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And now, onto the show. From Data Reels, this is FPNA today.
Welcome to FPNA today. I'm your host, Glenn Hopper.
Our guest today is Maria Del Dato-Alanzo Sanchez.
Dato is the former group CFO at BBG, a pioneer in the direct-to-consumer business, and has an impressive career spanning roles at Ezearian, NASPRS, CNA Netherlands, booking.com, Amazon, Europe, and Siemens.
She holds multiple advanced degrees and certifications, including masters degrees in both law and business administration, a CMA, and a corporate-governance certification from INSEAD.
She is also a distinguished professional speaker, a member of the IFAC Professional Accountants and Business Advisory Group, in an advocate for women and AI.
Dato, welcome to the show.
Thank you for having me, Glenn.
It's a pleasure to be here.
Yeah, looking forward to diving in today.
You've got an impressive track record of companies you worked for before.
Can you kind of walk us through your career journey, maybe highlighting the key roles and types of work that you've been focused on?
Well, look, my younger year actually starts in a very small town, in traditional Northern Spain, in León.
I, you know, with two degrees under my belt, I went to Germany in search of opportunities, and I have over 20 years as finance professional in blue chip companies.
Over 10 of them as finance director, as CFO.
My first job as Siemens was as business finance, finance controller.
And since then, I actually learned to grow into different facets of the function.
I actually consider that I grew as finance professional in Amazon.
I was actually privileged to work in Europe, Amazon, when it went through significant transformation.
And at the time, that's when Prime was brought into Europe, actually, and Amazon Europe was created.
So you can imagine what was the type of energy and good spirits that we had over there.
Then in booking, you know, I was actually involved in a period where booking.com had just been acquired by price line.
We had started the market, attacking the market, the US market, and we had actually expanded into housing, vacation market.
So also very, very transformational moment.
I would say, you know, another pivotal experience in my career was Assyrian.
This Assyrian was a company that operated in gaming and online advertising.
And it grew actually from 200 million euros to 500 million in almost two and a half years.
And you know, very dynamic.
We acquired 15 companies, which raised two bonds.
And ultimately, you know, it was phenomenal because we actually went floated in, you know, in Amsterdam Stock Exchange.
Finally, as you well mentioned, you know, I was formerly the Group CFO at Perlins brand Group.
It was a private equity, you know, backed by paying capital.
I was leading the e-commerce group, but you know, we actually ended up in a leveraged buyout.
So as you can see, look, my career has been nothing more than transformation, moving, continuing, moving.
I cannot wait to dive in the new exciting challenges that come to me.
When I talk to guests who have such a broad range of experience, I like to talk to them about what initially led you to finance and how your passion for FPNA is evolved over time.
And I think this is especially interesting as a question for you, because I know you also studied law before going into finance.
So could you kind of tell me about your interest in finance and how it's evolved over the years?
As you all said, right, from I studied two degrees actually simultaneously.
That was law and finance business administration.
It was always in my desire to explore always new horizons.
And for me, it was always like the bigger the challenge, the more motivated I get.
So I guess that is part of my personality.
When I was studying really business controlling seemed to me the perfect role for me.
That was what I was thinking.
I had the luxury of the wide scope and business understanding.
I had also the exposure to strategic and tactical roles from a very, very starting in the career.
And very important matters for the company.
So you can actually influence quite a lot through insights and advice.
I cannot hide it. I like power to influence and to create change.
So that's how you know, there is passion for for continuous learning and also for finance and in particular for FPNA and business partnering team.
You know, I almost don't know which companies to pick to talk about first because it's so many interesting companies.
And I know like the KPIs across companies are going to be different.
The metrics that you're tracking.
And I guess I'll just say as groups CFO at BBG or at Sarian.
Could you tell us a little bit about the main KPIs and metrics you focused on that those companies?
Yeah, absolutely. Depending on the company you are in and the industry that company is operating actually the KPIs the metrics that you track are slightly different.
But all in all, there are some common metrics that you track in every company.
