a passionate advocate for the International Business Communication Standards (IBCS), a methodology he helped popularize to improve data reporting and visualization.
Expect to Learn:
Why is consistent, clear communication in data visualization vital for FP&A professionals?
The key skills FP&A professionals need to master include data modeling and communication.
How Zebra BI helps businesses generate actionable insights with ease.
Andrej's methodology for data visualization and the importance of standardized charting in business reporting.Key advice on mastering data modeling and communication skills for finance professionals
Here are a few quotes from the episode:
“Effective communication is the key to FP&A. You can have all the data, but if you can’t communicate the insights, it’s wasted.” - Andrej Lapajne
“AI is transforming the way we consume analytics and freeing up time for more strategic decision-making.” - Andrej Lapajne
“Effective communication is the key to FP&A. You can have all the data, but if you can’t communicate the insights, it’s wasted.” - Andrej Lapajne
Andrej Lapajne shared a clear and insightful perspective on the future of data visualization in financial planning and analysis. He emphasized the need for standardized communication, the importance of clean data, and the power of automation in transforming analytics. Together with Paul Barnhurst, this episode highlights the critical role of FP&A professionals in driving business decisions and how the integration of effective data visualization and modern technology will shape the future of the profession.
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In Today’s Episode
[01:51] - Andrej’s Background
[02:38] - What Great Data Visualization Looks Like
[08:34] - Getting Into Data Visualization
[13:15] - Founding Zebra BI
[17:50] - IBCS: The Method Behind the Charts
[26:14] - Key Elements of a Compelling Visual
[34:54] - The Impact of AI on Analytics
[40:18] - AI Needs Clean Data
[45:27] - Essential FP&A Skills for Success
[52:29] - Last Question & Episode wrap-up
Full Show Transcript
[00:01:06] Host: Paul Barnhurst: Hello everyone. Welcome to FP&A Tomorrow. I am your host, Paul Barnhurst, the FP&A Guy, and this is a show where we delve into the world of financial planning and analysis, examining its current state and prospects. Each week, we're joined by thought leaders, industry experts, and practitioners who share their insights and experiences, helping us navigate today's complexities and tomorrow's uncertainties. This week, I'm thrilled to have with me a data visualization expert. We have Andrej from Zebra BI. Andrej, welcome to the show.
[00:02:12] Guest: Andrej Lapajne: Thanks for having me, Paul.
[00:02:14] Host: Paul Barnhurst: Yeah, really excited to have you. I know we got to chat beforehand, and I'm excited to share some of your knowledge with our audience. So let me give a quick background about Andrej. Andrej is the CEO and founder of Zebra BI. He brings more than 20 years of experience in business intelligence and software development. Before founding Zebra BI, he worked as a consultant and implemented reporting systems in BI dashboards across industries from pharma, telco and retail to insurance, banking, energy and other industries. He's also a Microsoft MVP and an international speaker. So again, we're thrilled to have you. I love the background. Did you ever think you'd be on an FP&A podcast?
[00:03:03] Guest: Andrej Lapajne: Very happy for the opportunity. I'm very excited. Thanks for having me again.
[00:03:07] Host: Paul Barnhurst: Thrilled to have you. I mean, I've known a zebra bi for several years, and I've worked with your team before on a project and so excited to get your perspective. We're going to talk about a lot of data visualization. Before I get that, I want to ask your perspective: what does great look like from your perspective? You could talk from your consulting experience as a CEO who has to do planning. You could take that wherever you want. I just love to get your thoughts on that.
[00:03:33] Guest: Andrej Lapajne: Okay. Let's start from the consulting experience, right. Because I was implementing basically a system for planning, reporting and analysis and so on. FP&A is actually an active partner to the management, the leadership, and is actively crafting and proposing 20 years ago, 30 years ago. And it's still true now. What does it actually mean today versus 30 years ago? In order to really do it well or excellent, you need to close the loop of the cycle of data insights actions. Right. And this looks very different today compared to, you know, ten years ago, 20 years ago, 30 years ago. Because you need to automate the whole path from data to insights and then from insights to actions. There's AI that's transforming it. You know, uh, in the last few years. And, you know, this trend will, of course, continue using AI even in the form of AI agents already, at least in certain parts of it, and being much, much more productive. And, and, uh, you know, making sure you integrate all the tools, uh, the volume of data is just much, much more than, you know, you had like ten years, 20 years ago, multiple data sources, managing all that, modeling all that, making sure all the tools work for you and then having extremely good communication, because all this automation actually allows you to focus this human factor more into really understanding and communicating right with your partners, which is always management leadership. You know, your board, whoever you're partnering with. In short, that would be my take.
[00:05:17] Host: Paul Barnhurst: Thank you for that answer, I appreciate it. I really liked how you mentioned data insights action. I think that's a very simple framework when it comes to data. And you said automate as much as you can, right? The volume of data we're dealing with today compared to five years ago. Ten 2030. There's just no comparison. I was talking at lunch with an FP&A guy. He mentioned he uses Python and, you know, working with large data sets, and sometimes he's dealing with billions of rows because he's looking at transactions. Works for banks, you know, and I can't even imagine, you know, know, ten, 20 years ago dealing with billions of records. But now there are a lot of places where that's the case. So definitely a lot of growth. And we have to be able to summarize that down and provide actionable insights, I appreciate that. All right. So now I want to ask a fun question. I haven't asked a guest this one before. I am confident you'll have a good story for us. Tell me about the worst visual you have seen in your career. What made it so bad?
[00:06:19] Guest: Andrej Lapajne: I've been in business intelligence now for close to 30 years actually, so I've seen everything. I guess like in the 90s when I started, it was basically like the charts in Excel. Very old versions of Excel and it was all 3D. At that point, 3D was big, right?
[00:06:35] Host: Paul Barnhurst: I was guilty of that early 2000, early 2000.
