How Financial Modeling Errors in Real Estate and Biotech Cost Analysts Millions with Narek Grigorian
In this episode of Financial Modeler's Corner, host Paul Barnhurst talks with Narek Grigorian, a seasoned financial modeler and investment professional with deep experience across real estate, energy, and biotech sectors. Narek shares candid stories about the worst financial model he ever worked on, one that looked polished but was fundamentally flawed, missing key components like taxes, depreciation, and tenant turnover. He explains how these mistakes can mislead decision-makers and why it’s critical to understand not just the n bers but also the assumptions behind them.
Narek Grigorian currently works at US Capital Global, a global investment banking firm focused on real estate and energy projects, particularly in the lower to middle market space. He holds degrees from Georgetown University and the University of Maryland and brings a passion for financial modeling, innovation, and teaching. Narek believes that while all models are inherently imperfect, they still provide valuable guidance, if built with thoughtful assumptions and continual refinement.
Expect to Learn:
Why can you never fully trust a model just because it looks polished.
The critical real estate assumptions that are often overlooked, like tenant turnover and escalating costs.
How to approach energy modeling with real-time data inputs and complex variables.
Why biotech models are uniquely challenging due to regulatory and clinical uncertainties.
Tips and shortcuts Narek uses in Excel to make modeling faster and more reliable.
Here are a few quotes from the episode:
““The toughest part is you have the wardrobe of clothes but have to create the person.” - Narek Grigorian
“Power Query and Power BI are essential tools for modern financial modelers.” - Narek Grigorian
“Vacancy rates and market growth assumptions are the most common pitfalls in real estate models.” - Narek Grigorian
Narek’s practical and approachable style makes this episode valuable for anyone involved in financial modeling whether you’re just starting out or have years of experience. His clear advice on key assumptions, Excel techniques, and industry-specific challenges offers useful takeaways to help you create more accurate and effective models.
Follow Narek :
Follow Paul:
Website - https://www.thefpandaguy.com
LinkedIn - https://www.linkedin.com/in/thefpandaguy
YouTube - https://www.youtube.com/@thefpandaguy
Follow Financial Modeler's Corner
LinkedIn Page- https://www.linkedin.com/company/financial-modeler-s-corner/?viewAsMember=true
Newsletter - Subscribe on LinkedIn-https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7079020077076905984
Sign up for the Advanced Financial Modeler Accreditation Today and receive 15% off by using the special show code ‘Podcast’.
Visit https://bit.ly/3AK5dYo and use the code “Podcast” to save 15% when you register.
In today’s episode:
[01:12] - Introduction of the Episode
[06:00] - About Narek and US Capital Global
[08:25] - Market Outlook: Inflation, Tariffs, and Stagflation
[10:33] - Narek’s Journey from Armenia to the US
[14:49] - Favorite Industry to Model: Energy
[17:42] - Real Estate Modeling Insights
[25:34] - Common Mistakes in Real Estate Models
[27:19] - Biopharma and Modeling Challenges
[31:42] - Excel Shortcuts and Tools
[38:22] - Power Query, Power BI, and the Future of Excel
[44:18] - How to Connect with Narek and Closing
Full Show Transcript
[00:01:12] Welcome to Financial Modelers Corner. I am your host, Paul Barnhurst, aka FP&A Guy, and this is a podcast where we talk all about the art and the science of financial modeling with distinguished financial modelers from around the globe. The Financial Modeler’s Corner podcast is brought to you by the Financial Modeling Institute. FMI offers the most respected accreditations in financial modeling. It's why last year I completed the Advanced Financial Modeler, and this year I'm scheduled to complete the Chartered Financial Modeler. I recommend you check them out. But let's get back to the show. I'm thrilled this week to welcome to the show Narek Grigorian. Welcome to Financial Modelers Corner.
[00:01:58] Guest: Narek Grigorian: Hey, Paul. Thanks for having me.
[00:02:00] Host: Paul Barnhurst: Yeah, really excited to have you. I'm looking forward to our conversation. And so we're going to start with a couple questions here. And then I'm going to give you an opportunity to tell us about your background. And we'll take the conversation from there and just have a fun time chatting about modeling here. So you probably know what's coming. Worst financial model you've ever built. You've seen you've worked with. Tell us the story.
[00:02:25] Guest: Narek Grigorian: Sure, sure. I'm very excited to be here. And thanks for having me again. Well, right off the bat, I think everyone in the financial world can remember one bad model they saw. And the big takeaway for me was that you can never trust a model that looks polished. As polished as a model can be. You just have to look at how it's built and the formulas and how they are all connected together. So the specific model that I remember right off the bat was that some basic formulas were totally off and we had used the very beginning starter modeler to put this model together. And what happened was the most basic things, such as debt service coverage ratios and operating expenses. They were not adding up. And these are the fundamentals. Right. And so if that's wrong then the whole model goes off track very, very quickly. And so, you know, one of the biggest issues that this model also had was that it did not account for things like escalating operating costs over time, which this was a real estate model. And in real estate it is very crucial. It also did not factor taxes, depreciation properly for the assets.
