Quantrix vs. Excel - Financial Modeling with Lyndsey Weber

What do you see as maybe the biggest difference between supply chain modeling and more traditional financial modeling?

I see a lot more in common than not in common between them. I tend to see supply chain models being much more. When we look at supply chain models and financial models together, I think you get 98% of the picture of what's going on in the business.

When do you think it's right to consider using something other than a traditional spreadsheet?

I know there's things like power pivot right in Excel, but to me this is one of the game changing features that quantrix had is just collaboration layered with role based access to different parts of a model I think is a major need in spreadsheets. One of the things that quantrix has is the ability to define different role based permissions. Auditing financial models is so important and is always required. I think it's very challenging to you.

Welcome to Financial Modelers Corner where we discuss the art and science of financial modeling with your host, Paul Barnhurst. Financial Modelers Corner is sponsored by Financial Modeling Institute. Welcome to Financial Modeler's Corner. I am your host, Paul Barnhurst. This is a podcast where we talk all about the art and science of financial modeling with distinguished guests from around the globe. The Financial Modelers Corner podcast is brought to you by the Financial Modeling Institute. FMI offers the most respected accreditations in financial modeling. I'm thrilled to welcome this week's guest to the show, Lindsay. Welcome to the show.

Thanks, Paul. Glad to be here.

Yeah, really excited to have you. So Lindsay Weber's joining us today. We're going to talk quite a bit about quantrix, which is a modeling tool. We'll get into that a little bit later. That's how we met. She used to work at the company and I thought it'd be a great opportunity for people to get familiar with tools beyond Excel. So we'll talk quite a bit about that. But before we get there, we always like to start every interview before we get into background and some other questions with the worst model you've ever seen. Tell me about that horror story. I know you have one.

Yeah, I think you know everybody has more than one. Of course, the one that sticks out in my mind was maybe one of the first really terrible models that I inherited from someone else pretty early in my career. We were trying to build a really cool workforce analytics model actually, which is not quite financial, but taking all of the data for our supply chain organization and the skill assessments that I think we all typically do in our corporations. Right. And matching People and their skill sets to future roles in the company to see who is, like, the perfect fit. Right. For certain roles that we had planned, you know, three, four, five years out. This model that I inherited had, I feel like, every kind of bad practice in the book. I vividly recall a couple of formulas where they just pointed to a, you know, what I would call like a cell island.

Right.

Like, there was a reference cell that was like row, you know, G B234.

Right.

And it was like a single value. And they had gone so far as to even make the text of that cell white, as if it was like super secretive and hidden. So, you know, trying to reverse engineer this model and figure out where everything was located and the references was horrible. And then, you know, you think you've got it cleaned up, and then you try and run the model and you realize there's a whole set of random VBA code that is lying underneath. Half of the code works, half of it doesn't. You run certain things at certain points and it crashes. So, yeah, crazy, crazy model. But maybe a really good start of the learning curve for reverse engineering some really complicated models with maybe not the best practices.

So did you end up starting over or did you actually salvage that existing model?

100% started over. Paul. Yeah, there was. There was nothing in there that I felt like I could rebuild from, but started certainly took a lot of lessons from that model to try and make it better the next time.

That's what I figured. As you were telling that I'm like, you had to start over. That's just not salvageable.

Nope.

We had a guest on one time when kind of similar to what you said, like the gb, whatever, he goes in one model. I found an assumption in row 7000.

Yeah. Yeah. It's. If you're trying to hide it, in my opinion, that's. You're already off on the wrong foot.

Right.

We don't. We don't want any. Any secrets in our models.

That's just where I use very hidden Right. In vba.

Exactly. Top secret, please.

I totally agree with you. So what was your key takeaway from that? Being one of your first models, what did that teach you?

Organization. And I think, you know, you probably talk to a lot of financial modelers who speak to this, but having a defined structure and approach that can be repeated, I think is essential.

Right.

So this model did not have a table of contents. There was no guide for end users to know where to start in the model or what to do. And there was no dedicated space for things like assumptions and, you know, raw data and things like that. And so to me, that was for sure. One of the biggest lessons from that model was, you know, I can try and build a better mousetrap, but if I just follow my own personal style and opinion on how this should be organized, this is going to be repeated. The next person that comes in and now opens my model.

Right.

And tries to figure out, what is it doing, how is it written, why is it organized this way? I think the analogy I've given people before is a poorly organized financial model, Whether it's in Excel or something else. It's kind of like going into some stranger's house and trying to unload the dishes from their dishwasher and put them into the right cabinets and drawers and cupboards.

Right.

You have no idea where anything goes. It's a complete guess. So we have to open. Got to open all the drawers and all the cabinets.

Right.

And show people where things belong to help them learn the model and how it works.

Yeah, I like that analogy. I hadn't heard that one before. I've heard others, but that's a really good one. And the end of the day come down to design. So important in models. If you follow a structured design, it's going to be a lot easier for people to understand the model. And it sounds like you learned that early on. I wish I had learned more design principles early on. For years, just kind of figuring it out on my own. Never really seen, hey, Hardcode, do this. Taking a modeling course to get really those good design principles. So I built plenty of what I like to call Franken models over the years.

Yes, we know those. Yeah, I think it. It just comes with time.

Right.

You. I feel like you pick up something new, a new best practice as you get the experience, and hopefully see some other good examples of models that other people have built.

