The FP&A Fix for Finance Leaders to Solve Data Trust Issues using Empathy and Strategy with Ramya

The FPA is very deep root embedded in the business. It's more like a very active nervous system for the organization. How it is actually making somebody's life easier.

Ramya Krishnaganth is the Founder and CEO of UVID Consulting where she helps businesses boost performance by simplifying and automating, budgeting, forecasting and reporting. Ramya empowers leaders to make faster data driven decisions. Why do you think so many companies struggle with their data?

There are some common reasons. It's a combination of process and technology which impacts the data quality or even the availability of data itself sometimes.

What is the number one technical skill that FP and a professional should master?

In technical terms we can call it as data Transformation. The communication is the biggest skill that is going to help you if you're dealing with a large enterprise customers. We are driven by a lot of data policies, data requirements, but is data the real problem?

What do you advise people to figure that out?

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This week's episode is brought to you by Corporate Finance Institute cfi, the global leader in online corporate finance training and certifications. With CFI's FMVA program, you'll learn how to build three statement models, perform DCF and comparable valuation forecasting and presenting insights with clarity the exact skills you need to move your career forward. And right now you can get 30% off when you sign up. Visit corporate financeinstitute.com and thanks to CFI for sponsoring this episode. 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. Paul I'm your host Paul Barnhurst, AKA the FPA 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. Ramia. Ramia, welcome to the show.

Thank you Paul. Thank you. Thank you for having me here.

Really excited to have you. So let me give a little bit about Ramya and then we'll jump into the questions. Ramya Krishna Ganth, founder of UVID 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 and A look like? What does it look like to you?

This is always a question whenever we say fpa. The conversation revolves around the numbers, the difficulty in looking at the data and all of those. But, but for me and for many as well, right, the FPA is more than the numbers. It's deep root embedded in the, in the business and number is the tool and number is the way you're going to see the business. So how, how you're seeing the numbers, how what is the business you're seeing behind the numbers and how you're conducting it to admins. That, that's just one, one line for me in terms of fpna. Right. But there are many characteristics to that FPNA in terms of like how agile you are which like every, every one of us talk about like your whole episode is like around that, right? Your, your effort is towards that. Like how agile the, the FPNA is, how quickly it can answer the questions in 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 be ahead of the competition. Like we always 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 FPN as.

I like that. I haven't had anyone use that analogy of, you know, kind of that nervous center, right. That activates and helps manage everything and manage to get business. I think that's a good comparison. So thank you for sharing that.

Sure.

And so now I'm going to ask you, can you think of an example maybe one you've seen or you know, one you've been involved in from your career where you've seen great FP and A in action. Like you look at it and then oh wow, that's really how FP&A should work?

Oh 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 knows, he decided that the whole company had, okay, in the next one or two 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 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 largely determined by market pricing. So, so look at what is 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, 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? Like 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. Right? This is just one example. So every line of every line of the P and L, he started like 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 in control. Right. Then he started focusing on other things. But the way he has done is like so amazing. Then this led to a lot of other things which we typically talk in terms of. Okay, There is an automation, other things. Okay, how do you need to structure your chart of account? So how are you going to bring it and then convert it in the way that you want to look at your P and L and how are you going to link those levels? And then connected to the metrics that is going to point to the production, your labor efficiency, direct and indirect labor efficiency on all of those. In that way he was, the FP team was able to have a very productive conversation with the department heads and then give them also like insight in terms of what they should be looking at. And 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 a, there is an increase in material cost, but very limited options on the vendors that we can go with. Right. So what we can do about it, these are the proactive way of FPA engaging with the business. So this is one of my recent classic favorites.

Thank you. I appreciate you sharing that. And I love how 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.

That's right.

So during your career, you spent a lot of time in financial transformations. Why is that? What is it you like about, you know, working on, on transformations and big projects like that?

Again, it just goes back to the excitement I was showing in the previous question. So this fpa, which is part of the financial transformation, right, It's a very 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 direct impact on the decision making and you can see it on happening in the 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. They 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 that time this thing started slowly opening up, but the county was not allowing so many people to be contained 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. So this was a decision that the management had to make within a week's time. So the FPA 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 like 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 it 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, they made the decision, I could literally be part of that and see that within that like weeks timeframe, 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 leaders, the goals they have, the challenges they have and the environment in which they operate, they're completely different. So no two FP and A transformations are same. So this constant change and this is what keeps me so excited, interested about this transformation space of that 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 techno technology, you know, process, whatever it may be, seeing how it allows them to make better decisions for the business.

