Power BI and a Creator Mindset Are Essential for FP&A Teams to Replace Excel with Rishi Sapra

The challenge is that finance teams see themselves still very much as consumers of these technologies. And actually that shift that needs to happen is mindset shift of going from being a consumer to being a creator, creating technical solutions using these tools and that will completely change how you use AI.

Meet Rishi Sapra, currently leading data and AI strategic projects at Avinoid, a chartered accountant and Microsoft mvp. Also the owner of Microsoft Fabric Training, runs an accelerator program, Power Platform Finance for finance professionals. He combines deep financial expertise with cutting edge data and AI capabilities to drive business transformation. Many, many dashboards are built. You'll look six months later like oh, ten people have looked at it. Why did I spend two days building this?

If you're trying to build something that's all things to all people, it's unlikely to serve anyone's particular needs. Start with the story, start with the audience, start with the insights, start with the problem statements.

What do you think is the number one technical skill that FP&A professionals need to master?

Foreign.

Are you tired of being seen as just a spreadsheet person while others get a seat at the table? Well then, welcome to FPA Unlocked, where finance meets strategy. I'm your host, Paul Barnhurst. The FP and A Guy. Each week we bring you conversations and practical advice from thought leaders, industry experts and practitioners who are reshaping the role of FP and A in today's business world. Together, we'll uncover the strategies and experiences that separate good FP&A professionals from great ones, helping you elevate your career and drive strategic impact. Speaking of strategic impact, our title sponsor for FP and A Unlock is Campfire, the ERP that's helping modern finance teams close fast and scale faster. This week I'm really excited to welcome our guest, Rishi Sapara. Rishi, welcome to the show.

Thanks so much Paul. Great to be here.

Yeah, really excited to have you. So let me give a little bit about Rishi's background and then we'll jump into our conversation. So Rishi is a Chartered Accountant and Microsoft MVP with an executive MBA and a first class degree from the London School of Economics. He currently leads data and AI strategic projects Avanade an Accenture Microsoft JV focusing on Microsoft fabric solutions, governance frameworks and enterprise migrations. With 20 plus years of experience at big four firms, technology consulting and leading financial institutions including Deloitte, KPMG, HSBC, Barclays and Accenture. He combines deep financial experience with cutting edge data and AI capabilities to drive business transformation. He also runs an accelerator program called Power Platform Finance for finance professionals to learn Power BI through a combination of interactive elearning and instructor led training in a combination of. That allows learners to be able to apply it effectively to their own data and processes. Really excited to have you. Love the background. Let's jump in. I'd love to ask you a little bit. You earned your chartered accountant degree, so I know you're a, you're a ca, but I spent much of your career working with data and bi. So how did that transition happen? How did you go from kind of accounting to data in bi?

Yeah, sure. I mean it wasn't, you know, just a sudden move, it was kind of gradual. I got more and more into data, I think, you know, I started when I was, I was at HSBC doing product control and you know, it was, it was, you know, doing P Ls daily PNLs in Excel and I remember getting quite interested in automating that with BBA and you know, trying to work on their solutions for automation. And I think my manager said, well, this looks like something you're really interested in. Why didn't you, why don't you do more of that? And so I did and I left and joined Barclays to process automation and then financial modeling at kpmg, which was kind of that hybrid between the Excel financial modeling world and data and obviously the accountancy. And then from there really got into Power Query and Power Pivot and then joined a BI consultancy after a few years to actually focus on this more full time. So yeah, over a period of a few years I kind of got more and more into data and into technology and, and just really enjoyed it.

Did you ever picture that happening or what was kind of your thought when you got your accounting degree? Was it, hey, I'll go more toward finance or just kind of see where it leads?

I mean, to be fair, even when I qualified as an accountant, I was working in tax technology and actually it was, you know, software. I don't know if you remember it from back in the day. It was ABACUS software that was, you know, tax compliance for CT600. And so it was still a quite technical role, if I'm honest. I've always kind of been in that technical space and that's just where I kind of landed. Not sure I really had much of an idea about where my career was going for quite a while or.

Yeah, no, I think that that's many of us. If you told me I'd be interviewing people for a podcast, I would have told you you're crazy.

Exactly. But yeah, I mean, and that's the great thing around, you know, the opportunities that, you know, technology provides as well and you know, where we could work and you know, having skills like accountancy and having that background is, is valuable in anything you do. Even if you're running your own business or you know, working in an executive role, you know, having that financial accounting background is just a great skill to have.

I agree. Understanding finance, understanding accounting can be incredibly valuable no matter what you do. I'm with you there. Have you always had a passion for kind of technology and educating others on technology? I know you mentioned you did that earlier in your career like as a kid. Were you the one that always playing with the newest technology or kind of. How did you develop that? Not so much.

I do really wish I learned programming when I was younger and actually started to learn software and things like that. And I didn't really. My dad did actually run a software company doing software for care homes and hospitals, but he wasn't technical at all himself. You just have teams in India to build the software. I think when I was a kid I think I used to do hardware, you know, I used to like taking apart machines and you know, putting stuff together again in a hardware. Well, but I didn't really do, you know, and I did, you know, I got into the Internet I think when it came out with AOL and the dial ups and things like that, but not really. I didn't really get into programming or you know, web development or things like that. And actually I do kind of wish I did have a bit more of a software background because, you know, now trying to pick up coding and stuff and you know, learn Python and you know, unless you could really apply it and you've got something to really kind of do, it's part of your role, which I don't really at the moment. It's a bit of a hard thing to try and actually pick up, you know, all these years later.

