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From Data Rails, this is FP&A.
Welcome to FP&A Today.
I'm your host, Glenn Hopper.
Today, I'm joined by Aurelien Nolfe, Vice President of FP&A and Investor Relations at Lyft.
Aurelien has built his career at the intersection of numbers and narrative, starting in audit and accounting, spending more than 15 years at Electronic Arts in both controllership and FPA leadership roles, and now leading both financial planning and investor relations for one of the most recognized names in mobility.
At Lyft.
He's helped to drive profitability, scale a global FPA team and shape the company's investor story.
We're going to talk about his unique dual role, how finance leaders can bridge data with storytelling, and where FPA is headed in an era of AI and data science.
Aurelien, welcome to the show.
Hi, Glenn.
Great to be here.
Thank you for having me.
So I don't want to dwell on the past, but I was just out in Redwood City on the Electronic Arts Campus, which it was one of the coolest campuses I've been to, seeing all the video game stuff and the big Madden field out there.
And everything.
But I know you started in audit and accounting before moving into FP&A at Electronic Arts.
And now you're leading FP&A and IR at Lyft.
And I guess I was quick to jump into Electronic Arts.
But I want to go back just before that, when you were in audit and accounting.
And walk me through...
What motivated that transition and how your accounting foundation sort of shaped your approach to FPA and what you've done since then.
Yeah, I spent a few years at PwC at the beginning of my career and that's been a great foundation for who I became as a finance professional.
You know Audi told me a lot around.
You know verifying your numbers but, more importantly, thinking about the why behind the numbers.
You know I remember going in the corridors and meeting with all the accounting teams and looking at the inventory, going to the warehouses.
So I've been building pretty deep knowledge of the businesses.
And yeah, that was a great foundation.
But the reason why I switched to first accounting at EA, really love the business.
As you said, it's a great company.
It's pretty awesome.
But then transitioning to FP&A, just because I really love business decisions.
I'm really interested in discussing about the business behind the numbers.
I love storytelling.
That's what really energizes me.
But the accounting is still serving me daily, honestly.
It's making sure all our forecasts are grounded in reality, that all the assumptions are defensible.
And knowing about how a transaction is going to flow through a balance sheet and then your statement of cash flow.
It's super important for FP&A people as well.
So I highly recommend, you know, my son is in college right now.
He's learning about accounting and I really push him to, you know, get started with Audit.
I think it's a great start for any career in finance.
I love hearing about your son.
My kids, neither of them wanted to touch finance, accounting, business.
So my son was a STEM guy in college, and he's applying to PhD programs now.
And my daughter went public policy and political science for her dual major and they, just they couldn't go into business.
So it's, I love hearing about it.
And it's interesting though, I talked to so many accountants, whose children and I was.
You know, I came up through FPA and finance, not the accounting side.
And it seems like on the accounting side, Like their kids pick it up.
It's like, well, this is a pretty practical way to go.
And I see it a lot more in straight accounting than finance that having that accounting basis.
And I guess it's like Warren Buffett said, accounting is the language of business.
So if you speak that, you've got the foundation, whichever direction you ultimately go.
Absolutely.
Yeah.
One thing that I thought was interesting, and maybe this is just my anecdotal view of it.
But once you get to a company, when I've seen people make the move and I know you were at PwC before but once you're at a company, to move people from accounting to finance within the same company seems like it can be a difficult shift because you kind of get stuck in a lane and they say, oh well, he does accounting, so that's kind of the career progression.
Can you walk me through how you decided to make that shift into finance and maybe What lessons within the same company, what lessons from that experience still kind of guide how you work today?
Yeah, I'd say first and foremost, I've been very fortunate.
You know, EA is a very supportive organization.
They support people and career growth.
And so they gave me the opportunity.
I think even when I was on the accounting team at EA, I was very oriented toward the business conversations, like accounting being the translation of what happens in the business.
And so it was kind of a natural thing for me to do.
And the first opportunity I had for within FP&A was corporate FP&A.
And so the corporate FPA team within the brand of FPA is clearly the place where accountants can transition pretty easily, because you need a lot of those skill sets, the foundations, the rigor, the detail orientation to be successful in those roles.