[00:06:40] Guest: Andrej Lapajne: Right. You always go for the cool stuff, you know? There was not a lot of visualization, right? I mean, the reporting back then was just numbers. You know, it was spreadsheets, tables and, you know, printed reports or 50 pages of text and tables. So it was really the lack of visualization and some like, really like the very decorative attempts and so on. So at that point I saw like the 3D charts and so on, of course, but pie charts, it's like the constant enemy. Good visual communication. Still true today. So I'm still fighting those biases even today, right? I mean, the situation I think actually did not change that much if you just like think of it like what you typically if you see a dashboard or a modern report right now with any kind of tool like, like, you know, probably a tableau, take any modern BI tool today or even Excel today, right? It's still the same chart. It's still like your column charts, your bar charts, you know, your pies and so on. So you rarely see waterfall charts. Do you see a chart that would, you know, explain your variance to plan or like really important things in Fp&a you don't you still have basically the same toolset. Uh, even though it's like, you know, now, like 30 years later, uh, it's more or less the same situation.
[00:07:56] Guest: Andrej Lapajne: Very colorful charts. To really try to answer your question. I don't think it's really about like, one chart or the worst chart. What really isn't working is that we have no consistency. We have no language. Right? If you imagine you're like, you know, in a company, a board member or you know, your, your manager or something, he's getting different charts from different people, like, you know, from FP&A and from finance. They are getting like, you know, those huge tables, very detailed. So it's basically just tables, maybe with some highlighting. And from marketing they get very colorful, you know, pie charts and stuff. And maybe then you have something else, uh, sales reporting done in a specific tool. And it looks like the default, the design is basically the default design of the tool. So basically you don't manage the language and the communication through the visualization. It's not unified. Yeah. It's just determined by basically the tool you're using or, you know, the preference of the person who is creating it. Oh, I like these colors. You know, I'll go for blue here. I just like it and so on. But there's no language.
[00:09:02] Host: Paul Barnhurst: It's disjointed, so to speak, which you often see with modeling. You know, in investment banking they do a better job of, hey, here's the design standards. We'll talk more about that later. But I would love to ask, when you and I chatted, you told me the story about how you got into data visualization. There was a course you attended in Switzerland. Can you tell our audience that story?
[00:09:22] Guest: Andrej Lapajne: I was working for a consulting company, uh, implementing systems data modeling and stuff. And, you know, those are projects like, you know, one year of ETL, you know, connecting data, modeling and so on. And then after the whole project was done and everything was installed and so on, you know, we presented that to the end users like the management and so on. You know, the end result. It just doesn't reflect all the work and all the investment, right? The managers get they are not actually to the extent that it's, you know, would be possible even back then. Um, but they're not getting the value out of it. Why? Because of the poor presentation of those tables. And it's like, oh, it was like a lot of clicking to get to something. And it was too interactive for the management or it was too, too detailed. It was not explaining things. So people were just like looking at one table in row number ten, because they knew that this is my data there, and they just did not. It could not drill down. They did not really get the insight and they could not plan actions. It was really not actionable. And since I had some, um, uh, you know, preferences like visual design and so on because I actually studied information science, but in parallel I started painting. Right. So I was thinking like, oh, I need a better visual presentation here and so on.
[00:10:45] Guest: Andrej Lapajne: So I started studying, uh, data visualization. So at that point, I, you know, I discovered, like, the world of Edward Tufte and, you know, Jack Burton and, you know, other gurus of data visualization. I studied everything on my own in this company. And then I heard about this course in Switzerland. A very interesting thing. But it was all in German. You know, I could speak some German and or understand it, but not really. Uh, but it was so compelling, right? Because everything that I saw there made so much sense. Like all the variances, like, neatly visualized in, like, red and green, everything was so, you know, it looked like, wow, that's a completely different approach. And I told my boss, I said to my boss, look, um, this is really interesting. Like, we should just implement this methodology, this in our projects. And he said, well, you know, visualization, that's that it doesn't really have the added value and so on. You know, our goal is really to make sure that the data is correct and we deliver it. And you know, people have it, you know, everybody's fine with tables and so on. But I was so compelled. I said, well, all right then, I'll just take like two days off annual leave. Uh, for two days. I'll pay for the course, uh, myself.
[00:11:53] Guest: Andrej Lapajne: So I hopped on a train, went to, uh, Zurich, paid for everything by myself out of my salary. And it was quite expensive in Switzerland, you can imagine, I'm sure. And it was in German. Uh, but it made so much sense. I loved the system, I learned it, and then I got to the professor who was running the course. His name was Doctor Rolf, he heard, and he basically just changed my life. He was a professor of FP&A in Germany, and he had his own system of visualizing, you know, what would be ideal communication in business reporting and especially in FP&A And, uh, it just makes so much sense to me. So when I came back, I just handed in my resignation and started my own consulting company.Out of sheer enthusiasm, I had nothing. I had no clients, no plan, nothing. But I just knew, like, I want to do this. Like I want to work with this system. I want to take it further. I want to, you know, start implementing it and so on. Then I started, uh, teaching the concept and implementing it, companies in the region, mostly in Europe, uh, across various industries and so on. And everybody loved it. It made so much sense. And then sort of that totally changed my life.
[00:13:18] Host: Paul Barnhurst: Now I'm going to guess you must have been still young. And were you single when you put in your notice and started a business with no plans?
[00:13:24] Guest: Andrej Lapajne: Yes, I was.
[00:13:26] Host: Paul Barnhurst: Sleep makes it a little easier.
[00:13:29] Host: Paul Barnhurst: I love the courage and I'm sure there was some moments afterwards I know when I started this, you're like, what was I thinking? Is this a good idea? But you keep pushing through and you try to stay positive and it's amazing what you've accomplished.