Yeah, no, I, I hear you. I know what you're talking about. I didn't pick up any coding as a kid and I would have loved to earlier in my career pick up a little bit of Python and some of those type of things. I'm curious, can you talk a little bit? You're a Microsoft mvp. What was it like when you first found out you earned the award and kind of.

What is it?

Maybe tell our audience a little bit about that.

Yeah, sure. So I mean, MVPs, I mean you had yourself as well, right? It's people who work very closely with The Microsoft Teams, so they're the kind of technical influencers for the community. So they're people who evangelize the products but also work with those teams to get feedback from on what users are saying. They get access to early releases of the products and help shape the direction. So those product teams in Microsoft who build products like Power Bi and Fabric, they're always after feedback and insights into how it's being used and what works, what doesn't work. And they have a few channels for that. But they really like the MVP channel because it's quite a technical community and you know, it's quite an evangelist community as well. So, you know, they're able to get that feedback from the kind of technical influences in there as well. So that's kind of the mvp. It's something that's just, you know, a recognition of community contributions. You know, I think people sometimes see it as a bit of a kind of certification type path and it's just not like that at all. It's not like you do, you know, your Power BI and Fabric certifications and then come MVP up naturally after that. It's a very different type of. Well, and it's not, it's not actually based on your technical skills. It's based on your community engagement, your contributions to the community, whether that's speaking at conferences or blogging or videos. And you know, I've tried all of those things in the past to vary levels of success. And yeah, I mean, some things work well at certain times, other things at other times and it's just, it's less about, you know, oh, I get 10,000 views on this. So, you know, I should be an mvp. It's more about actually I've got a community and you know, people, you know, like hearing some of the things I have to say. And actually I like sharing that knowledge. So it's much more about that than necessarily the peer metrics or technical experience.

I completely agree. I mean, I know lots of people who are much better technically than I am that aren't MVPs or some, that maybe they have, you know, a better community, but depending on how they're sharing it, their interest, whatever. So it definitely varies, varies a lot of how it comes together. And Microsoft is looking for those people that have the right combination. So speaking to that, if someone's listening and they want to be an mvp, any advice you'd offer to them, I.

Mean, don't focus on being an mvp. It's not really in your control if I'm honest. And as you Say there's lots of people who do loads of great stuff and are not recognized, you know, so it's. It's more just about. For me, you know, doing the community contributions is really one of my main ways of learning this technology, right. Rather than just now and consuming, you know, blogs and videos. You know, I actually learned by doing and I learned by building and sharing and then seeing how it applies in a particular scenario. And actually, it's great when you're to do it in a community capacity rather than just for clients, because in a community capacity, you're your own customer. You could build whatever you want. So actually it's that you've got a lot more freedom to kind of just build solutions and think about innovative ways to solve things and build those solutions and put them on the community, get feedback on it and see how, you know, teaching other people. And that's really, is, for me at least, is the best way to learn. So that's kind of why I really got into it. That was the why the motivation for me. And other people might have other motivations as well, but really I think it's just about finding that passion. If you're passionate about it and you want to try and build stuff and learn or share your knowledge, just do it. And maybe you'll get recognized mvp, maybe you won't. But to be honest, Most of the MVPs that I know at least, are not really that concerned about the mvp. They'll do it regardless of whether they have an MVP or not, because it's who they are.

I think that's great advice. If you enjoy sharing, you enjoy community, you enjoy the learning that comes from it, do it. And if you get to be an mvp, great. And if you don't, great. You're still learning, right? As you said, you can't control it. And I want to kind of shift gears here a little bit and spend most of the rest of our time diving into business intelligence for FP and A professionals. Right? There's lots of FP and A people that want to learn business intelligence, power bi. I remember going through my own journey, but where I want to start is I want to get your thoughts. I recently interviewed a nationwide recruiter in the US who said one of the top things employers are looking for from FPA professionals. He said one of the biggest things they asked for is either power bi or tableau experience. Okay, when I. When you hear that, what do you think? Is that what you're seeing or what's your thoughts on that?

I mean, I could See why? Especially for fpa, because FPA professionals are strategic partners of the business, right? They're not data jockeys. They're not people who just produce some numbers and then, you know, send it off in an email and hope that people understand it. Right. To really have that impact, to be able to do the planning and analysis, it needs to be actionable insights. And that's quite difficult to do with static reports, those traditional kind of, you know, PDFs that it reports used to be and or even, you know, Excel tables. It needs to really be that self service storytelling capability with your data. So and that's what Power BI and Tableau allow you to really do. Go from, you know, here are the numbers to actually here are the numbers, but here's what's driving those numbers, here's what's driving performance and here's what we can do about it. Here's how we can make actionable change in the business to be able to drive better performance. So absolutely, you know, Power BI and Tableau for the storytelling capabilities, I can absolutely see why that is. And also for automation to be able to use Power Query for some of those automation capabilities. So spend less time manually crunching data or cleaning data each period and really just being able to have that foundation of being able to combine different data sources together and build those semantic models, those rich semantic models that have the logic in there, that have that context for your data, that allow you to tell that story, but also allow Gen AI to be on top of semantic models as well. I think that's the next, that's the next direction this is all going in. So yeah, for all those reasons I think I can absolutely see, especially for people in those kind of analytic roles, why these tools are, should have or even a must have, I think for kind of certain hires.

