The FP&A Fix for Finance Leaders to Solve Data Trust Issues using Empathy and Strategy with Ramya
In this episode of FP&A Tomorrow, host Paul Barnhurst sits down with Ramya Krishnaganth, founder of Yuvi Consulting and a leader in finance transformation. Ramya brings a thoughtful and practical perspective on how FP&A goes far beyond numbers; it's about understanding the business, working across departments, and making real-world decisions easier. She shares stories from her work helping companies solve messy data problems, improve cost control, and build stronger financial processes.
Ramya Krishnaganth is an experienced advisor with a background in cost accounting, financial planning, and enterprise transformations. She holds an executive MBA from Wharton and has helped companies across industries build smarter, more responsive finance functions. Her passion is making data more meaningful and empowering teams to work better together not just through systems, but through clarity, communication, and care.
Expect to Learn:
Why great FP&A is about being the “nervous system” of a company, not just reporting numbers.
How a CFO used one simple metric to drive company-wide cost discipline.
Why fixing data issues means looking beyond tech and starting with people and processes.
How to build credibility in finance by solving one problem at a time.
What it means to approach data with empathy and why it changes how you solve problems.
Here are a few quotes from the episode:
“You don’t always need a new system. Sometimes clarity and better definitions solve the problem.” - Ramya Krishnaganth
“Credibility comes when you give people answers they can use, when they need them.” - Ramya Krishnaganth
“Transformations aren’t about technology alone. They’re about making real decisions easier.” - Ramya Krishnaganth
Ramya brings warmth and wisdom to a topic that often feels technical and dry. This episode is a great listen for finance professionals looking to strengthen their influence, better understand how to approach messy data, or simply hear how someone else has helped real companies tackle hard problems. If you’ve ever felt overwhelmed by data or unsure where to start, Ramya’s insights will give you both a fresh perspective and practical next steps.
Corporate Finance Institute:
Master real-world finance skills with CFI’s FMVA program to learn financial modeling, valuations, and strategic insights top finance teams use. Get 30% off any plan and take the next step in your career. Explore now at https://corporatefinanceinstitute.com/pricing-fpaguy/?utm_source=fpaguy&utm_medium=organic&utm_campaign=podcast_ads
Follow FP&A Tomorrow:
Newsletter - Subscribe on LinkedIn - https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=6957679529595162624
Follow Ramya:
LinkedIn - https://www.linkedin.com/in/ramyadurgak/
Website - https://uvidconsulting.com/
Follow Paul:
Website - https://www.thefpandaguy.com
LinkedIn - https://www.linkedin.com/in/thefpandaguy
Earn Your CPE Credit
For CPE credit please go to earmarkcpe.com, listen to the episode, download the app, and answer a few questions and earn your CPE certification. To earn education credits for FPAC Certificate, take the quiz on earmark and contact Paul Barnhurst for further details.
In Today’s Episode
[01:51] - Welcome to The Episode
[05:16] - A CFO’s Smart Cost-Control Strategy
[08:55] - Why Financial Transformation Matters
[13:05] - Why Companies Struggle With Data
[14:32] - Root Causes: People, Process, or Tech
[19:25] - Smart Approaches to Fixing Data
[24:29] - Empathy and Data: What It Really Means
[27:41] - Finding and Solving the Right Problems
[32:48] - Practical Advice for Analysts
[38:42] - Must-Have Skills for FP&A
[43:04] - Ramya’s Personal Interests
[49:01] - Final Thoughts and How to Connect
Full Show Transcript
[00:01:51] Host: Paul Barnhurst: Hello everyone! Welcome to FP&A tomorrow, where we delve into the world of financial planning and analysis. Examining its current state and future prospects. I'm your host, Paul Barnhurst, aka The FP&A Guy, and I will be guiding you through the evolving landscape of FP&A . Each week, we're joined by thought leaders, industry experts, and practitioners who share their insights and experiences, helping us navigate today's complexities and tomorrow's uncertainties. Whether you're a seasoned professional or just starting your journey, this show has something for everyone. This week, I'm thrilled to welcome to the show Ramya. welcome to the show.
[00:02:32] Guest: Ramya Krishnaganth: Thank you Paul. Thank you for having me here.
[00:02:35] Host: Paul Barnhurst: Really excited to have you. So let me give a little bit about Ramya and then we'll jump into the questions. Ramya Krishnaganth, founder of Yuvi Consulting, is an experienced leader in business and finance technology, helping companies improve performance through smarter processes and technology. She specializes in streamlining and automating budgeting, forecasting, and reporting, enabling leadership teams to make faster, data driven decisions with experience across global enterprises and high growth businesses. She combines deep financial expertise with practical technical solutions. She holds an executive MBA from Wharton and professional degrees in chartered and cost accounting from India. Outside of work, she enjoys a variety of interests, including listening to holistic life podcasts such as FP&A tomorrow and competing with her kids in board games, amongst others. Again, welcome to the show! Really excited to get to chat with you today. So here's the question I always like to start with. In your mind, what does great FP&A look like? What does it look like to you?