[00:13:42] Guest: Andrej Lapajne: This is really the right thing, and then you just do it.
[00:13:45] Host: Paul Barnhurst: Yeah. No, many times when I pulled the trigger on my own business.
[00:13:49] Guest: Andrej Lapajne: A strong, strong feeling. I just went for it. And yeah, luckily.
[00:13:52] Host: Paul Barnhurst: Love that. I love the enthusiasm. So you start with.
[00:13:56] Host: Paul Barnhurst: Your own consulting. And then in 2014 you started zebra BI. So a little over ten years now for the company. What made you decide to start a software company around visualization? You're doing all the consulting, like kind of how zebra BI came about?
[00:14:09] Guest: Andrej Lapajne: But it was again, maybe quite an obvious, obvious thing because I was doing my, my consulting for some seven years, uh, working with all those clients. I was helping clients implement reporting systems. At that point, I really focused on reporting and not not planning anymore, but mostly reporting dashboards, um, you know, visual analysis and so on. I was just using as a consultant every tool on the market. Uh, at that point that was like 80% Excel, but also other tools like, you know, Clarity. At that point. I was one of the first actual resellers of Tableau in my region and things like that. So I was trying different tools, but whatever tool I took, I just could not do what I really wanted. Like, you know, I could not bring this whole methodology, uh, I could not implement it in any tool, you know, however, you know, good. It was not providing the features and so on. So, you know, I was doing a hacking of visualization in Excel, like working with Excel charts. Like I still know every little hack in Excel charts, twisting and bending and workarounds and strange things and so on. Uh, and we implemented that. But I was always thinking, oh, if I just had a tool like, you know, okay, this company has, I don't know, 12 business units and you know, and I would love to have the plan and actuals and all that, you know, just drop this data into this tool.
[00:15:32] Guest: Andrej Lapajne: Just click one button and it would like, it would present like uh, it would create like 12 waterfall Charts. All scales so that we understand what's the impact and how big is each unit and what's the growth rate. And I would have all the growth rates and variances to plan and so on like this with one click. Right. That would be really cool because this took like, you know, like maybe one month to set up everything and band all those tools. Yeah. And then at some point I started fiddling around with Excel. I started the VBA at that point. Uh, so I did my, my little prototype that actually did that, like, you know, you clicked and then it would like insert like 12 charts or something and then, you know, turn them into waterfall charts and correct all the labels and calculate everything and like tons of hacks to make it work. And I had this prototype in a conference in Germany and everybody was, whoa, you know, so we would love to have this.
[00:16:29] Guest: Andrej Lapajne: Right. And so I just, I just programmed something here and it's basically just a VDI script. Right. And but, you know, it just gave me, uh, this. I just got this feedback like, all right, it's something people would need. When I returned from that conference, it was like, maybe it's time I tried to just build this product. Um, so yeah, again, I just went for it. A job post, uh, for a programmer because I knew, okay, I need a programmer. Right? Uh, and that was in 2013, and we started like, we created a beta version. We tested it with some clients, um, and everybody loved it. And, you know, we said, all right, that's it. Now we are doing this right. And then we started the company. I just transitioned from consulting work doing this manually to actually building the product. Yeah. Let people use the product to do this for them. And this is how I started. And our first product was actually this add in for Excel. And then later on, of course it developed into products for power BI. And now we even have an AI version of it and so on. But that's how we started.
[00:17:35] Host: Paul Barnhurst: Not surprised. I started with Excel. That's, uh, or just about everybody starts their data visualization journey, right? You know, anyone who works with finance, we all start Excel. Now. You see a lot more power BI. You still see some Tableau. I remember in 2010 helping implement MicroStrategy.
[00:17:52] Guest: Andrej Lapajne: It was one of the tools, the MicroStrategy Business Objects Proclarity reporting service reports. But you know, when you saw what is actually in production in FP&A, it was always excellent. So no matter what the tool was, you know, the FP&A guys, they excelled. And that's actually what got presented. Um, and it's still like that in, in, you know, in the market.
[00:18:19] Host: Paul Barnhurst: We.
[00:18:19] Host: Paul Barnhurst: Like to say you'll have to pry it out of our cold dead hands.
[00:18:23] Host: Paul Barnhurst: Yeah. Yeah.
[00:18:24] Guest: Andrej Lapajne: Exactly. Yeah. And you.
[00:18:25] Host: Paul Barnhurst: See, actually, we.
[00:18:26] Host: Paul Barnhurst: Definitely love our spreadsheets and love Excel. So I'd like to talk a little bit about how I know you've built a methodology you use with your different charts and graphs. Very much a structure to all of them, so they're very similar. Can you talk a little bit about the methodology of why you do that? The benefits. Just talk. I'd love to talk a little bit about that.
[00:18:48] Guest: Andrej Lapajne: The methodology actually has a name. It is called International Business Communication Standards.
[00:18:55] Host: Paul Barnhurst: Yep.
[00:18:56] Host: Paul Barnhurst: Ibcs.
[00:18:57] Guest: Andrej Lapajne: Ibcs. Exactly. It's a tongue twister. But the thing that I learned in this course right at that point, uh, it was still called, like, it was just called success rules. Um, and it's an invention of Doctor Rolfe, right? And he always wanted to actually, uh, standardize it because he believed so firmly that, you know, every company in the world should actually report with those types of charts, colors and shapes and so on. So that's now, uh, well established, actually standard, uh, also well documented and so on. And right now it's actually in the process of getting certified by ISO. if this will be successful, it will actually become an ISO standard. It's basically a language. It's a language that defines, you know, how you should present certain types of data, like, I don't know, um, that, you know, for, for time trends, uh, you know, you should use charts with like, horizontal axis. So time should, uh, should run from left to right. And then if you have structural analysis, uh, then, you know, your chart should have a vertical axis and then you can merge your chart into tables and so on. And uh, then it has some rules. How do your actuals look versus your plan? Right. So like a plan is like it only has an outline and then uh, actuals are like a column that has a full color. So it's like you have an empty planet and you need to fill it up with your actuals. Right. And then you have variances which are red and green, and then you have absolute variance. Relative variance. Everything has its own shape. So it's basically you assign your code certain categories in FP&A, to certain shapes and colors. And it's consistent. So it's basically in the end it's a language. It's like we can communicate now because we both speak English. Right. We are not as good as you obviously, but you know, we can.