I almost thought I was going to get through an interview without hearing the word Gen AI.

There's such transformation.

It's amazing how it's changing everything we do. And so I'm curious, do you find yourself working with a lot of finance departments and finance teams? I know you do a lot of different consulting work and BI and a lot of your background is finance. So are you seeing a lot of them, you know, asking for help with business intelligence, you know, Power bi, Microsoft fabric, you know, the whole stack and figuring out, you know, their reporting?

Not as much as I'd like, if I'm honest. I think I still work primarily at least, you know, in Avanart, et cetera. I work primarily with IT departments. Right. Essentially Coming at it from a data platform perspective and building reporting solutions. And I think the challenge is that finance teams, I think, see themselves still very much as consumers of these technologies and technology in general, perhaps. And actually that shift that needs to happen is a mindset shift of going from being a consumer to being a creator of these and creating technical solutions using these tools. And that will completely change how you use AI or how you use, you know, Excel even and Power Bi and things like that, because it will start to, as you become a creator of solutions rather than just a consumer. And, you know, here you go. I use Excel and I know how to use Excel for what I mean to do, and I will continue doing that. And if there's something nice and easy, a new feature that comes out and it's easy for me to do, I'll adopt it. But otherwise, you know, it's the world I live in and other people need to, you know, give me solutions to. They do the technology stuff, I do the accounting stuff. Right. That's, I think, a bit of a mindset that a lot of finance professionals are in still at the moment. And it's, it's a bit of a shame that I'm hoping I'm starting to see more, I think, especially in finance teams where they are starting to actually learn this and take more responsibility for shifting their own mindset to be actually be like, actually this is stuff that could really help me in my career and in my role and, you know, in life in general, maybe as well. Right. To be able to learn how to use these technologies, to, to create something, to, to be able to create story I need to tell with my data, to be able to create the analysis, to be able to create insights, to be able to create solutions and models that, you know, could drive forward an organization to. So as I say, it's a bit of a mindset shift and I think we're starting to see a lot more of that now. And it's an absolutely very welcome thing. I think it will really help in terms of how people will start to adopt the technology. And I think that's generally across society. Right. I imagine if they're like billion chatgpt users in the world, I'm sure about 95% of them use it in pure consumer mode. Give it a prompt, hope it gives you their answer. If it doesn't, you know, that's a problem with it. All right. Whereas if you switch from using AI into using AI as a creator, and then you're starting to think about, well, how can I give it the right context to be able to answer these questions, how can I use these tools to be able to learn and to be able to build the kind of solutions, then it's a very different way of working and we're starting to see that more. But I think we need that shift in, in the mindset first.

Interesting. So, you know, you've kind of outlined a difference between those that consume bia, whatever, and those who create solutions. So in your mind, for the average FP and a professional working with business intelligence, you know, working with Power bi, what level of knowledge do they have to have when you say create solutions? Or are they going to need to be able to build schema, you know, semantic models, understand deep DAX beyond, you know, or is it just they need to be able to build the graphs on top? Or what do you think is that? Do you have an opinion on the right level? And I realize it's different for everybody to a certain extent, but just your general thoughts of how far you think it would really help for most FP and A professionals to dive down the rabbit hole, so to speak. And now a brief message from our sponsor, Campfire. Build a best in class AI native ERP designed for modern finance and accounting teams. With Campfire, you can automate revenue, streamline your close, and centralize accounting all in one unified platform. And now they've hosted Finance Forward, a first of its kind AI summit in San Francisco. They brought together the sharpest minds in finance and operations, all focused on how to actually use AI. AI to move the needle. You don't even have to travel to learn the tactical skills to put your team ahead. You can stream the whole thing on demand, totally free, anytime after the event. So if you're ready to get tactical about AI and finance, head to Campfire AI and register for the on demand content for free. That's Campfire, where finance teams go to think forward. Sure.