Where you are talking about revenue growth, revenue growth rate, growth margin, operating expenses, EBITDA and free cash flow.
I mean, I would say those are the common metrics that you always track.
Then actually depending on whether a company is more on the leverage side or not.
And you can also start tracking some depth, let's say metrics.
But those are in general those are in general the metrics that you typically track.
Now if we talk about Berlin Brands Group, BBG, which was an e-commerce business or a serial, which was actually operating in digital entertainment.
Obviously, I mean, they are following and we used to follow different metrics.
In Berlin Brands Group e-commerce, as I said, inventory was very, very important.
So in that case, we were tracking inventory turnover.
So how many turns we were given our inventory, inventory healthiness, the aging of the inventory, we could drill in many shapes and forms how the inventory was formed and so on.
And then obviously the return rate, right?
I mean, monitoring the percentage of products that are returned, the customer service information that those were also very, very important to make sure that our trading would be as healthy as possible.
In a serial, actually, the type of metrics that we were tracking were a little bit different.
We were talking about a company that was operating in gaming and in ATTEC.
So practically, the metrics that the KPIs that we were using were daily active users, monthly active users, average revenue per user return revenue.
So practically, revenue, I mean, metrics that are actually linked to the users, to the revenue and the very, very top-line type of metrics.
So depending on the sector, depending on the industry, you tend to focus on one or the other metric.
Yeah. And I guess a follow-up question that I hadn't considered on this before, you know, moving from industry to industry, when you come into an industry, you sort of know the industry metrics that you're looking at.
But when you're trying to establish yourself in this new industry, like what do you look at and what do you look for to help define those metrics and to get a better understanding of what you need to be tracking by those businesses?
Yes. Look, the first thing I look actually, I mean, the first thing I do is to get actually my finance, let's say I call it finance footprint, right?
This is kind of like the small contract that I signed with my manager, typically the CEO, right?
And with that, I get quite a good understanding of where the situation of the company is, right?
So what is the challenges, what are the challenges, what is the strategic mandate, what is practically, you know, the positioning of the company and how how we want to track operationally the, you know, kind of the delivery and the results, right?
Starting from that business inside, that's where I start thinking about, okay, so what should be the metrics that we should track, right?
I'm always looking at metrics that are very, very close to operations because I think that building that link between operations and finance is the best way to create insights that are actionable and that is kind of a positive flywheel.
So it gives information to the business of how to improve results and it also positions finance at the table, right?
At the decision table because we go there talking kind of the same language.
Great, that makes a lot of sense.
And then, you know, bouncing from those two companies, I can imagine what the environment was like at booking.com or Amazon Europe at that point in time, rolling primed out in the EU.
And sometimes we learn a lot from these, you know, maybe in hindsight, they're pretty stressful times when things are just moving that quickly.
So I'm wondering being at those places, at those big companies that important times in their evolution, how did your experiences, their shape your approach to financial leadership?
What kind of lessons and takeaways did you get from that?
To say short, they were phenomenal, right?
So I can elaborate a little bit more of course, but they were phenomenal.
I love a very dynamic and fast, and fast-paced environment.
That's where I thrived.
And I like the energy and like positive energy.
I like when you have teams that you're in together to build something, you know, and that's I think something that you it's a positive energy that you get in this type of environments.
So in this case, booking and Amazon, they were, as I said, very, very dynamic and fast-paced.
I can only say that both experiences really, you know, kind of lent me the importance of agility.
So being fast and being quick in whatever you do allows you the possibility to fail also very quick and learn very fast from your mistakes, right?
So this is very important in a fast growing environment.
And the other thing that I learned very fast and by need was actually adaptability.
So you need to keep yourself flexible in finding that middle way to find your way and get things done and progress and continue progressing, right?
In Amazon in particular, you know, I learned the meaning of customer obsession.
I know this is one of the Amazon principles, right?
