Power BI and a Creator Mindset Are Essential for FP&A Teams to Replace Excel with Rishi Sapra
In this episode of FP&A Unlocked, host Paul Barnhurst sits down with Rishi Sapra to explore how finance professionals can leverage business intelligence tools like Power BI to drive better decision-making. Rishi discusses how the role of FP&A is evolving with technology, and why it’s essential for finance teams to not only consume data but to create and model it in ways that deliver actionable insights.
Rishi Sapra is a Group Manager at Avanade, a global technology consulting firm, and a Microsoft Most Valuable Professional (MVP). With over 20 years of experience in major firms such as Deloitte, KPMG, HSBC, and Accenture, Rishi combines his financial expertise with cutting-edge data and AI solutions. Rishi is also the founder of Power Platform Finance, where he runs an accelerator program to teach finance professionals how to use tools like Power BI, Power Query, and semantic modeling to transform business data into actionable insights.
Expect to Learn:
Why learning Power Query is a must-have skill for every finance professional
The mindset shift from being a consumer of data to becoming a creator of data solutions
How to build simple, effective data models and dashboards using Power BI
Tips for applying semantic models and data storytelling in financial reporting
How AI and business intelligence tools are changing the role of FP&A professionals
Here are a few quotes from the episode:
“As a finance professional, you need to understand not just the data, but how to create the solutions that bring out insights from it.” – Rishi Sapra
“It’s less about learning every tool, and more about understanding the fundamentals that remain the same, regardless of the software.” – Rishi Sapra
Rishi Sapra highlights the importance of shifting from being a consumer to a creator of data solutions within finance teams. By mastering tools like Power BI and embracing a mindset of data storytelling, finance professionals can unlock actionable insights and drive meaningful change. Rishi’s advice empowers finance teams to not just adapt to technology, but to lead the way in transforming business intelligence.
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Explore Campfire today: https://campfire.ai/?utm_source=fpaguy_podcast&utm_medium=podcast&utm_campaign=100225_fpaguy
Follow Rishi:
LinkedIn - https://www.linkedin.com/in/rsaprano/
Website - www.rishisapra.com
Company 1 - www.msfabrictraining.com
Company 2 - www.learndatainsights.com
Company 3 - www.powerplatformfinance.com
Earn Your CPE Credit
For CPE credit, please go to earmarkcpe.com, listen to the episode, download the app, answer a few questions, and earn your CPE certification. To earn education credits for the FP&A Certificate, take the quiz on Earmark and contact Paul Barnhurst for further details.
In Today’s Episode:
[02:04] - Rishi’s Career Journey
[04:41] - Career Expectations After Accounting
[07:19] - Becoming a Microsoft MVP
[11:40] - Why Finance Needs Power BI
[14:04] - Shifting from Consumer to Creator
[26:21] - Best Ways to Learn BI
[33:13] - Integrating BI into FP&A
[38:55] - Dashboard & Visualization Tips
[44:27] - Best Career Advice
Full Show Transcript
[00:01:07] Host: Paul Barnhurst: Are you tired of being seen as just a spreadsheet person? Well, others get a seat at the table. Well, then, welcome to FP&A Unlocked where finance meets strategy. I'm your host, Paul Barnhurst, the FP&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&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&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 Sapra, to the show.
[00:02:02] Guest: Rishi: Thanks very much. Great to be here.
[00:02:04] Host: Paul Barnhurst: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. 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 at Avanade and Accenture, a Microsoft JV, focusing on Microsoft Fabric solutions, governance frameworks, and enterprise migrations. With over 20 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, allowing learners to apply it effectively to their own data and processes. Really excited to have you. I 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 CA, but you spent much of your career working with data and BI. So how did that transition happen? How did you go from accounting to data and BI?
[00:03:42] Guest: Rishi: Yeah, sure. I mean, there 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 first started when I was, I was at HSBC doing product control and, you know, it was um, it was, you know, doing Parnell's Daily Parnell's and in Excel. And I remember getting quite interested in automating that with VBA and, you know, trying to work on those solutions for automation. And I think my manager said, well, this looks like something you're really interested in. Why don't you? Why don't you do more of that? And so I did and I left and, and joined Barclays to do process automation and then financial modeling at KPMG, which was kind of that hybrid between, you know, the Excel financial modeling world and data and, and obviously the accountancy. And then from there, you know, really got into Power Query and Power Pivot and then joined a BI consultancy after a few years to actually focus on this more, 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.