[00:03:47] Guest: Ramya Krishnaganth: This is always a question, right? Whenever we say FP&A , the conversation revolves around the numbers, the difficulty in looking at the data and all of those. But for me and for many as well, right? The FP&A is more than the numbers. It's deep rooted in the business. And number is the tool. And number is the way you're going to see the business. So how you're seeing the numbers how what is the business you are seeing behind the numbers and how you're connecting it to different departments? That's just one line for me in terms of FP&A , right? But there are many characteristics to that. FP&A in terms of how agile you are, which like every one of us talk about, like your whole episode is like around that, right? Your effort is towards that. Like how agile the FP&A is, how quickly it can answer the questions and more like a very active central nervous system in our body. Right? Like keep track of what is going on, understand the signals, convert it into the information, and then like maybe like being ahead of the competition, like, oh, is there a threat? Should we fight or flight? So that's what we call a scenario analysis. So it's more like a very active nervous system for the organization. That's what I would define FP&A as.
[00:05:02] Host: Paul Barnhurst: I like that I haven't had anyone use that analogy of, you know, kind of that nervous center that activates and helps manage everything and manage the business. I think that's a good comparison. So thank you for sharing that.
[00:05:15] Guest: Ramya Krishnaganth: Sure.
[00:05:16] Host: Paul Barnhurst: And so now I'm going to ask you, can you think of an example, maybe one you've seen or one you've been involved in from your career where you've seen great FP&A in action, like you look at it and oh wow, that's really how FP&A should work.
[00:05:29] Guest: Ramya Krishnaganth: Well, yeah, there are many, right? But one of my recent favorites, I'm going to talk about one of my recent favorites. So this was with one of the OEM manufacturers in the semiconductor industry. Right. So the CFO came in and he knew he decided that, okay, the whole company had okay, in the next 1 or 2 years, we are going to streamline all the operations of the company and have better control over the cost. Right. Which in turn is going to be reflected in the margin. But their focus was how are we going to streamline the whole operations and how the cost is going to be controlled? So the CFO was a big fan of variable cost in that kind of industry. He strongly believed in the variable cost. So he they started aligning everything with the lens of the variable cost. Right. So okay I'm going to look at my labor. So take out the material cost because material cost is out of our control. It is largely determined by market pricing. So look at what the value add we are making on that value add. What is the the labor cost. Right. So put the industry percentage your direct labor. What is the direct labor percentage you are incurring in line with the industry percentage. And then start driving the questions like why is our percentage high? Why are we spending more ? Are we less efficient in terms of productivity? Or if it is less, are we kind of squeezing more out of like people? Right. So do we need to really go on like bring in more headcount? So he started questioning or rather looking at the whole business from this perspective.
[00:07:08] Guest: Ramya Krishnaganth: Right. This is just one example. So every line of every line of the PNL, he started linking that variable cost with the whole objective of bringing the whole operation streamlined and also reducing the cost. He took one lever, just one lever for that period, to bring everything under control. Right. Then he started focusing on other things. But the way he has done it is so amazing. Then this led to a lot of other things which we typically talk about in terms of, okay, there is automation and other things. Okay. How do you need to structure your chart of accounts? So how are you going to bring it and then convert it in the way that you want to look at your PNL. And how are you going to link those levels and then connect it to the metrics that is going to point to the production, your, um, labor efficiency, direct and indirect labor efficiency on all of those. In that way, the team was able to have a very productive conversation with the department heads. Uh, and then give them also like insight in terms of what they should be, uh, looking at. And, uh, even they did similar thing on the material side as well. Right. So they were able to have a conversation. Okay. We see there is an increase in material cost but very limited options, uh, on the vendors that we can go with. Right. So what we can do about it, these are the proactive way of engaging with the business. So this is one of my recent classic, uh, favorites.
[00:08:33] Host: Paul Barnhurst: Thank you. I appreciate you sharing that. And I love how, you know, he went through methodically and looked at everything, understood it, then figured out what the levers were to impact it. I think that's a great example of being very analytical and process driven to accomplish a goal.
[00:08:54] Guest: Ramya Krishnaganth: That's right.
[00:08:55] Host: Paul Barnhurst: So during your career, you spent a lot of time in financial transformations. Why is that? What is it you like about working on transformations and big projects like that?
[00:09:04] Guest: Ramya Krishnaganth: Again, it just goes back to the excitement I was showing in the previous question. So this FP&A which is part of the financial transformation, right? It's a very, uh, rare and unique area within finance where the numbers are connected to strategy. Right? Where the numbers are connected to how your business is operating and impact the decision making in real time. So it starts with like again, we can go to the principle of how we do that. But the whole idea is the reality is this has a direct impact on the decision making. And you can see it happening in real time. Right. Again, like one of my favorites which I keep talking about whenever this kind of situation comes up, is. So he was working with one of the event management companies during the pandemic time. He had to make a decision. Should they conduct the show on the time they originally planned by splitting the show into two different weeks, because at that time these things started slowly opening up. But the county was not allowing so many people to be confined in one place, so only the limitation on numbers. So should they do it in two weekends as per the originally planned timeline, or should they push it out a little bit where everything opens up? Still conducted in the original format, but in a different time frame.