[00:20:54] Host: Paul Barnhurst: Exchange our ideas and so on, especially for.
[00:20:56] Host: Paul Barnhurst: Not being your first language.
[00:20:58] Host: Paul Barnhurst: Yeah.
[00:20:58] Guest: Andrej Lapajne: Exactly. So I mean, it would be much harder if I suddenly started talking in Slovene, which is my native language, or German or whatever. Right. Um, and this is exactly what we have in, inside the company, you know, so like, like, you know, there's one language, um, that FP&A is using or accounting or finance and then one language the marketing is using. And then, you know, at the end you have the same person, you know, CFO, whoever it is, like, you know, just getting reports written in those different languages so that the whole idea is actually simple. Just use one language when you communicate business information. And it's not just charting. It's also like, you know, okay, how do you write? What kind of labels and are you using the titles and so on. So it's about. Quantitative and qualitative aspects of communication bring everything together and use it to make sure that your reports are much more understandable by everyone.
[00:21:00]Host: Paul Barnhurst: FP&A guy here today, I want to talk about the certified corporate FP&A professional, or the FPAC, from the Association for Financial Professionals. I am often asked what makes the FPAC unique. And I respond by saying it's the only FP&A program that is a credential versus a training program with a certificate. Three key differences include: The FPAC requires work experience to enrol in the program two. The FPAC exam is closed-book and administered at a testing center. Three to keep your credential current, you have to do continuing education hours. I went through the program a few years ago, and it was a great learning experience. Not only did I learn a lot studying for the exam, but I am grateful for my membership in AFP for the networking opportunities and the opportunity I have to continue to learn through events and resources provided by AFP. If you're serious about building your career in FP&A and want an FP&A credential, I recommend looking into the FPAC program. Head on over to my website to learn more. And if you sign up for the program, don't forget to use my code to receive a discount. Those codes are the TheFPAGuy-FPAC – Exam $150 discount, and TheFPAGuy-FPACEPP – Exam prep platform $100 discount. Again, head on over to my website for those codes and to learn more.
[00:21:56] Host: Paul Barnhurst: Thank you for sharing that. I am a little familiar with Ibcs. I've heard Doctor Jurgen fast present a few times. I know he's one of their consultants. I've chatted with him and I know I've seen that in Zebra BI. I think I've seen some other tools. I think it might be that Lumel or Inforiver have a lot of graphs that follow the standards. I'm sure there's some others, but what do you think it will take? Because in general, I mean, I didn't know about it, the standards or any of that. I started my own business and started talking to different software vendors. I'd never heard of it in my career, nor have I say I've ever really used it. I've seen it a little bit. What is it going to take to get general adoption? Like, why do you think it's still very much everybody who does their own thing? Kind of a wild West, so to speak.
[00:22:43] Guest: Andrej Lapajne: The thing is, I mean, it started in Germany. So basically it originated in Germany. And like it started spreading in German speaking countries like the dark region, Germany, Switzerland, Austria and so on. This is really the home territory of ibex. But then once you know, we started building all those tools and so on, then, you know, other people started using it. Many other companies or users don't even know that, okay, it's ibex and so on. They just like the fact that, you know, everything is so clearly presented and it makes sense and it's easy to produce, um, by using the tools. So basically the tools are really the drivers for, for, for spreading the standard around. So right now, um, there are lots of companies also in the US, uh, using this standard, uh, also using our tools. So for example, zebra by key market is actually the largest number of, uh, are actually in, in the US followed by Germany and Switzerland, but it's actually North America now. Now it's um, it's actually our core market. Um, so it's spreading.
[00:23:55] Guest: Andrej Lapajne: But of course, slowly, you need to get used to the idea. And, you know, one and the other thing is, uh, the FP&A people are not always the guys that actually decide. And which is a shame, right? Um, because, you know, many times it's just the decision. All right. Yeah, we're using those tools and this is how it's done and so on. And, you know, if FP&A people are like more, more, more active and proactive and, uh, suggest some tools or solutions or methodologies and so on. Then it starts spreading, and at least they, uh, they transformed their reports intO. Uh, and so on. And then slowly it creeps into other departments and so on. So we now have, you know, uh, companies like, um, you know, big companies like, even even Microsoft is our client, and he uses this on top of power BI, but also like other other companies like Nestle and a lot of corporate clients are are switching to to to this. But it takes some time. There's always some resistance to change. Uh uh everywhere.
[00:25:09] Host: Paul Barnhurst: Makes sense. I mean, she'll be interesting to watch kind of how it spreads. And if we get to that point where we kind of have that adopted standard. But I want to step back and just talk about visuals in general. In your mind, what's the key? I mean, what are the key elements or things someone should think about. If they're trying to create a compelling visual that helps tell the story. You know, what kind of advice would you give to somebody?
[00:25:32] Guest: Andrej Lapajne: First of all, I would say, um, I would replace that with actionable, uh, that's my favorite one. That's my religion. Right. How do you present certain insights? Uh, in a way that is actually that's really actionable, uh, that, you know, you show it in a meeting and immediately. All right. Okay. This is interesting. What's this? And, you know, we understand it and. Okay, what's the action? Because that's the only point where you actually get a return on your investment from data and all the tools, right? When you make an action and then you improve your business, there are a couple of rules that are actually recommended by Ibcs. So um, number one would be to visualize your variances. Now if you're talking about FP&A, I would say that's number one. Like just visualize your variances because, you know, variance to plan variance to previous year to forecast and so on. That's, you know, the, the, the, the primary, uh, basically data category that you work with, this is how you steer your business and so on. So first make it really clear. Um, so that's number one. So make sure that your charts, your visuals actually show the variances, not just like absolute values.
