Episode 12 - From Rocks to Riches: The Power of Financial Models in the Mining Industry with Emilie Williams

Written By Paul Barnhurst

Show Notes

Welcome to Financial Modeler's Corner (FMC) where we discuss the art and science of financial modeling with your host Paul Barnhurst. Financial Modeler's Corner is sponsored by Financial Modeling Institute (FMI) the most respected accreditations in Financial Modeling globally.

In this episode, Paul Barnhurst is joined by Emilie Williams.

Emilie holds a Bachelor of Engineering (B.Eng.) in Mining, a Masters degree in (M.A.Sc.), Civil Engineering, and has earned her Level I and II FMI modeling certifications.  

She has been bridging the gap between mine engineers, operations, finance, and management for more than 15 years. She has real-world, industry experience working on mine project strategies, diagnosing, and solving for factors that lead to project delays and inefficiencies, and creating best-practice tools and models to help her clients manage their operations, costs and realize their objectives.

Listen to this episode as Emilie shares: 

·      Her journey from mine engineer to full-time financial modeler

·      Her learnings from the worst models she has come across 

·      The unique challenges of modeling in the mining industry

·      Her experience with competing in ESPN’s most recent Excel Battle

·      The importance of practicing to be a better Modeler

·      Her position on controversial modeling issues, including circular references, dynamic arrays, modeling standards, AI in modeling, and more

Quotes: 

“The dependencies on physical constraints are not always easy to model.”

"[Attending an FMI Course was] the first time I realized that there was actually a way to do it and actually the structure of modeling was a real thing, as opposed to, let's just stick things in our Excel spreadsheet…”
 

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Visit www.fminstitute.com/podcast and use code Podcast to save 15% when you register. 

 

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Link to signup: FMWC – Financial Modeling World Cup | $25,000 Prize Fund (fmworldcup.com)

 

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Host: Paul Barnhurst

 

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 Modelers Corner. I am your host, Paul Barnhurst. This is a brand new podcast where we will talk all about the art and science of financial modeling with distinguished financial modelers from around the globe. The Financial Modelers Corner Podcast is brought to you by Financial Modeling Institute.

 

FMI offers the most respected accreditations in financial modeling. I am thrilled and excited to welcome our guest this week to the show, Emily Williams.

 

Welcome to the show!

 

Guest: Emilie Williams

 

Hi, Paul! Thanks for having me.

 

Host: Paul Barnhurst

 

Yeah, super excited to have you! So, you know, we like to start each episode, before we give you an opportunity to introduce yourself, we like to start off with a fun question. Tell me about the worst financial model you ever saw. I know everybody has a horror story. If you've modeled, you got one.

 

Guest: Emilie Williams

 

Yeah, so one of the things I do is actually I teach university students, and so I get some pretty brutal ones in that, but they're just starting out, so we'll park those ones. I work with one now, and actually, as a model, it's not bad, but it's pretty hard on the eyes. I think they've got every single color Excel offers. There is no white space at all in this model, so that's pretty tough. And then I had another one that I got, and it had simulations in it, and it took me ten minutes to open. Every time I wanted to open it, it was ten minutes. So I was like, I don't even want to touch this model.

 

Host: Paul Barnhurst

 

Yeah, rainbow models, where they've used every color in the book can be just hard on the eyes. Even if they're a good structured model, you don't want to use them. The worst, though, in a lot of ways, are those ones that take forever to open because it's so hard to work in and to make any change. I once inherited, and I won't call it a model, it was really more of a data storage file. It was an Excel file, and they were using it to generate some results, but not necessarily a financial model. But the file was over a gigabyte, and I still remember the guy going, well, it opens pretty quick on my 64-gigabyte gaming machine. Like, if you need 64 gig of RAM to open the file, you got bigger problems.

 

Guest: Emilie Williams

 

Exactly! That's what he was doing, and the client was sending it to me, it was a review, and they couldn't send it to me. And we had to open all sorts of sharing locations to try to get one that would accept this file.

 

Host: Paul Barnhurst

 

So what's kind of been the takeaway from seeing some of those models? What do you take away into your practice?

 

Guest: Emilie Williams

 

So now I know that it's okay to break your models up, you can break them up and have a separate file and then just dump your output as an input to your new model. You can break it up, keep it streamlined. One or two colors is perfectly okay. You don't need the whole box of Crayons in your model.

 

Host: Paul Barnhurst

 

I one time tried to model, I don't know if you've ever used it, Excel has some default colors in it for outputs and inputs, and they're kind of, frankly, I think, an ugly orange. And I decided to use them for an entire model, and it hurt my eyes. By the time I was done, I'm like, hey, never them again am I using their default colors.