[00:10:24] Guest: Ramya Krishnaganth: So this was a decision that the management had to make within a week's time. So the FP&A team was able to turn around this result within a day's time. Then the management, even before the broader decision making, all the heads had the opportunity to kind of poke holes into that and then come up with different assumptions and other things. And finally they decided, you know what? We are not going to conduct the event. Now we are going to postpone it to a later date where we can do full justice to that event. Right. Like considering the cost and also what is how the people are going to enjoy the event, considering all those like financial and non-financial factors that made the decision. I could literally be part of that and see that within that like weeks time frame, the decision being made and announced and coming out like everywhere, right? So this is what excites me. And moreover, like every customer, every industry and every leader, the goals they have, the challenges they have and the environment in which they operate, they are completely different. So no two FP&A transformations are the same. So this constant change and this, this is what keeps me so excited and interested about this transformation space of that.
[00:11:42] Host: Paul Barnhurst: So kind of took two things away from that. One, that just the challenge is always changing. Different projects, different things so you don't feel like you're doing the same thing day after day. I think we've all been in a job like that. It can be tough. And then the other is seeing the real world benefit of the transformation, whether that's technology, you know, process, whatever it may be, seeing how it allows them to make better decisions for the business.
[00:12:10] Guest: Ramya Krishnaganth: Right, right. One is for the business, Paul. And the other thing, I also look at it as how it is actually making somebody's life easier. Right? Like especially people on the FP&A team, how they feel a lot relieved after having this transformation in place, right? So that is another human aspect which always makes my heart warm, right? So that's another big piece of that which, uh, I love in this whole.
[00:12:39] Host: Paul Barnhurst: I really appreciate you adding that human aspect that's great that you get to see that, you know. So as you talk about transformations, I think one of the big areas that every company struggles with, and you and I talked about this before we, you know, did the podcast today is data. Every company seems to have data challenges. Nobody's data seems to be good a lot of times. I mean there's obviously nobody's perfect. But why do you think so many companies struggle with their data? Why is that?
[00:13:10] Guest: Ramya Krishnaganth: There are some common, common reasons, right? So we often talk about technology. Maybe you have the legacy technology which cannot keep up with the fast changing business needs, which is again forced by the different technological advancements and other things happening in the environment. Right. So that's one reason. But is that the only reason? Not necessarily. Right. So discrete processes are happening right? The way the sales is looking at the revenue and the way the finance team is looking at the revenue. They are completely different. So they have their own definitions and then their own way of creating the customer structure, the way they define the sales structure. And also this is like one part of it. Another part of it is sometimes the culture and the mindset of people as well. Maybe they do not want to share all the information with everybody. Like sometimes hoarding the information that happens sometimes as well, right? So maybe they feel a little insecure or like feel more powerful when they have the data within themselves. So this is also, uh, another reason. So it's a combination of people, process and technology which impacts the data, the data quality or even the availability of data itself.
[00:14:32] Host: Paul Barnhurst: Sometimes I appreciate that there's not one issue, but there usually can group it into people process technology. And I would guess there's typically and I'd love to get your thoughts as you go into companies, is it usually a combination of all three or do you sometimes see where it really is just one. Like maybe it's just technology or just processes or just people. What do you typically see?
[00:14:57] Guest: Ramya Krishnaganth: It's almost a combination. It's only the question of which has a higher percentage. That is going to vary between companies. Like almost always it's a composite problem. It's not one single problem, right? Like most of the time the problem is in the process, right? When we mean by process, it could be a simple process of, as I mentioned, like creating, like who's creating the customer structure and who is following through that. Right. So that's a kind of process problem. And then people's problem is maybe they were entering with some hyphen, some semicolon. Some fields are not filled in. So this kind of thing also happens to some kind of people problem. Right. So it's always a technology like uh yeah. Like depending on which stage they are in it could be a basic technology problem. But if they are a little bit already on the foundational technology, and they may not have the advanced technology to go to the next level, right, because their needs are already to the level next to where they are. Right. So, it's always a mix of everything. It's a composite problem. In my experience. It has never been like one single reason that is contributing to the data problem. So what is your experience, Paul. Right. You definitely have.
[00:16:14] Host: Paul Barnhurst: Let's see in the companies I've worked in, I would agree. You know, I've been in some companies where I say it was mostly technology. I actually I'd say it was all three, but they had really, really old technology for. So for me the biggest problem was technology. But all three were definitely there in the company, you know? But I couldn't do the stuff I needed even if I had good processes and good people, because there are just so many technical challenges. But ultimately, I think this gets back to when you and I talked, you know, if I think about the companies, I looked at the problem. So, you know, process people, technology needed to be fixed. But the reason those became a problem was because the culture and leadership, you know, and I think that's that was really the if we get to the root of the problem, it was often at that level because they weren't putting a priority on data, and they were letting things happen that forced everybody downstream to suffer.
[00:17:12] Guest: Ramya Krishnaganth: That's right. Yeah, definitely. It's more of the accountability and responsibility, of course, goes back to the leadership that you're talking about, right. So how much they are paying attention to that, like how strict they are about how vigilant they are about it. Like so it's mostly the first thing is accountability and the controls. Who's accountable for that And who is going to control that? Right. So that's the biggest problem which actually is a starting point for anything that comes up. Right. Yeah, definitely. That's one. And then the education and training okay. You have the process. You have the accountability and control. Are you having a continuous training mechanism because like data is again it's not the constant thing. You are always like pivoting your business. You're always dealing with changes in the environment. It's going to reflect in your data. Are people continuously educated and trained about those changes to keep up with the data in a good quality in the system, right? So yes, these are the root causes. You're right. Right.