Yeah, it comes with time. And you know, I think there's some real value sometimes to just take a course and just get those best practice from the beginning. So you have at least that framework to help guide you, even though you need the experience to go with it.

Yep, absolutely.

So why don't you tell our audience about yourself, your background, what you're doing today?

Yeah, sure. So I have as far as undergrad degree, I typically just call it industrial engineering, but really it was a blend of supply chain management, business and engineering, which I loved and kind of picked that specifically because I didn't know exactly what I wanted to go and do. But I've always loved supply Chain. I love math and even took a class in ERP in college, which I think is a little bit unique. So, you know, was exposed to SAP even in my, in my college studies, took that degree and went and started at Exxon Mobil in the chemical company down in Houston. And that's really where I would say I started to really get the experience, not only in complex models and planning, but also seeing truly how supply chains are run at the largest companies in the globe. And I think that's a fascinating world and I'm sure we'll talk about that. But there is so much interesting overlap and significance, I think, in the relationships between finance and supply chain that really can help you understand what decisions need to be made in a business. One of the things that I did at Exxon was run global projects that had a technology piece to them. So sometimes it was looking at new palletizing equipment to run at our manufacturing plants or bringing in a new mobile application to help track and trace our inventory across the globe. And that really showed me that I love tech and kind of that overlap between supply chain and technology. So that's what ultimately brought me to Quantrix. Kind of a scrappy startup feel. Really small company compared to the, you know, conglomerate that is Exxon. But they were looking for employees versus.

What, 50,000 or whatever, right?

Yeah, something. Yes, something like that. Yeah. Insanely different and refreshing and fun, to be honest. But they were looking for somebody to help start up the pre sales organization at Quantrix, of course, hadn't done pre sales, but certainly had done internal selling to stakeholders with these projects at Exxon and with a lot of the kind of Excel background that I had built up at Exxon, it seemed like a good fit. Had never used the Quantrix product before being hired, but was very fortunate to have jumped into the company and realized, I would say really quickly that this is a really powerful and very cool tool. And I regret not knowing about it when I was at Exxon, for sure.

Thank you for sharing and appreciate getting a little more of the background. I don't even think I knew what an ERP was in college, let alone take a class about one. It's impressive.

Yeah, it was, it was unique. And I think it was really helpful to get that exposure early because certainly going into your first couple of internships and then obviously at a, you know, Fortune 100, Fortune 3.

Right.

Or 4, which is Exxon, you see that right away, right? There's, there's not too many roles that I don't think you end up at. Some point in, you know, an SAP or an Oracle or something like that.

If you're working for big, large global companies, odds are you're going to use one of my used SAP. With Navy. I used Oracle at American Express. Right, I get it. I did procurement. That's where I started my career. Not, you know, which is very close to supply chain. I was a. Writing a lot of contracts and things. Although yeah, very unique for the Navy is you're ordering a bomb or research about a passive surveillance radar. It was all.

That's so cool.

It was a weapons center. So it was service contract.

Awesome.

So it was really interesting. Some of the things you do like, okay, we can't tell you about that. You have to have a, a top secret clearance. But we can tell you what we want to buy, but we won't tell you how we're using it. Had that a few because they couldn't. So that was interesting. But it was fun. It was definitely different. Much better than buying pens and pencils as, you know, the kind.

Yes.

When you hear about. So at ExxonMobil, I know you had a lot of opportunities to build models. Were those mostly kind of supply chain models or what, what kind of models were you building there? What was kind of the goal with the models you worked on at ExxonMobil?

Yeah, it evolved, I would say, with the different roles that I ended up having. A lot of the early ones were, I would say significantly more project based financial models. So thinking about things like return on investment.

Right.

Or I would say large kind of capital equipment type models where the consideration is, you know, we're going to open a new plant in this country and we think we're going to need three or four new packaging lines or production lines. Can we justify that cost? And how much do we need to charge for the film wrapping, the palettes, all of this, as far as the raw material costs, how do we back then calculate and figure out what are our margins, how much could we go sell this product for, things like that. So I would say more kind of project based finance were some of the models that I built originally, of course, as I mentioned with the kind of force model, some of that later bled a little bit into I would say kind of like workforce analytics people, personnel planning, which is another kind of interesting, you know, tangent off of financial modeling. And then I would say towards the end it was a lot more true. What I would call supply chain planning models, so integrated business planning, sales and operations planning. Saying we've got, you know, this, this amount of Demand, Right. Coming in for all of our product lines for this month through the next six to nine months. How do we balance that with what our current supply is and what our production plans are and ensure that we're maximizing the fulfillment of products to customers? And that, of course, includes not only, you know, sales units, but also, like we said, margins, pricing, runtimes at the plants. My role was really to use the models that we had built to make those decisions and to make sure that we were hopefully maximizing the revenue for the, for the business unit.

And were those mostly in Excel or were you using other tools? Cause I imagine there's time, there's some optimization and different things you need to do that could be a challenge with just Excel. So I'm curious, was it all, all Excel based or were there other tools you use at all?

Yeah, primarily, I would say, Paul, I was pretty familiar frequently day to day in SAP and Excel as kind of the two primary tools of choice. You know, for obvious reasons, there's not as much, you know, nitty gritty decision making I think that you can make in SAP, particularly when you have disruptions to your supply chain.