 

Guest: Emilie Williams

 

No. So usually, yeah, usually I just set up the colors in advance so that when I export them to PowerPoint, they're already going to match the template and it saves a lot of time.

 

Host: Paul Barnhurst

 

Yeah, I hear you on that one. So tell us a little bit about your background, how you ended up where you're at, and how you got into modeling. I know you come from an engineering and a little bit of a mining background, so love to hear your story.

 

Guest: Emilie Williams

 

So I'm a mining engineer and living in Toronto now, but started out graduating from engineering school, then did a Master's and went out to work in the industry, and best way to do that is to go on-site. So went up to a small mining town up north, then I meant to be there for two years, and 20 years later we finally said, okay, we're ready to come back down south. But it was really a great time working in operations, so really hands-on in the field, seeing how mines really worked. So it started out the first few years doing operations and then started doing planning.

 

And mining is just so closely tied with economics. You run economics all the time. You're always looking up the gold price and all your metrics like that. You do a lot of that. And actually the first mine I worked at, engineering was responsible for the budget process. So I started doing that and said, you know what, this I like doing. Started working more and more with the finance groups and became sort of the economics person for the site. Moved around, moved up the ladder a little bit and said, you know what, this is really what I want to do. So that's now my focus, is taking this mining background and making models that take advantage of that.

 

So I've left operations, I'm now freelancing. I work with different consulting companies and different clients on feasibility studies, due diligence, things like that as well as I teach mining engineering to first-year university students.

 

Host: Paul Barnhurst

 

It's great you teach, and I love you telling a little bit of that background and story. I'm curious, with the mines you worked with, was there mostly one kind of material they were mining over the years or do you kind of cover all the different commodities out there? Is there a specialty within that mining? Kind of what do you typically see?

 

Guest: Emilie Williams

 

The mines I worked at was gold. So gold mines will typically have gold and we had silver byproducts. You will get some gold and copper mines, for example, but the area of Canada we were at is really gold. So that's kind of a specialty and it is quite different than some of the big polymetallic mines. I'm working on a project and it's base metals, and there we have nine or ten different metals that we consider. But my specialty is gold.

 

Host: Paul Barnhurst

 

That makes sense. And I would imagine when you're dealing with nine or ten different metals, it probably adds a lot of complexity because there's a lot more economics going into that.

 

Guest: Emilie Williams

 

It does. And also is the recovery and the smelting contracts are very complex because it's not just one metal and it behaves in one way, it's the combination of all the different metals that does the recovery and does the treatment charges.

Host: Paul Barnhurst

 

Makes a lot of sense. The process has to be quite different when you have nine different products and you got to separate them and go through all that process versus when you're dealing with one or two.

 

Guest: Emilie Williams

 

Exactly! The other thing too is that just the unit value is different. In gold, you tend to have smaller scale operations because it's a high unit value, you're going to be much more selective. When you're in base metals, you're going to have more bulk, you're going to have economies of scale, much larger projects in terms of size, not necessarily in terms of value.

 

Host: Paul Barnhurst

 

That makes sense. So as you mentioned, you started in mining operations and you were lucky enough, I guess, to have engineering do the budget and you started to realize you liked it. So what was it you liked about the finance side? What was it that really enjoyed and made you decide to make that switch to move from operations to much more of the finance and the economics?

 

Guest: Emilie Williams

 

So I guess in the industry you've got really sort of the people who want to do operations and want to make things happen and then you've got the planners. So I was always more on that planning side. But you can't just plan your physical extraction in a vacuum. You want to make sure that you're doing the right plan. And the only way you do that is by testing the economics as you go. And so the first plan you always do is generally always terrible economics. And you look at it and you're like, yeah, this doesn't make any money. You start going, well, what if I increased the production? Or if I did this, I went over here first.

 

And you do all these sort of things and you're just kind of pulling different levers and you're seeing at the end whether you make money. I just really enjoyed doing that, pulling the levers, which things make the most sense, what's the best you can do with this hand of cards you've been given, which is the ore body?

 

Host: Paul Barnhurst

 

How do you optimize the resources we have.

 

Guest: Emilie Williams

 

Exactly! The challenge is that it's not a fixed quantity. Your resource, and this is known as the ore reserve problem, it changes depending on what you select as a mining method, for example, or as a productivity or as your equipment. So if you decide, I'm going to use this size of trucks and you run everything, well, it doesn't work. You can't just go and change the size of trucks, you probably have to go back and adjust your ore. What's my starting quantity? Either higher or lower. And then that sort of changes everything.

 

So all of your parameters, there's no actual starting point. You kind of have to make some guesses, you test them out. Does this make sense? And if it doesn't, you change them. If it does, you keep refining things. People think or, oh, well, it's whatever you can measure. Well, it's not actually it's a fluctuating definition because it's economic definition. It's not like anything that has a certain density that you can measure. If the gold price changes every day, the amount of material you have to work with technically changes every day too.