[00:03:35] Guest: Narek Grigorian: And, you know, it could be both equipments and the homes that we're looking at also just totally skewed the long term projections by not factoring in the taxes and depreciation. And then for this specific real estate model also they did not consider that the tenant turnover, which is a key revenue driver in a real estate model. And if you have built one, you know exactly what I'm talking about. When you're leasing out commercial spaces, then this is a key, a very niche and important revenue driver. All of this combined was forcing me to go through every part of this model and micromanaging things, starting from assumptions, recalculating everything, and updating each and every cell basically to better reflect market conditions. And you know, the big takeaway here again, for me was that you can never trust the model. It can look as polished as it can be. And you know, models are very powerful. If they're not done right, they can lead you down the wrong path. And based on the model that I was given, everything was completely off. And this could make everything in your model unpredictable, especially in real estate.
[00:04:51] Host: Paul Barnhurst: Yeah, I could imagine a model without depreciation, taxes and no capacity assumptions that turn over whatever you want to call it, right? You can't assume you're going to have 100% tenants at all times. It's just completely unrealistic. I don't build real estate models, and I know that that's pretty common sense.
[00:05:11] Guest: Narek Grigorian: And they did not have a correct WACC. So, you know, if you don't have a correct WACC and the cap rates you're using are way too optimistic for the market, then you're really going down the wrong path with the real estate model that you're building.
[00:05:23] Host: Paul Barnhurst: I could see where whatever the answer was, it wasn't the answer the business should be receiving.
[00:05:29] Guest: Narek Grigorian: Right, 100%.
[00:05:30] Host: Paul Barnhurst: And so the answer they wanted because they showed really good revenue. But, you know, that only means you're gonna have problems down the line if that's not achievable.
[00:05:39] Guest: Narek Grigorian: So what I was given essentially was a wardrobe of clothes. And instead of being given a person to dress, the person with the wardrobe of clothes that I have, I had the clothes and I had to create a person and put the clothes on the person, which is the toughest part. So essentially I had to redo the whole model. It was, you know, nice looking and everything, but it doesn't matter.
[00:06:00] Host: Paul Barnhurst: Yeah. I mean, like I said, you can have as nice a looking model as you want, but if it doesn't make sense, it's not valuable. And you can have a model that's not structured well but at least has good assumptions sometimes. And that can be valuable. Obviously you want both because we've all had those models where maybe it gives a good answer, but it's impossible to follow and figure out. And then you've had the ones that look really nice but have wrong assumptions everywhere. And you want a model with good assumptions and good design at the end of the day. So tell us about your background. Tell us a little bit about yourself and you know what you're doing today.
[00:06:38] Guest: Narek Grigorian: Yeah. So currently I work at US Capital Global, which is a global investment banking firm, financial services firm headquartered out of San Francisco with offices in London and Dubai. We are able to provide credit and securities wealth management. So full services financial services firm in short, I specifically concentrate on the real estate vertical within the firm and the energy vertical. I think that in the past few months there has been a lot of energy based , project excitement within the US as there's a lot of capital inflow within certain states, , such as the Southern Belt, mainly the Sunbelt states such as Texas, Louisiana, to mention a few. And specifically within the LNG world, there's a lot of excitement within the US. So, , you know, we're in the lower middle market to middle market. We cover the space that JP Morgan and the likes of Goldman Sachs don't really look at. So , that's what US Capital Global does. It's a very nice and reputable firm , Finra licensed broker dealer. And, , we are doing projects in the realm of 10 million to 200 million or higher globally and within the US, depending on what sector. And , what field the projects are in. We are generalists, which that means is that we are sector agnostic. And, , this gives us the leverage to adapt and adjust based on global market trends and financial flows, where the capital is flowing from and it's where it's flowing to. So this global presence with my colleagues gives us that advantage, , to navigate the field of this very, very interesting and exciting times globally.
[00:08:25] Host: Paul Barnhurst: Now, it's definitely an exciting time. I mean, right, you got a lot going on. We have, , interest rates that have risen all the inflation concerns, tariffs, people saying, hey, are we going to deal with stagflation? Are we in a recession? When will we be right? It's been a weird market for five years. I think, you know, kind of from Covid since it's really, you know, we had historically low interest rates. Money was free. And then the last five years, we've had a ton of uncertainty and change. So it's definitely a time where models can help. And understanding all these different things and trying to make the best assumptions you can is important because there is a lot of risk, a lot of uncertainty for sure.
[00:09:07] Guest: Narek Grigorian: I totally agree, and I think we are at the time where it's very , very consequential in terms of are we in a stagflation? Is that coming? And so that is the doomsday scenario. And we had a, we had the first quarter results, which was not too good for the GDP of the United States.so everyone's holding their breath for the second quarter and what the effects are going to be in that sense.
[00:09:30] Host: Paul Barnhurst: Yep. At least the inflation in April was lower than we expected. And you know, some of these tariffs have backed off. So hopefully, you know, we're not spiraling toward a major recession. But so hard to predict.
[00:09:44] Guest: Narek Grigorian: From what we see. There's a lot of excitement for foreign direct Indirect investments in the United States. And there's a lot of excitement within the United States for specifically, let's say, real estate developers and, , energy investors. And I think we're at a crucial time where if these tariffs are waived off or done in the right way, where deals are being made between the two countries, then we're really going to see record breaking numbers in the next few years for the economy. If things can be adjusted and the supply shock can be mitigated from the tariffs within the last few weeks.
[00:10:19] Host: Paul Barnhurst: Yeah, it'll be exciting to watch. I know we've seen some big announcements on deals and so hopefully it all plays out well. So I have a question for you. I'm curious. You know you're obviously in the US now, but you started your career in Armenia. What was your path or thinking? How did you go from Armenia to deciding, you know, to kind of come work in the US?
