Gabriela Gutierrez is Financial Planning & Analysis Specialist at eBay Classifieds in Germany.
Gabriela is one of our most international guests. Growing up in Ecuador, she did an MBA in Barcelona and studied in the US. She now works in Germany leading revenue forecasts for the core divisions of the online juggernaut eBay Kleinanzeigen.
At eBay Kleinanzeigen (Kleinanzeigen is the German word for classifieds) she is responsible for revenue forecasting for 70% for the largest classified online ads portal in the country. She splits her days providing forecasts for the main business, advertising, subscriptions and classifieds. (After the sale of the eBay classifieds division it belongs to the Norwegian Adventina , in which eBay in turn holds 33 percent).
In this episode, Gabriela discusses the pivotal moment in her career: how she learnt to love coding and embraced data analytics and ML to deal with the vast amount of data at the company.
She discusses spending hours and days and months learning Python (“I would spend hours trying to understand where I had made an error”) and eventually experimented with Meta’s Prophet – a forecasting procedure implemented in R and Python and her strong working collaboration with the data analytics team at the company.
Originally choosing finance over a fashion career, she fell in love with FP&A as perfect for someone of her mindset, a natural introvert, who nevertheless comes alive when talking with others about numbers: “I love how you can see how any initiative in the business will influence the revenues or cost” and “tell the story using numbers.”
In this episode Gabriela talks to Paul about
- Her path to FP&A
- Her secrets to balancing the metrics across the company’s advertising, subscription and classified forecasts
- Her deep relationship with the analytics team
- Whether analytics should be within the finance team?
- Her journey from FP&A to data science
- Using AI to predict revenues in FP&A
- Her passion for Germany and interests outside of finance
- Her biggest advice to succeed in FP&A
- Her favorite Excel function
Paul Barnhurst:
Hello, everyone. Welcome to FP&A Today I am your host, Paul Barnhurst aka the FP&A Guy, and you are listening to FP&A Today. FP&A Today is brought to you by Datarails, the financial planning and analysis platform for Excel users. Every week, we welcome a leader from the world of financial planning and analysis and discuss some of the biggest stories and challenges in the world of FP&A. We’ll provide you with actionable advice about financial planning and analysis. This is going to be your go-to resource for everything FP&A, I am thrilled to welcome today’s guest on the show. Gabriela Gutierrez. Welcome to the show.
Gabriela Gutierrez:
Thank you, Paul, for having me very happy and excited to be here.
Paul Barnhurst:
We’re really excited to have you, so let me just give a little bit about Gabriela’s background. She’s currently working in Germany, but she has lived and worked all over the place. She grew up in Ecuador. She went to college in the US in the Boston area, I think both Boston and Babson college. And then she did an MBA in Spain at EA business school. She moved to Germany for work and has been working for company that looked like it spun off, but was originally owned by eBay. And I’ll let her talk a little bit about that, but that’s a little bit about her background. So maybe, can you tell us just a little bit more about yourself, take us through your career and how you ended up where you’re at
Gabriela Gutierrez:
So actually like when I was a teenager, like at the end of high school, it was kind of the time to decide what you want to study. And funny enough, I was always struggling between like going into like more into science. Something like would be like finance or engineering or more into art or fashion. So I always had this kind of a struggle at the end, obviously finance won the race and I made the decision, but at first I started like business administration. And then when needed to do some internships, like all the time, the areas that they were like will I would be more successful or I would be able to really deliver over 100% would be always related with numbers. So then I said, okay, finance makes sense. Like, because if I would be something like with marketing would be kind of like digital marketing, where you work with tons of data and like AB testing. So always with numbers. And then I remember in Spain, I worked for an NGO and then I was doing risk assessment. So we needed to work with tons again of data with numbers. And I really thought it was when I start falling in love, like really with finance. So it was not like the first love, but rather like over time kind of like acquiring this like to, to work with numbers and with finance.
Paul Barnhurst:
No, that, that makes a lot of sense. And I think we all go through that trying to figure out what we want to do when we grow up. Sometimes I still joke. I’m trying to figure that out. So I understand. You know, you mentioned thinking about, you know, finance, fashion, art, you know, those different things. We all have those passions. I have a sister that works in the fashion industry. So I understand that one. I remember helping her a lot through school, getting to cut patterns and all kinds of things a few times on the weekend when she needed help with her projects. So it’s a fun, fun industry. And I, I know the know, trying to figure it out. I didn’t know. I’d end up in finance. I originally did an entrepreneurship undergrad and in grad school, I fell in love with my finance class. So I can appreciate that one. So, you know, you talked about numbers, talked a little bit about that. Can you maybe talk a little bit about how you ended up in FP&A. What attracted you to that within finance? Right. There’s a lot of different areas. There’s the accounting, there’s corporate finance, there’s treasury. What is it about FP&A that interested you?