 

So it's a very, very dynamic process.

 

Host: Paul Barnhurst

 

Sure, and that makes sense because at certain prices you're going to do very different behavior than at other prices.

 

Guest: Emilie Williams

 

Now, obviously, you can't react on a day-to-day basis of the market. You have to build in some stability, but ideally that's what you'd like to do.

 

Host: Paul Barnhurst

 

You mean you can't swap out your equipment from one day to the next because the price is way different?

 

Guest: Emilie Williams

 

No, you can't. And your workers, if you send them home for the day, they don't really like that either. They kind of expect to be kept on for a certain amount of time. Sure.

 

Host: Paul Barnhurst

 

They expect to be paid. I mean, all makes sense. Which kind of leads into our next question. You and I had the opportunity to chat via email, and one of the things you really shared as we were talking in preparation for the show is just the challenge of building good mining models. You mentioned how many of models lack technical depth when built by finance. When the engineer does the model, they often have the technical, but usually, they're not well-designed models. They might be a little poor on the model side. Can you talk about what you're doing to try to bridge that gap? What is it that you're doing to improve that?

 

Guest: Emilie Williams

 

So one of the things about mine engineers is typically they don't like to start models. So they're always going to take a model that's close enough and work from there. So one of the good things you can do is if you build a really robust model to start with and you know that this is going to get recycled in a whole lot of different ways, but at least you're starting off in a good way and provide that. So I do that, I build models for people. The standards are a little bit tricky to follow in mining just because we have so many different parameters, but there are some rules that are applicable, so try to follow those, and, like right now I'm working with a bunch of junior and intermediate engineers and is really to, not just tell them, look, this is how you do it, but explain, this is why you do it. This is why I'm spending so much time setting up this part of my model and really showing that. And usually, it's paid off because I was working on a project last year and the project manager, 2 hours before he was presenting to his boss, he said, yeah, he asked us if we can change a few things in the model. And he's like, you'll never be ready in time, will you?

 

And I said, 15 minutes later, yes, you do have it, here's the model. I spent so much time up front building it in that structured way and they're like, yeah, I didn't think we could do that in 15 minutes, and it's like, you can if you've done it right. So just really showing them the benefit of doing that.

 

Host: Paul Barnhurst

 

Yeah, thank you for sharing, and I totally agree with you. When you have a well-designed model, when you've thought about it and you have it structured right, your inputs, your outputs, your calculations, it's much easier to modify. Sometimes you may still go away and say, you're going to have to give me some time, depending on the complexity of what they're asking, but often you can do it on the fly, so to speak, within the 15 minutes or sometimes right there, depending on the questions, if it's designed properly. It's amazing how much of a difference it makes.

 

Guest: Emilie Williams

 

Yes, and the same manager, once he found out that we had this nice dynamic model, he's like, oh, so you mean I can ask you all these scenario questions? What if we did thiS, right? So I ended up having this great relationship with him. He'd call me up, what would happen if we did this? And it's like this totally random idea that's just come to him and I'd do that. And I was like, yeah, no, don't do that, that's not going to help. And then he'd come up, what about this one? Yes, that one is go talk, let's go talk to the engineering and see if that one works. But that one makes sense to explore whereas the other one didn't. So he could do a lot of “what-ifs”.

 

Host: Paul Barnhurst

 

No, I totally understand! Different situation, but I built a model a little over a year ago for a business and they came back to me just recently because they switched their accounting system and so they want all the accounts switched out in the model, kind of update it. And they had mentioned it goes, I absolutely love this model. It helped us make good business decisions and move things forward. And it was just nice to know, okay, that was put together in such a way that it actually made a difference. They're using it a year later because I've definitely built some models where it's like, oh man, please just let me start over. This thing is horrible.

 

And so it's always nice, like you mentioned, when you get it right, not that it's perfect, but you get it right where it adds value.

 

Guest: Emilie Williams

 

Yes, and actually there was someone else on the team and she was telling me, oh yeah, I took that model and now I use it to test other things. So I was like, oh, perfect.

 

Host: Paul Barnhurst

 

Yeah! And speaking of kind of “what-if” scenario sensitivity analysis, I know that's a huge part of mining, right? You got price fluctuations, variables in the inputs and how much you have in the mine, all those type of things. So we talked a little bit about that prior to the show, about how difficult it is. And you had mentioned it requires a circular optimization approach, which creates some real challenges.

 

So first, can you tell our audience what that circular optimization is and just kind of how you manage that, how you do it in the mining industry with that challenge?