[00:10:38] Guest: Narek Grigorian: Yeah. So I did start my career in Armenia, but, , I think that the opportunities in the US really drew me and a lot of people are drawn to the US, obviously, for the opportunities that this country presents. You know, the United States is such a hub for innovation and growth. , there are certain cities that I can, , single out, you know, San Francisco being one, , for the innovation that comes out of the, you know, San Francisco and the surrounding area, Silicon Valley, obviously. And these are fields that I'm especially passionate about. Now, when it comes to education, there's something special about the system and how it encourages curiosity. And , there's something about the United States where it fosters creativity. Again, depending on the institutional education that you get. So I came here, , I also studied for university in the United States, in the D.C. area, at Georgetown University and University of Maryland in College Park so I think that the United States gives you that challenge to solve real world global problems. and it gives you this global perspective. , so this is something that I found especially appealing. And the opportunities are very diverse here. So that's what I'm really passionate about in the US and it helps people advance their careers, have a good, healthy life and kind of progress along and build a really nice environment around them and around their friends and families.
[00:12:01] Host: Paul Barnhurst: Now it makes a lot of sense. There's a lot of great, great opportunities in the US. And I kind of laughed when you said, you know, a lot of niche markets and innovation. My goal is to dominate the niche market of finance podcasts that don't have the title of CFO in them.
[00:12:17] Guest: Narek Grigorian: Yeah, I think I think you're doing it. You know, I've been listening to your podcast and I've been following it for the past, I would say 6 to 8 months. I came across it on LinkedIn organically. So I think that's the key. Organic growth is how the next sort of podcasts and this entertainments are coming along because people are stepping away from the TV and the traditional cable and podcasts are educational, and you can listen to them while you're driving, eating, doing whatever you want to do.
[00:12:45] Host: Paul Barnhurst: Content has changed the game. And you know, being recognized is more important than ever because with AI, it's so easy to create content, right? You could share pretty much anything and often it can be valuable. And so I think, you know, as you talk about that, as people recognize you and you build a presence that becomes so important when you combine that with content. In today's world, it's really interesting to watch. You know, when I started, there was no AI, and now I use AI to help me be more efficient and effective. I couldn't do nearly as much as I do, but I also see a lot of people that all the content is just AI. And so it's so interesting to just see how the content world has changed. But I agree with you. It's amazing what we can do now, right? Go to YouTube podcasts if you want to learn pretty much anything, you can go to your computer and find out about it.
[00:13:38] Guest: Narek Grigorian: Yeah, and I think not many people know that that was not a way that people could do some things back 30, 40 years ago or even even 20 years ago. You know, it was not this easy. Now we're we, you know, everything's accessible, whether you are in nature, in the middle of nowhere, , or you are inside a house with the Wi-Fi or wherever you are. We are so connected and there's so much information on us that, , I think it's creating a lot of good things and a lot of chaos. So let's work and take away the good things and use the I, , for things to help us, , progress along and learn and make our lives easier.
[00:14:16] Host: Paul Barnhurst: Right. It's like anything. It can be used for good and bad. It's, you know, it's just an instinct. And we have to choose to use it for good. But I totally agree with you. I look at my, you know, my daughter and she grew up with a touch screen in her hand and I'm like, weren't even cell phones when I was a kid. First computer was when I was in high school. And so it's just such a different world and it's pretty amazing. But I'm going to shift gears here a little bit and get more into modeling and talk about that. Since that is the show, I'm sure I could go in a different direction. We could have a great conversation, but my guests might be like, wait, what are they talking about? So I'm curious. I know you've worked in you know, you've modeled for several different industries, you know, real estate, bio firm and others. Do you have a favorite industry that you like to model? Is there one that you're like, oh yeah, I get you get really excited about.
[00:15:03] Guest: Narek Grigorian: I've done many, many different models across many different fields. As you mentioned, real estate, tech, bio biotech and, you know, energy. I have to say that probably because it's, you know, easier and more straightforward energy models are definitely one of my favorites to build. And there's something about the structure of the energy models that keeps it very interesting. And you want to finish it before you walk away. I know it's a little tough and, you know, you get a little geeky with this, but you do want to sit down and kind of get through it. And I'll give you an example. Okay. I was building a model for a refinery. , and, you know, this applies to any kind of energy infrastructure in general. So there's a lot of moving parts for the refinery specifically. And any other energy infrastructure you have CapEx, operational costs, , and most importantly, revenue assumptions. And a big part of this is also standing in the energy modeling offtake agreements, , which often remain fixed but are also linked to spot trading prices. So these prices can actually be pulled directly from live data sources. , and this adds a real time element to your model. And this makes it pretty unique , compared to other industries. Otherwise, , and the key assumptions evolve around things like planned utilization rates, , the product yields, energy markets , future prices, outlook that you have. And of course, you have to factor in regulations, shifts and policy and how it's going to perform long term, short term. You know, I would say 1 to 12 months. Long term, you have to start making adjustments.
[00:16:44] Host: Paul Barnhurst: You know, it makes a lot of sense. Thank you for sharing that. You know, I haven't modeled energy, so I'm not familiar, you know, with that industry. And so it's always fascinating to hear what different people say. So I, I love that because I hear a lot of people say they like energy models. And you know, I know they're very long. I know they can be complex. You know, there definitely are some challenges to them. But there's something that are big right now because we're all trying to figure out the next energy source and how we manage our energy for the planet going forward. So it's definitely something that a lot of money, a lot of time, a lot of capital is going into. But I want to step back. So I appreciate that. I want to switch gears a little bit and talk about real estate for a minute. And the reason why I do that is I really haven't talked real estate much on the show. Talk a little bit about energy and some of those models, but not a lot on real estate. So most of the real estate models you've built are commercial. Residential. Maybe. Let's start there. Like kind of. What are the general models you've built in real estate?