Gabriela Gutierrez:
I would say like, I’m an introvert. So for me, like talking really a lot with people, sometimes it came even like, not natural, but like in FP&A, it was kind of like a mix of you work with numbers. And I love forecasting, it’s like watching where most of the people will hate it. Like, like people at my company would be like, why? And I just love because you can completely have focused time. You create a forecast, you create a budget. You, you know how much, like any initiative in the business will influence the revenues or cost. So like, you can see the beauty of the numbers while you, you work through it. So, so then like there isn’t any better position ever in finance that FP&A and recently I was reading a book that it’s, I think it’s the Art of Statistics (David Spiegelhalter). And, uh, I read a quote there that it was like numbers, without you telling them the story. Like they are just numbers. We are kind of like humans. We need to give like the meaning of them. So I think that’s why I really love FP&A because you can’t tell the story using numbers.
Paul Barnhurst:
No, I, I, I can tell you love numbers and you’re a finance person when you use the term beauty and numbers together. That’s when I know I have someone who likes finance
Paul Barnhurst:
Because that’s usually not what you hear, so that that’s great. That’s great that you love it.
Gabriela Gutierrez:
Yeah. Many of my friends would be like, why? Like they, they would be working in completely different industries and they are always kind of like, oh, Gabby with finance and numbers. So they would kind of always make fun.
Paul Barnhurst:
Yeah, no, I, I hear you. A lot of, a lot of people do that. They’ll like, well, why finance? What, what do you like about that? Or, you know, there’s, there’s always the jokes about accountants and bean counters. And I think we’ve all, we’ve all heard them so I get it. But that’s, that’s great that you found something you’re, you know, you’re passionate about and you really like, so maybe talking a little bit sounds like, you know, budgeting and forecasting is really something you love. So what have you found and maybe some of the biggest challenges for you as you’re going through and trying to figure out, you know, a budget or a forecast and how those initiatives impact the business. What do you find to be the hardest part for you when you’re going through budget? Like what’s the challenge.
Gabriela Gutierrez:
I think it comes in different layers. I would say the first layer would be communication because you like FP&A doesn’t work can live with numbers. You work as well with humans. So then you have to have this alignment because whatever, like, even if you want to show the perfect budget or forecast, you need to understand, like, how is the sales team structured? Like, what are like, for example, initiatives coming from the product side that will impact the revenue, like any new features. So you really need to gather all the information. And that only comes with communication with the teams, with different stakeholders, and then you can really forecast even better.
Then the other kind of layer, I will say, where I see a lot of challenge is like how to include macro economical variables into a forecast. Like what would be, for example, right now, what would be the impact of higher inflation, the interest rates, the consumer index, like, like, are they going to still gonna have the same patterns as before, or what had happened like while we were during COVID times?
Gabriela Gutierrez:
So all of these kind of changes in the market, how we would be able to include them in a forecast. On a third layer, I would even say it would be accuracy. Like how we are able to really improve that because like we have right now, like a very completely different economical economy, like, sorry for being repetitive, but in a way that’s changing quite fast. And how are we as finance managers FP&A managers are going to be able to even be ahead of those changes and be able to incorporate them into the forecast? And once we incorporate it into the forecast, how we can communicate it back to the stakeholders of what could happen and what would be the decisions based on that can take to reduce risk or to take opportunities in the business.
Paul Barnhurst:
Now, I think there’s a lot you said there, and that all makes sense to me. As I heard it, you know, kind of three, three layers or key things you know, first obviously we have to understand and work with the business, understand those initiatives, understand the structure, right. I’ve seen, I’ve seen over my career kind of finance build the plan in a silo and it doesn’t work well. Right. You know, never a good idea. You really want those relationships with the business. The second, I think it’s an area we’re all, you know, kind of dealing with is what external factors should we bring in? How should we think about external factors? And then the third thing you mentioned is just all the uncertainty because of the environment we’re in, right? We’ve seen the inflation, everybody’s seen these numbers 40 year highs, you know, UK Euro US, right.
Paul Barnhurst:
We’ve seen the interest rates going up as we try to fight the inflation. You’ve seen FX rates like the Euro, right? If you have a lot of US dollars, there’s been a big change in what that rate is. Like, I look at it and go, wait, it’s one to one. I should go to Europe now, because I went back in 2008 and it was 1.6 to one and I was a college student and I was just like, you know, it just hit its highest point ever when I went, I’m like really? Can you be any higher for me?