 

Guest: Emilie Williams

 

So this is the thing. Let's say that you have been told we think we've got we'll just call it a million units of resource just for kicks, and it's got a certain quality. And okay, so you say, well, if I've got a million, then this might be a way to mine it, and you're going to start running some costs. How much would it cost me to build this mine? How much would it cost to run it? And then you come to the end and you're like, well, that doesn't make sense, I can't do that. So you're going to say, okay, I could get a million units at this quality, but what if I was able to accept some lower quality and I got 2 million of this lower quality material. So now I've got some economies of scale. If I've got economies of scale, well, maybe it's going to cost more in terms of capex to build it, but not so much to operate it. Does that move the needle on the economics on the end or vice versa?

 

You say, well, let's increase the quality of that. We're going to only take the best part of this deposit instead of getting everything, we're going to go down to half a million. but it's going to be really good stuff and you're going to build a smaller mine, you're going to operate it for a shorter amount of time. And so maybe that scenario you run the economics, and you're like, oh, you know what, this one is maybe a better starting point. But you've had to kind of guess your starting point. And so often you're going to use benchmarks. You're going to say, well, you know what, there is a mine just down the road and this is the way they do it. Let's start with something like them.

 

You're going to get some benchmarks. Let's look, yu know, there's databases, what's an average operating cost for this size of operation using this type of equipment? And you can just sort of do some back-of-the-envelope calculations and just sort of get an idea of what sort of scale might work. And once you've got a range, then you're going to start doing engineering. So we always do i, there's different studies we do. We call it like a scoping or preliminary economic analysis, and that's going to have relatively low level of engineering completion, you're going to have really high contingency on it, but it allows you to run a lot of scenarios fairly quickly.

 

Find one, then you're going to take your best scenario and you're going to go to another level of detail. You're not just going to use benchmarks anymore. You're actually going to go and start costing things, but not everything. And you're going to keep refining it, reducing your contingency, reducing your risk, and eventually, you get a scenario that is economic, reasonably advanced, you can get confidence in it.

 

So that's sort of the challenge on the model, is you've got to be able to accommodate all the different changes, but also the different levels of details.

There's maybe certain things you know very precisely because let's say you've already bought this type of truck for your other operations, so you know exactly what this truck costs because you just bought one last year. But there's other things you don't know anything about. So you got to be careful when you start adding things that are known and things that are just estimated or benchmarked.

 

Host: Paul Barnhurst

 

And that makes sense and I can definitely see that iterative process. It's like with many projects you start with, you're often benchmarking, you have a lot of unknowns, okay, you do the high level and say, okay, we think there's enough here, this makes economic sense, so let's go to the next level. Go to the next level and you're, okay, I still think it makes sense, but we want to drill down further. But what if we change this and you're, like I said, constantly optimizing and trying to make sure the model adjusts for all those different things. Like if I got six trucks, do I need 30 people or do I need 35 now? Do I got this, do I need this size power or that size power and how much is that going to cost?

 

Guest: Emilie Williams

 

Yeah. And then the other thing you've got to do is that you've got to consider the physical constraints. It's great to say you'd like these six trucks to be operating all the time, but you can't have a truck operating in space underneath another one. Right? There's physical constraints about which block you have to mine before another one so everything doesn't cave. So there's that 3D geometry aspect into how you sequence it as well. So that's one of the things that doesn't necessarily come out well in a model, is that they're not just numbers on a page or items on a shelf in a warehouse, right?

 

You got to physically drive your truck over to get it. Sometimes what you'd like the truck to do just physically isn't possible until you do seven other things.

 

Host: Paul Barnhurst

 

Yeah, the dependencies and those physical constraints are not always easy to model. There's models which you try to represent reality, and then there's reality, and some things are easy to represent in a model, and some are really hard.

 

Guest: Emilie Williams

 

Exactly. And so we always have to have our specialized mining software to do that 3D you'd never be able to do it in Excel. We have to get a data dump from that as to, okay, this is what we're actually going to do each year and then do the test. You got to integrate with that sort of 3D planning.

 

Host: Paul Barnhurst

 

Makes sense. I could definitely see where you'd want some optimization software to do those calculations and that math and then take those inputs or take that output and make it an input in your model.

 

Guest: Emilie Williams

 

Exactly. Now that we've got this plan, what does that mean in terms of people and of consumables and energy and things like that.

 

Host: Paul Barnhurst

 

Got it! Kind of stepping back a little bit, we've talked a lot about sensitivity, obviously, all the modeling you've done, but I'm curious, how has starting on the operations side of mining made you a better modeler? How has that helped you in your career?