I mean, I think it's, it's all about the foundations and I think it's very easy to get caught up in the tools and technologies and new features and all of those things and then, you know, to get overwhelmed by it. Because these things change on a daily basis. Like Power BI comes out with new features and Power BI and Fabric come up with new features every week and actually to take a step back and say, well, what are the fundamentals? Because those fundamentals don't change. Right. And those fundamentals are apps. Absolutely, yes. Data modeling. Right. Thinking about how you structure your data for it to work well with analytics and that's probably a different data structure to how you work within Excel, different way of thinking about your data, even to how you work within Excel. And it's different probably how it's represented in a transactional ERP system, for example. So knowing how to structure your data in the right way and how to model that data and how to build, you know, some core logic into there as well, I think. Absolutely. That skill doesn't change. Yes, you might not need to know all of the latest dax and, you know, AI can definitely help with that anyway. But the idea is all of that stuff, actually the best solutions in that space are always the simplest. Your best data models are always your simplest data models. And where your DAX is simple and that relies on you having a really simple, clean data structure that is well suited for analytics. And as I say, that might be quite different from what is in your erp. So actually you might need to think about how to restructure that data. So learning those skills of Power Query, essentially on how to. You need to know what you want to end up with. You need to know the data structure, semantic model, style schema, concepts of that that you need to end up with. And then you need to know the basics of how to go from whatever your transactional data is into that structure. So again, that's using kind of Power Query. And Power Query is absolutely somewhere I'd really suggest FP and a professional start because it's in Excel, it's where they're already familiar. So just they get data experience. In Excel Power query, you do things through the ui and again, you need to know what you want to achieve. You need to know what and why you're doing it, what's in it for you. Like, understand what these tools can do and why they're going to deliver that benefit. And then the rest of it should come quite easily. And then the last thing obviously is we talked a bit before as well about storytelling. Understand the core concepts of data visualization. Storytelling. It's all about. I think you had Andre on recently, didn't you, Andre? And data visualization is all about reducing cognitive load. It's all about making those insights obvious. Isn't my performance good or bad?

Why?

What can I do about it? And just being able to understand those concepts of how to communicate with data. Yeah, those things don't change. ASTA tools change and AI, you want AI to do those things and help you with those things, but those things don't change. So absolutely learn the foundations and then, you know, in terms of when you get stuck with doing stuff. Absolutely. You can use AI then as well. And you know, we've always relied on Google, even before AI. So there's always resources to learn, but you need to know what you want to learn and you need to have the why you need to know, you know, what's in it for me? Is it going to help me go home on time? Is it going to help me, you know, tell. Build better relationships and tell the story better in my data? Is it going to help me, you know, be able to provide the right context for my data so that gen AI can sit on top of it? All of those kinds of benefits you need to establish first and then, you know, learn the foundations.

You need to establish your why you're doing it so you stay committed, get it and then. But as to break it up from hearing you and just my experience, I think of it kind of three areas. There's some power query you need to learn some basics of how to get the data out. I recommend that to every finance professional. Even if you never touch Power bi, you should learn Power query if you're working in Excel. It's just, it's better for cleaning and transforming and shaping your data, bottom line. And if you're going to spend a lot of time in Excel, why do it with formulas and manually? That's the first section, I think. The second you mentioned is having a little bit of understanding of data data models that helps you with building tables in Excel. It helps you when you design models, financial and data models. I was fortunate enough. My first role was report writing before I went in FP and a for a year and a half I did a master of Science in Information management with an mba. So I had some of those ideas. And I'd been a little bit of a business analyst before going back to grad school of how data worked and having that understanding of data and how to structure it is invaluable for anything you're building with data, even if it's just a financial model. So I agree with you. You know, once you go to data models, a little more star schema, snowflake, it gets a little more. You want to call it technical, I don't know that I call it really technical, but a little more and then that third part is, okay, how do I build the visuals or some good visualization? And that may require knowing a little bit of dax. The reality is now with AI and everything else, you can definitely shorten the amount you need to know. The more you know, the easier it is to build, just like in Excel, even though AI can do a lot of it, it's easier to validate, it's easier to make sure you get it right. As I always like to say, the best user of a tool and AI is going to be the person who knows the tool really well versus the person who doesn't know it and is just trying to use AI to get through.

Absolutely. And actually it's interesting because I think the principles of good financial modeling are the same principles of Power bi. Really, it's that separation of logic and inputs, logic and outputs. And actually Power BI does that almost automatically with your cloud query, your reporting layer and your semantic model layer, your logic. So I think actually that's some of those principles. And also the other thing I'd say on that is you really need to focus not on the tools. Right. But focus on the problems. Focus on who your audience is and what problems they have and what insights they need. Right. And if you're from a finance background yourself, again, this, this will really help because you could really put yourself in the shoes of those end stakeholders, you know, what insights people need and, you know, kind of what's important. But starting there, like when I teach Power BI for finance, you know, the first module isn't technical at all. It's actually requirements gathering. It's listening to a stakeholder interview with a finance director and then using that to populate a scoping template to identify what are the business questions we want this report to answer. And those business questions then allow you to design the model, because you can design any model you want, but you have to design the model that's going to be right for your audience, that's going to be able to answer those questions and you have to tell the story that's going to be able to answer those questions. So that's why it's always really useful to start there. And those soft skills in terms of being able to understand and, you know, be able to interpret, you know, from, from an interview, go from an interview into a set of questions and insights and then be able to design a model out. That's all the stuff AI is actually not that good at right now. So, you know, that's the real skill set I think, that, you know, an FPA professional can bring to as well.

Yeah, it's funny how you related to a financial model, right? The best financial modelers don't spend most of their time in Excel. They spend most of their time with the customer. And, you know, that's basically what you're Getting at here is the requirements gathering, the working with others. So setting that aside for a minute, I think that's something every FP and a professional needs to be good at it. Whether it's a financial, a data model, someone wants to learn, you know, Power bi and I'm talking more the tool than the requirements gathering. Where would you recommend they start? Do they start with learning power query? Do they start with DAX data model? Kind of walk through how you would recommend as far as learning the tools, where they start and kind of the typical journey that you think works for most people.