Gabriela Gutierrez:
Perfect timing.
Paul Barnhurst:
Yeah, no, it was a fabulous trip. I loved it. We studied transitioning economies in Eastern Europe. I got to Croatia Crete Greece and Bosnia. And it was a lot of fun, but definitely wasn’t cheap.
Gabriela Gutierrez:
Yeah. I can imagine, but very interesting countries as well. And it’s also very interesting once, like, like for example, like the impact that had for the great economy to join the Euro and still like the likely effects of that we are sales unit and what’s like the social impact that is having into the society.
Paul Barnhurst:
No, totally agree. it was fascinating to see those different countries. Like we know we got the opportunity to meet with university students in Sarajevo in Bosnia and get to learn about their economy. And it was fascinating Croatia. We got to tour a pharmaceutical plant and talk to some people in the tourism industry because we in Dubrovnik, which is really big. So it was just, it was fascinating. Greece, we got to go to their stock market and talk to some people at the stock market. So it was really fun to learn these different countries and see the challenges and you know, the differences in their economy and how they were trying to transition and grow like, you know, Croatian, Bosnia, especially, I don’t think either of them are in the EU now. I can’t remember if they’re, I know they were, you know, some of them were trying to, and just the challenges of, you know, some of the different things they dealt with that they needed to take care of to be accepted and how they thought about that and how it would impact their economy. So yeah, it was, it was a great learning experience. I would love to do something like that again, so. Okay. So we’ve talked a little bit about forecasting, love of numbers. Can you talk a little bit about, you know, within FP&A how have you seen it structured? Like what, what responsibilities have you typically seen within your FP&A and kind of how the organization has worked?
Gabriela Gutierrez:
So far? So pretty much I have been responsible for revenue forecasting. So like within the finance cycle, we have like different verticals or different types of revenue and three or four of them I have been in charge of. So quite like I would say 70% or 80% of the revenue has fallen to my shoulder. Each of them it’s very different to the other one. So I can tell you, we have advertising, completely different business than what we have for features revenue and completely different business of what we have two transactions or like the subscription. So it’s kind like within the same company, we have total different revenue, forecasting metrics, and type of business. I can give you an example for advertising. We really take a look of what is like our revenue per KB, per 1000 visits for transactions.
Gabriela Gutierrez:
We have a funnel where we could take a look of like the number of organic ads that we have organic eligible ads because not all of them would be eligible for transactions and shipping and then what would be our adoption. Right. But there, you see, I manage like different models, different businesses, and even like how business develop over time advertising overall, it’s like already a very mature business transaction still are very young and as well, very young team. So even the level of support that it will require it’s totally different. So sometimes I feel that I’m worrying like in a sense, the same hat, but many hats because like the type of information that I would need to give to some like a business unit would be completely different to the other one. But I’m still doing kind of like the same FP&A roles.
Paul Barnhurst:
Yeah, no, that, that makes a lot of sense. If you have three or four different business, sounds like you got subscription, you got advertising, you got transactional going on. And you know, each of those have different metrics. I supported a business that was a marketing business as well as some others. So we had, you know, we had subscription and we had a lot of transactional and each business was a little different and different sell. Some were all inside. Some had a mix of filled and inside and a lot of account management and yes, very different in how you’re supporting each of them. Yeah. How, how do you boil that down and keep kind of those basic drivers to keep, keep track of that? Have you found, you know, that you just focus on the two or three key drivers or what has helped you build and manage having all those different types of revenue?
Gabriela Gutierrez:
Oh, that’s a really good question. So, so far it’s, I will say that I it’s pretty much how I dedicate my time. So I will say like, I don’t know, Mondays, I would really focus on that business we take a look at what happened last week. So we actually work with daily data, but then we take a review of what happened on a weekly basis. So got it. Pretty much Mondays would be advertising, Tuesday transactions, Wednesday, it features, and then I would connect all the data and then I will see app, okay, we work above or below our forecast or budget, let take a look where is coming from. But It wasn’t kind of like just one dashboard that it could tell me what’s happening because they are very different. They’re interconnected in a sense that obviously we are eCommerce in a sense business because we are a classified group and most of our activity comes from our website so we need to have like higher number of visits, higher number of listings or new ads. So pretty much that would be kind of like the first level of in our work final. But then the, the behavior from each revenue stream is totally different. So that’s why so far I hadn’t found one kind of dashboard that would be, this is the metric or this is the unit that could help me with, to measure what happened as week.