Leadership principles, but I can assure you customer obsession is the first principle and everybody from the first, you know, from the CEO to the associate in the fulfillment center really, you know, feel very, very strongly the power of customer obsession.
In the case of booking, there was one thing that was very powerful, right?
It was the 80-20 principle and it was around, you know, this Pareto principle where when you when you already have kind of, I mean, with 20% of the effort, you kind of tackle 80% of the need.
And that was when you are in an environment that is growing very fast, you know, being very aware of not investing too much time on getting the, you know, kind of called plating the results.
That's very important because it allows you to move much, much faster.
So I would say this pragmatism and the customer centric approach, those have been really vital in how I approach finance.
Yeah, great point on that.
And I think people in finance and accounting, we are risk averse.
So there's always the, you know, measure twice, cut once and slow down.
And it's hard to do that when you're also trying to grow a company really fast.
You can't have finance and accounting be looked at as someone that's slow in the company down.
So you have to sort of find that balance between move fast, but also be right because people have to trust the numbers.
So I wonder, and I think another, you know, you have so much experience in direct to consumer business.
And I'm wondering if the nature of that and maybe the pace of growth, but the fact that you're dealing with so many customers in that direct to consumer business, were there challenges and opportunities that you think come out of your experience working with that group?
Well, I mean, absolutely.
I mean, my experience in direct to consumer was pretty much in Berlin brand group, right?
My last, my last role. And what you need to understand or, you know, the audience also needs to understand is Berlin brand group was, you know, let's say 400 million revenue business and was operating, you know, over 8,000 SKU products, right?
Selling through different channels and also through our own stores, online stores.
In that context, what happens is you have practically the whole complexity of having to deal with consumers directly, but also in a, with a very, very complex footprint in terms of channels, right?
So that is what made it very, very difficult because in a way, you need to learn very fast that, you know, how not to cannibalize your own sales, depending on the channel.
But at the same time, you are very much exposed to everything that is going on in the market, right?
In the case of Berlin brand group, when I joined, it was, that was in summer, 2022, and summer 2022 actually was the summer that came off, you know, that was the e-commerce downturn in Europe.
So practically, the majority of the markets were really suffering from the post-COVID hype in terms of e-commerce, right?
And that, that, that required a very, very deep, very, deep, readjustment.
So if you add all that complexity with a deep, a readjustment, and you put that in combination with a very fast growing company, where initial investments are not, you know, done properly or they are done faster in the growth, but not necessary, the back office and support functions.
That's practically what, what makes it, you know, the perfect combination for a challenging environment.
Makes sense. And I think, you know, going from e-commerce to technology to retail, I mean, what do you think, would you say there's differences in financial strategies across those various industries, or how would you explain the similarities and differences between them?
Yeah, I mean, you have said, right?
I mean, in my career, I have, I have had the privilege, actually, to work across different industries.
I work in e-commerce technology gaming, at tech, in online hospitality, and it's actually really presented its unique, financial, you know, challenges and strategies.
They were actually tailored pretty much to the business model and and the market dynamics.
So for instance, in Berlin, Brings Group and Amazon, both e-commerce companies, the focus was on scaling operations and optimizing supply chain efficiencies, right?
In those companies, dynamic pricing, inventory management, and significant investments in technology were actually the strategies, the key strategies to improve user experience and and increase conversion rates.
If we, if I think about a Syrian, the gaming and at the sector, financial strategy was centered around user acquisition and retention, diverse monetization models, continuous innovation, substantial budgets were actually also allocated to marketing campaigns and research and development to stay ahead of the evolving tech landscape.
So, yeah, depends on a little bit what is the environment at that point.
In the book in and price line, you know, we highlighted the importance of global food print.
So in that case, global expansion and the metrics that were and challenges that were linked to that were more important.
So that's, as I said, so in my experience, across the different industries, yeah, the industries is triggering also a different position in and a different approach towards strategy and the challenges.
Yeah, and when you mentioned the global environment, I think about how difficult it can be to do financial modeling in forecasting, even in a B2B or a software company where you have long lead times and all that, but in a, you know, in global e-commerce, everything changes so quickly and there's so many things that are exogenous factors that are outside of your control.