[00:26:41] Guest: Andrej Lapajne: Oh, this is the plan. This is the actual right. But actually visualize that gap. Right. Either um you know green if it's positive. Red if it's negative. So it's very very simple. Of course you need special charts for that. You know you need variance charts. You need integrated variance charts, you need waterfall charts and so on. Right. Number two, label those charts uh, efficiently so that you know everybody the stuff and understand what those data categories actually represent. Number three would be to merge visuals with qualitative information like, you know, short annotations or comments and so on. Just integrate everything, not just okay, this is a chart and it's a perfect chart. But you know what's the story, right? I mean, you see it from the chart, but you know, why is something red and green and so on. You know, you just write it as a comment. Right? So just merge this together. And I could go on and on and on. But the key part. So like just take the color away and make sure that you visualize your variances and you explain your variances.
[00:28:57] Guest: Andrej Lapajne: Yeah, everybody likes pretty colors. And it's a common objection. I mean, now we are talking and so on. But if you actually saw one, you know, a typical chart or a dashboard, very colorful and so on. Oh yeah, I like it. I mean, I like it too, right? Nice colors and looks are really colorful and so on. But then you ask quick questions like, I actually have a four question test. It's actually effective or not, right? And the first very simple question would be: is my performance good or bad? Let's say it's a sales dashboard, lots of colorful charts and so on. And me as a sales manager, you know, I need to understand. All right. You know, is my performance now good or bad? Right. It's like I just need to see this immediately, like in under one second and not like, you know, yellow here and so on. Looks pretty. But, you know, I really want to understand what's going on. Like, you know, is my sales growing or not? How is it compared to the plan and why and so on. Right. So what is my performance? And then the next question, you know how much is right. So if we are like okay above the plan under under the plan exactly what's going on like.
[00:30:05] Guest: Andrej Lapajne: And then the third question would be why? Hmm. Right. Why is the key question? Okay. Why do we have like, you know, 11%? Why are we 11% behind in this business unit or in this product line or whatever this market or whatever the breakdown is. So I need the answer why. So and again you know pretty colors will not help you there. Right. What will help you is, you know, another breakdown and another breakdown of variance inside that data category. So, you know, and then the fourth question is what are we going to do about it. Which is the ultimate actual goal of FP&A. Or when you actually recommend to the management, what are we going to do about it? And this is like the qualitative part that, you know, you can add to the visualization in the form of a short comment or something. All right. You know this, this is you know, because of this and you know, this is what we recommend we should do, right? When you actually redesign your pretty, pretty charts with pretty colors into this form, uh, which maybe looks a little bit boring from the design perspective in the beginning, but once you see it, if you're the right person actually interested in in those insights, right, you would immediately, immediately prefer the second part because you know you would.
[00:31:32] Guest: Andrej Lapajne: And many times I had situations where we did this, we did the redesign. People for the first time saw the data for the first time and they could not believe me. It's exactly the same data, right? We only redesigned it in this format. But now you see, now you see. All right. You know, you know, the focus should be here. You know that there's negative growth here because of this and so on. And this data was already in the previous pretty chart. Everybody liked it and so on. But now they actually had a discussion about what's going on there. And we didn't know it. And they could not believe me that it was actually in their previous version of the report. In the end, the function, I think, Uh, wings over, uh, the sense of, you know, what is what is nice. That's like it's totally personal, you know, the gustibus .We don't want to. Don't discuss the taste. Right? It's really about taste. What? What is pretty. In the end, it's pretty. You know, it's not like when you really learn something and so on. That's the beauty of it. You. You know it.
[00:32:10] Host: Paul Barnhurst: And now a brief message from our sponsor, AFP. You know as well as I do, the world of finance is moving fast, and if you want to stay ahead, you need real insights. That’s exactly what you’ll find at the Association for Financial Professionals’ FP&A Forum, an immersive, three-day event built for financial professionals, by financial professionals. Last year, 96% of attendees joined to sharpen their FP&A processes, strategies, and stay on top of emerging trends. And this year, it’s even bigger. Experience unbiased, sales-free educational sessions, collaborate in 10 dynamic roundtables, test out the latest FP&A tools, and hear from powerful keynote speakers, tackling real-world challenges head-on. Plus, you’ll be networking with more than 500 of your peers, all in Indianapolis, March 23 through 25. So if you want high-impact insights without the spin, this is the place. Learn more at financialprofessionals.org.
[00:32:39] Host: Paul Barnhurst: It's like you said earlier, right? You want to go from data to insight to actions. Lots of color doesn't drive actions. You know, I kind of said jokingly, but I like my colors. I'm really big when I teach. People only add color when there's a deliberate purpose to it. Don't just add color for the sake of color. Color is like contrast. Eyes are going to be immediately drawn to it, and if they don't take a message away, you're just adding cognitive load to the brain. I always teach them to ruthlessly reduce clutter and everything you add. If it doesn't add a purpose, you've just made it harder for the brain to interpret the graph.
[00:33:17] Host: Paul Barnhurst: Exactly how I try to.
[00:33:19] Host: Paul Barnhurst: Look at everything. But I love your four points here. I'd never heard it that way. The four steps. So, you know.
[00:33:23] Guest: Andrej Lapajne: That's my my little personal tool to to actually evaluate the the.
[00:33:28] Host: Paul Barnhurst: And I really like that. Just so you know.
[00:33:31] Guest: Andrej Lapajne: Practical. Right. So you can.