 

Guest: Emilie Williams

 

It goes back to knowing which questions are going to want to be answered. It's so easy. Like when people don't know modeling, you just start, okay, well, this is the data I have, let's take that and then I'll do some calculations on it and eventually you work through a few lines of Excel and you come up and you plot a graph on it, right? You're like, here's my model. That's backwards!

 

 

So what I like to do is, okay, this is what the manager or the client is going to want to know. These are the things they're going to want to know. Once I present these results, let's say I've got a nice production plan and I've got a cash flow per year and a project NPV. Well, they're going to want to I can right away think about some of the questions they're going to ask me. Notably, how do we do better? How do I reduce risk? How do we do better? So we've got to be able to build the model from those results and work backwards and say these are the questions they're going to want to know. What happens if we change the size of the fleet? What happens if we lower the cutoff grade which is the quality of the material? What happens if we increase the quality for example? How do those things work?

 

So really, this operations background helps understand which levers you can actually pull, which ones are numbers on a page but you can't pull or are very difficult to pull. Because sometimes, let's say we look at when you do present project results, we always got these nice spider graphs on Sensitivities. And you say, okay, Capex goes up 10% or goes down 10%. What does it do to the NPV? Present these types of things. Well if you're looking at something like recovery, processing recovery, it's not really a symmetrical function.

 

It's very expensive to get better recovery. It's very easy to get lower recovery, you don't have to do much to mess that up. If you've just got somebody who said +5% on the recovery well that's not necessarily going to happen. Whereas -10% on the recovery maybe is going to happen.

 

Mining projects are huge capital projects, right? They take years to build, they can't build much for under a billion dollars anymore. If you start looking at the capital estimate on your project, the chances of you going under budget versus completely blowing your budget are not the same at all.

So you have to understand that so that when you're presenting your model you can reflect these types of actual risks and where the problems are and flag those in the model and be able to test those.

 

Host: Paul Barnhurst

 

Yeah, and that's been my experience as well, you know, most of my career is FP&A, and the better I learned the business and the economics, the much easier it made it to make sure those assumptions made sense, to be able to validate the model and know where to pull the levers, versus the times when you just build a model and you really knew nothing about the business. Okay, just tell me what you want it to be, because you're just putting in whatever they put in and like oh yeah, we can adjust this. And they're like no you can't, and here's why or that number isn't realistic. And so being able to have that sense check and understanding the economics, whatever industry you're in, I think is just invaluable when it comes to building models, because it allows you to really be part of the discussion and often the solution, instead of just, hey, I built the model, tell me what changes you want me to make.

 

Guest: Emilie Williams

 

And you could recommend, you know what, this is maybe an area in which you're not optimum right now. What do you think about digging into this one? Yeah. And then there's also a lot of simplifying assumptions that everything scales linearly. Well things don't. You've got step changes, you've got economies of scale you've got all these things, and understanding what are your constraints. If you add so many workers, well, after a while, you've got to add some supervisors to go with them, and then you've got to add more locker rooms for them, and you've got to add all these other things to go with your extra workers. You can't just keep saying, I'm going to add an extra worker, and an extra one.

 

Host: Paul Barnhurst

 

And think that's the only cost you have. At some point it's like, all right, we need a whole new facility, or at least an expansion to the facility.

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Host: Paul Barnhurst

 

You know, I imagine making the transition to modeling, there's a lot you did to become better at modeling and time you invested. So, maybe, can you talk about some of the key things you did that really helped you become a better modeler as you got into it and started to realize, okay, I enjoy this, I like budgeting, I like planning, but this isn't something I've naturally learned about in school.

 

So talk about that adjustment, maybe some of the things you did to become better at modeling.

 

Guest: Emilie Williams

 

The first time I realized that there was actually a way to do it and actually the structure of modeling was a real thing, as opposed to, let's just stick things in our Excel spreadsheet, so we'd gone to an industry conference, and they had a short course, and it was one of the FMI approved training partners, and they were running a short course on mining financial modeling. And I just went in, and I absolutely loved it. I was like, wow, this is really, really cool. So then after a while, I said, you know what, they just did sort of the one day version, but this is actually a two or three-day course. So I went back and I did the whole course, and I really took a lot away from that and really made me think, you know what? I can do a lot better in my models, just with this basic intro. And we didn't go into all the fancy Excel, but just the structure and things. I was like, oh, wow, okay, I can do a lot of things here.

 

And then after, when I did a couple more courses with them, and then they said, oh yeah, you can do the FMI exam. Hey, I should do that. Why not? Coming from mining, people say, oh, I can do models, and they're like, yeah, right. You're an engineer. We'll let finance do that. Well, maybe if I had a certificate, they would believe me that I actually do understand some of these finance concepts.