And I'm wondering, what was your approach to financial modeling and forecasting in the global e-commerce space?
Well, in my global e-commerce space, you know, as you can see from Amazon, Amazon experience was over 10 years back.
Berlin-Brands Group has been my last experience, right?
So, it has pretty much a model or a company made throughout my career.
I would say my approach is actually, yeah, quite pragmatic, right?
First and foremost, you know, investing in, you need to invest in the creation of the right database.
You need to ensure that you have strong data and governance is really essential.
Well, this involved actually defining clear and consistent metrics.
You need to talk to other stakeholders.
You need to have a common language across the company.
And by doing so, you can create actually the solid foundation for reliable data that afterwards, everyone in the organization is going to be able to use and trust.
Once you have that reliable data and that infrastructure in place, then that's cool, right?
Because then you start democratizing the access to this data and it becomes really the priority.
Once you democratize the access to the data and the data is accessible to all relevant teams, when then happens is that that fosters a culture of innovation of inter change and actually it empowers the employees to deliver insights that drive a better decision making.
Once you have obviously this well-known state of the art financial systems, it's also a critical component for the strategy.
So you add the financial systems, you add the data, you have the foundations and leveraging all these three components, then you build and you have in fact, you know, a robust and flexible and dynamic starting point to build financial models.
So that is absolutely crucial in the e-commerce landscape at the moment.
What we are actually doing now, looking ahead, because in this function, you always need to be, you know, with one foot in the today, but the other foot needs to be in the tomorrow, right?
So we are actually very, very, very conscious that machine learning and generative AI and in particular, the combination of those two together that will be practically the new standard, right?
Machine learning for forecasting, for dynamic pricing and generative AI for everything that has to do with summarizing and, you know, grinding, you know, the comments, commentaries.
I love that you are addressing generative AI, but also referring back to machine learning, and I do see, you know, so many people are just talking about generative AI right now, because this is maybe their first exposure to it, but combining what we get out of generative AI with, you know, sort of democratization and, you know, and I haven't a right python or whatever
to be able to access data, but then also referencing back to machine learning, which has been used to, you know, Amazon and booking.
I'm sure many companies where you've worked have used machine learning, even if not fully in the finance department, they used it in their operations and certainly plenty of application for machine learning and finance as well.
I really think and I expect we're going to see more crossover with this, but the idea of FPNA analyst, business intelligence analyst, and data scientist, there's the VIN diagrams where they all exist, have a lot of overlap in them, and I think that it's impossible today to talk about FPNA without talking about data and analytics.
So the fact that you referenced data and analytics, maybe give me a little more detail about how you leverage data and analytics to drive decision making and you're forecasting and business strategy in some of the roles where you've been before.
Yeah, the reality is for me, I think I have always seen data as absolutely core for finance and for finance to be in the decision making and to be a core pilot.
So that's something that I have seen from the very beginning.
In fact, when I was actually in booking, I had a mathematician in my team.
I hired two mathematicians afterwards and a technical person.
And that was part of my team in business controlling, which was quite unique.
We are talking 10 years back.
So that's to say that, for me, data is actually essential.
And the beauty of data is what I mentioned before.
So the market, the market is the decision making.
And with these data insights, when they are available to everyone, it is actually much easier to balance the power and to balance the influence within the companies, which makes everything much more challenging in a way, but much more equal in another way.
So then you don't have that department in finance that is monopolizing the access to information.
You don't have either the teams in commercial that actually are figuring out new numbers that do not type to anything, right?
Where actually, after the end of the day, you end up with meetings where people, instead of talking about what really matters and the issues in the business, they are actually talking about whether my data is more accurate or the other data is more accurate and then you waste time.
Coming back to your question and seeing how do I leverage data?
Let me share with you one example in CNA, which is not, I wouldn't say, is the typical examples of a company that is technology driven or very much technology driven or digital.