I think there is definitely a good opportunity to kind of really get the foundations right. Right. Rather than just trying to take courses and watch YouTube videos. So, you know, I've built lots of material, even self paced learning material, but I try and also combine it with instructor LED training. Right. To really get those foundations across and get people in a peer group learning together. I think some of that accountability really helps as well to keep people motivated and also just to give that opportunity to try things so that the it's all exercise based, it's all labs based on. Right. So you really need to be applying it. I think especially if you're not interested in the technology for the sake of the technology or the tools and you're coming at it as a finance user you really need to understand how to apply this so you can learn about a star schema. But it's not until you actually apply it into a financial model and try and build an income statement in Power BI that you're really going to understand why that's important or you know what that means really in real life. So absolutely focus on things that are going to be practical application led. So obviously doing it on your own data and processes is great and it's an absolute first step. I do find that's quite hard to do because finance data is quite hard to work with at this stuff. So to just start off and just go in and put data in and start to use it can be quite challenging. But just going off and trying to learn Power bi again, it's an absolute fire hose of information information. It's overwhelming. There's so much stuff there. So I would really recommend doing yeah, a course, but doing and doing structure training, but doing it in a scenario where it's. You're using relevant data sets, where you're using finance data and ideally where it's hands on and where it's kind of, you know, instructor led, where it's kind of in person or you know, virtually In a group, I think that kind of training will work really good to learn the foundations, right? So you can learn, take a use case, take a scenario. I use income statement reporting like month end board pack type reporting in Power bi, take some finance data. And we work through the exercises of actually building that out in Power bi all the way from the requirements gathering through to Power Query through to data modeling and Dax through to visualization. So those four weeks, those are the four weeks we kind of COVID So I think that's the really good foundation. Once you've done that, then you absolutely need to start to apply it straight away on your own data and processes. Then it's a case of saying, okay, now you've understood the basic concepts, you know what's involved. And I actually find that most people coming into the course actually don't know what's involved in Power bi. They just, they've got different expectations about what it is. They think it's data visualization tool or it's, you know, and when I try and explain all these things in Power bi, some of them look at me like why are you over complicating this? It's just an Excel on Stairways, right? It's just a data visualization tool. So actually trying to get everyone on the same level first and then maybe working with them to actually help them apply it on their end data and processes and you know, they're going to need coaching, they're going to get stuck. And I think it's an unrealistic expectation to say to someone, okay, go on a Power BI course and then have the expectation that they can just come back to their desk and start building reports straight away, I think they're going to need a little that handholding and coaching. So if you can find someone who's willing to provide that coaching, you know, to help you through those processes, whether that's someone internal or external and you know, really get you applying those concepts. That will be the best approach. And then after a few, a few times you've done it, maybe you switch it the other way. Maybe then you take the focus of kind of building it all and then advising you, you know, having, having a session with your coach to, to kind of, you know, check on what you're doing or when you get stuck.

You're a big fan of thinking the best way here is really kind of cohort course led instruction versus trying to learn it on your own.

I think it definitely to get those foundations right. So you're talking say language and then it's all about application, right? I mean you definitely, even with the learning, you know, learning by doing is always the best way. So any courses you pick, make sure there's a big hands on element in there because that's going to put it to life much more than just you know, watching YouTube videos or you know, reading articles and theoretical concepts around it. Definitely hands on. And then absolutely try and apply it as soon as you can straight afterwards and make sure you've got the support because I do see a lot of people who again they go on a Power BI course, they come back to their desk, their data sets, nothing like the course. They're working with some messy SAP data and they just get stuck and then they just go back to Excel. You need to make sure that supports there I think afterwards as well.

I remember learning it and I definitely at times wishes I wish I had more support. You know I did it through books and but I had done report writing before. I had used IT access database a lot. I did a master of science in information management. So understanding data even though I built Franken tables at first, you know, and Power Query was really kind of just different language but it's SQL in many ways and the fact that it's just, you know, another tool to pull your data. So I, I definitely had, you know, training that made it an easier learning curve and I did it all in Excel first before I ever went to Power bi.

It's a hard journey, right. And I think a lot of people are not necessarily prepared for that as well. Right. So it'd be quite a long journey and I think, you know, now with Gen AI, you know, I think, I think previously you, to do stuff properly in Power bi you'd probably have to really dedicate, you know, your role to it. Right. You know, almost quit your job as an accountant and you know, train as a data analyst for a couple of years. I think we can shorten that significantly now, you know, with tools that we've got available and things like that. But yeah, it is absolutely a huge commitment and I think to have that commitment, to have that motivation, you really need to understand the why. You know, as we talked before like you know, what's it going to do? What are these processes, you know, that you're doing now that take you hours each month that you can automate with these tools? What are the stakeholder questions that you keep getting that you want them to be able to self serve on that you could actually rather than having the back and forth, you know, you could have a report that Allows them to drill through into detail, allows them to be able to look at what's driving the performance. So, you know, those are the kind of benefits I think you really need to understand that it will get them and that will provide some of that motivation to go on that journey.