Right.

If there's a stock out or there's a plant strike or tsunami or a typhoon.

Right.

We don't typically have the luxury of running to an ERP system to make those decisions quickly. So we end up in Excel. Of course, other departments within the company and some of my close friends worked in, I would say more of a true optimization department, and they had some very sophisticated, to your point, optimization type tools.

Right.

That they used to do. You know, I would say complex, you know, linear programming, running algorithms, things like that. But for the most part we were, we were putting our heads together and working through the details in Excel.

And that's why I was wondering when you, Is there some optimization or things like that and that makes sense for the bigger optimization, running it through a specialized tool or an algorithm or whatever the basics in Excel, and I think that's pretty common for most companies. And then you may have something else depending on the complexity. What do you see? I'm curious. You've built financial models, obviously the project finance, you've done supply chain, a number of different areas. What do you see as maybe the biggest difference between supply chain modeling and more traditional financial modeling?

Yeah, this is actually kind of a hard question, I think, because I see a lot more in common than not in common between them. You know, one of the things I would say too, Paul, and maybe this is just from my experience is I tend to see supply chain models being much more granular and detailed, at least in the assumptions that we're making.

Right.

Because oftentimes it is boiling down to not only a particular, let's say sku.

Right.

Or item that we're selling, but even peeling back two or three more layers of that to say, well, what are the raw materials that go into those who are the suppliers that are feeding us those who are the suppliers of those suppliers.

Right.

So typically I feel like in a supply chain model we have maybe two or three tiers, even deeper of assumptions that we're making than at least in like a traditional, you know, three statement financial model or something like that. Right. So I think that's one of the primary differences. I have seen financial models that go to a detailed kind of daily basis, especially if we're dealing with like stocks or, you know, futures, something on like the trading markets. But I think that's another, you know, kind of maybe differentiator of supply chain models is oftentimes we are looking at, you know, daily data, daily decisions, or at least weekly if we're looking at, let's say, production plans in a market where there's, you know, a lot of volatility and we have to make adjustments to those plans, you know, pretty frequently.

Yeah. So it sounds like, I mean, I'm going to guess there's a couple things. Biggest you mentioned is granularity. Often it's more granular because you need to know how much to order. There's a lot of things that you have to get right or you end up with a working capital problem, a cash, all those type of challenges, a bunch of inventory that goes bad, whatever it might be, or customers who can't get what they want and they're all upset and go elsewhere.

Yes.

One of those type of things. And then I would imagine the other is with a lot of those models, you're probably not building with supply chain, like three statements.

Yeah, not, not.

You're not, you're not modeling the balance sheet per se. Right. You're modeling the inventory, you're modeling cash. You're not thinking of it in a three statement type of.

Yes.

Way.

Yeah, for sure. And I think, you know, to me that's one of the things that I have found so fun and interesting about seeing both the supply chain side and the finance side is because I actually feel like they're two different sides of the same coin. When we look at supply chain models and financial models together, I think you get 98% of the picture of what's going on in the business.

Right.

Because yeah, to your point. Exactly. We have very specific KPIs in the supply chain planning world that we want to track.

Right.

Unit cost, to serve on time, in full margins, on a per product or even a very specific per SKU basis. All of that information ultimately does feed into the three statements.

Right.

And so I think it's very interesting where you could really start either direction. But I think it's kind of fun to start at kind of the three statement kind of PNL view of a business drill down into some areas where you have some questions and see the links through all the way to the supply chain. Because through the supply chain lenses, where you're going to get access to the intel around. You know, what are our customers buying behaviors? Do we have an efficiency problem? Is that coming from manufacturing to your point, even on procurement, like, do we have an opportunity to renegotiate a raw materials contract that could significantly reduce some of our expenses? Right. It's fascinating to me, kind of the clues that you can pull together from both of those types of models.

Yeah, well. And you see a lot of companies that will have supply chain finance roles. Sometimes you see supply chain kind of sitting in finance. You know, I was at a large Fortune 100 company last week and you know, we trained both finance and sourcing people. They were both in the same group. And so there's people doing sourcing, there's people doing more traditional finance roles. Because you're right, in many ways they are just opposite sides of the same coin. Whether you're building three statement model or you're building supply chain model, you really need to understand the operations of the business. And seeing both those together helps you understand them at different levels, which makes you better. Whether you're doing supply chain or you're building the traditional three statement model, you'll be better at the job understanding the other.

Absolutely.

And so you've had definitely had a good opportunity to kind of see both sides of that. And I would imagine kind of coming to Quantrix probably opened your eyes and helped you see a lot more at a bigger level than probably some of the detail you were doing at ExxonMobil.

Yeah, absolutely. I mean, one of my favorite parts of my time at Quantrix was seeing industries outside of oil and gas and chemicals. Right. Of course. That's where I started my career at Exxon. It's so fun and interesting, I think, to see how financial models vary based on the industries that you're working with.

Right.

So you Know, Quantrix has customers across, you know, tons of different industry verticals. So you know, one day we might be talking to a company that's doing a big M and A model.

Right.

We may be talking to another company that is in, you know, electronics and they're trying to make decisions on these multi year contracts, right. With communications providers and they maybe also have a retail arm and then they also have a semiconductor planning arm.

Right.