So CNA is a fashion, it operates in its available company, it operates in the fashion industry.
And if you think about H&M is a similar, H&M would be a competitor of CNA, right?
And it operates in Europe.
So during my tenure in CNA, Netherlands, the typical, you have the typical structure, you have the headquarters and you have the regions, right?
And in Netherlands, we didn't have the visibility, any visibility to key data.
So the unit economics or profitability, that was all lacking.
And we lacked insights and that lack of insight really hindered our ability to make sound decisions.
So the first thing I did was actually, when I was hired, I hired also a business analyst because, you know, and this was very, very unusual for the company, right?
They were actually saying, why do you need this role?
I mean, what is that person going to do?
Right? So I said, no, this is, I mean, I started the company, I need a business finance analyst, right?
And well, I hired this person, I empowered him to, you know, to find ways to improve, you know, the country decision making potential.
So I gave him a broad kind of mandate and we had kind of regular, regular meetings.
So to tackle this challenge, actually, the business analyst first built a strong relationship with different teams, both in the country, but also in the headquarters, he had actually to understand the various different types of data and decisions and what systems they were using in the center, in the country.
With that, we actually created a local database, a data system that could allow us to understand the economics, right?
So the economics of the garments we were selling, the processes, how it ended, how those garments ended up in our shop floors.
And the system actually would track crucial metrics, such as size, cows, landing prices, expected discounts, time of arrival, and many more, right?
As you can imagine, there were quite a lot of obstacles in executing this project, right?
It was particular challenging to build, you know, kind of the connection with the teams and many of them were actually quite resistant of these chains, right?
And that was a challenge that I had to tackle myself.
So practically the cultural change, that is something that I had to push for.
The reality is that we were able to create some quick wins.
We created reports showing products that were overpriced and were about to land in our stores.
We created overviews to show stock.
And by creating these actionable insights, actually the teams started collaborating, right?
So that broke the glass.
And then we started scaling.
And that was phenomenal, right?
And by integrating this information with historical data and also with past trends and by brother, by region, by even by city, right?
So we were able to generate insights that enabled us to analyze our future connections.
We're likely to perform and to make proactive adjustments far before the products were coming to the countries.
So that was also helping allocating accountability, where they should be allocated, right?
What I can say is that with that, we could influence pricing strategies, optimizing sizes, manage batches and deliveries, up to 12 months in a month.
And that was much more, you know, it allowed us to decisions much earlier.
The reality of the matter was that this project was actually a success and it had really a transformative impact.
Not only improved our visibility and control the business, but actually, you know, very soon all countries wanted a business finance analyst and also are too similar to this one.
So the tool was developed and became highly sought after, you know, and the role of the of finance analyst was pretty much standard after after my push.
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What I'm hearing here and I hear this a lot when I talk to finance leaders.
When you're an individual contributor and when you first start your career out, you know, okay, I have to get really good at FPNA and I have to be really laser focused and these are the things I do.
But as you move up in your career, you have to know what your mission is and sort of the why of what you're doing and what the end goal that you want to achieve.
So you have to sort of branch out from just doing what's in finance.
So I think a general business degree probably helps some in that too.
But it's also what you learn along the way because you talked about, you know, hiring a position that the company thought, why are we hiring this position?
But you knew the mission and where to go.
And I think that another thing that we have to do as finance people a lot is how much we're crossing over IT and software.
And so we can't just the metrics and what we want to get.
And we have to start having an understanding of data in the systems.
And I know before they show you and I were talking about implementing BI tools.
And we don't have to talk about specific brands or not.
But I'm thinking about I'm the finance person.
And suddenly I have to figure out how I'm going to implement this BI process, which BI and finance again, a lot of similarities, but they're not the exact same role.
So I guess sort of continuing out what you were just talking about, talk to me about implementing BI tools and how you've approached that.
Yeah. So it's funny actually that you asked this question because really literally since the beginning of my career, I have been involved in implementing BI tools.