[00:17:45] Guest: Narek Grigorian: Yeah, yeah. , happy to talk about it. I think the reason I didn't mention real estate, because I do it too often. And. Yeah.
[00:17:52] Host: Paul Barnhurst: No, I get it. Totally. Yeah. Energy mentioning energy. That was great.
[00:17:56] Guest: Narek Grigorian: It just stands out. But like with real estate, right? When it comes to the real estate model, there's just such a wide range. And you touched upon them, Paul, , talking about commercial, residential and all the different options we have. So, , I've done most of them. I think there's new things that pop up. There's, , the new models with the 3D printed houses, and that requires new modeling skills and new assumptions, like, , the one Lennar did with Icon. I think it was in Dallas, Texas, if I'm not mistaken, and that it has had a lot of success.
[00:18:26] Host: Paul Barnhurst: So have you modeled a 3D printing one yet? Have you done any of that? It would be fascinating to see the cost. And you got my brain thinking right now.
[00:18:36] Guest: Narek Grigorian: Just so many factors and variables in it with, , what's the cost of pouring out the cement from that needle? And, you know, if you spit out a little more cement, how that's going to change it and make the walls thinner, make the walls thicker. It's really crazy. But, you know, I'll tell you about one that I've built specifically. And I do this the most often. So building a subdivision land development model. Right. Subdivision is when you buy raw land and then, , you know, you're doing your wet utilities, dry utilities, putting roads and getting it vertical ready for the builder to come in to step up and build the house. So for building a model specifically for subdivision, land development is complex because you're not just looking at construction costs right here. You're factoring in zoning regulations, permitting the overall market demand. Okay. And the first step is usually understanding the raw land costs and then projecting out the buildable units, whether it could be homes, it could be condos or it's mixed use, right? A lot of these subdivisions are, uh. The majority of it is residential. And then the frontage where it's hitting the main road is. As we mentioned before, commercial spaces. So from there, you calculate, you know, the infrastructure development costs again roads, utilities, drainage systems.
[00:19:53] Guest: Narek Grigorian: The environmental impact assessments if necessary. And there are even TIF bonds sometimes that you get. So you have to calculate that. and understand how you're going to factor those in the key assumptions with this model that I'm specifically talking about revolve around the projected sales price per unit, the timing of the construction, the cost of financing , and the construction loans. Also, of course, I would say the very, very important one are interest rates. And what is the timing of your construction? Because interest rates can be variable or it can be fixed depending on the basis. Right now it is Sofr. So secured overnight financing rate. So sulfur is just getting adjusted as the bonds obviously. And the markets playing in the Fed's, you know, deciding to cut rates or keep them steady. So what makes the subdivision model unique is that it's very cash flow intensive in the early stages. But when the payback comes, , it's done very nicely. And the units are sold over time, which makes it crucial, right, to track everything from construction progress, which is the beginning part, to sales velocity, which is the last part of it.
[00:21:02] Host: Paul Barnhurst: Yeah, of course they want to return their money. That's what it's all about. And so I'm curious if you mean, not always, but you know what I mean. In general. That's what it's about. Sometimes people want to do the project for passion and other things and they want to return, but that may not be as important. There are definitely some of those get done. But I think in general, for most people it's what the return is that they're really focused on, right?
[00:21:26] Guest: Narek Grigorian: The developer can do projects for what they have a passion for, but when the developer is attracting pref equity or equity investors. Now the investors, what they're looking for is the payback. So if the developer has all of the equity lined up and he can, you know, the developer can borrow the credit. They're good to go. They can build whatever they would like to. Your point though, the passion is what really should drive anything that you do in life.
[00:21:49] Host: Paul Barnhurst: While my background is in FP&A. I am also passionate about financial modeling. Like many financial Modelers, I was self-taught. Then I discovered the Financial Modeling Institute, the organization that offers the advanced financial modeling program. I am a proud holder of the AFM. Preparing for the AFM exam made me a better modeler. If you want to improve your modeling skills, I recommend the AFM program. Podcast listeners. Save 15% on the AFM program. Just use Code Podcast.
[00:22:30] Host: Paul Barnhurst: Yeah, and you know, hey, if you're passionate, you want to build something, but it's not going to be profitable. You can only do that so long.
[00:22:38] Guest: Narek Grigorian: I agree. I agree.
[00:22:39] Host: Paul Barnhurst: You know, it's like I remember that we had a guy here. He was one of the richest people at the time in the state of Utah. And, you know, he built a sports park because that was his passion. And they eventually ended up closing it down. It was a big money pit. So he passed away. And he loved it. And he had a ton of fun with it. But at some point, you know, the company looked at it and said, we're d ping 100 million a year into this. And, you know, that's not sustainable long term or whatever the number was. It was a really big n ber. And so, you know, have fun. But generally you want both if you can have fun and make money. That's always a winning combination. So if you were to say financial models and I think you mentioned a few of these, the key assumptions, what are the most important assumptions with your real estate models?