It's, it's just so cool to see, you know, the variety of the industries there. But I, I think to your point, Paul, for sure, it felt like coming from the supply chain, very tactical planning at Exxon to this role at Quantrix, we certainly kind of, you know, went up 20,000ft, if you will. A lot of the models are, you know, much more strategic and kind of high level in the sense of, like you said, rolling up to the financial statements, looking at things from a P and L level. Even if you have a large company where it's multiple P and ls.

Right.

That just the level of detail is certainly, I think rolled up and consolidated a lot more with what we were often seeing at quantrix.

Sure makes a lot of sense. So why don't you tell our audience a little bit about, a little bit more about what Quantrix is, maybe an overview of what the tool is and then I have a few specific questions I'd like to get into to just introduce our audience because I'm guessing 99% of the listeners may be more like Quantrix. What's that?

Yeah, yeah, this, this was always the, the greatest challenge and the greatest passion I think of, of my time at Quantrix was spreading on the product and what it could do. So in short, quantrix is a multi dimensional modeling and planning platform or tool. So certainly it's, I think, you know, usually easiest for people to think of it as kind of like an Excel alternative. Certainly it plays in that space. I would say more often than not it has an in memory calculation engine. And I would say the best way I've described it to people is if you are an expert financial modeler and you know all of the best practices and tricks in Excel to make a beautiful, consistent, airtight financial model. I think you would love Quantrics because most of those best practices are built in inherently to the way that the tool operates from a structural perspective. How you build a model from scratch, how you can prototype in a model and then ultimately share that with other users, I think is incredibly flexible and to me the biggest differentiator, you know, especially if we're comparing it to Excel as the reference point is just the level of built in efficiency that I think modelers could gain while still retaining a little bit of that kind of cell based user interface that everybody loves from Excel.

So talk about what are a few of those things when you mean if you're doing best design, a lot of it's built in. Maybe give us a few examples of that. With Quantrix where it may not be in Excel, can you throw out a few examples?

Yeah. So maybe my favorite is there's a concept in Quantrix of categories or dimensions. So oftentimes I think, you know, expert financial modelers will define named ranges. Maybe if you're ultra fancy, a dynamic array, right. To help you as your model is usually expanding, sometimes contracting, but usually it's expanding and growing. We want to try and make those references to cells as dynamic and bulletproof as possible. In Quantrix that concept of a dynamic array or range is automatically built in. It's not something that the user, the modeler has to define. You can really just press enter on the keyboard and create those subsets of items within your model and then drag and drop them actually to different places in the model to use them in multiple places. So I think that's one example. The other example, of course I think that is most common that people see when they first start looking at Quantrics is not, not super unique among a lot of other modeling tools, but natural language formulas. So again, you know, the benefits that we use for named ranges, tables, all of those kind of best practices.

Right.

In Excel or in Google Sheets, that is out of the box. How you refer to objects within a quantrix model is simply by the kind of plain English name that you've given to every single thing within your model. There are no, as we used to call them, kind of battleship formulas.

Right.

There is no concept of a C7 in Quantrix. It's going to be the name of that month or that product or that line item in your P and L that you're going to specifically refer to in your formula. So they end up being a lot more human readable.

Yeah, no, I, I teach a lot about Excel tables and trying to help people understand the difference. Like okay, it's structured references and that's what most pretty much all multi dimensional modeling tools, whether it's quantrix or you know, pigment, anaplan, whatever. There's, there's quite a few out there. That's what they're doing. They give you that natural language which is really nice because you know we all understand the C7, B7. It's ingrained if you've used a spreadsheet for any part of your life, but it really doesn't make sense in a lot of ways. Like it's not intuitive to go, okay, C7 times B7, that's revenue times quantity. Like, wouldn't it be a lot easier to just say revenue times quantity and have it applied to the entire column? Which is the type of benefits you see with a tool like quantrix. Those are a couple great examples. What were maybe your favorite things about quantrix? Like what did you really, you, you mentioned the multi dimensional modeling, but any other things that you really enjoyed that you're like, oh, I'd love to see Excel adopt that or, you know, this makes it so much easier, so to speak, from your perspective.

Yeah. So a couple of the things I loved about quantrix were, number one, how easy and kind of native pivoting is in quantrix. So we always talked about this, as always on pivoting in quantrix. So given that kind of flexible structure and the ability to easily define dimensions or categories in your model, we also had the ability, or the modeler has the ability to really drag and drop those categories to the x or the Y axes in your model on demand, on the fly. And it doesn't impact formulas whatsoever. So you know, quantrix doesn't require formulas to be oriented. You can pivot at any time and that logic kind of holds together. So of course that's one thing. I know there's things like power pivot right in Excel. But to me this is one of the game changing features that quantrix had is just, even if it's just personal preference of different modelers and the same model of one person wants to, to see, you know, time along the X axis, the other person wants to see time, you know, broken down across all of the different rows. I would love to see an easier way to just quickly pivot all of the data you might have in a single sheet in Excel. I think that would be awesome. And then, you know, maybe number two, I know Excel is making a lot of headway, especially with, you know, the ability to integrate with teams and things like that. But collaboration layered with role based access to different parts of a model I think is a major need in spreadsheets and oftentimes not super easy to set up without being a little bit restrictive, frankly, or even just not intuitive. One of the things that quantrix has is the ability to define different role based permissions and that can do everything from hide certain aspects of your model to remove certain even interfaces or navigation components to the model, or dynamically filter a really large data set to only show that user the aspects of the data that you've configured for them. So that was really great because it's a little bit richer than just permissions based or you know, protection in a spreadsheet. That would be something I'd love to see in spreadsheets or in Excel.