[00:04:41] Host: Paul Barnhurst: Did you ever picture that happening or what was 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?
[00:04:49] Guest: Rishi: 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 600. 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.
[00:05:15] Host: Paul Barnhurst: 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.
[00:05:21] Guest: Rishi: Exactly. But, yeah, I mean, that's the great thing around, you know, the opportunities that 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 is just a great skill to have.
[00:05:43] Host: Paul Barnhurst: I agree, understanding finance and accounting can be incredibly valuable no matter what you do. With you there. Have you always had a passion for this 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 played with the newest technology or kind of how did you develop that? Uh.
[00:06:08] Guest: Rishi: I do really wish I learned programming. You know, when I was younger and actually started to learn, you know, software and things like that. And I did it really. I mean, actually, my dad did actually run a software company doing software for care homes and hospitals, but he wasn't technical at all himself. He just had teams in India to build the software. I mean, I think when I was a kid, I used to do hardware, you know, I used to like taking apart machines and, you know, putting stuff together again in the hardware. 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 up and things like that, but not really. I didn't really get into programming or web development or things like that. And, 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 as 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.
[00:07:07] Host: Paul Barnhurst: 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, early in my career, pick up a little bit of Python and some of those types 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 it is. Maybe tell our audience a little bit about that?
[00:07:31] Guest: Rishi: Yeah, sure. So I mean, MVP's I mean you had yourself as well, right? It's um, 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 what users are saying. They get access to early releases of the products and help shape the direction. So you know those product teams at Microsoft who build products like power BI and fabric, you know, they're always after feedback and, you know, insights into how it's being used and you know what works, what doesn't work. And they have a few channels for that. But, you know, 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, um, you know, they're able to get that feedback from the kind of technical influencers 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 role. And it's not actually based on your technical skills. Is based on your community engagement. Your contributions to the community, whether that's speaking at conferences or blogging or videos. And, you know, I tried all of those things in the past to varying 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. Um, so it's much more about that than necessarily the pure metrics or technical experience.
[00:09:24] Host: Paul Barnhurst: 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 to 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?
[00:09:53] Guest: Rishi: 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. Um, you know, so it's more just about for me, you know, doing community contributions is really one of my main ways of learning this technology, right? Rather than just there and consuming, you know, blogs and videos. You know, I actually learn by doing and I learn 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 can 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 out in the community, get feedback on it and see how I teach other people. And that's really, for me at least, the best way to learn. So that's kind of why I really got into it. That was 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, you know, build stuff and learn or share your knowledge, um, just do it. And, you know, 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.
[00:11:15] Host: Paul Barnhurst: I think that's great advice. If you enjoy sharing, you enjoy community, 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&A professionals. Right. There's lots of 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 FP&A professionals. He said one of the biggest things they ask for is either power BI or Tableau experience. But when you hear that, what do you think? Is that what you're seeing or what's your thoughts on that?
[00:12:05] Guest: Rishi: I mean, I could see why, especially for FP&A , because FP&A professionals are strategic partners of the business, right? They're not data junkies. They're not people who just produce some numbers and then, you know, send it off in an email and, and hope that people understand it. Right. To really have that impact, to be able to do the planning and and analysis, it needs to be actionable insights. And that's quite difficult to do with static reports. Those traditional kinds of 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. And that's what power BI and Tableau allow you to really do. Go from 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 changes 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, you know, to be able to use Power Query for some of those automation capabilities to 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 kinds of analytic roles, why these tools are, should have or even a must have. I think it is a kind of hires.
[00:13:52] Host: Paul Barnhurst: I almost thought I was going to get through an interview without hearing the word Jen. I think there's.
[00:13:57] Guest: Rishi: Such a chance, but.
[00:13:58] Host: Paul Barnhurst: 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, they're reporting.
[00:14:25] Guest: Rishi: Not as much as I'd like, if I'm honest. I think I still work primarily, at least, you know, in Avanade Accenture. 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 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 need 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. 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, in my career and in my role and, you know, in, 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 my data to be able to create the analysis, to be able to create insights, to be able to create solutions and models that can drive forward an organization.