[00:23:24] Guest: Narek Grigorian: Great question. , I would say first is purchase price, right, which includes the cost of land, property transaction fees, closing costs, title fees, you know, everything. And then from there, the purchase price. We look at the construction costs or the renovation costs, whatever you're doing. Right. Depending on if you're flipping or if you're going ground up. Next from there, right, is the sales price or the rental rate if you are keeping them as rentals. These assumptions are based on market comps, the market comps, and the demand projections within the area where you are conducting the development. Then there's the financing piece, which is again, in my opinion, one of the most, if not the most important part of this, where the interest rates and the loan terms are aligned. How much equity you'll need to put it all into a nice big role. And this shapes the cash flow, the projections. Another key assumption is obviously operating expenses. Especially if you have rental units, there's property management costs. Even while you're building a subdivision there's property management costs. There's utilities, there's maintenance. Right. Because you're not putting up 100 houses at once, you're going at a stage of 10 or 5 and you know, the other ten and five.
[00:24:37] Host: Paul Barnhurst: So yeah, you're building it over six months, a year, two years, whatever it may be, depending on the size of the project, sometimes longer.
[00:24:44] Guest: Narek Grigorian: Yeah.
[00:24:45] Host: Paul Barnhurst: Five years, whatever. I mean.
[00:24:47] Guest: Narek Grigorian: Yeah. So in real estate, you know, especially if you have a rental market, right. If you're dealing with rentals, real estate models, look at how the market will perform in the next 5 to 10 years, because you're really trying to get it into this condition of what we call stabilization, a stabilized product in order to sell it off to a REIT. And during Covid, we saw a lot of those transactions where the modeling was done correctly, and large reads from areas like Miami came and picked it up for very, very large equity returns. The in the multiples of 3 to 6, seven x, which was unheard of. And so, you know, real estate models look at how the asset will perform in the next 5 to 10 years. The factoring trends and the overall economic conditions.
[00:25:34] Host: Paul Barnhurst: Yeah. Yeah. No, it all makes a lot of sense to me. What would you say is the most common mistake you see in real estate models? Where do you think they have kind of the highest risk of going wrong?
[00:25:45] Guest: Narek Grigorian: Yeah, I would say factors are market growth as options and tenant vacancy rates. So a lot of people do not calculate tenants vacancy rates correctly. And it is very important to estimate how many units might be vacant at any given time, which affects the rental income. For example, somebody is , you know, you rent out a unit for 13 months, right? People assess that after the individual in that unit or the family is gone after 13 months, it is immediately rented the next day. Wait, hold on a second. Let's break down the costs day by day. Right. So you have to go into the accounting and understand what is the daily cost of holding this unit vacant. And so you usually have a hold or a renovation period between tenants of 30 to 50 or 30 to 60 days. So again, vacancy tenant vacancy rates are really important to calculate with this given period. Right.
[00:26:45] Host: Paul Barnhurst: Sure. If you have an average of six month leases and you have 100 units and those are staggered, you know, every so often you're going to have maybe on average four units open constantly or whatever it might be. But understanding that assumption makes sense, because that can be a huge difference in that revenue. You know, if you're ass ing 100% operation, of course it's going to look profitable, but it doesn't mean it's right.
[00:27:13] Guest: Narek Grigorian: It's a false model.
[00:27:15] Host: Paul Barnhurst: Exactly. It's not the right answer.
[00:27:17] Guest: Narek Grigorian: Right, right.
[00:27:19] Host: Paul Barnhurst: All right. So, you know, we've talked a little about real estate. I know you've also done a little bit of biopharm. And when we chatted before this, I made a comment about one of my favorite quotes and you commented back with something. And so I want to kind of talk a little bit about this. Many people that have listened to the show have heard me say all models are wrong. Some are useful, you know, quotes by George Box. And I said that and you modified that for Biopharm. What did you have to say when I said that?
[00:27:49] Guest: Narek Grigorian: Yes. George Box right. A great statistician, and had a great conversation about it. What I said for biotech Biopharma is that all models are wrong. And so it's just that all models are wrong. Full stop. I can go about it explaining why. Paul, would you like me to.
[00:28:06] Host: Paul Barnhurst: Yeah, that's why I'd love to go next. Why is that so hard? Or why do you say all models are wrong?
[00:28:12] Guest: Narek Grigorian: Look, obviously there's a little bit of irony here, but let me let me kind of go through it. , and what I meant by that all models are wrong and, you know, that's that for this specific industry. And essentially what this means is that it is biopharma biotech tech bio. However you would like to refer, would you know in the industry that we're talking about? , there's so many unpredictable factors at play from the basic regulatory changes that happen intraday. Clinical trial outcomes. Are you going to need to prove to the FDA something that you didn't in your first clinical trial for the second one to come up, or are they going to spot something, you know, patient responses to treatments when you're conducting, , the experiments or the the you're going to conduct the specific study, right? The clinical trials, these are all incredibly difficult to model. Now when I say all models are wrong, , they're not I wasn't implying that they're useless. Right. Of course you need models. If you're going into this specific arena on the field without modeling, then you should just leave the field and not not have to do anything with it. And the key point is that while you know all models are going to be flawed, they can still provide incredible value, especially when used for decision making. A model in biopharma, for example, can forecast the potential market size for a new drug and estimate the timeline for that drug's regulatory approval. It could be based on historical data. There's always an inherent, you know, uncertainty. So the models might rely on ass options about the, you know, rate of patient enrollment, likelihood of your clinical trial success, or the pricing of the drugs once approved. , and I think the value here comes from recognizing the limitations of the model and continuously refining it as you progress, , as new data becomes available.