[00:18:12] Host: Paul Barnhurst: Yeah. And you know that that was one company. Others I worked at, I thought they did a good job. And when I was there I saw the commitment where we were doing about a $20 million, you know, transformation of our entire finance office. And there's a lot of commitment around data. And you could see leadership was talking, not just by spending money, but really the way they thought about things. And it was a good example. And then one other company I was brought in really to help with the data. And so you saw the commitment. There was a lot of conversations. I still remember having conversations trying to define what bookings meant. You know, as we try to figure it out. And I really liked their cfo's approach and he said one time he goes, look, before I spend any money cleaning up any historic data, we need to get our processes in order. So we're getting good data for the current. We need to make sure we're on the same page. We got things defined then no problem. I'll go spend the money to clean up the past. So we have a good history. But until we got things working well, I'm not investing anything on our past data because it doesn't make sense. Because we'll just mess it up again. And then I got to pay someone two years from now to come in and fix the same thing.
[00:19:21] Guest: Ramya Krishnaganth: That's a smart approach. That's a smart and a very practical approach.
[00:19:25] Host: Paul Barnhurst: What do you typically see? I mean, do you see companies doing that or do you often see them, you know, kind of trying to fix all the processes and data, everything at once or what's your kind of experience on that.
[00:19:36] Guest: Ramya Krishnaganth: So they come with great ambition. Right. Just to stir the entire ocean in the first go. So this is where we need to go back and educate them. Of course, if you come I would not say it's not about whether they are making us not making a smart decision or not making a smart decision because they were driven by what was demanded from them by the business. Right. So, with that in mind, they probably will come with the suggestion. Okay, let's do all of them together. Right. So when we start having these intricacies, discussion about these intricacies on the challenges we have, then we always like to take a step back and take the very methodical approach. So to your question, is it always. No, always. Not everybody asks for okay, go and do everything. Uh, and especially after the pandemic, right? The interesting thing after the pandemic, you know, like it's been like almost four years, I should not be bringing this up. But like previously before that, the ask has always been, okay, I have like eight and ten years of data in my system. Can you bring all of them in? Right. So can you. Can you cleanse all of that data? But now it has changed. They are saying, okay, before 2020 or 2021 the data is not relevant to us. Right. So let's start looking at only from 20 or 21. Right. So that shifted a lot. Like so it's like a little bit of reset of okay where are you going. Where your starting point is from that perspective, the intensity of that discussion, uh, we didn't need to deal with it like before, but it is going to grow up as we like to move in years. It's the number of years of historical data that is going to increase, right. So yeah it depends. So what agenda they come with, what is required of them. So accordingly the request is going to be.
[00:21:28] Host: Paul Barnhurst: Yeah. And so talk a little bit more about that. You know you mentioned not always a few years do you think I think I know the answer. I think you hinted at this that we'll just continue. So 2021 is kind of that cut line. And as long as there's no, you know, big pandemic or something that totally alters the data, we'll just get back to where we were before. So they'll start asking for, you know, six years, then seven years, then eight years. Or do you think there's been a little bit of shift in mindset and going, what do we really need? Do we need eight years? Can we get by with just four? What do you think?
[00:22:04] Guest: Ramya Krishnaganth: So it again, like I'm not giving a typical consultant answer, but this is what I'm seeing with the customer.
[00:22:11] Host: Paul Barnhurst: And I appreciate that. That's what we want. You're not going to give me the consultant. It depends.
[00:22:17] Guest: Ramya Krishnaganth: It's not a consultant. Depends. It's the industry.
[00:22:20] Host: Paul Barnhurst: Yes.
[00:22:21] Guest: Ramya Krishnaganth: So the trend is if you are dealing with large enterprise customers, right? So they are driven by a lot of, uh, data policies, data requirements and other things. So whether it is relevant from the business decision standpoint or not, they would still want the.
[00:22:43] Host: Paul Barnhurst: Regulatory type.
[00:22:45] Guest: Ramya Krishnaganth: Stuff, regulatory stuff. Right. So that kind of data, the only conversation there we have is okay, you need that. Like since I'm dealing with FP&A , then we will get into a discussion of do you want it in the FP&A area. Right. You still can archive it. You can still have it, but you really want it in the app to FP&A , um, like report or model what whatever we call it in the technology terms. Right. So where you are working is it needed? Right. That's a conversation we are trying to have. But still the tendency is like sometimes since they know like they kind of like given a mandate okay, you need to have eight years of data in your system. Right. So that kind of drives a lot of that conversation. That's why it depends if it's a larger enterprise customer, there is if you are dealing with fast growing companies where they are not like they make decisions very quick and they have access to every department, like in a much easier way than the enterprise department. So most of them, they are like okay with okay, these data make sense. I'm okay to archive this data or not bring them or put effort in transforming all that information. Right. I'm the for me, what I'm looking for from the standpoint is to drive better business decisions. Right. What is going to like coming up and how I'm doing today. So from that perspective, uh, they are okay with having just like starting with one year of data. That's good for me because I know my business has changed a lot. I have all the data in my other environment. I know I don't need them for FP&A . Right. So there are customers depending on where they are coming from and what they are using the data for, how they are looking at. So this is also happening. So there is no one single trend but large enterprises. They tend to ask more data for sure.