[00:16:21] Guest: Rishi: 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, you know, I'm sure about 95% of them are using pure consumer mode. Give it a prompt. Hope it gives you the answer. If it doesn't, you know that's the 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 the mindset first.
[00:17:16] Host: Paul Barnhurst: Interesting. So, you know, you've kind of outlined the difference between those that consume by AI whatever and those who create solutions. So in your mind, for the average FP&A professional now 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, 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&A professionals to dive down the the rabbit hole, so to speak.
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[00:19:04] Guest: Rishi: Sure. I mean, I think 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, right? Power BI comes out with new features, and power BI and fabric come out 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. And those fundamentals are 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 with it in Excel. Different way of thinking about your data. Even how you work with Excel. And it's different to 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 that 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.
[00:20:16] Guest: Rishi: 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 how query essentially and how to you need to know what you want to end up with. You need to know the data structure semantic model, star 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 Power Query. And Power Query is absolutely somewhere I'd really suggest professionals start because it's an Excel. It's where they're already familiar. So just they get data experience in Excel, Power Query uh 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 understanding 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. Right. Understand the core concepts of data visualization, storytelling.
[00:21:25] Guest: Rishi: It's all about. I think you had Andre on recently, didn't you, Andre? And yeah, you know, data visualization is all about reducing cognitive load. It's all about making those insights obvious. You know, is 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 as the 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, we're 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 I can sit on top of it. All of those kinds of benefits you need to establish first and then, you know, learn the foundations.
[00:22:31] Host: Paul Barnhurst: 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 into FP&A for a year and a half, I did a master of Science in Information Management with an MBA, so I added 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.
[00:23:33] Host: Paul Barnhurst: So I agree with you. You know, once you go to data models, you're a little more star schema snowflake. It gets a little more. You want to call it technical, I don't know. 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 is, 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.
[00:24:19] Guest: Rishi: Absolutely. And actually it's interesting because I think the principles of good financial modeling are the same principles of power BI, really. You know, it's that separation of logic and, you know, inputs, logic and outputs. And actually power BI does that almost automatically, right? With your, your Power Query, your reporting layer and your semantic model layer. Right. Your logic. So I think actually, you know, that's some of those principles. And also the other thing I'd say is that 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 will really help because you could really put yourself in the shoes of those 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 be able to interpret, you know, from an interview, go from an interview into a set of questions and insights and then be able to design a model out of that. 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 FP&A professional can bring to it as well.
[00:26:04] Host: Paul Barnhurst: 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 professional needs to be good at. Whether it's a financial data model someone wants to learn, you know, power BI and I'm talking more about the tool than the requirements gathering. Where would you recommend they start? Do they start with a Learning Power Query? Do they start with the 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.
[00:27:55] Guest: Rishi: 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, um, to keep people motivated and also just to give that opportunity to try things so that it's all exercise based. It's all labs based, 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, and it starts to just start off and just go in and put data in and start to use.
[00:29:19] Guest: Rishi: It can be quite challenging, but just going off and trying to learn power BI again, it's an absolute firehose of information. It's overwhelming. There's so much stuff there. So I would really recommend doing. Yeah of 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 using income statement reporting like month end board pack type reporting in power BI. You know, 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 3D visualization. So those four weeks, those are the four weeks we kind of cover. 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 data and processes. So 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.
[00:30:34] Guest: Rishi: They just have different expectations about what it is. They think it's a data visualization tool or it's, you know, and when I try and explain all these things to power BI, some of them look at me like, why are you overcomplicating? It's just an Excel on steroids. Just a 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 own 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 lot of 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 switched 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 check on what you're doing or when you get stuck.
[00:31:38] Host: Paul Barnhurst: 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.
[00:31:47] Guest: Rishi: I think it's definitely to get those foundations right. So you're talking say language and then it's all about application, right? I mean, 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 bring 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.
[00:32:35] Host: Paul Barnhurst: I remember learning it and I definitely at times wish I had more support. You know, I did it through books, but I had done report writing before I'd used it to access databases 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 a 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.
[00:33:11] Guest: Rishi: 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 the tools that we've got available and, you know, 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're talking 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 could 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 there, and that will provide some of that motivation to go on that journey.