 

So I said, okay, so I'll do the level one exam. So I did that, and I did all the training and the practicing, and I passed that and I said, great, let's go do the next one. The first one was pretty straightforward, but the level two was really not in my wheelhouse at all and was really tricky, not my specialty. So I had to work really hard on that one.

 

Preparing for that exam is how I got involved in doing the FMWC competitions. At that point, they were just still the regular finance ones, but I did that as a way to prepare for my exam. So then after I passed the exam, I said, okay, that's great, but I'll keep going on these competitions. They're kind of fun, but I'd like to be better. So I'm going to keep going, I'm going to keep practicing. And you start watching the YouTube videos and all this stuff and taking additional classes on it. Then you start getting, okay, you know, I'm not so bad at this. And then they brought in the Excel, the battles. It's like, oh, okay, got to start again. Start learning that because it's really a different type of exercise, but interesting in a different way. But the speed is definitely a challenge that you need to do for that.

 

So that's, I guess, sort of how I really just started is just step by step, yeah, I can push that a little more. I could do better on this.

 

Host: Paul Barnhurst

 

One thing I really hear kind of weave throughout all of that is you spent a lot of time practicing, whether it was for the test, whether it was for a competition, whether it was for your own learning. And I love how you just said you have to. Why is that so important? I think sometimes people think you can just learn the concepts and then you'll be able to build it when the time comes. Why is that practice so critical?

 

Guest: Emilie Williams

 

It isn't, because in my day job, you just keep using the same formulas, like the same things over and over again if I do a better way to do it. And then you just keep doing the same thing. So you've got to push yourself to go. You know what, this part of my model, I wonder if there's a better way to do it. And you go and you look up and you find out a couple of years ago, it's like I was using Index Match, and then all of a sudden, what do all these people keep talking about XLOOKUP, wonder what that is? And then you go in and you're like, oh yeah, this could help. Let me try that. But if you don't push yourself to do it, you'll just keep the same functions over and over again in your model, and those won't get better.

 

Host: Paul Barnhurst

 

That’s so very true. I do Excel training, and it's amazing how many people have never heard of Power Query or their eyes light up when I show them, oh, you can do Unique to remove duplicates, and they're just like, what? I don't have to copy and paste and go up to the button and hit remove duplicates or manually do it, or however they were doing it before.

 

If you're not challenging yourself because Excel changes at such a rapid pace nowadays, you're going to be missing out. You're going to be doing things probably a longer way or not as efficient as they can be, like not using Power Query or not learning about Dynamic Arrays. Say you have to use all of them right away, but you really need to keep yourself current and just know what's out there, because even if you don't use them, as I heard someone say, someone else is going to give you a model that's used them, and you need to be able to understand it

 

Guest: Emilie Williams

 

Exactly. So for the moment, I don't need to use Dynamic Arrays in my day job. I don't think they'd be helpful because I don't think it would be very transparent necessarily for the client and the type of models I do. But it's still really good to know that these are out there, and if I need them, I can go and dig into that when I need to.

 

Host: Paul Barnhurst

 

Switching gears here a little bit, you mentioned how you got into financial modeling World Cup and Excel Esports, doing some of those competitions. Recently, you got to be on the elimination battle on Excel. What was it like? Tell us a little bit about that experience.

 

Guest: Emilie Williams

 

It was actually pretty scary. I did not feel prepared at all. I was working with Leanna Garrish because she'd been preparing for a battle before, so I said, okay, I'll help her out as part of the women in Financial modeling group. So a few of us were saying, we'll help you prepare for this. I remember thinking at that point, I'm so glad this is not me. I'm not ready for this. Oh, well, a couple of months later, they called me and said, hey, do you want to do this? And it's like, I don't know, I'm not ready. But I said, okay, I'm going to do it anyway.

 

I'm glad I did. So for those of you who've watched it, I did not do well was first out, but it's really important. I think, in order to get the skill, the battles to face that kind of pressure because it's completely different from doing them at home. Just got to the battle. Okay, question one. Okay, I think I can do question one and then not even prepared, didn't even remember to copy my answers over to the other, very basic thing, put your answers in this sheet. Couldn't remember to do that.

Looked at question two, total blank.

 

So even though I thought I'd prepared, and I'd done all the practice cases I could, you can't train for that sort of pressure and especially the time pressure. So I'm glad I did it, and now I kind of know a bit more on how to prepare for that, and hopefully, I'll get another chance sometime and put myself a little bit better.

 

Host: Paul Barnhurst

 

Well, great. I'm glad you had fun. And I have an episode coming out soon talking about my experience, and it was similar to yours, so I can definitely relate to it, and the pressure and the challenges. Mine wasn't elimination, mine wasn't on ESPN, but it was streamed and there were four contestants, and I came in fourth. So, I can at least commiserate with you there. I get it.