[00:24:29] Host: Paul Barnhurst: Sure that not not surprising. That totally makes sense. So I want to kind of shift gears a little bit. But you had previously said to approach data with empathy. What did you mean when you said that? What does that mean?
[00:24:42] Guest: Ramya Krishnaganth: I'm a big, big it's a big word to use, right? I'm more inclined towards spirituality, right? That's why I start looking at everything with a little more empathy. So when I, when I made that statement, we always have every conversation you have, whether you are like even why you have to do a transformation. So why do you need to do that? Why do you need to do automation like everything? Because what do you say? Like what is your first first pointer to bring up and talk about. Right. This is going to help get the right data. Right. So your data is going to clean up your data. Right. Maybe that's true, but is data the real problem? Data is just just the um it's a footprint of what you are doing. Your other activities like how people are like what activity people are doing in the organization, what processes you are carrying out. So data is just an outcome of that. So they think okay, by doing something the data is going to miraculously become so qualitative, right. So that's why I said I like to approach data with empathy. Because not always the data is a problem. Your process is a problem. It is creating the wrong data. So don't blame it on the data. Just see the root cause of what is causing the, uh, data problem and then address that problem. Then the data will become good data. So that's why I said that approach data is empathy.
[00:26:18] Host: Paul Barnhurst: If you're ready to take your finance career to the next level, this is your moment. Corporate Finance Institute, or CFI, is the global leader in online corporate finance certifications. Their FMVA program is built for professionals who want to move beyond theory and master the skills top finance teams actually use with FMVA. You'll learn how to build robust three statement models, perform DCF and comparable valuation analysis, create accurate forecasts, and communicate your insights clearly using the same practical skills that top finance teams rely on to guide strategy and make better business decisions. Whether you're targeting a promotion, transitioning into FP&A, or aiming to stand out in a competitive job market, these are the qualifications that hiring managers are actively looking for. Over 2 million professionals worldwide trust CFI to gain skills, earn promotions and advance their careers. And right now, you can do the same with 30% off any CFI plan. Visit Corporate Finance Institute to start building the skills that get you noticed and get you hired.
[00:27:41] Host: Paul Barnhurst: Got it, I like that. How do you recommend somebody determine what the root cause of their problem is? If you're advising someone, you know you're coming in or they ask you, I know I have a data problem, but I'm not sure where to start. How do you find out where the root cause is if it's processed, if it's people, it's technology. What do you advise people to kind of, you know, figure that out.
[00:28:04] Guest: Ramya Krishnaganth: So it's again goes back to the fundamentals right. So first thing is what are you trying to solve for. Right. So like when you say you have a data problem you're seeing something. Something is not right. Right. So the first question is what are you trying to solve for? Is there any report where your management is not trusting you on that report? Or is there a place where you have to, like, do a lot of work? So what is it you're trying to solve for, right? That will be the first question. So once you have that, like if I need to put it in the context of, um, one of the construction, um, example. So the problem was, okay, whip, uh, report it is always delayed. We know then why whip is important. We all know why work in progress is very important for a company from the construction standpoint. Right. It is going to tell what is the health of the project from a financial standpoint. Are you like, uh, overbilling or under billing? So are you on track? Is the project going to be in trouble? Management would want to be on top of that on a very, very regular basis. So if so, okay. Then it means okay. So there is a problem with that. Your management is not trusting that report.
[00:29:15] Guest: Ramya Krishnaganth: But this is a very important decision. Uh, lever then let's talk about, okay, where is the data residing? Right then to generate that data, who all are doing what kind of activities? What process actually ends up creating that data. Right. So these are the steps that we like to take, okay. Once we identify that once we identify then that will clearly say where the problem is. Right. Is it the legacy technology where you have the data but you are not able to take the data out or the technology is like, um, I can even say like one of the, the, the technology doesn't keep track of the audit trail of what is entered and what is changed. It will just go and directly change the entry. Right. This is clearly the technology problem, right? Coming from an accounting background, I would want to know who has entered the original transaction and who has reversed the transaction. If somebody has the ability to go and directly change the original transaction, No way on earth I can find how things have changed, right? So? So this is a technology problem. So then we clearly know this is a technology problem. Okay. So then this is just one example right. So it could be like multiple then okay. You have the jobs your whip reports like what are the jobs you want to see.
[00:30:31] Guest: Ramya Krishnaganth: Right. You want to see only the active jobs. So how are you identifying that job like nobody is maintaining the job master. That's a process problem. Who's responsible for maintaining the job right? So they like regularly maintaining it uh, how they are accountable for that. So that's a process problem. So like I first get the inventory of where the data is on the report or the area, the problem you're trying to address, and then go deeper from there. Right. So once you identify all that, you have a very clear picture of, even if you put a very simple flow chart, it is going to depend on how much spaghetti you are dealing with. Right. So you're telling you it's a data problem. It's a people problem, technology problem. It's going to kind of show everything out one. Then it's very easy for you to address. So okay, you know you have the you you talk about okay. Now you bring in the process definition. Bring in the control. Say okay. Going forward this is going to be one report where all the metrics are going to be defined. Everybody is going to refer to this report. So look at that. You need not even go for a big new technology.