In today's business world, financial modeling skills are more important than ever. With Financial Modeling Institute's Advanced Financial Modeler accreditation program, you can become recognized as an expert in the field by validating your financial modeling skills. Join the Financial Modeling Institute's community of top financial modelers, gain access to extensive learning resources and attain the prestigious Advanced Financial Modeler accreditation. Visit www.fminstitute.com backslash podcast and use code podcast to save 15 when you register. Yeah, it'd be great to lock certain things down, share them, show only parts. So really it's that object oriented, compartmentalizing things versus hey, here's your whole sheet. And I've seen a few tools that have created some stuff like that for Excel. What? It's a tool that sits on top that allows you to do some of those things. And yeah, it would be nice to see more of that. We're, we're making progress. But yes, collaboration, enterprise, scalability, there's, there's a number of things like that that are definitely challenges. Right. So on the flip side, what's something you disliked about modeling and Quantrix? Like what were some of those things that maybe I'd like to see this a little different or that you found maybe not as intuitive as you would like.

Yeah, you know, I think some of these things, even while I was at the company, we were already making a ton of headway in this. One of the things that I really loved doing and kind of built a passion for and a little bit of a reputation for at Exxon with that, with the models I was building was the user interface. So, you know, we talk a lot about this I think in the financial modeling space, but you know, different preferences for formatting, layout, color coding, and actually building a user interface or kind of an application layer, if you will, on top of your financial model to make it easier for people to interact with it. That is something I loved doing. And when I first joined Quantrix, I feel like we had some really good kind of baseline. I'd call it like design or application functionalities where you could take your model and then you could start laying over what we called canvases to give people kind of a nice friendly entry point into maybe a complicated model. At least at the beginning it felt like we were, we needed a little bit more rich functionality.

Right.

To make the types of interfaces that I think are needed for models and especially if you are sharing your financial model with non financial modelers.

Right.

To use, either they're inputting data or they're reviewing a sales forecast, for example. We made a ton of progress in that, I would say on kind of the second half of the time I spent at quantrix, which was exciting to see, but that was definitely one piece where at first I was like, oh, like there's so much potential here. But we don't quite yet have the functionality that I think we need to build beautiful financially driven model driven applications. That's probably one, I would say number two, I don't know if anybody's fully cracked this code yet, but you know, auditing financial models is so important and is always required and I think it's very challenging to build an auditable component of a modeling application. We of course had an audit trail in Quantrix and it was super detailed. You could see everything that was changed or modified within the model. But I think tracing through the evolution of the model over time is something that can be really challenging to get right and to answer all of the different questions that different Personas want to get answers to. You know, an investor or an auditor maybe wants to see different information from just you or me who's maybe been building this model for the past six months and we want to revert back or see, you know, why did we build something a certain way or why did a user go in and change a certain value? So I think there's, there's always an opportunity to enrich the capabilities on kind of the auditing or the audit trail functionality.

Makes sense. Yeah. Auditing is always a challenge when you're trying to figure out, okay, who changed the number, why, what's the logic and what's story. Yeah. And that's usually the challenge. Yeah, I could see all the, the words here that tell me what happened, but that doesn't give you context.

Exactly. Yeah. The qualitative information I think is so hard to document and make it easy for users to access when they're, they're trying to do that work.

But that's the fun when you inherit somebody's model.

Absolutely. The, the treasure hunt is, is always fun. Yeah, I, I, I do love that part. Even though sometimes it makes you want to pull your hair out.

There are aspects that can be fun to try to figure out. Other times when you're just like cursing somebody's name. It's a little both. The love hate relationship for sure.

Definitely.

So I'm curious if somebody's listening to this and they're thinking, ah, you know, I might like to go beyond a, beyond Excel for building models, you know.

Yeah. I think a couple things come to mind. One is scalability, which I think is a probably way overused term, but I think it has become clear, you know, even during the time I was at Quantrix on the pre sales team at some point people oftentimes reach, I would say, kind of a threshold where it just becomes difficult to maintain and extend and even the most sophisticated, elegant spreadsheet model.

Right.

Whether that's because the business is scaling and becoming just so complex that we can't, we can't manage it with kind of a hub and spoke Excel, you know, environment anymore or oftentimes I would also see the team, the financial modeling organization at the company is growing such that it's not sustainable for everyone to be even the, you know, online collaborative Excel environment. There, there are limitations.

Right.

And sometimes we need something that allows us to move quickly and prototype faster and create a series or a network of models that are connected outside of externally linked workbooks. Right.

As come on, who doesn't love external workbook links?