 

Guest: Emilie Williams

 

Exactly. And as soon as you're eliminated, you're like, oh, yeah, that's how I needed to do this question.

 

Host: Paul Barnhurst

 

Yeah, I started working on it the rest of the day, going, why did I not even think about this or that?

 

So we're nearing the end of our time, and we have this next section, we call it rapid-fire questions. You get no more than 10 to 15 seconds to answer each question. You can't tell me ”it depends”, because every single one of these, you could say, “it depends”. We want you to pick a side. I get that it may not be 100% that way, but you get to take a position, and then at the end, we'll give you the opportunity to elaborate on one, maybe two, that you feel really strongly about.

So I'm going to go ahead and read each of these and just ask your view.

 

So when building models, circular or no circular references?

 

Guest: Emilie Williams

 

Never. It always means I've made a mistake.

 

Host: Paul Barnhurst

 

VBA or no VBA?

 

Guest: Emilie Williams

 

VBA. Only if absolutely necessary, but almost never.

 

Host: Paul Barnhurst

 

We'll take that as a no for the most part. Horizontal or vertical?

 

Guest: Emilie Williams

 

Horizontal.

 

Host: Paul Barnhurst

 

All right. I'm a horizontal person, so I get that one. Excel Dynamic Arrays in your model, yes or no?

 

Guest: Emilie Williams

 

No, but maybe if I learn them, yes.

 

Host: Paul Barnhurst

 

That works. External workbook links, yes or no?

 

Guest: Emilie Williams

 

No.

 

Host: Paul Barnhurst

 

That's the typical answer we get for that one. Named ranges versus no-named ranges.

 

Guest: Emilie Williams

 

No, but I can talk about that one after.

 

Host: Paul Barnhurst

 

All right, we'll talk a little bit more about that one. Do you follow a formal standards, like Smart or Fast or some of the others when building your model?

 

Guest: Emilie Williams

 

No, I don't find they're very well adapted to mining, but I try to follow some of the general principles.

 

Host: Paul Barnhurst

 

That's fair. The next question, this is a fun one we added recently. Will Excel ever die? Yes or no?

 

Guest: Emilie Williams

 

I would say yes, but it's going to take a while.

 

Host: Paul Barnhurst

 

That's where I'm at. When it will happen, I don't know, but I think eventually will AI build the models for us in the future?

 

Guest: Emilie Williams

 

Build, yes. Design, not so much.

 

Host: Paul Barnhurst

 

Fair enough. And then the last one is, what is your Lookup function of choice? I'm going to give you four options, I realize there can be more. VLOOKUP, XLOOKUP, Index Match, or Choose?

 

Guest: Emilie Williams

 

I'm a recent convert to XLOOKUP.

 

Host: Paul Barnhurst

 

Okay. Yeah, I'm an XLOOKUP fan. I asked that question to Dim Early and he goes, I would question if there's only four. I'm like, yes, I know, but I'm not going to list all of them.

 

Guest: Emilie Williams

 

I still use Index Match for some cases, but XLOOKUP a lot of the time.

 

Host: Paul Barnhurst

 

All right, you have a minute here to elaborate. I think you said you were going to elaborate on named ranges, right?

 

Guest: Emilie Williams

 

Yeah, so I don't actually use them for ranges. I use them for certain parameters where I find it really helps in clarity of the model. So I'll use them for things like density, which I know one cell, that's where I'll use it. But I'm not going to say production inputs and refer to that because I really don't like the structured tables and I try to avoid those except if I'm going into power query. So I'll use them a lot, like conversion factor, grams to ounces. I'll label that because I find that really helps when you've got non-mining people follow your conversion. So I find that's the one place where it really helps.

 

Host: Paul Barnhurst

 

I agree with you. That's an area I've definitely used them a lot in a model. I also like using them sometimes for other things, but they can be very helpful, single-cell when you just want to name it, so all the formulas are referencing that cell, but you don't want to do table or table structure for whatever reason. I definitely use tables a lot, but that's because I'm a huge power query user, and you have to use tables.

 

Guest: Emilie Williams

 

Yes, I use them on my data inputs. When I'm getting the inputs from the production dump that I will use power query there, and then I will transform the data, get it set up, but then after that, I try to avoid it.

 

Host: Paul Barnhurst

 

I love tables for dealing with data and the analysis, but yeah, when you get into a model, there are areas where it can be hard sometimes.

 

So now we're heading into the last section here. We have two questions left. So the first one is, if you could offer one piece of advice to our audience to be a better financial modeler, what advice would you give them?

 

Guest: Emilie Williams

 

Kind of touched on this before, but start at the end. What questions do you need to answer? How are you going to sort of justify the story that your model is telling you? How is it going to say, okay, the production is going up in this year and then it's going to decline from here. Can you back that up? Do you understand what that input is?