[00:31:34] Guest: Ramya Krishnaganth: You can do all of these with existing technology. What you have on hand even before thinking about investing in the bigger technologies. Right. So define that and say this is the report which is going to be, uh, central for everybody. And then give the definition for like a little data dictionary, how you're going to define that, how everybody is going to revenue means like revenue. Job eligibility means it's the same for everybody. Like the same terminology across the organization. Define that. And then you address all the problems, bring in the control. Whatever we talked about right. Bring in the control, accountability, clear the process and educate the team. Bring all that and then you start bringing in all this like collected and address what is a major manual work that you want to avoid there? Is there like any like problem in bringing multiple excels together like merging or is there a manual intervention happening? Instead of putting a journal entry in the system, you're trying to address it in the Excel itself. So these are the kinds of processes that combine technology. Address that and you go from there. Right. Then you have a good process addressing the data issue. Now you can think about whether you want to invest in a higher technology to make it more sophisticated.
[00:32:48] Host: Paul Barnhurst: Got it. And what do you recommend? So let's you know, you're an analyst or a manager. You're not in a position where you have a lot of authority, but the data is kind of a mess. You know, you have an IT team, all those things. What do individuals kind of do? You know, the real world day to day where they're struggling and spending half their time dealing with and cleaning up messy data. What advice do you have for them?
[00:33:12] Guest: Ramya Krishnaganth: This is a lot of larger organizations. This is a problem you're facing. Okay. A lot of.
[00:33:18] Host: Paul Barnhurst: Yeah, I've been there. I spent my life sometimes cleaning up data when I have no ability to spend or get the resources I need. And I'm like, okay, I love Power Query, but it only goes so far.
[00:33:30] Guest: Ramya Krishnaganth: Right? Again, this is where I feel that your original initial question that we talked about, right. Do they have the tendency to do everything together? It's not just in terms of how back you want to go. Also in terms of like how do you want to go? Right. So that also matters in terms of how much you want to deal with. Right. So again here also the important question is just pick 5 or 10 important questions that you that your business is asking that you're trying to answer. Right. So one question could be okay in my automotive test like automatic testing instrument manufacturer, right? So you just want to see which are the product lines within that division that are eroding in margin. If that is the question you are trying to answer, then start looking at what are the insights that you're going to need, right? Or are you going to need the insight in terms of how the material is changing, like given material in a semiconductor is like very, very it's very fluctuating. Uh, all the market things that are happening. So like do you want to know then you probably you're going to need like what is your budget versus actual on the material cost. Right. If you want to look at what is the productivity on the assembly line, then you're going to need information on what is your cost per labor.
[00:34:50] Guest: Ramya Krishnaganth: Right. So you identify the problem you're trying to address. What are the data points that you're going to need? And then start focusing on bringing the data relevant to that. Right. So maybe you need to go for the Bom and look at the cost related to the important materials in the bomb. Like bring it to address your material, go to your assembly line and get the standard and the actual cost per labor. So bring all of those because not all data is relevant. So that's a problem, right? The reason you're struggling with the data is we are trying to bring all the data together. We do not know what to use, but as long as you have your objective, what you are really trying to solve, then it is very easy to get back to work and it all goes back to your original discussion. FP&A is so embedded in the business. So okay, you know what problem, the question the business is going to ask you. Unless you are so embedded in the business, you cannot identify what the data points are. You need to answer that question from the business. Right? So it all again ties together.
[00:35:55] Host: Paul Barnhurst: I really like the way you broke that apart. I think that would be helpful for people if it's the reminder of, look, whether you're overwhelmed with data, whether you have bad data, Start with what's the most important question you need answered. Work back from there and work to solve that problem. Yes, you're going to have to do some cleanup if and different things depending on you know, how good your data is, which almost we always have to do. But just focus on the most important things that you can control and solve those answers. And then, you know, there may be opportunities for the broader discussion where, hey, we there's things we need to do to process that are outside of my control or technology or whatever, because if you're solving people's problems, they'll notice and you'll start to be respected in the organization and be able to have more of those conversations about, well, what's limiting you when they come? Because there'll be a question where, like, I can't get there. The data is not there. Well, what's the cause of that? And then they realize, oh, this person's solving all these other problems. If we make some changes, they could help solve this one as well.
[00:36:54] Guest: Ramya Krishnaganth: Yeah. You are bringing up a very important point, right? So it definitely creates a lot of credibility for the finance professional. So I know when I like having conversation with some of the FP&A and like, I, uh, leads in the finance organization, they're like they say, oh, there were times where my number was trusted. Trusted, right. I was like, okay, you're like giving me the information. First of all, it's wrong information. And it has come one month later, right? So like they used to say, this is like such a frustrating time for me because I had no way to get that answer satisfied in the right manner at the right time. Right. So these are real problems that everybody is dealing with. So you're right, it actually brings in credibility, uh, to the individual and the organization.
[00:37:49] Host: Paul Barnhurst: Yeah. And I've definitely seen it. When the organization worked, we had really rough data. You know, I spent a lot of time cleaning different things and getting answers and getting answers that they hadn't got before. And it gave me more and more credibility. So when I was promoted, my manager trusted me. When I said the first hire I want to bring is somebody who can work on the data because we don't have the budget to spend on anything else. I'll manage the finance stuff. If I can just have someone help me clean the data and structure it in such a way that we can answer the questions the business really needs answered, and it was one of the better decisions I've made in my career. He ended up being a great hire and it really allowed me to accomplish more. And so I totally agree with you. You do. You build credibility and then they start to trust you and you have a better chance of really influencing, you know, some of the data challenges that a company may face, whether it's technology or whatever.