So I, you know, I think I would say two things in summary on that Paul. One is definitely scalability. The company is growing at a rate at which we can no longer successfully, reliably, confidently maintain the spreadsheets that we have. And also I think number two is likely the pace at which the business is changing. We can't continue to rely on a kind of single threaded Excel expert in the organization to spin up new models or change complicated models fast enough to where, you know, we might be having changes to scenarios and to assumptions daily or even hourly. And we can't put the businesses kind of success right on one or two core subject matter experts. And one of the things that I think quantrix unlocks is a, the ability for people to all jump into a model and quite quickly understand how it works, what the formulas are doing, read and validate. But even number two, one of the things that I think is, is pretty unique to quantrix is the prototyping phase. How quickly you can literally start from a completely blank Quantrix model and begin building out and extending that model so much quicker than even a very, very adept Excel modeler. Can do. And part of that is just the way that the structure is built and the fact that in Quantrix you don't need data, you don't need numbers and cells to write formulas and completely build out the frame of your model. The data can actually be the very last piece that you pull into a Quantrix model. And I think people oftentimes underestimate the amount of time and risk that that removes when comparing Quantrix to something like Excel.

Okay, now that's really helpful. So as I'm hearing it, it sounds like if people are dealing with small models, relatively simple use cases, you would recommend a spreadsheet. That's probably the easiest way to do it. Cost effective, people know it all those type of things. But when you hit those scalability issues, or as I often like to call it, when you find yourself in Excel, hell is probably time to look at something like a Quantrix or others. When you really need to scale, you need that higher collaboration, you need to be able to quickly make all those changes. Because we all know if you have a really complex model, we've all been there where they want a bunch of changes made and you're like, okay, that's going to take some time. Even if you designed it well, depending on how extensive the changes are, it can be material. If they're simple changes and you've built a model well, you can do it on the fly like changing assumption or whatever, but the more complex it is, it can be really challenging. We're having multi dimensional modeling. Sometimes it can be as simple as just moving the pivot around.

Yes, yep, absolutely.

I mean, and that all makes sense. So I'm curious, have you used any other tools for modeling beyond kind of quantrix in a spreadsheet, are there any other tools you use or that you've had experience with?

Not many, of course. You know, I've probably like you, I try and keep tabs on a lot of the seemingly daily new entrants right into the market. On this I've seen some pretty interesting, some honestly just beautiful looking tools out there, but I haven't had the same amount of experience using them. Truly my I love Excel. We used to talk about this even at quantrix. You know I think there is, there are many times of places where we should just use Excel because it is amazing how much you can do. And there are thousands of successful global companies that use Excel.

Right.

It's their primary tool of choice. I haven't used as many outside of Excel or Quantrix to probably give a fair shake on what those are like. But I am constantly impressed, I would say, by the, especially the user interfaces of some of the ones I feel like have come out recently. They're just, they're beautiful looking products where I think, you know, somebody that was not in finance could look at this and say like, wow, that's a beautiful looking application. Like I'd be interested in looking at some data or, you know, looking at a scenario within this application.

Yeah. And I know one of you and I have talked about before and I just released an episode this week is from somebody who uses Causal for all their modeling. I know that one has a really clean interface that you and I have talked about and there's, there's a number of others out there. Some of them are more purpose built just for planning and may not really be more general purpose modeling, which I think Quantrix is a little more of that general purpose modeling. I think of it as kind of a little more enterprise tool than Causal, which I, if anyone goes to my website, I've done reviews of Causal. I've done a review of quantrix. They're a couple of years old, so I'm sure things have changed in the software, but it'll give you a general idea about them. So if people want to learn more, they can do that, you know, and I'll obviously find the website. But yeah, it is, it's, it's amazing to watch how many are out there and I've seen a few I really like that have tried unique things and then you see some that they're very similar to the other 50 multi dimensional modeling tools. Yeah, so I get it. All right, so we're gonna move on here to a couple Excel questions and then we're gonna go to what we call rapid fire and I'll walk through how that's gonna work. So what's your favorite Excel shortcut?

Yeah, I am probably super lame compared to some of your guests on the podcast here. I, I love Control T. I probably have used Control T to build tables more than any other shortcut. Of course, some of the, you know, easy ones to navigate up and down, lots of rows and columns. But I would say probably the one that I consistently felt like was, you know, really helpful was making tables for sure. And that was just setting you up for success. I think a good habit to use Control T to remind yourself to make tables when you're building complex models.

Well, if it makes you feel better, you're in good company. I interviewed Ken Pulse, if you know who that is. He expert on Power Query, expert on Excel Power.

Yes.

He's been an Excel MVP for almost 20 years now. And one of the global experts first training. One of the very first trainings ever was his on Power Query that was out there. And his favorite he mentioned was Control T. But what he said, he goes, my Control T is an Excel's Control T because he has his own tool he's building at. It's like mine also allows you to re. Requires you to rename the table an appropriate name. When you press Control T and I'm like, I love it.

That's brilliant. Yes. Excel. Take notes.

That's the first thing you have to do. And if you forget, you're like, oh, which one's table 16?

That's awesome.

When you look at your formula, go table 16. That doesn't tell me. I don't know, I miss name.

I love it.

Yeah, so I'm a big control T2 that. That's high on my list. I love Control T because I think tables are critical. If you're going to use Excel for any real data work, you have to know tables. So next question is, do you have a favorite formula?

Oh, this is a tough one, I would say. Prior to knowing quantrix, I always loved Index Match. I think Index Match is really cool, what you can do with it. Of course, now I think with xlookup that maybe slightly edges it out just for kind of ease of use. But I always thought Index Match was super cool just with the way that you could kind of navigate, I would say pretty quickly to kind of the subset of the data that you were looking to, you know, return.

So probably Index Match, that, that's a good one. We get a lot of people to say that. And then as you look back at your career so far, what's the number one lesson you've learned that saved you the most time over your career, especially.