[00:33:32] Host: Paul Barnhurst: Analyze any dashboard. Very practical. Right.
[00:33:36] Host: Paul Barnhurst: Is it good or bad. What is the variance? Why and what should I do about it.
[00:33:41] Guest: Andrej Lapajne: Yes exactly.
[00:33:42] Host: Paul Barnhurst: Love that.
[00:33:43] Host: Paul Barnhurst: So thank you. So I think we've talked about visuals. I want to spend a few minutes and this is still visuals but just talk about AI right. We can't have a podcast nowadays without at least the AI word coming up once or twice. So how do you see AI changing the way we consume analytics moving forward? What's your take?
[00:34:02] Guest: Andrej Lapajne: Ai is already transforming the way we are consuming, um, creating and consuming, you know, analytics, uh, Uh, consuming data, consuming insights basically completely transform transform the processes around, uh, data insights action. Already today you have tools. And I mean, we are even building tools, uh, with zebra AI, uh, that are able to take your data and actually try to build a model, uh, calculate, you know, uh, certain KPIs, variances, you know, and so on, and actually spits out, uh, a dashboard, uh, with charts and messages and comments even and even a business advice. Uh, of course, right now this is still at the very beginning, but, um, it is changing the way the whole organization around data and analytics, because it is basically cutting through typical business intelligence infrastructure. The whole BI stack. Right? Because right now, if you want to have efficiency like FP&A or even general analytics in your company, even beyond FP&A, you certainly need uh, in order to like, automate it and so on. You need to to basically build all the layers like you need the ETL, you know, clean the data, transform the data and so on. You need to model it for sure. Right. And then there are so many layers. Right. Calculate all the, you know, the KPIs and so on. And then I like to visualize it and report it and share it and so on. So you have like some five layers. And for each of the layers you know you have specialized tools, specialized languages and knowledge and so on. Just look at power BI for example. You need something like M language and Power Query to massage your data and so on to feed it into the next layer, which is modeling where you need to understand. All right. What is the star schema? How do I do that? How do I model my dimensions, my fact tables, and so on and so on. And what are the best practices? And again.
[00:36:17] Host: Paul Barnhurst: Bringing back some memories.
[00:36:19] Guest: Andrej Lapajne: And so on and so on. Like it takes forever. Plus it takes like a couple of teams in your company. Right. You need to know some IT people. You're maybe you're lucky and you have a, you know a BI department or reporting department and FBI and everyone and then design your reports. And now imagine that you have a tool or you just, you know, you just connect your data and do everything for you in seven seconds. Right? Which is actually the benchmark we're, we're at with zebra AI. Right. Um, and just do all that for you. It completely redesigns the whole process. You don't need other teams. Uh, you are not dependent on other teams anymore. So like order this from your it or from bi or even then any change. Oh. Can we add this? This little data here? Yes. But then, you know, we need to go to it and so on. It takes like three months to actually fix it. Uh, now it's all in seconds. And you start basically switching from all these data massaging, copy pasting and so on to actually talking to your data. Right. Because you have a little chat window, it would let you drop your data in. It would present, you know, the dashboard. And then you start basically chatting with uh, AI agent, uh, that does everything for you.
[00:37:43] Guest: Andrej Lapajne: Uh, so it's a totally different way of consuming analytics and then you share all this and so on. So I think it's going to completely transform the way people are preparing, like analytical products like dashboards, reports and so on. Consuming sharing, collaborating around that. And in the end, it'll be like a mixture of people, of humans communicating, interpreting, team, finding stuff and so on, and AI agents that will do the dirty work for them. Finally, which because I think that's actually finally for the first time with this technology, FP&A departments and FBA professionals will do their core job, which they're supposed to do, which is interpreting, finding insights, interpreting and communicating and acting as a partner and not like copy pasting the data, checking the data like 80% of the time and then okay, presented in one meeting. So we'll have much more time, which means much more, you know, much deeper insights, thinking about it and so on. And this will lead, I think, to, you know, just, uh, better decisions, much more patterns uncovered and so on, because AI is so much stronger. It can just, you know, search through like millions and billions of rows and patterns and combinations and you just cannot do that as a human, just interacting with your data, clicking and drilling down and so on. It takes forever, right? So yeah, totally transformative.
[00:39:15] Host: Paul Barnhurst: It's definitely exciting. And we see a lot of areas where it's transforming the way we work. But the question I would have is to have to do all that. Don't you still need clean data. You need your data definitions. And right. Most companies I would argue the data is the bigger issue when it comes to AI than implementing AI. Am I missing something? There is. There's still a lot of work we as humans need to do for a data definition dictionary.
[00:39:41] Guest: Andrej Lapajne: Having percent agreement here. There's like you know, there's this marketing or whatever expectation for okay, I'll just drop anything at AI and you know, I'll get a perfect thing out of it, no more than ever. Uh, today, more than ever. Um. In the history of humankind, it is important that you have clean data. Ai can clean data up to a certain point, but you do not need just like, you know, understandable data to a certain degree. You also need your basic data model, right? That's not something that AI will just create from any kind of like, like messy report. And if you really want great value out of AI, at least today, who knows what will happen in three years, right? But today you absolutely need this. And if you have it, it is today your by far the biggest resource. It's gold today, right? Because if you have this then you can already today get enormous value from AI. And if you don't you can just play around it. You know try, try you know 100 tools. You will never get value out of it.
[00:41:03] Guest: Andrej Lapajne: Uh, and it's a similar story with zebra II. I mean, if you have, like, you know, solid data and, you know, even if you have billions of rows, it actually works better if you have a lot of data, but it needs to be in a certain, you know, format and so on. You cannot just throw like a messy spreadsheet with, you know, like a one snapshot and then, you know, expect that AI will just figure out everything. No, you know, you need to export all of your transactions with as many columns as possible and so on. If you organize like one really flat, long, flat table, a lot of data, as long a timeline as possible, right? Because AI is quite powerful, it has much more than we can process. But you need to provide it in one, one, one neat format. Then you throw it at it. Okay. Then it will do the dirty work for you and find patterns that you will never find. But yes, you need clean data. Absolutely.