And you know, one thing I'll say is how do you balance. Because the reality most people aren't going to go into this full time, right? FP and A still the primary job. And you know, you see more and more business intelligence being pushed in there, wanting some skills. So how do they balance the two of, hey, you know, FP and A is my job. I need to learn some bi, I need to be able to build some dashboards, I need to be able to help work with it.

Kind of.

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I mean you've got to try and integrate it, right? If this is something you're just trying to do on the side outside of the day job, it's going to be very hard to find the time to do it, to devote to it, you know. And you know, there are, there are some people who will sit there and watch Power BI and Fabric videos on the weekends, but I imagine the vast majority of finance professionals wouldn't. So it's about then trying to be able to apply it, as I say, into your role, right? So you know, really understand from the outset what this technology does and how it can help you, not just tech for tech's sake, but how is this going to apply in your scenario and your role? What would you. What will it allow you to do? What. What would be the benefits? You know, say, automation, you know, being able to go home on time, you know, being able to tell the story, being able to spend less of your time with those manual processes. So understand the why, and then that will provide some of the motivation. But then as soon as you've learned some of those fundamental concepts, apply it straight into what you do on a daily basis where you can and, you know, try and get that support from your manager and from, you know, consultants and experts as well, to actually use it, to then be able to apply it. And once you start to apply in it, then it becomes part of your role rather than this separate thing that you need to try and learn on the side.

What was the hardest part for you when you first learned Power bi? What was the hardest part of making that transition?

So I think it is actually a different way of thinking about your data and, you know, trying to be able to apply that to an area like finance. It's not obvious, right? Obviously, it's a tool like Excel that can be applied for anything. So it's not just about learning the tool or learning the features. It's knowing how to apply them to achieve particular outcomes and why you might want to learn those features. So I think being able to apply it. And then also, I mean, the pace of change, say, with all this stuff, is incredible, right? Especially, I think, when Power BI first came out. For those first 10 years that power BI has been out, it's been, you know, so many features. Like every week or every month there'll be 20, 30 features and the release. And I think, again, it's useful to kind of take a step back and say, okay, you know, maybe I don't need to learn everything right now. I need to learn the fundamentals, and then I need to see and evaluate things that come out as technology changes in terms of thinking about how it applies to me. So, absolutely, there is a mindset shift. And I think for me, the hardest part, it's a lot less flexible than Excel, right? In Excel, you can go and you can just insert O and you can, you know, go and have this cell different to this cell. You can apply one format in here and show a currency value, and then in your gross margin, you can show a percentage value. And it's just easy to do. It's just flexible. In Power bi, it's not so flexible, right? What I would argue is actually that flexibility, the lack of flexibility in Power bi. I think I said this in my talk and you know, the lack of flexibility in Power BI compared to Excel is not a bug, it's a feature. Right? It's that it allows you to have some of that discipline because. And again, it's similar to like Excel, when you go from just using Excel in a very ad hoc fashion to trying to apply financial modeling principles and doing things in a much more structured fashion. It's. There's that friction and there's things you have to learn and you're like, do I really need to do it like this? I can't. I just, you know, put in, you know, having consistent formulas or just put in a cell value actually know to have that discipline, you need to actually be able to learn how to do things in a different way. And I think if you're used to just using Excel, how you've always used it, and then you're going to use a tool that's a lot less flexible. It takes, it's that learning curve of thinking about, well actually there's a reason it's less flexible. And actually that reason is less flexible is probably a good thing.

Sure. No, it's by design. I get it. But it is definitely adjustment for people. I want to talk just for a second on visualizations before we move on to the next section here. So obviously building dashboards, building visualizations, graph charts, all that is a huge part of Finance and FP&A. Any tips, you know, things we should avoid to make sure our dashboards are actually being used because I'm sure you've seen it. Many, many dashboards are built. You'll look six months later like, oh, 10 people have looked at it. Why did I spend two days building this?

Oh yeah, absolutely. I mean I've been there. My stuff that I've built rolled out to 10,000 people and yeah, doesn't just doesn't get the adoption. And I think that that is the key. Right. If you're trying to build something that's all things to all people, it's unlikely to serve anyone's particular needs. Right. So the first thing I'd say is absolutely start with the story, start with the audience, start with the insight, start with the problem statements like what decisions need to be made, what is the key tension there that they, you know, that they need of data to help make data driven decisions. So really identify the very specific audience it's for and speak to those people and really understand and go into not just, you know, don't just ask them what do you want to see? Because they'll just say, oh, just give me the same report I had in Excel but make it look prettier. Or you know, I want to see a line graph or a bar chart. That's not the kind of level of detail you need to get to, you need to get to the insights and what, what information do you need to know and what are you going to do about that information? Because that's what's, how are you going to evaluate a number when you see it? Because that's the key to data visualization is context, right? It's also the key to Gen AI is context, right? If you just showing a number on a dashboard, you know, we made a million dollars last month, is that good or bad? Well, it depends, right? It depends on what it was last year, depends on what the budget number was. So how are you going to look at a number and evaluate whether that performance is good or bad? And that's where you need the context. So how are you going to be able to evaluate it? What's the context we need to show here? Those are the kind of insights that you need to get up front and that will, if you bake those into your report, it will be much, much better. The next thing is thinking about again, data visualization, right? Reducing cognitive load, not using things like color just by default as creating a chart and you have all these rainbow color charts because they don't help people to be able to understand the data and what it's telling them. So actually using color really sparingly and using it to draw attention to things that you want to draw attention to that are important, you know, making sure you apply some of those principles and also just thinking about that whole user journey, right? What are the users going to do? How are we going to provide, you know, a user experience to go from a top level number down into the detail, right? So providing those drill through experiences, for example say from an income statement into underlying journals or transactions like those kinds of things I think are the things we need to really think about and make sure we build in makes sense.