Paul Barnhurst:
Uh, that makes a lot of sense. And there’s rarely one number, right? It’d be nice. Here’s your, here’s your number? Just focus on this, but never, never works that easy. So it sounds like obviously website, I would guess a lot of, you know, monitoring number of visits, traffic time on site, a lot of those type of things is kind of top of funnel. And then seeing how that filters down to what’s the conversion rate, how many subscriptions or how many ads, how many views on the ads, all those type of metrics, is that a lot of what you’re looking at?
Gabriela Gutierrez:
Yeah. And then like also you need to partner, for example, for key metrics with other teams with the analytics team, because there would be like on top of the key metrics as FP&A would focus on revenue, but in a sense, we also need to focus on metrics because that’s our funnel. So if you need this partnering with other teams, and that’s why I was referring as the first layer for FP&A, the communication, because you always need to understand what’s happening besides, from only taking a look at revenue costs.
Paul Barnhurst:
Yeah, no, totally agree. I mean, I think business partnering and working with the business is critical. A lot of people think finance does just numbers and I’ll admit my favorite part of finances working with the business. I enjoy getting into a spreadsheet and doing numbers, but I also really like, you know, being with people. And so I, you know, big believer that finance needs to get out of a spreadsheet from time to time. We can’t spend all day in Excel there’s days. We might, it doesn’t, it doesn’t work that way.
Gabriela Gutierrez:
Yeah. Um, that’s why I also like to structure my days, like, but like within a week, because then it would come the end of the week and I would focus on like Thursday, Fridays, pretty much focus, work on Excel or Gsheets, like really just do it like modeling.
Paul Barnhurst:
No, I under understand that one. That makes a lot of sense. So obviously you work with a lot of departments and you mentioned analytics. Do you guys have, do you work with data scientists or maybe kind of talk a little bit with the key group you’re working with revenue, I’m guessing sales, probably some kind of analytics team, but how does that work kind of, how is your relationships and how do you, you know, kind of partner on the data cause it’s so different in every company, how they structure that.
Gabriela Gutierrez:
Yeah. So we work quite closely with the analytics team and, uh, and, and for me, especially because most of the revenues depend on the key metrics on the, these, like, we are in constant like pretty much when I need to update. It’s like, if I see something odd in the data, I would be like, okay, my contact person for the analytics team here, like we need to fix this. Or like something happens like, can you please take a look at that? But, and that, in a sense, I would be in a bridge of like being a very analytical person and being like a finance person, because some of the metrics I would, sometimes I would be able to forecast them myself because I would say, okay, I already have my models. I would just run them and I will see what’s happening into the revenue. So sometimes I also like to have this non dependency into another department to really kind of be proactive. And then just seeing, and, and with that, you could also challenge, like, for example, if they would come with different metrics forecast and received, no, like I have done the same part as I see a different results. Like let’s align, where is this coming from?
Paul Barnhurst:
Yeah. No, that’s, it’s great. When you’re able to do that yourself and be able to run the numbers and compare right. Kind of do that. Well, you came up with 2 million and I came up with 1.6, why are we 20% different? Oh, you use this assumption. I use that assumption or you tweaked the data this way and I tweaked it that way or whatever, you know, there’s been a lot of debate. I’m curious, your take, you know, there’s some people and I’ve seen it go back. You know, I’ve seen it go back and forth in different companies that, you know, the analytics department should sit it within finance. You know, my last company I worked at before I started my own business, when we got a new CFO, that’s one of the first things he did is he put analytics under finance, you know, and the funny thing is that’s where it was five years ago in this company. And then they broke it out on its own. And now they’ve brought it back in and there’s always kind of this debate because, you know, finance is so data driven is, you know, should, should analytics and the data ship with finance. Should it sit with it? Do you have any thoughts on that? Do you have a preference of where you think it, it naturally fits or what’s your take
Gabriela Gutierrez:
A very, like a good question as well. Um, I would say it depends because I will break it down, not like a single group of analytics, but rather I would divide like the analytics in a sense as a general business and there, I would totally agree that it should be within finance. And then if it is like product, like more product business analyst, it should be within tech and product because like even the job description would be completely different. Like a product analyst, it would be running AB testing. Like it would give us like kind of the first overview of how the product will like reactor evolve and what would be the revenue impact. But it won’t, for example, in our case, it won’t tell you how many new visits we’ll have next month. So I think this product be testing would be, should be closer to product and tech because it would bring more value to them like a generalist or like. General analyst definitely would bring more value to finance. And that’s where like there, we should really work closely. But good question, because I have also seen this debate of where should analytics sit, like in which department.