Right, right. One is for the business fall and the other thing I also look at it is how it is actually making somebody's life easier. Right. Like especially people on the FPA team, how they feel a lot relieved after having this transformation in place. Right. So that is another human aspect which always make my heart warm. Right. So that's, that's another big piece of that which I love in this whole.

I, I, I really appreciate you adding that, that human aspect, that's great that you get to see that, you know. So as you talk 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 be good a lot of times. I mean there's some, obviously nobody's perfect. But why do you think so many companies struggle with their data? Why is that?

There are some common, common reasons. Right. So we often, the reason we often talk about is the 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 there are discrete processes happening. The way the sales is looking at the revenue and the way 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, the way they define the sales structure and all of, so this is like one part of it other part of it is sometimes the, the. The culture and the mindset of people as well. Maybe they do not want to share all the information with everybody. Like sometimes like holding the information. That happens sometimes as well. Right. So maybe they feel little insecure or like feel more powered when they have the data within themselves. So this is like also 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. 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?

It's. It's almost combination. It's only the question of which has more 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 on the process. Right. When we mean by process, it could be a simple process of as I mentioned, like creating like who, who's creating the customer structure and who's following through that. Right. So that's a kind of like process problem. And then people problem is maybe they were like entering with some hyphen, some semicolon, some fields are not filled in. So these kind of like this also happens some kind of like people problem. Right. So it's always untechnology. Like. Yeah, like depending on which stage they are in, it could be a basic technology problem. But if they are like 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. 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. What is your experience, Paul? Right. You. You definitely have.

Let's see. In the companies I've worked in, I, I would agree. You know, I've been at some companies where I say it was mostly technology. 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 is 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.

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's 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. Quality in. In the system. Right. So, yes, these are. These are the root causes. You're right. Right.

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 was a lot of commitment around data. And you could see leadership was talking the talk not just by spending money, but really the way they thought about things. And was 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 like their CFO's approach in that 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.

That's a smart approach. That's a smart and a very practical approach too.

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 your experience on that?

So they, they come with always a great ambition, right, Just to steal the entire ocean in the first go. So this is where we need to like go back and educate them. Of course, few come. I would not say it's. It's not about they whether they are making a smart decision or not making a smart decision because they were driven by what was demanded from them by the business. So with that in mind, they probably will come with the suggestion, okay, let's do all of them together. Right? So then when we start having these intricacies, discussion about these intricacies on the challenges we have, then we always 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. And especially after pandemic, right? The interesting thing, after, after pandemic, I 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 8 and 10 years of data in my system. Can you bring all of them in? Right. So can you cleanse all of those data? But now it has changed. They are saying, okay, before 2020 or 2021, the rater is of data is of 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 little bit of reset of okay, where are you going? Where your starting point is. So from that perspective, the intensity of that discussion we needn't need to deal with like before. But it is going to grow up as we like move in years. It's to the number of years of historical data is going to like 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 yeah, and so talk a little bit more about that you know, you mentioned not always a few years. Do you think and I think I know the answer. Think you hit it at this. That will just, they'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's totally alters the data, we'll just get back to where we were before. So they'll start asking for you know, six years and seven years, then eight years. Or do you think there's been a little bit of shift in mindset and going, you know, what do we really need? Do we need eight years? Can we get by with just four? What do you, what do you think?

So it again like I'm not giving a typical consultant answered but this is what I'm seeing with a.

And I appreciate that that's what we want. You're not going to give me the consultant. It depends.

It's not a consultant depends, it's. It's the industry depends. Yes. So the trend is if you're dealing with a large enterprise customer, right. So they are driven by a lot of data policies, data requirements and other things. So they, whether it is relevant from the business decision standpoint or not, they would still want it for regulatory type stuff. Right. So that kind of data, the only conversation there we have is okay, you need that like since I'm dealing with fpa then we will get into a discussion of do you want it in the FPA area. Right. You still can archive it, you can still can have it, but you really want it in the active FP and a like report or model what we, whatever we call it in the technology terms. Right. So where you are working with is, is it needed? Right. That's a conversation we are trying to have. But still the tendency is like sometimes they, 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 the conversation. That's why it depends if it's a larger enterprise customers. Whereas if you're dealing with the fast growing companies where they, they are not like they make decisions very quick and they have access to like every department like in a much easier way than the enterprise department. So most of them they are like okay with okay, these data makes sense. I'm okay to archive this data or not bring then or put effort in transforming all those information. Right. I'm the. For me, what I'm looking for from the FPNA standpoint is to drive A better business decisions, right? What is going to like coming up and how I'm doing today. So from that perspective they are like okay with having a just like start 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 fpa, 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 number of data for sure, 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?