[00:42:00] Host: Paul Barnhurst: So there's our public service announcement for the day. Garbage in, garbage out still applies to AI, I mean, and that's the thing I so often caution people like, oh yeah, we're seeing it move fast and there's a lot we can do. But I've said a few times and I don't think a lot of people have realized it yet, but I'm like 25 and maybe even some of 26 is really the year of cleaning our data. Everybody's like, it's a year of agents. I can all of a sudden just change everything. Uh, for most companies, at least my experience of my whole career, the data was just not good enough. Like, you know, the fact that the average person spends some studies have said anywhere from, you know, 30 to 55% of their time cleaning data tells us they're not going to just drop it into AI and get insights and results that they can trust.
[00:42:50] Guest: Andrej Lapajne: Yeah, absolutely. And I mean, this percentage, maybe it's even on the, on on on the lower end I could even go higher. Yeah absolutely. And it's not just like cleaning like one data source. I mean, the problem with the data is, you know, the complexity in the data. It has two dimensions, actually. One thing is, you know, the amount of data is increasing. So now instead of like 100 rows or a couple of thousand rows, right. You have millions or billions of rows, right. That's one thing, one dimension. But the other dimension is we have more data sources from, you know, different places from different systems, you know, just internal data. We also started finally using external data, which brings another challenge and so on. And so basically and then this is this matrix like more data and more data sources. And it's like you know a two dimensional explosion. So you need to control, you know, the quality in the amount of data, but also in the amount of data sources. How do you bring this together? Right. How do you feed this into a model or even into AI so that you know you can combine it in a meaningful way so that AI will actually understand. It's even a harder challenge today, but it's the critical thing. It's the absolute fundamental for the future.
[00:44:14] Host: Paul Barnhurst: Agree.
[00:44:15] Host: Paul Barnhurst: Thank you for that. So I want to move on to some standard questions. We ask about FP&A of each of our guests. And then we're going to move into the Get to know You section, where we ask some fun questions to get to know a little bit more about you. So the first one is what would you say is the number one technical skill FP&A professionals should master.
[00:44:35] Host: Paul Barnhurst: Given.
[00:44:36] Guest: Andrej Lapajne: What we've just said about data modeling.
[00:44:39] Host: Paul Barnhurst: Data modeling.
[00:44:40] Host: Paul Barnhurst: Love it.
[00:44:41] Guest: Andrej Lapajne: Today, I think still, this is like even if you have a BI department or reporting department or IT somebody else doing it for you and so on, I think FP&A should at least know the fundamentals and so on. But of course, if you are in a smaller company, you know you're doing it yourself. Yeah, from a technical point. It's like, uh, the number one data model. Just conceptual data modeling. It doesn't really matter which tool you are using because, you know, learn the tool and so on. But the fundamental concepts of a clean data model, star schema and so on, the basic rules are even more important today because, you know, spreadsheets are not cutting it anymore. You know, they're fine with some small things and, you know, flexible ad hoc analysis and stuff like that. But, um, we really need to move into data modeling because this is where you actually handle all this data problem, like the quantity of data, multiple data sources and so on. So yeah, I would choose this one if it's right.
[00:45:41] Host: Paul Barnhurst: What about soft skills? What's the kind of software human skill that we should master?
[00:45:46] Guest: Andrej Lapajne: This one is very clear to me I think already like decades ago, you know, it was one thing that was also quite kind of missing in FP&A, right? Everybody was learning the tools in Excel and, you know, your KPIs and your, you know, calculation models and so on. Your business models. But communication, not something that was actually like it was its course or education, you know, maybe a little bit, but it's not really a core thing to master. And so that's kind of I would say like a standard gap inFP&A. Um, but as you know, if you want to be really good and be a proper partner to the management, uh, you need to master your communication. And I would definitely include Ibcs as a part of that. Right. So this skill, the rules of communicating business information, also with the visuals with charts and so on. I think it will be increasingly important because, you know, AI and, you know, other technology will slowly really help us and do this dirty work for us. And what is left, you know, we as humans, um, really have and it's like this understanding and then, you know, just communicating, Indicating conversing to make sure that we, you know, really get to those actions and, and so on. So yeah, that would be my bet.
[00:47:01] Host: Paul Barnhurst: All right.
[00:47:02] Host: Paul Barnhurst: So we got communication and data modeling. All right. So here's a fun one. I'm curious to see what you say on this one. If Excel removed one feature tomorrow, which one would cause you the most panic.
[00:47:14] Guest: Andrej Lapajne: Oh if they removed pivot tables I would be lost today, right? I would say today probably pivot tables, especially because, you know, if you want to use Excel today in a modern way and really get the value out of it, you really need pivot tables because then you can connect to your power BI data sources, other data sources and so on. And that's really the, you know, modern Excel now. So yeah.
[00:47:39] Host: Paul Barnhurst: That's.
[00:47:40] Host: Paul Barnhurst: The first time we've had that answer. We get different ones. But I totally get it with PowerPivot and BI and so many things run on the data side through pivot tables.
[00:47:50] Host: Paul Barnhurst: It's amazing.
[00:47:50] Guest: Andrej Lapajne: Absolutely.
[00:47:51] Host: Paul Barnhurst: Yeah.
[00:47:53] Host: Paul Barnhurst: All right. So now we're going to ask some fun questions to get to know you a little better. Personally. Outside of work, outside of visualization, what's a favorite hobby or passion? What do you like to do in your spare time?
[00:48:03] Guest: Andrej Lapajne: Right now it's actually windsurfing.