Implementing BI tools typically requires a very, very significant investment, right?
In terms of time, resources, and effort.
So it's something that you cannot just decide in finance.
It is a strategic decision.
And once you have the company buying into the idea, buying into the need of having a BI tool, then the journey can start.
And I can assure you the journey is challenging, questionally painful.
But I can assure you that well implemented BI tools can really improve decision-making and enhance operational efficiency and also drive the daily growth, right?
When I was CFO, I mean, in my tenure in the in the Lindbrands group, I had the opportunity to implement this advanced business intelligent tool.
And you know, initially a Lindbrands group used a Power BI tool, right?
So we had it already as you can imagine.
This is a company that was already operating in e-commerce for 10 years.
We had one. But the reality was that this BI tool was linked to operating systems.
And it was actually not very well, you know, from an accuracy point of view, it was not very good, right?
So it had been created as many as by need, you start adding one piece of information.
A system comes to the database, then we just start creating several metrics.
At the end of the day, you have metrics.
They all give some sort of data of information.
But because you don't have that governance around the data and you don't have governance around definitions, what happened was that the results could be up to 10% deviations, right?
Could bring to up to 10% deviation.
So we are talking about a database that was actually the core of the business, right?
So you would decide whether to sell a product in a particular country or not, whether you would drop or increase a promotion in a particular product, right?
Or whether you would invest more or less marketing in a particular product because you were expecting a profit contribution that was above 5% or lower, right?
So it was a very, very critical tool in order to make really operational decisions, right?
So what happened was that we all recognized the critical need for reliable and consistency data.
And what happened, yeah, we said, okay, let's work with a partner that is very reputable.
We were working with Quantum Black.
This is the company from McKinsey.
And we work with them for over a year to build a comprehensive business that business warehouse, right?
And this initiative actually involved the whole company.
So it involved establishing created data, defining metrics and very robust governance process.
I think that is very critical.
Once it was finished, right?
So the new database really provided faster and more flexible data.
We were actually able then to access information around profit contribution, in the product contribution insights by brother, by SKU, by country, by channel, I will automate it and all very, very flexible and dynamic.
And really by ensuring that this data and the insights were consistent about across the teams, we actually increased and improved the accuracy and the reliability of our analysis.
But I was really mentioning before, right?
So you go into a meeting and then you already start talking about what matters.
And you just don't disagree about the numbers, you know?
So that was very, I mean, not only a waste of time, but also very frustrating, right?
Because it's very easy that you start into the finger pointing type of situation, right?
So the impact of all these improvements was very, very profound, right?
So decision-making became much more efficient and we could actually match better monitor project execution.
The fact that we had consistent and accurate data, it actually enabled, as I said, to make better informed decisions and even what I mentioned, right?
Allowed us to introduce a dynamic pricing tooling.
So I can only stress, you know, I mean, if you can afford, you should think about implementing a robust business intelligent tool because that opens a whole bunch of additional opportunities that without this robust business intelligent tool, you will not be able to harvest.
Yeah, great point. And I think, you know, with so many companies, maybe who have been behind on digital evolution, I think that they may be not even, they may not even be worth, I'm thinking more of the smaller companies, hopefully the enterprise, but there are companies that still need to advance their data maturity, but I think you have to get to BI before you can even
think of AI. And it sounds like with your background, and you know, you sort of understand or not sort of you definitely do understand that the foundation of being able to use AI is to have this BI in place and to have a solid data foundation.
And I know that you're passionate about where the industry is going and where the, or where the profession is going so much so that you've joined the advisory board of women and AI at Netherlands.
For again, classical machine learning, classical AI will call it, I know companies have been using that for years, but more and more people are interested now in generative AI.
So tell me about your desire to be at the forefront of this and how you're seeing, and if you get out your crystal ball here and are predicting the future, how do you see AI in general transforming what we do in finance?
I really view the advent of AI finance as a phenomenal opportunity.
I mean, don't think I'm crazy, right?