From there I evolved and took more of a business role, but the transition happened pretty naturally there.
But again, picking the company that is going to help you grow your career and not, you know, just grow people in their silo, it made a big difference for me.
And I've been very fortunate to be within that organization for sure.
That's great.
And I love your role now at Lyft.
And we talked about this a lot before the show.
Just because I was.
So at Lyft, you're overseeing both FP&A and IR.
And so I guess, before we talk about there's gotta be.
I feel like there has to be challenges around that.
But from your experience now doing both, what's the value of combining the two functions under a single leader?
Yeah, it's something that happened over time.
When I joined Lyft initially, my focus was on FP&A.
And then over time, I had conversations with our CFO, Erin Brewer.
She's been very supportive of me.
And I wanted to... combine both because it is a great alignment between the two functions.
If you think about the forecast, that's the way we build guidance.
That's the foundation of our guidance that we share externally.
Having both under the same team, it eliminates the telephone game.
I know exactly what's included in the forecast that have been used to create a guidance.
It means also that I think we are able to do a better job at crafting a story that is more authentic.
The ride-share-lift business is very complicated.
There's a lot of data, many different markets, many things happen in the market.
And so being able to really understand the operational drivers not just the numbers, but the business that is behind it makes a big difference.
And then the other way is also true.
I get a lot of feedback from investors.
Oh, my God, we get a lot of feedback from them.
And that feeds directly into the planning process.
It's also a two-way street that I think has been very interesting.
Yeah.
And this is what we talked about mostly before the show.
It feels like that ability to partition your brain.
It has to be, because there's very different messages in being a public company.
Obviously, you've got what you can and can't say to investors and should and shouldn't.
And then what you use for internal management and guidance, they're very different.
Like you said, they are aligned but at the same time sort of the controlling the information and keeping that audience in mind.
So is there...
I might be making too big of a deal out of this, but is there a way that you have to kind of partition your brain when switching between that internal planning with executives and the external communication with the investors?
100%.
I mean, it's getting easier now.
I've been doing that for a longer time, but at the beginning, it was my biggest challenge.
The good news is, it's just a different lens.
It's the same story.
It's the same truth, obviously.
It's just that internally, we are going very granular.
We're looking at scenarios.
Obviously, we know things in advance.
Last week, we announced a very big deal between Lyft and Waymo, which is super exciting.
I've been working on this for months on my FPNA role.
But then investors have been asking about it and I was like, I don't know what you're talking about.
And so, you know, you have to really be able to separate the two.
But the key is consistency.
Right.
And you know, as a company we want to be, we want to be very transparent guide investor, the right way.
And so everything we say is the truth.
It's just a different level of detail.
Yeah.
And that's a very important point.
It's not like you're withholding or telling a different story that has different outcomes.
It's just the type of information.
So that makes complete sense and actually we did talk a lot and this is we talk about it all the time on the show because it's such a it's such a pivotal part of our role that when you're just studying accounting uh, or you know, studying accounting or finance and the kind of the ivory tower of education, you don't really start to realize how important storytelling is with what we do.
Because it seems like oh, we're just learning how to do the numbers and create the ratios and the formulas and everything we're going to track, and this is how we do it.
But being able to get that story across, whether it's internally or on the IR side.
But It's crafting that story and then knowing the key pieces of information to pass on to whichever audience.
So, when you're thinking about, I guess, both executives and investors, how do you decide what metrics matter the most and where to shine that light and where that focus is?
And is it?
I mean, I know there are your key metrics that you track quarter over quarter, but are there factors levers, that drive?
Hey, we're going to really focus on this one area this quarter or that kind of drive that.
Yeah.
It's actually a very important conversation because today companies have so many data points.
We have so many data points every day, and so it's easy to be distracted.
But we try to start with what create it's the value for the company for the business and so in the in the lift example that would be active riders or frequency or you know margin and then Then depending on the audience, you're going to go very deep or not very deep.
Internally, our executive, they need early warning indicators that something is going wrong.