I want to move on to a section we call this kind of the where I asked some FPA questions. I've tweaked it a little bit for you, but there's four questions here. First one is a yes or no pie charts. Should we use them?

I mean it's okay if it's like one or two categories and you just want to show, you know, Overall, yes or no, you know, and show a high level number. I mean, generally it's not the best way to interpret data, especially if you've got more than two or three categories.

All right, I'm going to count that as a no, but I get it. All right. What do you think is the number one technical skill that FP&A professionals need to master for their job?

Well, I mean, technical skill, I think we've said power query is a key one. Right. And being able to use that to clean data and shape data. Right. Because it's the foundation for everything else. If your data is clean and structured well, you know, everything else becomes much easier. If you don't structure your data well and it's not clean, you will spend a lot more time doing the data modeling than the dax. It'll be more complicated, it'll be much harder to tell that story. Everything else, Genai will struggle with it. All of those things, you know, need that. Right. Data foundation. So technical skill. Absolutely. Power query, I think, and then data modeling, they're both in the top two.

So basically being able to understand and work with data. Yeah, it kind of, I just lump it together. I get it. There's the tools. Okay, that's helpful. What about softer human skill? What do we need to master?

Yeah, so absolutely it's about understanding. You know, again, it's not just data visualization isn't just about taking what you have in Excel and making it look pretty. Right. It's about being able to really get to the insights, to be able to answer the questions that your stakeholders need answering. So really being able to understand what those insights are, what those business questions that need answering from a reporter and then being able to translate those into data visualization, for example. So it's really about understanding the strategic insights and how that information is going to be used, how is it going to drive actionable insights and then, you know, being able to communicate that in a way that allows it to be able to, to get to those insights in the easiest way possible. So again, reducing cognitive load. But until you know what you're trying to get to, it's very hard to do that.

And so next one, what's the best piece of a career advice you've ever received?

I think it's, it's really about trying to, to get empathy with your customers and stakeholders. Right. Rather than trying to kind of be the best technical person and to try and, you know, do things faster or to, to try and, you know, build, build the best, you know, reports you could Do I think it's really about that, meeting people where they are. Right. So if you're in a technical consulting role, for example, you know, your stakeholders might not necessarily care about the features and capabilities of these tools. They care about their world. They care about their world of, you know, making decisions and you know, getting, getting insights and being able to drive, you know, reduce re. Reduce costs, increase revenue, reduce risk. Those are the things that people care about. So being able to translate what you do into the things that those people care about so you know, that's that empathy. It's that meeting people where they are. I think that's probably some of the best advice I think I've had before.

It's funny how often people mention empathy, you know, in different questions. And here, here we are mostly talking on what I'd call a more technical topic. Not technical, but you know, for Finance and FP&A people learning data modeling, learning power query. These aren't soft, isn't a soft skill topic. Right. But yet you still bring up empathy. I always find that fascinating. It's amazing how important that is to any job we do. But I think especially FP and A when you have a lot of business partners. So I appreciate that answer. All right, we now have the get to know you section. That's where I get to ask you a couple questions a little more personal. So tell me about a favorite hobby or passion. What do you like to do in your free time?

Free time's a bit of a weird concept for me at the moment. It's, you know, obviously there's work but.

I thought, I mean with the two year old you had running around earlier. You're busy.

Yes, I've got a baby, so yeah, that's restricted free time quite a lot. But, but also, I mean it's, you know, I do a lot of stuff kind of related but you know, not technical work. Right. To be honest, I don't do a huge amount of technical work even in my job right now, but even outside of that. Right. For me doing things like creating content. Right. Like videos and you know, I just played around with Synthesia, you know, to create interactive videos and things like that. Like that kind of stuff I really enjoy doing and it's, it's definitely a passion. So you know, EdTech, you know, having that being, being a bit entrepreneurial and trying to build, create stuff and you know, put it out there and you know, I put a lot of time and, and, and money into my websites and things like that, like those kind of things. For me are a passion. I mean, outside of that, you know, I, I enjoy kind of been learning to play piano for a long time and, you know, just using the apps to do that. Enjoy traveling, you know, going to the gym and stuff like that as well. So. Yeah, I mean, lots of, lots of different things, but yeah, absolutely. I really enjoy the kind of content creation and, you know, business side of things as well. Awesome.

Well, you do a lot of it. You do a good job. All right, so this is. I chose this one since we were talking visualization bi to have a little fun. I haven't ever asked this question before, so we'll see how it lands. If you had to pick a chart to represent your life journey, what type of chart would you pick and why?

I'm going to say a waterfall chart.

Elaborate. Why a waterfall? You didn't say a pie chart, so that's good.