When it comes to financial modeling? You know, we covered this earlier. I personally, I don't think you can ever be too organized, whether that's in building a model or even, you know, one of the biggest things I feel like I learned pretty early on, even at Exxon, that I feel like has helped carry me through my career so far. Is understanding, taking the time to learn and to document what the stakeholders on your project or for your model, what they are looking for, what they need and what is important to them, even if it's something that is just emotionally important to them and less so, you know, critical to the business, designing a financial model, coming into a meeting prepared, knowing who your stakeholders are and what they want to get out of the meeting or the model or the project, I think serves you incredibly well. The sooner that we can kind of train ourselves to be on the lookout for that in every conversation, I think it's amazing how much more effective you.

Can be in your role.

Fully agree that that makes sense to me. And design organization is so important in models. And I really like how you said not just design from, hey, here's a process I'm going to follow, but also understanding the needs of, of your business partners. Like you said, even if it's just an emotional need, as long as it doesn't cause issues with the model, trying to address those particularly. And you said the input layer, right, that executive summary, not input, but I mean, the more the user layer, whether it's an executive summary or whatever it may be, where most people are just going to be looking at that part of the model, if you could really make sure it meets their needs, they're going to be thrilled because the last thing they want to do is dig through the entire model.

Yeah.

The example I've heard used a lot of times that I love is when we get in a car, nobody wants to pop the hood, make sure the engine's working. You just turn the button, expect it to work. And that's like a financial model. You just want to turn it on, be able to see the dashboards and everything. So you can do what you need to do. You can drive.

Yeah.

You don't care about what happened under the hood. You want to see enough to know that it's directionally correct or it meets your needs for your decision.

Yeah, absolutely. And I think, you know, we used to talk about this even from my role at quantrix, being in pre sales, trying to set the first impression of the product. When you're talking to an expert financial modeler that's maybe considering something outside of Excel, the emotional kind of tie to what the product looks like I think can't be overstated.

Right.

And whether you agree with it or not, I think the reality is Excel, the emotional kind of tie to what the product looks like, I think can't be overstated.

Right.

And whether you agree with it or not, I think the reality is people tend to trust products, people that they think come. People tend to trust products, people that they think come well presented.

Right.

So I think a financial model, frankly, should be no different. A presentation, a PowerPoint should be the same way.

Right.

It should be something that looks clean, is eye catching.

Right.

Maybe even sure Color has its time and place, right. In a financial model, but something that upon the first impressions, well presented.

Right.

So I think a financial model, frankly, should be no different. A presentation, a PowerPoint should. Somebody feels like it looks like it has been cared for, there's been attention to detail, it has a good appearance to it, makes people want to use it, and I think want to trust it.

Sure. There's something to say to have a professional, clean look that makes them feel comfortable. Totally agree. Like, when you're selecting software, if the user interface looks more appealing, you're automatically going to be more interested. Obviously, you should get under the hood when you're selecting software and make sure it meets all your needs. But what's the sales guy? The salespeople typically show. They want to show the bells and whistles and what highlights the tool. And that's usually kind of like the, you know, the model of what you're showing the end user. I think there's definitely some comparisons between the two. All right, so this next section is our rapid fire section. And so what I'm going to do is I'm going to ask all the questions for Excel and then we'll go through and ask for quantrix. And with quantrix, they'll be the answer. You can either pick it or you could say, doesn't apply. Right. Like some of them I know won't apply to quantrix here, and a few of them I may not even ask because I know they won't apply. A few of them will only need to ask once. But we'll start with Excel, and here's how the rules work. You get no more than 10, 10 to 15 seconds to answer. It's a yes or no. You can't say it depends because all of them could be that. And then at the end you can elaborate on one or two that you kind of have a passion about. Like, I want to explain more. This is too nuanced to go with just yes or no, because I recognize some of them are. So you ready?

Yep. Let's do it.

All right. Circular or no circular references?

No, let's avoid at all cost.

Yeah, that's. That's one. That's pretty universal for the most part. Vba or no vba, I lean towards.

No, there's. There should be a better way. Question your motives.

I would say, okay, and then do you prefer a horizontal. When I say horizontal, like more tabs, or a vertical model where, like all your schedules, everything's kind of mostly compact in one sheet.

So I think horizontal for Most users of the model vertical for the architect of the model depends on maybe the audience, but generally that's how I feel.

Makes sense. Dynamic array. Should you use them in your models, yes or no?

Absolutely yes. All day, every day, as much as possible.

I think you would love. I had a guest on where they've done a hundred percent of their financial models, including the corkscrews with dynamic arrays because they've had Lambdas built. There's a guy who's built a bunch of lamb.

Oh wow.

You go on my website, you can download it. If you go to the Excel files, there's a link to their model they've built and you'll look at half the formulas like, okay, those are custom formulas. I don't recognize them. But they're doing it for 100 of their modeling firm.

Impressive.

So it's really interesting because. Right. There's all those little limitations that people have to overcome. External workbook links, yes or no?

No. No.

Just don't, don't put yourself through that pain.

Just don't.

Named ranges, yes or no?

Yes, definitely.

And when you build models, have you ever used like a formal standards board that you followed? Like there's Fast and some others out there for Excel?

Yeah, you know, we had that come up a handful of times when I was at quantrix personally. For me there's a time and a place for it. For me, I have not had a need for them. So I'll say no.