Okay, I'm a big, big. It's a big word to use, right? I'm like more inclined towards spirituality, right? That's why I start looking at everything with little more empathy. So when I, when I made that statement, the always, every conversation you have, whether you are like even why do you have to do a transformation? So why do you need to do that? Why do you need to do an automation like everything whom. 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, data is. It's going to clean up your data, right? Maybe that's true. But is data the real problem? Data is just, just the. It's. 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 like, okay, by doing something the data is going to be miraculously become so qualitative, right? So that's why I said like approach data with empathy. Because not always the data is a problem, your process is a problem. It is creating a wrong data. So don't blame it on the data. Just see the root cause of what is causing the data problem and then address that problem. Then the data will become a good data. So that's why I said like approach data is empathy.

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So the it's, 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, 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 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 one of the construction example, so the problem was, okay, WIP report, it is always delayed. We know then why WIP is like 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 the financial standpoint. Are you like over billing or under billing? So are you on track? Is the project is 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. But this is a very important decision lever. Then let's talk about, okay, where are the data residing? Right? Then to generate the 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 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, I can even say like one of the technology doesn't keep track of the audit trail of what is entered and what has changed. It will just go and directly change the entry, right? This is clearly the technology problem, right? Coming from 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 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 WIP reports. Like what are the jobs you want to see? Right? You want to see only that two jobs. So how are you identifying that to job? Like nobody is maintaining the job master. That's a process problem. Who's responsible for maintaining the job? Right? So are they like regularly maintaining it? 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 for a deeper from there, right? So once you identify all that, you have a very clear picture of. Even if you put a very simple flowchart, it is going to how much of a spaghetti you are dealing with, right? So they're telling you it's a data problem, it's a people problem, technology problem. It's, it's going to kind of show everything out one. Then it's very easy for you to address. So okay, you, now you have that you, you talk about, okay, now you bring in, 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 here everybody is going to refer to this report. So look at that. You need not even go for a big new technology. 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 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 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 collected and address what is a major manual work that you want to avoid there. Is there any 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 again process, combination of technology, address that and you go from there, right? Then you have a good process addressing the data issue. Now you can think about do you want to invest in a higher technology to make it more sophisticated?

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, 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?

This is a lot of larger organizations. This is a problem you're facing. Okay.

A lot of yeah, I've been there. I, I've spent my, it feels like my life sometimes cleaning up data when have no ability to spend or get the resources I need. And I'm like I love power query, but it only goes so far.

Right. Again, this is where I feel that your original, the initial question that we talked about, right. Do they have the tendency to do everything together? It's not just in terms of like how back you want to go, also in terms of like how wide 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 five or ten important questions that your business is asking that you are trying to answer, right? So one question could be okay in my automato test like automatic testing instrument manufacturer, right. So you just want to see which are the product lines within that division is eroding in margin. If that is a question you are trying to answer, then start looking at what are the insights that you're going to need, right? Are you going to need the insight in terms of how the material is changing? Given material in semiconductor is very fluctuating. All the market things that are happening. Do you Want to know, then you probably are going to need what is your budget versus actual on the material cost. 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, right? So, so you identify for 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, the BOM and look at the, the cost related to the important materials in the bom, like bring it to address your material, go to your assembly line and get the standard and the actual like cost per labor. So bring all of those. Because not all data is relevant. So that's a problem. Right? The reason you're dealing like 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 you start from the end objective, what you're really trying to solve, then it is very easy to back work. And it all goes back to your original discussion. FPNA is so embedded in the business. So, okay, you know what problem the what question the business is going to ask you? Unless you're so embedded in the business, you cannot identify what are the data points you need to answer that question from the business. Right. So it all again ties together.

I really like the way you broke that apart. I think that'll be helpful for people is 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 to answer? Work back from there and you know, work to solve that problem. Yes, you're gonna have to do some cleanup if and, 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 need, there's things we need to do a 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 we're like, I can't get there. The data's 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.

Yeah, you are bringing up a very important point. Right. So it definitely creates lot of credibility for the finance professional. So I know like when I like having conversation with some of the FPA and like high 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 a wrong information and it has come one, one month later. Right. So they're like, those are 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 to the individual and the organization.

Yeah. And I've definitely seen it. When the organization work, 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, trust me, 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. All managers to 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. 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.

That's right. Yeah. Yeah.

All right, so we're going to move into our, our FPA section. I have three questions I'm going to ask you here. These are some standard ones. We ask a lot of different guests. So the number one. What is the number one technical skill that FP and a professional should master?

I think that's exactly what you defined a moment ago. Right. How you can deal with data in technical term, we can call it as data transformation, but just fun way data wrangling. Right. So how you can take the data and then, and then like convert it in a more useful way so that it's able, it has the ability to generate insight. Right. Even before insight, you need to bring it into a like. Otherwise it's garbage in and garbage out. We all know that terminology. So, so, so that's exactly the skill, right? I think that is where you're 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 fpa. Justice to the FPNA rule. That's what I would call it.