Paul Barnhurst:
Yeah. And, and that’s why I asked it right. There’s no, and there’s no right answer. I, you know, I think that can work well in finance. I think there’s times when it can sit, you know, in multiple places, depending on the data and what you’re doing, the key thing is a couple things. There’s, you know, one data source, you don’t have everybody using different data sources and you have the culture where everybody’s sharing. That’s really the key things for me. I do think, you know, there’s a natural fit to finance, like you mentioned for a lot of it, but it’s always interesting to see what different people think about it. Because different experiences and different companies all manage it so differently. And it really has been you know, a very popular debate. I’ve seen the debate happen a number of times on LinkedIn with different people of, no, it should be this way. Well, no, it should work that way. And it’s like, as long as it works, that’s what matters.
Gabriela Gutierrez:
Yep. So, and I think it would be almost impossible to under it to have it like, yeah, it should be finance. No, it should be product or tech. It would really depend on like how the company is like and what, like the what’s analytics serving as a purpose. Like I think that’s where they like the real good answer will light on.
Paul Barnhurst:
No, I, I, I agree with you. A lot of it depends on industry and company and the leadership and there isn’t, it’s like most things, like you said at the beginning, almost any question you can say, it depends, right? There’s it’s rarely, can you boil it down to a simple, this is how it works. Yeah. It’d be nice sometimes, but it’s rarely ever that simple.
So, you know, kind of moving on here, you had mentioned on LinkedIn, you had talked, I think it was a while back, probably about 10 months ago or so a little bit of an AI initiative that you were working on, you know, trying to improve some accuracy of forecasting. Can you maybe talk a little bit about that and how, you know, that initiative went, how you were thinking of using AI?
Gabriela Gutierrez:
Yeah sure. Um, so everything that started and when, when I joined eBay Kleinanzeigen, because I realized we have a lot of data and we hadn’t figured it out, like in a sense, like how to really leverage the amount of data that we have. Yes. We can use Excel for forecasting, but I was seeing some like that we would reaching the capabilities that we could do in Excel and then I said like, okay, what’s the next step? And that’s where I see a lot of opportunities for FP&A also for FP&A managers, because once we kind of reached this point, what else is there? And, and for me, like I went to really, I didn’t know how to code before I went into this journey and I always tried to avoid kind of like known code solution for better prediction, financial forecasting.
Gabriela Gutierrez:
Like I spent like days on that, like Google it and I couldn’t find something that would be good enough and would give like solid results. And then I said, okay. So if there isn’t something in there, okay, let’s go to the next step. Let’s go, okay. What’s the next option? And that was kind of like artificial intelligence models and kind of like machine learning. But then you have at least for my experience, kind of a high adoption, like you need to really jump kind of like a wall because you need to understand how like height on the code or like syntax work. And then you need to understand what a model will do. And like really, without having the knowledge, it was like sometimes even overwhelming. And I took it like, okay, first step let’s learn Python, how to code.
Gabriela Gutierrez:
And I went and it was like, oh, it looks Excel. And sometimes it doesn’t look like it, but some of the syntaxes were, uh, similar. And then as I took it and then I went into everything that would be related to time serious predictions. And, uh, funny enough, um, I did it this all on, on my leisure time. And I came out to an algorithm like really developed by Facebook and it’s called Prophet without knowing that, uh, that also within our analytics team, that would also be using the same algorithm to predict the metrics. And that was really funny. Once I started predicting the revenues and we like, wait a second, you are also using it. And oh yeah, we get like really good results with that. So that was kind of like the story, but in a sense, it was just the beginning, because once you kind of step like of that barrier of like being able to code, you can like really create a lot of more beauty within numbers and within like, uh, machine learning models, like with Prophet, it was like a very simple model.
Gabriela Gutierrez:
Like it’s, uh, more or less like deep learning, but then that would work with searching products that once you have a lot of historical data, but if you would go to like a new launch product and you want to use like a statistical model, it wouldn’t work, you don’t have any data. But then I just found like so much like information about different like data models. And then it was really just the beginning. And for now I’m just only using them. And since then I have leveraged up. And when, once I posted on LinkedIn about the comment, I really wanted to, to see like what were like the people challenges, because for me was a lot about this accuracy and how people were resolving in this. And especially they were still using Excel. How were they doing?
Paul Barnhurst:
No L lot of great information there and that’s, you know, great that you took that initiative and learned Python. I’ve, uh, I’ve toyed with it a little bit. I’ve never learned it. It’s still on my list. In fact, I have a book back here, uh, maybe I must be upstairs right now, but I have a book I’ve been reading again about, uh, learning a little bit about Python and R so I can understand that. And I think you mentioned right now, if I remember I toward the beginning, or it might have been even before the podcast, you’re reading a statistics book, I think you’d said. Yeah.
Gabriela Gutierrez:
Yep.