[00:30:11] Host: Paul Barnhurst: Yeah. You know, and I've had someone on the show talking about biopharma, and I've talked to a few people and they all express a similar thing. It's a very difficult area to model. It's a little bit of a portfolio in the sense of, okay, I got ten different drugs. Nine of them might fail, but if one hits, I can make good money as long as it, you know, hits big or whatever. And so. Right. You know, many of those models are going to be completely wrong. But in the hole you can still make money. It's kind of like movies in some ways a little bit different. But right. Movies are all about portfolios. It's not about every movie making money. They know when they start they're going to have big losers, right? We've all seen the blockbusters they spend $ 300 million on, and it makes 80 million in the movie theater. And it's like, oh wow, we really lost a lot of money on this. But then you have the one that costs 40 million to make and makes 500 million.
[00:31:05] Guest: Narek Grigorian: Yeah. And that's a, that's a, you know, that's a hit out of the park. So there you go.
[00:31:09] Host: Paul Barnhurst: Yeah. So it's definitely interesting. I think those type of interests should be a little scary for me. I relate it to, you know, the people that when I worked , in FP&A or one of one thing they did is I calculated a lot of people's sales incentives, their commissions, and every so often it's the guy that made 80,000in one month. And I'm like, man, I should be in sales. But then I'd look at the other five people that I'm paying $0 to and I'd be like, no, I'm good with this nice, steady paycheck.
[00:31:36] Guest: Narek Grigorian: Right, right. Yeah, you're totally right, I get it. That's that's the case. Yep.
[00:31:41] Host: Paul Barnhurst: So. All right, so I want to shift gears here a little bit. We have some kind of standard questions we ask each guest. And so the first one is what's your favorite Excel shortcut. What do you use the most.
[00:31:51] Guest: Narek Grigorian: You know right off the bat I have to say the most basic one that's his daily. And it's, you know, the favorite is the control. Plus you know, right arrow or left arrow or control the down arrow. So it takes it to the last cell in the col n with the data you're working with or, you know, makes you j p around large data sets pretty easily.
[00:32:09] Host: Paul Barnhurst: I agree. Control plus arrows are some fabulous, fabulous ones. I like it all right. As you look back over your career, what's the n ber one lesson you've learned that's helped you the most?
[00:32:22] Guest: Narek Grigorian: I think the number one lesson has always been in my life, specifically the passion. So I'm passionate about what I'm doing. I think passion isn't just about being excited, but it's really believing in the work you do and feeling a deep connection with it, waking up and wanting to do it. So I think when you care about things that you're doing, , it just doesn't feel like work anymore. It feels like you're contributing to something larger than life, and it provides you with an energy that helps you push through challenges, , you know, embrace new opportunities and continuously grow.
[00:32:56] Host: Paul Barnhurst: I like it. Thank you for sharing that. All right. So this is a fun question. We ask everybody what's the most unique or funnest kind of thing you've used Excel for in your personal life?
[00:33:08] Guest: Narek Grigorian: I've listened to your podcast. I've been listening to it for the past few months, and I was waiting for this because I do have a little quirk. And , so I'm a big water bottle drinker. I bought a lot of water bottles from different brands. My favorite. I have no equity ownership of a Sentra. I just like the water or any other water company for that matter. You know what? I created an actual model for water bottles because I was spending a lot of money on various sizes, right? They come in various sizes and shapes. They can be reused if it's glass. , so I was curious about how much I was spending with my family on water bottles. So I created this full fledged model to figure out the best deal and how there are sometimes deals in various stores, right? You know, whether you buy it from Whole Foods or Giant or Kroger's or wherever you are. You know, my model compared the cost per ounce. And it sounds ridiculous. And then it turned into this whole analysis where sort of the cheap store brands to, you know, the premiwater brands. , it was just a fun little metric I used, and I got a good laugh out of it with the family, but that was a fun model I made.
[00:34:19] Host: Paul Barnhurst:Bad financial models can lead to bad decisions or worse. So, how do you minimize the risk of a bad model? You make sure the models you build are great. The Financial Modeling Institute developed the Advanced Financial Modeler accreditation program to help modelers like you. The AFM program offers a step-by-step approach to building world-class financial models. The program ensures that you know the best practices in model design and structure, and will help you brush up on your Excel and accounting skills to be the one on your team to build great models. If you want to impress your boss and your clients, get AFM accredited. Podcast listeners. Save 15% on the AFM program. Just use Code Podcast at www.fminstitute.com/podcast.
[00:35:25] Host: Paul Barnhurst: Yeah, so that's when you know you're a nerd. When you build a model like that, we've all done it. I've had one guy, you know, keep taking his dog to the, , you know, kind of dog hotel, one of those type places. And so he finally went back and calculated. What does that look like? How much money could they make? And, you know, the whole business. So I appreciate you sharing that. So what did you determine? Are you spending too much on water and did it save you money?
[00:35:53] Guest: Narek Grigorian: No, definitely spending too much. And I'm actually on the cusp of doing another calculation because I called a contractor over for, , putting a filter on the whole, , system of the house. it is costly upfront, but I am about to run a model to understand what is the payback period for that filter. It is in the thousands. , so, you know, I got to understand the cost of, you know, the net present. What's the present value of this? What's the future value? And so this will help me.
[00:36:20] Host: Paul Barnhurst: When you get all done, share that model with me. I want to see that one.
[00:36:23] Guest: Narek Grigorian: I would love to. Yes. And we can.