No, I didn't say a pie chart. This a pie chart. I mean, life is not all about proportions, I think. Waterfall charts, I think, are a very good way of representing that bridge. Right. From where you are at one point in your life to where you are in the other point of life. Right. And that's actually, that's not actually how waterfall chart really works in. In power bi by default. So you need to actually do a bit of. A bit of trickery to get it to work like that or you use like sebr BI or something. But essentially, I think that whole idea of a waterfall bridge chart of saying, okay, this was my balance or my, you know, opening period balance or, you know, prior period balance or whatever it was, this is my starting point, this was my endpoint, and this is what's led me from there to there. This is what contributes to that difference. And I think actually being able to represent your life in that way, I've never tried it, never used a data set that has something like that. But I think that would be a really interesting way of kind of saying, okay, in my 20s and my 30s, you know, here's where it went from an accounting career into a bi career. And these are all the things that, you know, contributed to that and their ups and downs. Right. And I think that's the whole thing with waterfalls as well. Some things are positive, something negative. And overall, you see where you are here, where you are there, and you've gone up and gone down, then gone up, then go down and. Yeah, I think, I think that would be a quite cool way to visualize a life journey.

Yeah. And I'm trying to think so let's, let's play with this for a second because I think it's kind of interesting. We'll just go for a minute. Say you're doing from the year 20 to 30.

Right.

So you're starting your water fault with year 20. You're 30, you know, do you. Because you're going up 10 in the sense. If you're thinking of this mathematically what do you show as down vs up? Like how do you group? I think it's a fascinating idea and it almost feels like you just have to have that be up and show the things that you know, went well in life, like lost a job and it's a down. Like it'd be really hard to figure out how you mathematically represent all of it. But I think you could easily do the idea of a waterfall chart to show, hey, I progressed from here to here and here's the things that help me progress. Right?

Yeah. And I think it's quite, it'd be quite encouraging to see your second bar being higher than your first. Right.

Yeah. It'd be a real problem if you showed here's where I started, here's where I finished.

Yeah. But also to show that downs are fine because you know they're balanced overall by the ups. Right. The ups take you up there and then the jump into the up into.

Level and well, I'll look forward to seeing your, your power bi life, the Rishi Life waterfall chart. When you build it. Let me know, I'll share it.

Sure, sure. Sounds good.

Last question before we head up. We just have a wrap up question. So last get to know you. If you could have any person's job in the world for one week, who or what job would you pick and why?

Maybe a CFO of a company that's really kind of data driven. Right. Because I really want to see how, how you really bring these worlds together. Right. At a really top strategic level on a day to day basis. Right. Like I say, I typically work a lot with kind of IT teams in the kind of enterprise world and then maybe with you know, finance professionals on more of a kind of B2C and individual basis. Right. But I think actually being able to, to actually be in that position off that, you know, bridge of, you know, technology and finance and, and be there, I think that would be a cool role to do. I don't know if a day would be enough there. Maybe if it's a day I'd pick something more interesting. Maybe if a day I'd pick, I don't know, maybe Maybe I'd pick Satya's job for a day. Satya Nadella.

You know, that would be a fascinating.

One for the CEO of Microsoft for a day. Yep.

Well, maybe you could be the CFO for a week and the CEO for a day.

There we go. Come on both. There you go.

So tell our audience just kind of the services you offer, how they can contact you or learn more about you and what you offer.

I've got a website, rishisuppla.com that's just kind of a personal kind of portfolio website. I've got lots of solutions on there and links on there to kind of some of the communities and things that I run. Right. So I run kind of three main kind of brands if you like, under there. So there's Learn Data Insights, which is kind of the overall color brand and that's just kind of pointing people to kind of various different material. And then power platform finance, obviously for this, very relevant for this audience. For the, for the finance. I've got a PPF accelerator program, say cohort based training shot to lead with elearning, like 20, 30 hours of elearning to support that as well. And then microsoftfabrictraining.com or msfabrictraining.com, which is all around the kind of analytics engineer journey. So kind of helping people really understand things with that break. So yeah, I've done lots of stuff like quizzes like exam practice questions and then you know, E learning courses, like interactive elearning courses. I'd say that's the kind of stuff I really just get a buzz out of creating. It's just, it's, it's cool stuff to try and bring some of these, you know, technical topics which can be quite dry in certain areas and bring them to life with kind of, you know, interaction and you know, E learning and things like that.

Thank you so much for joining me, Rishi. It's been great chatting. I know our audience will learn from you and I think, you know, Power, bi, Power, Query Data, all great tools to have and being able to bridge that gap between it and finance is important and how to bring AI into all that. So thank you for spending a few minutes with me. I really appreciate it.

Great.

And I'm sure my audience as well. So thank you Rishi.

Speak soon. Thanks so much.

That's it for Today's episode of FPA Unlocked. If you enjoy FP&A Unlocked, please take a moment to leave a five star rating and review. It's the best way to support the FP&A guy and help more FP&A professionals discover the show. Remember, you can earn CPE credit for this episode by visiting earmarkcpe.com, downloading the app, and completing the quiz. If you need continuing education credits for the FPAC certification, complete the quiz and reach out to me directly. Thanks for listening. I'm Paul Barnhurst, the FPA guy, and I'll see you next time.