[00:34:17] Host: Paul Barnhurst: 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 now is 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&A is my job. I need to learn some B.I. I need to be able to build some dashboards. I need to be able to help work with it. Kind of. Any advice on how to balance the two?
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[00:36:08] Guest: Rishi: 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 some people who will sit there and watch power BI and fabric videos on the weekends, but I imagine the vast majority of professionals wouldn't. So, um, 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, in your role? What would allow you to do? 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 to 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. Now once you start applying it, then it becomes part of your role rather than this separate thing that you need to try and learn on the side.
[00:37:24] Host: Paul Barnhurst: What was the hardest part for you when you first learned power BI? What was the hardest part of making that transition?
[00:37:29] Guest: Rishi: 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, is incredible, right? I especially think that with power BI first came out for those first ten years, that power BI has been out. It's been, you know, so many features, like every week or every month, there'll be, you know, 20, 30 features in 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. And Excel, you can go and you can just insert a row and you can, you know, go and you know, have this cell different to this cell. You know, you can apply one format here and show a currency value.
[00:38:43] Guest: Rishi: And then your gross margin, you can show a percentage value. And it's just easy to do. It's just flexible. Um 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 and compared to Excel is not a bug. It's a feature, right? It allows you to have some of that discipline because and again, it's similar to 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. 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, then you're going to use a tool that's a lot less flexible. 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.
[00:39:55] Host: Paul Barnhurst: Sure. No, it's by design, I get it, but it's definitely an 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 look six months later, you're like, oh, ten people have looked at it. Why did I spend two days building this?
[00:40:28] Guest: Rishi: Oh, yeah. Absolutely. I mean, I've been there myself. Stuff that I've built got rolled out to 10,000 people. And yeah, it just doesn't get adopted. 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 insights. Start with the problem statements like what decisions need to be made? What is the key tension there that they need some 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, um, 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 information do you need to know, and what are you going to do about that information? Because that's how you are going to evaluate a number when you see it? Because that's the key to data visualization is context. It's also the key to Jenny's context, right. If you just show a number on a dashboard, you know, we made $1 million last month. Is that good or bad? Well, it depends, right? It depends on what it was last year.
[00:41:48] Guest: Rishi: It 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 if you bake those into your report it will be much, much better. The next thing is thinking about data visualization again. Right. Reducing cognitive load, not using things like color just by default. That's creating a chart. And you have all these rainbow colored 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 drills 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 and make sense.
[00:43:06] Host: Paul Barnhurst: But I want to move on to a section we call this kind of where I ask some questions. I've tweaked it a little bit for you, but there's four questions here. The first one is a yes or no. Pie charts. Should we use them?
[00:43:20] Guest: Rishi: I mean, it's okay if it's like 1 or 2 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 2 or 3 categories.
[00:43:36] Host: Paul Barnhurst: 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.
[00:43:47] Guest: Rishi: Well, I mean, technical skill. I think we've said Power Query is a 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. Gen AI 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 both in the top two.
[00:44:26] Host: Paul Barnhurst: So basically being able to understand and work with data. Yeah it kind of lump it together I get it. The tools are okay. That's helpful. What about softer human skills? What do we need to master?
[00:44:37] Guest: Rishi: 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 it is going to drive actionable insights. And then 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.
[00:45:31] Host: Paul Barnhurst: And so next one what's the best piece of career advice you've ever received?
[00:45:36] Guest: Rishi: I think it's really about trying 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, um, you know, build, build the best, you know, reports you can 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 insights and being able to drive, you know, reduce, um, 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 and say, you know, that's that empathy. It's meeting people where they are. I think that's probably some of the best advice I think I've had before.
[00:46:44] Host: Paul Barnhurst: It's funny how often people mention empathy, you know, in different questions. And here we are mostly talking on what I'd call a more technical topic, not technical, but, you know, for finance and for people learning data, modeling, learning Power Query, these aren't soft skills, 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 for when you have a lot of business partners, so I appreciate that answer. All right. We now have the get to know You section 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?
[00:47:24] Guest: Rishi: Free time is a bit of a weird concept for me at the moment. It's, you know, obviously there's work, but I.
[00:47:29] Host: Paul Barnhurst: Mean, with the two year old you have running around earlier, you're busy.