 

So, first of all, this is what the output looks like. Can you justify it? Can you answer questions about it, then work backwards from that figure out how to build it and understand that, because that output is always what you're going to want. But like I said, in our case, the input, it changes levels as you go through the different processes. That output is fixed. The story that you want to be able to tell with your model, the questions that you need to answer or explain, those are fixed. So I would always say start with that.

 

Host: Paul Barnhurst

 

So if our audience wants to learn more about you or get in touch with you, what is the best way for them to do that?

 

Guest: Emilie Williams

 

I'm not a big poster on LinkedIn, but I do check messages and I do follow a lot of the threads so you can get in touch with me there. And there's a link to my website. You can reach out to the contact information.

 

Host: Paul Barnhurst

 

Great! So we'll put your website, and we'll put LinkedIn in the show notes, and I just want to conclude by saying thank you so much for joining us, Emily. I really enjoyed talking. It was fun to learn a little bit about the mining industry and just see the way you went from engineering and operations to modeling and the passion you have for it. So thank you so much for joining us!

 

Guest: Emilie Williams

 

Thanks for having me. It's been a lot of fun.

 

Host: Paul Barnhurst

 

What a fun episode that was with Emily Williams. I'm really excited we had her on the show, and I have to thank Danielle Stein Fairhurst for mentioning in her Financial Modeling for Women's group that they could be on the show. And Emily reached out and said, I'd love to be on the show. What a great background she has.

 

I want to talk a little bit about a couple of things from that episode. First is just her nontraditional background, right? She talks about how she worked in a mine for 20 years and lived in a small mining town, and she came up on finance, basically, and modeling by chance, right? Someone said, hey, you need to work on the budget. Okay, what's that? And she found she liked the operational planning.

 

And then what I love is she took the time to invest in herself. She didn't just do what many people do and, hey, I'll just make it up and figure it out in Excel. She took courses. She talks about how she took courses to learn how to model. She talks about how she invested in financial modeling World Cup to improve her Excel skills, to experience new things, and how she did Excel Esports.

 

And so what I love is she just showed her passion and willingness to learn, which really leads to the number two thing I'd like to mention. First, I love her nontraditional background, but two is the importance of practice. She talked about how she invested time, how she learned new Excel formulas, learned about Dynamic Arrays, learned about different things, and how she'll continue to learn. And that's so important. If you want to be good at modeling or anything in life, you have to practice. And I love the advice Chris Riley gave. If you want somewhere to start when it comes to modeling, start by modeling your life, model your own budget, your inflows and outflows.

 

And then the last thing I really want to emphasize from that episode is just how different each industry is. As you can see, she talked about how the mining industry can be very different from other industries, and the complexity and how different assumptions lead you down a certain way, and you can't just say, oh, all of a sudden I'm going to do this, and you have constraints and how you have to optimize things and use additional software. And so every industry has its nuances. Yes, we have general guides for modeling and things we'd like to do, but also sometimes things have to be different in the real world, and that's important to understand. And so those are the things I'd just like to talk a little bit about from that episode.

 

And then the next thing I'd like to talk about is the road to Vegas. As many of you know, I've had David Brown, Dim Early, Emily Williams on the show. Those are all people who have competed in the Financial Modeling World Cup. And so how great was that to hear each of them and to learn from each of them. If you want to join me in Vegas, please, by all means, come December 7 through 9th will be the World Championship. And they just selected all the finalists. They just completed the last round, and so they have everybody who will be competing in Vegas.

 

And if you'd like to get a discount to attend that event, please use my code FP&AGUY10 to save 10% for the event. If you have any questions, you could always reach out to me and email me at pbarnhurst@thefpandaguy.com, but I'd love to have you join me.

 

And then as a reminder, if you ever have any questions or you want to submit a question, you can do that to my email as well. You can send me a question about a show, a question you have about finance and we'll look to answer it in a future episode.

 

And then as a reminder, you can earn CPE credit for this podcast by going to earmarkcpe.com, downloading the app, and answering a few questions.

 

And then last but not least, I have a huge favor to ask! If you enjoy listening to Financial Modelers Corner, then please take the time to write a review to give us a ranking on your podcast platform, whether that be Apple, Spotify, Google, or wherever you listen to your podcast, that helps us grow the show, that helps us to continue to provide great content for each of you and for each episode.

 

Thank you again for joining me!

 

Financial Modeler's Corner was brought to you by Financial Modeling Institute. Visit FMI at www.fminstitute.com/podcast and use code PODCAST to save 15% when you enroll in one of their accreditations today.

 

 

Paul Barnhurst
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