So I, of course, I'm aware of the risks.
I'm aware of the ethical risk of the royalties and attribution issues.
I'm aware of the bias. I'm aware of hallucinations.
I'm aware of all those risks, right?
And that's why we need to be aware and we need to know how to use the tool.
For me, nonetheless, it represents, I have to say, intelligence represents a phenomenal opportunity for finance because the way I think about it is it's actually elevating or eliminating a little bit the barrier of entry, into everything that has to do with data.
In the past, in order to access data, you needed actually to know how to program.
And now, perhaps it's not so much needed.
You need to know just a tiny bit, but with that tiny bit, you can actually find your way, right?
So for me, AI really represents journey of evolution, of innovation and possibilities.
I'm sure that we will benefit from digital transformation in terms of both professional and personal growth, increasing our productivity and sizing and forcing opportunities.
So we, I don't know anybody that does not know or that is not using today's activity, right?
So for personal use. So the way I think about it is I see a machine learning and Gen.
AI as tools, right? And depending on the use case that you may think of, then the finance professionals we use will use a different tool.
So we will use most probably machine learning for forecasting.
We will use Gen. AI for summarizing.
We will use the robotics RPA and Gen.
AI in combination for finance operations.
So I guess what I'm trying to say is the more we understand the tools, the more we will be able to think about use cases that will be suitable to be solved with the use of these tools.
So according to Garner data, we finance professionals, we are actually quite optimistic and quite positive towards artificial intelligence, right?
However, it doesn't seem really that we have started using these tools widely yet.
And I say it is really important to adopt this new technology and get started because even McKinsey is foreseen the adoption in four to five years.
Just let's think about it, right?
So normal technologies take around 15 years to be fully adopted.
So Gen. AI, artificial intelligence, machine learning, it's going to be accelerated.
The adoption is going to be much, much faster.
So in my view, no finance professionals should be left behind because this is a great opportunity if we are fast in getting into it.
Yeah, so great points on that.
And I think in finance, we never want to be on the bleeding edge of a technology.
I think leave that to sales and marketing and maybe to some extent on the product side.
But for us, we don't want to be laggards, but we're going to let other people go and get the bruises because we've got to have the numbers right.
And again, I'm right there with you though, I'm super optimistic.
I'm trying to find ways to use it today.
We still have a lot, you know, there's still the hallucination and bias issues that you talked about.
And I think that we're the tech companies are working through that.
But I also along with that, I feel like the entire industry right now is saying, yes, I understand it's coming.
I don't know what I should do.
So I guess, you know, from from your vantage point, what do you see as the biggest opportunities and challenges for these FPNA pros in the next five to 10 years?
You know, if they really, if if if Gartner is right and we are going to be fully adopting the generative AI in the next five, where do you see these opportunities and challenges coming for us?
Yeah, I mean, as I as I said, right?
I mean, short term, the biggest opportunities lie in harnessing emerging technologies like artificial intelligence and data analytics, combining machine learning, GNII and automation.
And I really think it will shape the future of the profession, but was, you know, a niche qualification, mastering data analytics now is somehow essential.
So as you will set at the very beginning, I'm part of the international Federation of Accountants, right?
I mean, one thing that we look for is, okay, how is the future of the profession going to look like?
And for sure, artificial intelligence, the new technologies is actually very, very much in the top of our agenda to see, okay, so how should the finance profession look like?
So how should the university studies and the curriculum look like in order to accommodate these new, you know, technologies and these needs that will actually shape the profession so found this?
So yes, I mean, very important.
And if we think in 10 years, look, I mean, the most crucial skills, most probably will be around cyber security, digital collaboration, digital ethics, digital literacy, you know, how do you use these tools and remain being human?
So how do you build on critical thinking, on emotional intelligence, and on social skills?
Thinking about that, if you were giving advice to someone just starting out in finance, or if you were working on re-skilling and upskilling your team, what advice would you give to the kind of the more junior personnel, or really at any level, if they're looking to build their career and keep up with the times, and it doesn't have to just be around AI, but what advice
would you give? Well, I mean, that's quite difficult, right?