[00:47:32] Guest: Rishi: 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. 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 at Avanade and Accenture, a Microsoft JV, focusing on Microsoft Fabric solutions, governance frameworks, and enterprise migrations. With over 20 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, allowing learners to apply it effectively to their own data and processes. Really excited to have you. I 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 CA, but you spent much of your career working with data and BI. So how did that transition happen? How did you go from accounting to data and BI?
[00:48:39] Host: Paul Barnhurst: Awesome. Well, you do a lot of it. You do a good job. All right. So I chose this one since we were talking about visualization 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?
[00:48:58] Guest: Rishi: I'm going to say a waterfall chart.
[00:49:02] Host: Paul Barnhurst: Elaborate. Why a waterfall? You didn't say a pie chart, so that's good. No it.
[00:49:06] Guest: Rishi: Is. A pie chart is 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 really works in, in, in power BI by default. So you need to actually do a bit of trickery to get it to work like that. Or you use like bi or something. But essentially I think that whole idea of a waterfall bridge chart saying, okay, this is 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 end point. And this is what 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. I've never used a data set that has something like that. But I think that would be a really interesting way of saying, okay, in my 20s and my 30s, you know, here's where you went from an accounting career into a PI career, and these are all the things that 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, some things are negative. And overall you see where you are here, where you are there and you've gone up and gone down and gone up then gone down. And yeah, I think, I think that would be quite cool way to visualize a life journey.
[00:50:28] Host: Paul Barnhurst: Yeah. And I'm trying to think so 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 waterfall with year 20. You're 30, you know, do you? Because you're going up ten in the sense, if you're thinking this mathematically, what do you show as down versus 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 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 helped me progress, right?
[00:51:13] Guest: Rishi: Yeah. And I think it'd be quite encouraging to see your second bar being higher than your first. Right?
[00:51:19] Host: Paul Barnhurst: Yeah. It'd be a real problem if you showed. Here's where I started. Here's where I finished.
[00:51:24] Guest: Rishi: 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 to jump up and.
[00:51:35] Host: Paul Barnhurst: Well, I'll look forward to seeing your power bi life. The Ricci life waterfall chart. When you build it, let me know. I'll share it.
[00:51:44] Speaker6: Sure, sure. Sounds good.
[00:51:46] Host: Paul Barnhurst: Last question before we head up, we just have a wrap up question, so let's 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?
[00:51:58] Guest: Rishi: Maybe a CFO of a company that's really kind of data driven, right? Because I really want to see 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 different IT teams in the enterprise world, and then maybe with, you know, finance professionals and more of a kind of B2C and individual basis. Right. But I think actually being able to to actually be in that position of 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 there is a day I've picked, I don't know, maybe. Maybe I've picked Sasha's job for a day. Satya Nadella you know.
[00:52:47] Host: Paul Barnhurst: That would be a fascinating one for the.
[00:52:49] Guest: Rishi: CEO of Microsoft. Per day.
[00:52:51] Host: Paul Barnhurst: Yep. Well, maybe you could be the CFO for a week and the CEO for a day. There we go.
[00:52:56] Guest: Rishi: There you.
[00:52:56] Host: Paul Barnhurst: 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.
[00:53:04] Guest: Rishi: I've got a website that's just kind of a personal kind of portfolio website. I've got lots of solutions there and links there to some of the communities and things that I run. Right. So I run three main kinds of brands if you like. So there's Learn Data Insights, which is kind of the overall kind of brand. And that's just kind of pointing people to kinds of various different materials 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 e-learning like 20 30 hours of e-learning to support that as well. And then Microsoft Fabric training or Ms. fabric training, which is all around the kind of analytics engineer journey. So kind of helping people really understand things with fabric. So yeah, I've done lots of stuff like quizzes like exam practice questions and then, you know, e-learning courses like interactive e-learning courses. I'd say that's the kind of stuff I really just get a buzz out of creating. It's just 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 e-learning and things like that.
[00:54:15] Host: Paul Barnhurst: 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 finances are 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 audiences will. So thank you. Rishi.
[00:54:38] Guest: Rishi: Speak soon. Thanks.
[00:54:40] Host: Paul Barnhurst: Thanks, Paul. Thanks, everyone. That's it for today's episode of FP&A 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 FP&A guy, and I'll see you next time.