[00:36:25] Host: Paul Barnhurst: Put it up on the website. Anyone who needs a bottled water versus filter model. Here you go.
[00:36:31] Guest: Narek Grigorian: That the comparison to that is, you know, making a model for solar panels or, you know, continuously using utilities that you're provided. So yeah.
[00:36:39] Host: Paul Barnhurst: Yeah. Exactly.
[00:36:40] Guest: Narek Grigorian: So it's actually stemming. It's actually largely going to stem from that when I was modeling it in my head. It's going to stem from the same factors.
[00:36:47] Host: Paul Barnhurst: Yeah. I'm sure you thought of all that because you've done that type of. That's funny.
[00:36:51] Guest: Narek Grigorian: Right.
[00:36:51] Host: Paul Barnhurst: So let me know what you decide. I'll be curious to see what the payback period is.
[00:36:56] Guest: Narek Grigorian: Of course.
[00:36:57] Host: Paul Barnhurst: All right. So now we're going to move into rapid fire. No it depends. You get to say yes or no on each of them. And then at the end you can elaborate. So I'm going to run through these quickly. First one is circular references and models. Yes or no. No VBA. Yes or no?
[00:37:14] Guest: Narek Grigorian: Yes VBA.
[00:37:15] Host: Paul Barnhurst: Do you prefer horizontal? You know, one kind of sheet or vertical? Lots and vertical. All on one sheet. Horizontal. Lots of sheets. I'll get it right eventually.
[00:37:24] Guest: Narek Grigorian: I prefer vertical models.
[00:37:26] Host: Paul Barnhurst: All right. What about dynamic arrays and models? Yes or no?
[00:37:30] Guest: Narek Grigorian: , yes. I like dynamic arrays. Yes.
[00:37:33] Host: Paul Barnhurst: How about fully dynamic array models where you're using lambda and different things to manage corkscrews. So the entire model is dynamic.
[00:37:40] Guest: Narek Grigorian: Yeah I actually yeah, I think I use it all the time for the most part I love it.
[00:37:45] Host: Paul Barnhurst: All right. External workbook links yes or no.
[00:37:48] Guest: Narek Grigorian: You know they slow things down, but I prefer to keep it in one workbook usually named ranges.
[00:37:55] Host: Paul Barnhurst: Yes or no.
[00:37:56] Guest: Narek Grigorian: Yeah I use named ranges.
[00:37:58] Host: Paul Barnhurst: Alrighty. Do you follow a formal standard like fast or Smart or any of these that, you know, those formal boards out there that say, hey, model this way?
[00:38:06] Guest: Narek Grigorian: Yeah, I do, I do from time to time. I try to stay consistent and organized in that sense.
[00:38:13] Host: Paul Barnhurst: Okay. Should financial modelers learn Python in Excel? Yes or no?
[00:38:17] Guest: Narek Grigorian: I think it's a great skill to have. I think Python can help with automation and, you know, a bunch of other things.
[00:38:22] Host: Paul Barnhurst: What about Power Query?
[00:38:24] Guest: Narek Grigorian: Power query is incredibly useful as well.
[00:38:27] Host: Paul Barnhurst: I'm a huge Power Query fan. What power BI?
[00:38:30] Guest: Narek Grigorian: Yeah, I think power BI is also essential. I mean, I have to for data visualization especially, so I like it.
[00:38:37] Host: Paul Barnhurst: Will excel ever die?
[00:38:40] Speaker3: That's tough.
[00:38:41] Guest: Narek Grigorian: Question. You know, right now I'll say no, but we can talk about it later.
[00:38:46] Host: Paul Barnhurst: All right. Well, we'll elaborate on that one at the end. Do you think I will build the models for us in the future?
[00:38:52] Guest: Narek Grigorian: In the near future? No. In the far future? Possibly, yes.
[00:38:56] Host: Paul Barnhurst: Okay. Fair enough. Our financial models. The n ber one corporate decision making tool.
[00:39:04] Speaker3: I'll keep it simple for now.
[00:39:05] Guest: Narek Grigorian: No.
[00:39:06] Host: Paul Barnhurst: So, what do you think it is?
[00:39:09] Guest: Narek Grigorian: A great question? I think it's very important. I think that it should drive. It should be the number one factor. Okay. I have to say that, okay, if the model is not making sense, then stop what you're doing right away. If the model shows that you're not, you know, going to proceed with the ass options that you want it to stop immediately and, you know, rethink about what you're doing. But I think that if the model again, this if this is a good model, it should have, you know, data driven insights in a sense, it should stem from market research. So when I'm saying no, I'm talking about simple models. Now if we have models that have data to back it up that have market research and qualitative analysis, these are if everything is contributed to the making of the model, then I believe that financial models are the number one corporate decision making tool. So that's what I meant by saying no.
[00:39:59] Host: Paul Barnhurst: Okay. I thank you for working there. All right. What's your lookup function of choice? Which formula do you go to?
[00:40:06] Guest: Narek Grigorian: Yeah, it would have to be xlookup, because I think that it's more flexible and handles a lot of things with more ease than lookup.
[00:40:15] Host: Paul Barnhurst: Yeah, I, I prefer Xlookup, I'm probably xlookup index match Vlookup, right.
[00:40:20] Guest: Narek Grigorian: I like that's actually a good order. That's actually a good order.