Paul Barnhurst:
So it, it, it sounds like you’ve really embraced, you know, a little bit of the data science side of finance and that in FP&A and seeing how machine learning and AI can help improve models and interesting of that, I think you’ll find this interesting. I had the opportunity about a month or two ago to talk to a lady. She was the first data scientist in finance for Facebook. She started up their data science organization. And she was telling me about how she’d built some of the models and, you know, they were getting to within 1% of accuracy of their daily revenue. So it was really fascinating listening to her talk about, she had a mathematics, she had worked on a PhD in mathematics or something like that, you know, really smart lady. And like that would’ve been fascinating and talking about just all the resources they had at Facebook. Right. Huge data science department.
Gabriela Gutierrez:
Yeah. For example, the algorithm that they develop, it was by two data scientists. Like, I’m so sorry. I don’t remember their name.
Paul Barnhurst:
You’re fine.
Gabriela Gutierrez:
But, but yeah, it’s like, for example, I would also say like another barrier, it’s like the level of mathematics that you need to know to be able to understand them, because in a sense it would just give you data but then you wouldn’t know like, okay, what does that mean? Why did it was eight instead of 10 or 100? And I have been also into that journey to really kind of going backwards to really, okay. I did the fitting of the model like this, so that’s why I’m coming to this result. And then it makes sense to do like that. And I would be like, still like very new into like the data science, but I find it like really fascinating. And, and I think the future will lie there because we have more and more data. And what our jobs will become in the future is really about predictive analytics. What are we going to do? And how can we really predict what would happen? But it’s really tough.
Paul Barnhurst:
Yeah no. So it sounds like you’ve really embraced, you know, the data analytics and the data science journey. So as you’ve gone through that over the last, you know, year or two here, and you’ve kind of learned Python, obviously studying some statistics, what advice would you have for somebody who works in finance, who wants to learn more about the data science, maybe, you know, Python or statistics, or how would you recommend they go about that? Do you have any advice from kind of your journey that would help others?
Gabriela Gutierrez:
I think there is a lot of like free information already out there. Like if you person that like self taught yourself, you could just like watch a YouTube video or you could go to, or there’s tons of information out there. I found like the MIT for free and statistics and data science. They are also like, you can just sign up. They have a lot of good, like content, like the classes, the exercises, they are simple to use, they can accommodate to your schedule whenever you want to practice. So I would totally recommend everything that be online. So then you can have your own pace because it’ll take up while it’s kind of like learning. I always compare it sometimes to learning Mandarin. Like if you will go this jump from zero to, to be fluent in another language. So I will feel like that more or less, but you, everything it’s out there. And, uh, I would also encourage, like, not to be afraid because for some people it will sound that it’s too complicated or you need to have a lot of resources or have a lot of knowledge about mathematics. And I would say like, no, like really once you, you just do it, the first steps you will get it. And then you would come in, like in layers and then you would be able to learn more.
Paul Barnhurst:
That that makes a lot of sense. And it’s so a number of resources we have today, it’s amazing what you can find with the internet, right. That you can do virtually. So appreciate the advice there. So kind of switching gears here a little bit, you know, this is a question we kind of, we, we like to ask people just to see how different people have managed through what I like to call mistakes. You know, we’ve all made, them I’ve had some huge ones in my career, but you know, what’s maybe a big mistake you’ve had in your career. Say for example, an analysis that went wrong, you know, maybe a mistake in a budget. And what did you learn from the experience?
Gabriela Gutierrez:
Interesting question. Actually okay. I have a silly mistake that happened yesterday to me, I had a mistake in a SUMIF formula and I was, um, so usually like once we, like, we predict lower visits, our revenue would also decrease and I was like, Hmm, something is wrong. My revenue is increasing. Like, and, and I just noticed it and it was like a very SUMIF formula and I should have known better. And yeah, literally like 10 minutes. And where is this coming from? But in a serious way? Like for example, for me the biggest mistake would be like that I didn’t run into this data science path before I really regretted. Like, for example, if I would have taken in college more like a statistical and mathematical, like lectures, I think like the capabilities that I would currently have and the level of value that I would even able to bring into the company would be much higher. And like, my goal right now is to really build my own forecasting model and not use like the current ones that we have, but rather like build it from scratch. And I think if I would have started that journey for it, I like right now I wouldn’t have it. So that’s kind of like, oh, I should have.