[00:48:05] Host: Paul Barnhurst: How did you pick that one?
[00:48:06] Guest: Andrej Lapajne: I just came from the seaside, hence my beautiful reddish reddish.
[00:48:11] Host: Paul Barnhurst: I was wondering about that now I understand. Yeah.
[00:48:13] Guest: Andrej Lapajne: So but it's like yeah, it's windsurfing. I love the feeling of the, you know, the freedom you get when you get on the board, put up the sail and then, you know, it's just you and the water and the wind and, you know, you drive around and say, yeah, it's you in nature. So that's my favorite hobby right now.
[00:48:33] Host: Paul Barnhurst: And how long have you been? How long ago did you pick up windsurfing? Is that a fairly recent hobby or.
[00:48:38] Guest: Andrej Lapajne: I actually started doing it as a kid. Uh, I was self-taught. I started doing it in the 80s, really, when I was like.
[00:48:46] Host: Paul Barnhurst: Okay, so.
[00:48:46] Guest: Andrej Lapajne: Maybe.
[00:48:47] Host: Paul Barnhurst: 12, 13 years old my whole life.
[00:48:50] Guest: Andrej Lapajne: Yeah. But I was self-taught. And now basically, you know, after decades, I picked it up this time, like more professional. I mean, professionally, more seriously. Uh, and yeah, now I love it even more.
[00:49:03] Host: Paul Barnhurst: Favorite travel destination? If you could go anywhere in the world tomorrow, where are you going?
[00:49:07] Guest: Andrej Lapajne: Or once again, to, like, Central Australia. You know something? I love it? A little bit of an adventure. Like some sublime nature. So on and so on. But anything in nature, like I get a lot of, like CDs and then technology and so on. So then, you know, I balance it out in nature, like either mountains or like deserts or something really sublime.
[00:49:29] Host: Paul Barnhurst: If you ever get a chance, if you come to Utah, let me know. We'll do some nature, we'll do some hiking or southern Utah or.
[00:49:36] Host: Paul Barnhurst: I.
[00:49:36] Guest: Andrej Lapajne: Would love it. It's on my bucket list. Absolutely. Utah. Wow. I would love it.
[00:49:41] Host: Paul Barnhurst: To be sure.
[00:49:42] Host: Paul Barnhurst: I'll definitely take you out to dinner and we'll do a hike if you come.
[00:49:45] Host: Paul Barnhurst: Great. No. All right.
[00:49:48] Host: Paul Barnhurst: If you could instantly master, what skill would you want to master if you could just, you know, without having to go through all the learning, what would be that skill?
[00:49:56] Guest: Andrej Lapajne: I think Python, you know, I haven't been programming for decades, but, uh, yeah, if I had the time and, you know, to master one skill. Yeah, I would definitely love to, uh, learn that to code in Python.
[00:50:09] Host: Paul Barnhurst: That's a good one. That would be on my short list. I hadn't thought of that, but I just had a lunch conversation with somebody who was trying to convince me to learn Python. Last one here on the Get to Know You section. What was your first job and what was your key learning from that job?
[00:50:23] Guest: Andrej Lapajne: Well, I started actually as a programmer, basically a software developer, and for a brief period and then I moved on to like, uh, project management and then more into marketing and sales and stuff like. But what did I learn? I mean, keep learning. Uh, if you have this, like learning mindsets, you can really achieve anything beyond your wildest dreams because, uh. Yeah. I mean, I was always like this curious person, just like studying everything and keep learning. It's still my motto. Like, you know, when I stop learning, I'll be dead. I think that was really the learning from my very first job when I started. Like, I was really proactive and I studied this and that and, you know, and I always, always had those ideas based on this learning, I think I just progressed and moved and just opened my world. I think the path that I enjoy so much, and it just gives me back so much. So I am learning from them. I just keep learning, keep, keep growing in your head and, uh, you'll be fine.
[00:51:26] Host: Paul Barnhurst: Thanks for sharing that one. Great, great lesson to learn and always be learning. Last question: if someone wants to learn more about you, learn more about Zvi. Possibly get in touch. What's the best way for them to do that?
[00:51:39] Guest: Andrej Lapajne: You can always connect to me on LinkedIn. So that would be Andrej Lapin on LinkedIn. Or just search Andrej Zebra VI on LinkedIn. Happy to connect with everyone. Follow up with any conversations on a personal level. Follow zebra BI on LinkedIn. But we also have a lot of resources on our website. So if you go to zebra B.Com, uh, we have free courses, uh, that, you know, people can just like, uh, we have a course on power BI on everything like modeling and modeling, data preparation, visualization, uh, dashboards, effective dashboards, reporting, financial reports and so on and so on. How to do, you know, panels in power BI and Excel. So those are two courses. So go to our website for helpful information. And then you will also find contact information to get in contact with us.
[00:52:31] Host: Paul Barnhurst: A great well thank you for that. And we'll make sure to put your LinkedIn profile in the show notes and a link to, uh, zebra bi. Thank you so much for joining me today. It was a real pleasure chatting with you. And, uh, keep, uh, fighting for better data Visualization. It's an area we can all improve at for sure. And so appreciate what you're doing and for carving out some time today. So thanks for coming on the show.
[00:52:55] Guest: Andrej Lapajne: Thanks for having me, Paul. I enjoyed it. Thanks, everyone for listening. Cheers. Bye bye.
[00:53:02] Host: Paul Barnhurst:Thanks for listening to FP&A tomorrow. If you enjoyed the show, please leave us a five star rating and a review on your podcast platform of choice. This allows us to continue to bring you great guests from around the globe. As a reminder, you can earn CPE credit by going to earmarkcpe.com, downloading the app, taking a short quiz, and getting your CPE certificate to earn continuing education credits for the FPAC certification. Take the quiz on earmark and contact me the show host for further details.