I mean, it really depends on each individual, how each individual defines success, okay?
So for me, success meant climbing the ladder and having the opportunity to do what I thought it was necessary to influence and create value.
And in that definition, one key aspect is hard work, but it is important, obviously, to know that many people work hard.
So the true differentiator is not only hard work, but it's also your commitment to continuous growth, inner motivation, and be a little bit better every day, right?
On a personal level, I can say that being bold helped me, especially being a woman, young professionals need to master the courage to speak up, especially in the field of finance, right?
And remember, in finance, we need a team to be able to think out of the box.
So everything that helps you, you know, critical thinking and use your head and not only your hands is super critical, right?
So my advice is clear, work hard, continuous learning, be bold in pursuing what you want, express your aspirations, stay positive.
And look, if things don't always go perfectly, well, that's okay.
Half a long-term aspiration, work hard for it, invest in it, do not despair, continue trying.
This is a marathon. It's not spring.
So yeah, great, great advice.
I've really liked hearing your insights and it's, I don't know, there's something about doing this podcast where when I talk to people who've been in the business as, I don't know, I'm older than dirt, so nobody's been in as long as I have.
I mean, but people who've been doing this a while, it's, I love, it's, there's that phrase preaching to the choir.
It reinforces my beliefs and maybe it's a bit of a positive feedback loop, but I love hearing how people have overcome very similar challenges to what I did or anyone that's been in the business for a while.
And yeah, I think some great experience and guidance there.
And we do, before we wrap all of our shows, I do like to take a moment and, and learn a little bit about who's behind the finance leader character.
So one of the questions we always ask is, what's something that not many people know about you?
And I typically will throw on the caveat of something that we couldn't just find by googling you really quick.
I think not everybody knows that I like kickboxing.
I do kickboxing with my son and that I enjoy karaoke, you know, long karaoke sessions with my family.
That's great. I was trying to figure out how you could combine the karaoke and the kickboxing.
I guess if there were critics in the audience, you could put them in their place.
That's great. And one that it's everybody's favorite question and it's funny.
I think it'll be 20 years from now and we'll still be asking this question, but because I think no matter what other technology is out there, it's going back to Excel.
It's sort of our comfort zone.
And so we always ask, what is your favorite Excel function and why?
Yeah. So I mean, of course, in hardcore functions, I love ifs, some ifs, and V-lookups.
But the more, you know, the one that I really use the most is the pivot tables.
They are super flexible.
They allow for multiple types of analysis, creation of new metrics.
I still use them in the old look on feel.
So I guess for some like me, you know, the new things can't be a little bit too many at once.
But yeah, pivot tables are the ones.
I love pivot tables too.
And I also still go to the old view of them.
And I know people do all kinds of crazy stuff with slicers and, you know, ways to do it.
But it just a lot of times I'm doing pivot tables just from, you know, because I'm not front line FPNA reporting anymore.
If I'm looking at something, I'm trying to find some answer.
So I love going in and, you know, I'll just take my data and start pivoting it and looking at it in different ways so I can get a good summary of it.
So I'm in agreement with you there.
So that's right. How can our listeners connect with you and to learn more about you, especially your involvement with women and AI and your other organizations?
Yeah, I mean, well, I'm in LinkedIn.
So you can, you can follow me there.
I tried to be, you know, to be active and share things that inspire me.
So that would be one one way.
I would recommend, you know, to connect and follow also women in AI in general, but also in the organization in Netherlands.
That will, I mean, it will give a little bit of an idea of what is the progress in raising the women's of tech and AI in women's and minorities.
And finally, obviously, I mean, if you want to be abreast of, you know, what's going on in finance, you know, I mean, follow the international Federation of Accountants website to be, you know, updated and to keep yourself updated on yesterday matters that affect our profession.
All right. Well, thank you, Dotto, for being on the show.
Thank you so much, Glenn.