Paul Barnhurst:
Yeah, that’s a great example there. And it’s clear, you’re passionate about what you do. I mean, I can see your excitement as you talk and that you love the, know, the state of science side to finance the machine, learning the digging in and building those models and working with the numbers. And it’s great to see because I can, you know, I can see that, that passion and I laugh when you mention the SUMIFs, because we’ve all been there where you, you do a formula and you’re spending, you know, 20 minutes, 30 minutes, 10 minutes, whatever a day sometimes. Why is this not working? You know, I used to do SQL I, I wrote reports and right the code doesn’t work and you’re spending hours trying to like, why am I getting a billion dollars back? The numbers should be like a million. I know something’s wrong. So we’ve all been there. And there are days when I’s just like, okay, I’m just putting this aside. I’ll look at it tomorrow. Cause I can’t figure out where I screwed it up.
Gabriela Gutierrez:
Yep. So, and like, I like, like really like, like too long to really figure it out. And because I was thinking the formula right there is something, everything else was correct. The, the formula right?. And there you
Paul Barnhurst:
Go, that that’s exactly, you go through the process and you’re like, and you keep coming back. You’re like, well, it can’t be that. But then you go through it logically and like, well, it can’t be anything else. So it has to be that. And then you start going, okay, so, well what did I do wrong? Say, yep. Yeah. Like I saw a shirt that made me laugh and you would appreciate this in coding. And it was, uh, you know, said, I think it said something like roses are red, violets are blue. You have a left bracket, line 32, you know. And anyone who’s coded can understand that one. Right. You can appreciate the we’ve all been there where it’s like, could someone just tell me where the mistake is? Because I’m tired of looking,
Gabriela Gutierrez:
For example, coding. There was like, when I was learning it, I would’ve spent like hours to really understand why did it would come up an error? And I would go to like Google, like error, blah, blah, blah. And then I wouldn’t understand anything. And then I would be like, oh my God. Like about to cry. Because like it wouldn’t work. And then yeah. But yeah, that’s like the funniest stories that the later you can laugh.
Paul Barnhurst:
Yeah. At the time you’re very frustrated later on you look back and you laugh and just be like, I did what? So Yeah. I can, I definitely have plenty of those throughout my career so I can, I can relate. So, you know, switching gears here, this is a little more kind of personal question to help our audience, get to know about you. What is something unique about yourself that you can share with our audience? Something they wouldn’t find online. I mean, unique hobby or whatever you wanna share, just something unique.
Gabriela Gutierrez:
Oh, I love the sports and I really like love art. That’s why it was another reason why I moved to Berlin because it’s like a very artistic city and I would’ve spent some time when I was even younger, like weekends just going from a gallery to the next gallery and then like going to museums and then like photography would be kind of my secret hobby that I would just, you will see me sometimes I would like I would be walking and then in the middle of the street and I would be fascinated with something about architecture or art or making a picture and everyone would be, are you okay?
Paul Barnhurst:
That’s great. Art, art is a beautiful thing. Do you have a favorite artist or museum or anything like that?
Gabriela Gutierrez:
Uh, yeah like actually so in Berlin there is a spirit Mar and gallery as well. There is also a new national gallery that opened recently in Berlin. It’s like with these brutalism style and at the bottom, like you have like really nice garden. I went in summer. So like also it helps because I imagine in winter it would be pretty much great and very cold, but in summer it was really beautiful and they have an exhibition about women in the 19th century. And what was the role? So very as well, relevant. I also work as a part of, uh, diversity and inclusion group within my company. So I’m always kind of keen to like to see this type of exhibitions and how we can really improve the role of like minorities in companies.
Paul Barnhurst:
No, that’s great. I love, you know, that you’ve been involved in diversity and inclusion because it’s so important, right. Companies when we embrace diversity and embrace, you know, different groups and welcome different thought and include everybody, you get better results. Plus it’s fascinating. I mean, I love learning about different people and seeing their different views. I, you know, I embrace that and having those discussions, because it often opens my eyes like, oh, I’d never thought about it that way or, oh, that’s how you experience that. I see it this way. Like you’re your experience is so different even though we may be looking at the same thing, we, we interpret it so differently. So that’s great that you’re involved in that. So it sounds like it’s a passion of yours.
Gabriela Gutierrez:
Oh yeah. True. Like you, you can see, I have many passions, but yeah. It’s something like really, because sometimes with finance would be like very numbers-driven and like where it’s like kind of like more social part would be like DEI, like really what would be, for example, in our case. But would it be initiatives that we can do to have like a better belonging like that will people will feel more welcome to work in a company? Like, um, I remember, um, a couple of years ago I, I work in a company where I was the only women and that was like in a sense, very challenging to really make yourself heard or like really express a point, because then you would feel like, a lot of pressure. So right now that like in our group, what have we tried to do is like really a touch point in belonging, how we can make everyone welcome.