All right, so I like that data wrangling or data now being able to get the data in, in a situation where you can get the insights, the value out of the data.

Right.

Okay, what about softer human skill? What do you think the number one is?

I would say I go a lot on empathy actually. And then empathy again it, it manifests in multiple ways, right? Like a communication, right. So the, 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, your counterparts are coming from, right. So and again for that the, the communication is the biggest skill that is going to 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 my, when I try to, when I get into the teaching mode with my kids, I'll say do you know what 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 I, 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 conflict complex financial information into the way in a very simple layman language 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. 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, the river.

It's like how some people Feel about the word transformation.

Exactly. Though I supported transformation in some of the areas. But yeah, definitely diving word. Right. So, but, but it basically how you can explain what has happened behind the numbers. Right. You know, that's, that's a communication skill. The narrative behind the numbers or the process or the action that happened behind the numbers. Right. So okay, maybe customer service cost has increased from 15% compared to, compared to last period. That's not, that's not what you're trying to explain, right? You have to like explain. Okay, but out of this 10% retention has increased. So there is an positive impact. But we need to keep an eye on productivity. So if you give, give this kind of what is happening in the business behind the numbers, I think these all tied to the communication, which actually is again according to me, empathy, where communication is an important portion.

I appreciate the answer. I've definitely had other people say empathy before. I think 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 just some personal questions, get to know you a little bit better. Let our audience know you. What's a 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 no surprising and interestingly so I'm finding 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 passion. I try to put myself in more uncomfortable personal development and personal growth situations. And also let as I mentioned, right. Little bit of 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, chronic healing certified. So these are not for like profession, just for me to really know what they are. So that, that's my hobby, just getting into those kind of things and really go a little deeper and understand what it is. So that's, that's what I really, really enjoy a lot.

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?

I'm not sure if I would recommend. Don't take this as a recommendation. Right. But I can talk about the book that I'm reading now. It's the Magic by Rhonda Bryan. So the, the person who has done the secret and the power of the book, the magic. So this talks a lot about gratitude practice. Right. So I'm reading, I'm in middle of that book. This really helps me to take a pause from that 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, can go and take a look at it. But yeah, this is what I'm reading now.

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?

That's already you're making me think.

Well, that's good. I like to make people think.

Yeah, maybe. You know what, like since I'm. I would definitely want to go back to that like my, my dad's or my granddad's dad's age of living because their life was very simple those times. Of course we, we have the luxury of everything. I really appreciate and like, like 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 be with the nature or most of opportunity to be with the nature most of the time. Can we really live without technology and all those gadgets and, and interferences around? I'm so curious. I would definitely like to go and like live that life once at least.

Yeah, that would be kind of. Would be 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?

Right. So my dad is 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 like to say that he was like that till his dad. He, he died at 69. But he never had the memory problem. He was never dependent on technology. Still he was very tech savvy at 60s. He never is dependent on that. But for me, when I lose my phone, I will not know my dad's number to call him.

That was a situation I'm not surprised. It's amazing how that's. That that's changed. Like my daughter wouldn't know our phone numbers. They're in her, in her watch that she can call us on. But you know, I, as a kid, I still know my parents phone number because it's the same one that when I was a little kid. But newer numbers, it's much harder because you just put them in your phone and forget about it.

Right. Well, what would you. Where would you want to go and live? What is.

Oh, that's a good question. I haven't given this a lot of thought.

You see how difficult it is to live.

It's a tough one. You know, I had someone answer this one the other day and I, I kind of liked it. He wanted to go to the future. But for me, I think I go to the past. No, I would, I would probably go. We'll say that the Civil War era, I'd love to watch. I don't know that that's when 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 when 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 there's my answer.

Yeah, yeah. Any answer is the best answer. Right. So that's what we want. Yeah, There you go.

It's all about getting you to think.

Yeah.

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, 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 type of things. How can they get in touch with you or how can they learn more about your services?

Oh, they can go to UVIT Consulting, my company's website. It's called Uvid u v I-consulting.com or they can get in touch with me through LinkedIn. Just Ramya Durga K. That's the LinkedIn profile name. 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 carving out some time on a Friday afternoon. I appreciate it and hope you have a great weekend. And thanks again for joining me.

Oh, thanks Paul. It's really, really fun talking to you. That's what I would say. Very fun.

Well, thank you. I appreciate that. 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 will allows us to continue to bring you great guests from around the globe. As a reminder, you can earn CPE credit by going to earmark cpe.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. Sam.