[00:40:24] Host: Paul Barnhurst: You know I put filters in there as well depending on how my data is structured, you know. But yeah, I, I agree with you. I probably use Xlookup the most. All right. You also wanted to elaborate. I think on will excel ever die.
[00:40:37] Guest: Narek Grigorian: You know.
[00:40:38] Guest: Narek Grigorian: Excel.
[00:40:38] Guest: Narek Grigorian: Is essential right now. , now the same way that, , there are new programs and, you know, things happen, right? Microsoft comes up with, , a new name, maybe for something that's based on Excel, but, , integrates, , maybe many, many AI components within this new framework. Right. So you can have Excel that is for example, spitting out, , some form of Excel that's starting to spit out formulas and begin to, you know, fold out ass options so I can see something of a new, innovative way where Excel can be integrated. But not, again, not in the near future, but not in the far future. Also, I think we might be seeing something within the next, you know, 4 to 8 years in that realm where it could be a new version of Excel, or it could be a rebranding for marketing purposes.
[00:41:32] Host: Paul Barnhurst: Yeah, it'll be really interesting to watch. Everybody kind of has a different opinion on this. You know, as I always say, in the long run, everything's dead. The question of how long do I think it's going to go away anytime soon? No, I think, you know, the rebranding, going to a cloud, some of those type of things. But it's going to take time. I agree. I had a big debate about this on LinkedIn, and I think the biggest thing that will take time is, you know, VBA. Yeah, right. Vba doesn't work in the cloud. Microsoft hasn't really supported VBA for a while. They still allow it, but I mean, they're not developing new stuff for VBA. I agree. If they had their choice they would like it to go away in the sense of it's not easy to support in the cloud. There are better languages, but at the same time, you know, if they stop supporting VBA tomorrow, the financial world would just about collapse.
[00:42:20] Guest: Narek Grigorian: I agree, I couldn't agree more, I couldn't.
[00:42:23] Host: Paul Barnhurst: So you know that that's a long journey. I mean, it's years from the day they say, hey, we're going to go to a platform that doesn't support it, to untangle everything and to move forward in whatever way they choose to move forward when they do. I think it's a matter of time personally. Yeah, the VBA will be here forever. We'll see.
[00:42:40] Guest: Narek Grigorian: Well, VBA is.
[00:42:41] Guest: Narek Grigorian: Essential right now. I mean, you know, you automate repetitive tasks or you want to streamline some things, but, you know, you keep it to a good amount, you keep it to a minimum. So you don't want to add too much complexity to what you are doing. That's unnecessary, but it is absolutely needed. I agree with you.
[00:42:58] Host: Paul Barnhurst: You know, I mean, I think you could do a lot. You could do a lot with office scripts. If they open up Python more power Automate, They're putting the building blocks in place to allow you to do those things. Power query replaced a lot of things you used to do in VBA, but they're not fully there. I think anyone would acknowledge that.
[00:43:16] Guest: Narek Grigorian: Yeah, and that's what I mean.
[00:43:17] Guest: Narek Grigorian: I think there's just so many things spread out within the industry, Paul, that, , a few things have to come together, whether it's the AI models merging and getting integrated into different software programs. I think there's, you know, there's going to be a lot of M&A coming into this industry, generally speaking.
[00:43:35] Host: Paul Barnhurst: Oh, I think in the finance space, the spreadsheet other I mean, there's so many AI tools being developed right now, right. At some point we're going to have something similar to a.com. Yes. There's going to be a n ber of companies that the bubble bursts. There will be a lot of acquisition and a lot of change. There'll be some huge winners. There'll be some big losers. But I mean, what did I read recently? There's 75,000 native AI companies that have been created since, you know, ChatGPT was released.
[00:44:04] Guest: Narek Grigorian: I did not know that.
[00:44:06] Host: Paul Barnhurst: Yeah, that's the number I think I'd heard is 75,000. Right? Think how many that is a day. Because we're only talking. Not even three years.
[00:44:13] Guest: Narek Grigorian: And how many went down the drain because ChatGPT was released. You know, how many did that kill?
[00:44:18] Host: Paul Barnhurst: You know, so we're seeing, like, 100 new companies a day or whatever that are AI native. To me, that's not sustainable in the long run, but we'll see. So last question for you before I let you go. I had a great time chatting. You know, if our audience wants to learn more about you or potentially get in touch with you, what's the best way for them to do that?
[00:44:42] Guest: Narek Grigorian: I think the best way is on LinkedIn. I have a LinkedIn presence. You can look me up. Nareg Gregorian, filter me with the workplace, US Capital Global or school. I went to Georgetown University or University of Maryland, College Park. We would love to have a chat. I always like meeting new people and having exciting conversations. I know Paul does too. So you know, it's a pleasure being on your podcast, Paul, and thanks for allowing me to have this, you know, amazing chat with you. And I look forward to having more of these.
[00:45:11] Host: Paul Barnhurst: Yeah. No, thank you for joining me, Narek. I really enjoyed it. Like I said, I do love chatting with people and I'm sure you'll get some people reaching out to you. And I'm excited to share this with my audience. So, thank you again for joining me.
[00:45:23] Guest: Narek Grigorian: Thank you Paul. Have a great day.You too.
[00:45:26] Host: Paul Barnhurst: Financial Modeler's Corner was brought to you by the Financial Modeling Institute. This year, I completed the Advanced Financial Modeler certification and it made me a better financial modeler. What are you waiting for? Visit FMI at www.fminstitute.com/podcast and use Code Podcast to save 15% when you enroll in one of the accreditations today.