Okay. Yeah, we, we definitely, we get a lot of both on that. Will Excel ever die? Yes or no?

No, I think it will continue to evolve. However, I don't think we will ever eliminate it.

Okay, fair enough. Will AI build financial models for us in the future?

I think maybe I would say for the sake of brevity, no. I think it is more likely to help guide our model building than actually build one.

Sure makes a lot of sense. She sell protection in your models, yes or no? No.

Use a better tool.

Oh, I can see the quantric stuff coming through on a few of these. So here's the next one. Do you believe financial models are the number one corporate decision making tools?

Not on their own, no.

So what?

I think we need a combination of supply chain and financial models to make good decisions in the business.

I like it. I had one person that responded, no, politics are the number one corporate decision.

That may be true.

Yeah, exactly. I'm like, that's a hard one to argue with.

Yeah.

All right. When you're working in Excel and I think I know the answer to this one because you mentioned it as your favorite function. What's your lookup function of choice? You like choose Vlookup, Index Match or xlookup?

Yeah, probably varies based on what I'm doing. Probably my classic favorite is Index Match.

And is it Index X Match now or you still use mostly?

Yeah, of course. Yeah, it's definitely Index X Match now.

Yeah, just want to make sure because there's some that still go with the old match. Yes, I've finally started adopting the X match only in the last few months.

It's a little weird.

I'm like, why didn't I do this earlier? It's just so much better.

It is better.

So, all right, so now we're going to run through those questions for quantrix and for a few of them I won't, I won't run through, but do you deal with circular or. No circular references? How's that?

The Quantrix usually don't. Don't have them very rare.

So no, you don't have vba in Quantric, so we'll skip that one. Do you prefer modeling horizontally or vertically in quantrix or is that not really applying? And is it Index X Match now or you still use mostly?

Yeah, of course. Yeah, it's definitely Index X Match now.

Yeah, just want to make sure because there's some that still go with the old match. Yes, I've finally started adopting the X match only in the last few months.

It's a little weird.

I'm like, why didn't I do this earlier? It's just so much better.

It is better.

So, all right, so now we're going to run through those questions for quantrix.

You can do both. Just pivot the dimensions.

That's true. So it really doesn't matter because you can just flip it.

Yes.

Obviously everything's dynamic, so dynamic arrays don't apply. External workbook links, is that an issue? Do you link out to other stuff or what's the.

With Quantrix you can link to other models on cloud, which is really cool. So there are models that can actually talk back and forth to each other without having to hard code a link within the model itself, which is really cool.

Got it. Nice. Name ranges aren't going to apply because everything's kind of named.

Yep.

Formal standards board. Again, that one doesn't apply. Excel AI. I'm guessing you can lock down permissions at any level. So sheet cell protection really, again, doesn't apply.

Completely unlocked from a mindset perspective. In Quantrix, role based access can be data driven model Location driven, highly, highly flexible. It's incredible. Yep.

So that, that concludes our rapid fire. So now we're going to go into the last section here. If you could offer advice to our audience to be a better financial modeler from your experience or just better modeler in general, whether it's supply chain or finance, but just a better modeler, what is the number one advice you'd give them?

I think what has helped me the most other than the things we've already mentioned about, you know, getting to know your stakeholders, being organized. I have always started any model I've built out by drawing out on a piece of paper or a whiteboard the inputs, the outputs, the key calculations. And the key, I think with the calculations is to write them out in English, not in formula syntax. Get serious about what it is you are actually trying to solve for. Once you have those things written out, I think it becomes quite easy to start drawing lines and mapping things together. And what I have always ended up with, even for, you know, prototypes where I was building custom demos for some of our prospects at Quantrix and pre sales, you end up with kind of a beautiful page that really guides you on exactly how you should build the model. And even a complex model, it's kind of the eat the elephant concept.

Right.

Like one bite at a time. Once you have this kind of working page, it doesn't have to be, you know, super clean or pretty. It can be kind of, you know, back at the napkin. But I think there's something to be said about writing it down, drawing the connections, using it in kind of plain English and then going to your modeling tool of choice and building that according to what you've drawn out. It really helps, I think crisp, kind of your, your thoughts around how this should be done and it makes it easy to, to make sure that you're tracking along and building it with the.

Best practices basically to prototype it ahead of time. And your recommendation is to pull out a good piece of paper, pencil, pen, and kind of map it out in business terms.

Yes.

Before you go to the tool and start writing it and whatever, you know, the tools kind of language is. Yep, got it. Makes a lot of sense. There's definitely something to be said for, for prototyping it. Usually, you know, what did I hear once? 20 minutes of planning saves you an hour of work later down the road.

I totally.

Generally you get a big return if you invest the time up front.

Yes, Agreed.

Alrighty. So last question. If our audience wants to learn more about you or get in touch with you what would be the best way for them to do that?

Yeah, I would say connect with me on LinkedIn. I'm pretty often on the platform there. Always happy to chat about either financial modeling or if you have questions about quantrix. Of course, I think I'll always be a lifelong fan the product there, but would be happy to connect with anybody on LinkedIn.

All right, great. Well, thank you, Lindsay. I really appreciate it and enjoyed having you on the show today. So thank you for carving out a few minutes of your time.

Yep, thanks, Paul. This is fun.

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