[00:38:40] Guest: Ramya Krishnaganth: That's right. Yeah. Yeah.
[00:38:42] Host: Paul Barnhurst: All right. So we're going to move into our uh FP&A section. I have three questions I'm going to ask you here. These are, uh, some standard ones. We ask a lot of different guests. So the number one, what is the number one technical skill that FP&A professionals should master.
[00:38:59] Guest: Ramya Krishnaganth: I think that's exactly what you defined a moment ago, right? How you can deal with data in technical terms. We can call it data transformation, but just in a fun way. Data wrangling. Right. So how you can take the data and then and then convert it in a more useful way so that it's able to generate insights, right. Even before insight you need to bring it into a like otherwise it's garbage in garbage out. We all know that terminology. So that's exactly the skill, right? Uh, I think that is where you are also contributing a lot in terms of, okay, your Excel skills, your Power Query basic SQL. So these are the skills that you need. But the technical bent that you have is on data because you need to map the data to your financial models as well. Unless you know how to wrangle the data It's not going to help in the FP&A justice to the FP&A role. That's what I would call it.
[00:40:03] Host: Paul Barnhurst: All right. So I like that data wrangling or data not being able to get the data in a situation where you can get the insights, the value out of the data.
[00:40:13] Guest: Ramya Krishnaganth: Right.
[00:40:13] Host: Paul Barnhurst: Okay. What about softer human skill. What do you think the number one is?
[00:40:18] Guest: Ramya Krishnaganth: I would say, um, I go a lot on empathy actually. And then empathy. Again, it it manifests in multiple ways. Right. Like a communication. Right. So the empathy, the reason I say empathy is always like once we are so much embedded in the business, then we can really understand what is the the point from which the, the your counterparts are coming from. Right. So and again, for that, the communication is the biggest skill that is going to, uh, help you. So how you can break down your like once you empathize them. So when I say, why do I say empathy and communication together? According to me, they go very hand in hand, right? So for me, it's very easy to talk about. I always tend to tell myself when I try to, when I get into the teaching mode with my kids, I'll say, do you know what it is? What is the cost of that? You know, like how to like they have no clue what that cost or profit means, right? Like they are like small kids. I need to break down in a way they can understand it, right? So so that's where like so the communication reflects how good you communicate reflects the empathy. So how you can break down the complex financial information into the way in a very simple layman language, the the department heads or the other counterparts can understand. Right. So and use that to help them see the point you are seeing in steering the business. Right. That's the way you really can be with them and help the business move forward towards a goal. And also the other popular one. Right. Communication is um, I really don't want to use the word storytelling for me. Honestly, I'm so tired of hearing that word. Storytelling. I'm looking for another. Another word.
[00:42:04] Host: Paul Barnhurst: Uh, it's like how some people feel about the word transformation.
[00:42:07] Guest: Ramya Krishnaganth: Exactly. Though I supported transformation in some of the areas, yeah, definitely a tiring word. Right. So, but but basically, um, how you can explain what has happened behind the numbers, right. You know, that's a communication skill, the narrative behind the numbers or the or the process or the action that happened behind the numbers. Right. So okay, maybe, uh, customer service cost has increased from 15% compared to last period. That's not what you're trying to explain. Right. You have to like, explain. Okay. But out of this, 10% retention is increased. So there is a positive impact. But we need to keep an eye on productivity. So if you give this kind of what is happening in the business behind the numbers. I think these all tie to communication. Um, which actually is, is again, according to me, empathy, where communication is an important portion.
[00:43:04] Host: Paul Barnhurst: Okay. I appreciate the answer. I've definitely had other people say empathy before. I think it's, uh, it's a critical skill you need as a business partner, so I can totally go with that. I get it, I appreciate the answer, and I like how you brought in the communication and those examples there. Now we're going to move on and ask you some personal questions. Get to know you a little bit better. Let our audience know you. What's your favorite hobby or passion? What's something you like to do in your spare time? I know with kids you probably don't have much, but.
[00:43:32] Guest: Ramya Krishnaganth: Not surprising and interesting so I'm finding a way to have my own time for other things, right? So again, here the consultant mindset, right? I get bored with one single hobby or like one fun pastime. I, I, I try to put myself in more uncomfortable personal development and personal growth situations. And also, let us say I mentioned, right, a little bit more in trying to know what that spirituality means, what that energy means, right? So yeah, I do various things like hypnotherapy certified and then yoga certified Pranic Healing certified. So these are not for being proficient just for me to really know what they are. So that's my hobby, just getting into those kinds of things and really going a little deeper and understanding what it is. So that's what I really, really enjoy a lot.
[00:44:28] Host: Paul Barnhurst: Good. Thank you. Thank you for sharing. And so next one, if you could recommend one book to our audience, what book would you recommend?
[00:44:37] Guest: Ramya Krishnaganth: I'm not sure if I would recommend not take this as a recommendation. Right. But I can talk about the book that I'm reading now. It's, uh, The Magic by Rhonda Brian. So the person who has done the secret and the power of the book are the magic. So this talks a lot about gratitude practice, right? So I'm reading. I'm in the middle of reading that book. This really helps me to take a pause from the busy life and really look around and appreciate the things that you are gifted with. So I'm personally enjoying that a lot. Yeah, if everybody is interested, you can go and take a look at it. But yeah, this is what I'm reading now.