Paul Barnhurst:
Yeah, no, that, that makes a lot of sense. You know? And in finance mostly career, obviously it’s tended to be most men, but I did get the experience in college. I worked for a couple years and there was about two years where of all the students, I was the only guy, it was all girls. And so it gave me a different perspective of kind of, you know, being the minority, so to speak. Because you know, most of my career I’ve been the, in the majority, it’s a lot of people, you know, male. And so I haven’t had those experiences as much as others. So I always appreciate people sharing because I get, you know, there’s, it really, you know, really is important that we make sure we’re embracing and involving everybody because a lot of people have been marginalized throughout society. So I, I really appreciate you being involved in that and sharing that, that that’s great to see. So next question here, you know, as you look over your career and just kind of look back what is an accomplishment you’re most proud of? So if you’re in a job interview and I ask you, Hey, what’s the proudest moment of your career? What’s your greatest accomplishment? What you going to tell me?
Gabriela Gutierrez:
I would say like the models that I, that I currently run in like when I talk about them would be like, yes, I did it like. I was able to learn it and to run it and we get like, for example, like sometimes I get a request, like we need to do a long term planning and we need to forecast revenues for the next five years. And then like really how like if you would do it manually, it would be like such manual work. And that I’m like, okay, no problem. We can do it. I just need to run like at least the brand brain models that will work and then talking and aligning with the team. And then we would be able to build a case, but that’s totally feasible if you use machine learning and then you u just have it like in five minutes, more or less, but you need to check like then the checks, the fitting that if you would just run the model you could have for the next 10 years, if you want.
Paul Barnhurst:
Thank you for sharing that. And I know who I’m coming to, when I wanna, uh, get more involved in machine learning, you might get a message from me.
Gabriela Gutierrez:
Yes, please. Anytime. Like, I would’ve be more than happy to like really to talk about this with other finance managers like everyone.
Paul Barnhurst:
Great. So now this is a question we ask everybody, it’s kind of our fun question. You, I know you’ve seen the video about this. What is your favorite Excel function and why?
Gabriela Gutierrez:
Yeah like I think that’s the most tricky question. Because like I couldn’t decide, um, yesterday before the mistake I had yesterday, I was going to say SUMIF, because it’s like so simple and then you could just whatever you need in a second, would it be like, OK, you just get the nod. But after my mistake, not anymore. I would really choose to, to use pivot tables. Uh, why? Because once you have ton of data, a pivot table can just summarize everything quite quickly. You don’t need to kind of experiment with like crazy formulas. You just have an overview of the data and then yeah. So pivot.
Paul Barnhurst:
Yeah. No pivot tables are a great one. I remember the first time someone asked me about pivot tables and this was back 20 years ago now. We were trying to figure it out and I’d never used them. And we were trying to summarize text cause I had no idea what pivot tables were with my boss. And I was like, what good are these? And then, you know, went back, finally figured it out. And I’m like, oh, these are great. These are now I get how they work. And now I look at it and go, how did I not understand that? It just seems so simple. But when you’re first trying to learn it, it can take a little while. But yeah, no in my last job I use pivot tables pretty much every day, huge fan of pivot tables. So I, I can appreciate that one. They’re a great one. So last question we wanna ask you here. We’ve really enjoyed this time and I’m excited. You know, we’ll be excited to release this episode to our audience and them to get to learn a little bit about you, but you know, if somebody was starting in FP&A today, so they’re just starting out in their career, what’s the one piece of advice you’d give them. What would you tell them to as a piece of advice if they came to you?
Gabriela Gutierrez:
I would say like first of all, always have an understanding of the business. Like really spend time talking with people because as I mentioned it, I think at the beginning it was like numbers or numbers. Like we are the ones that we need to give them the context and the meaning. So it would be like understand the business and understand where are the challenges and like opportunities as well. And then how do you can understand that it’s like through data. If we want to see a challenge, you need to see like what’s the like economical environment. If you want to see an opportunity, you need to understand how the industry is working and where is it going to so that data. So also I spend a lot of time having the right tools and the right skills, how you can manage tons of data.
Paul Barnhurst:
No, thank you. I think that’s great is, you know, the advice that I love, the first part of learn the business, right? Really understand the business. That’s something that’s helped me a ton in my career and then get to know the numbers, get to know the data. So that’s great advice really appreciate that. And we’ve really enjoyed having you on the show. Thank you for, you know, carving out some time for us today and hope you have a great, I, it was Friday, so I hope you have a good weekend and get to enjoy some downtime there in Germany. So thanks again for being on the show. Gabriela,
Gabriela Gutierrez:
Thanks to you, Paul. It was a pleasure to be here.