[00:45:19] Host: Paul Barnhurst: Got it. All right. Next question. If you could live in any other time but the one you're in right now, when would you live?
[00:45:27] Guest: Ramya Krishnaganth: That's a very. You're making me think.
[00:45:30] Host: Paul Barnhurst: Well that's good. I like to make people think.
[00:45:32] Guest: Ramya Krishnaganth: Yeah, maybe. You know what? Like, since I'm, um, I would definitely want to go back to that. Like, my dad's or my granddad's dad's age of living because their life was very simple. Until those times. Of course, we have the luxury of everything. I really appreciate and like to be thankful for this, but I really want to, like, see what that life is going to be, right? Like so simple life without technology, without any of those. And then like being with nature or having the opportunity to be with nature most of the time, can we really live without technology and all those gadgets and interferences around? I'm so curious. I would definitely like to go and live that life once at least.
[00:46:19] Host: Paul Barnhurst: Yeah, that would be kind of fun to see. I mean, it's amazing today how dependent we are on technology, right? Try leaving your phone at home when you run somewhere and you're like, you feel like you've lost an appendage. Oh no, my arm's gone. It's like, well, I live with a phone for years without a phone. Why can't I just go to the store and not be worried about it?
[00:46:41] Guest: Ramya Krishnaganth: Right. So my dad was a telephone operator in India, right? So he used to work in the telephone exchange, and he remembered so many numbers in his mind. He would say that he was like that till his dad died at 69, but he never had the memory problem. He was never dependent on technology. Still, he was very tech savvy. In the 60s he was never dependent on that. But for me, when I lose my phone, I will not know my dad's number to call him. That was the situation.
[00:47:14] Host: Paul Barnhurst: I'm not surprised. It's amazing how that's that. That's changed. Like, my daughter wouldn't know our phone numbers there in her, in her watch that she can call us on. But, you know, as a kid, I still know my parent's phone number because it's the same one that I had when I was a little kid. So. But newer numbers, it's much harder because you just put them in your phone and forget about it.
[00:47:35] Guest: Ramya Krishnaganth: Right. But what would you wear if you want to go and live? What is, uh.
[00:47:40] Host: Paul Barnhurst: Oh, that's a good question. I haven't given this a lot of thought.
[00:47:44] Guest: Ramya Krishnaganth: You see how difficult it is to.
[00:47:46] Host: Paul Barnhurst: It's a tough one.
[00:47:48] Host: Paul Barnhurst: You know, I had someone answer this one the other day, and I kind of liked it. He wanted to go to the future, but for me, I think I go to the past. You know, I would probably go. We'll say that the Civil War era. I'd love to watch. I don't know that that's where I'd want to live, if that makes sense. Like, I would not have to go through all that, but I'd love to observe that in person and see how Abraham Lincoln managed that. Just all those challenges. But I can't say that's what I would have chose to live in the sense of. I wouldn't want to have had to go through all that. So there you go. I don't know if that's the best answer, but here's my answer.
[00:48:28] Guest: Ramya Krishnaganth: Yeah, yeah, any answer is the best answer. Right. So that's what we want. Yeah.
[00:48:32] Host: Paul Barnhurst: There you go. It's all about.
[00:48:33] Host: Paul Barnhurst: Getting you to think.
[00:48:34] Guest: Ramya Krishnaganth: Yeah.
[00:48:35] Host: Paul Barnhurst: So.
[00:48:36] Host: Paul Barnhurst: Well, I just want to take a few minutes. And thank you so much for joining me today. I've really enjoyed our conversation. I've had a lot of fun. I think people find it helpful because we all struggle with data, as I've once heard it said, or kind of paraphrased, you know, all data is messy. No data is really clean. Hopefully it's useful. That's really the goal is to have useful data, not perfect data. So if someone wants to learn more about you or get in touch, I know you run your own practice. You help people with transformations and these types of things. How can they get in touch with you or how can they learn more about your services?
[00:49:11] Guest: Ramya Krishnaganth: Oh, they can, uh, go to UVic consulting, my company's website. It's called Uved. You've ID consulting.com, or, um, they can get in touch with me through LinkedIn. That's the LinkedIn profile name.
[00:49:28] Host: Paul Barnhurst: Okay. Yeah. We'll put both those in the show notes so people can reach out to you. If you have any questions. You know they need help with data or just want to reach out. They enjoyed the episode. So thanks again for, uh, carving out some time on a Friday afternoon. I appreciate it and hope you have a great weekend. And thanks again for joining me.
[00:49:45] Guest: Ramya Krishnaganth: Oh thanks Paul. It's really, really fun talking to you. That's what I would say. Very fun.
[00:49:51] Host: Paul Barnhurst: Well thank you I appreciate that.
[00:49:53] Host: Paul Barnhurst: Thanks for listening to FP&A tomorrow. If you enjoyed the show, please leave us a five star rating and a review on your podcast platform of choice. This allows us to continue to bring you great guests from around the globe. As a reminder, you can earn CPE credit by going to earmarkcpe.com, downloading the app, taking a short quiz, and getting your CPE certificate to earn continuing education credits for the FPAC certification. Take the quiz on earmark and contact me the show host for further details.