We focus on the same metrics, But that's the reason why we focus on them is that's helping us understanding what's going on in the business.
But for investors, they are using the same metrics.
But for them, it's more about understanding growth and where we're going as a company.
It's an evolving thing, and those metrics are meant to change all the time.
But we need metrics that are both predictive internally and that are going to be meaningful externally.
And usually the operational metrics are much better than just the financial ones because they tell more a story about what's in the underlying business, as opposed to just the financial output which everybody can find in our disclosures.
You talked about the way investors use it for making estimates and forecasts for the company.
And I think one of the things that you've spoken about before and this is such a key shift to make because it's easy and I feel like, as the CFO's role and as the role of finance has evolved over the last couple of decades, it used to be like you said if you're doing financial metrics, it's a lot of lagging sort of PL.
Metrics is what people were looking at.
But the shift and being able to focus on what is going to drive growth going forward.
What are we looking at?
That's more of a leading indicator on where we're headed.
But making that shift, I know, is something you've spoken about before.
And I'm wondering with that in mind, how has that changed, what you're looking at and sort of the whole decision-making process at Lyft?
Pretty much everything.
I mean, it's been a big transformation.
When I think about the way we close our books every month and when the FPA team is driving reporting.
The real estate that is occupied by metrics became bigger and bigger.
It's clearly something that we are now focusing on.
And then at the end of the day, we look at the lagging indicator, which is the P&L.
But when we look at our business, we really focus on the riders, on their frequency, the number of drivers.
We look region by region, we look more and more at rider cohorts and how they behave and how they spend money and how we retain them.
And so when we do that, not only are we able to explain our financials, but we are also able to guide the business and help them make better business decisions.
So it's not just about the bottom line and the profit, but it's more about the business.
Now, it's a very challenging thing to do because historically the fine short systems and everything we do as a team has not been designed, you know, to handle this complexity.
It was really designed, you know, the link between your ERP and your SPNS system, very basic things.
And so we have to integrate more and more of those metrics.
You know forecasting processes, which you know many new tools are now helping people do.
It's so interesting talking to anyone in finance and accounting these days because, if you think about where we were trained, I mean it's obviously our domain expertise in finance and accounting but we're more and more having to become technology experts and we need to understand the software that we're using.
We need to understand a lot more about.
I guess it kind of goes hand in hand with data and analytics.
But once you start looking at data and data governance, you end up kind of leaning into having to be a bit of a data scientist almost, and have those approaches.
I'm wondering...
As you talk about linking systems and when you are looking for those, the main KPIs that you're looking at, the things that are levers that can control the business how much do you feel like you're going outside of sort of the finance domain and having to be a data sleuth or investigator and understand more about analytics maybe than you initially did?
Are you having to lean a lot into that and understanding the data outside of systems and then just looking at data going across systems?
How much focus do you have there?
Yeah, it's a huge focus.
I don't think we are yet there, but honestly, the future of FPA is clearly hybrid between finance, people and data science.
It's clearly at the intersection of both.
Pretty much everything that is driving our business and helps us tell a story is not available in our financial systems.
If you just start with that, you can download all the information from our ERP on our forecasting system.
You're not going to be able to tell a story.
We have to go to the data science teams, to their SQL models and all those things, to be able to to craft a narrative and really understand what's going on.
And so you know, historically it's been a lot of fpna asking questions and then you know this back and forth movement between the two teams.
But clearly the lines are roaring right now and it's clearly the future of FPA.
It's clearly hybrid.
It's key, right?
We need to connect the data And to the business story and then connect this business story to the financial results.
Otherwise, you're just a spreadsheet nerd and you don't know anything about what's going on.
And by the way, FP&A is all about creating connection with the business leaders.
And if you don't know their business well, you are useless to them.
And so being relevant and having a seat at the table really requires us to make that shift.
Yeah, and we're going to, because I talked to all guests about it.
We're going to dig into AI and automation a little bit more later.
But I also think it doesn't matter what industry or profession you're in.
You know, there's the existential crisis right now around AI and automation.
And is it going to take our jobs?
But to the point of what you just said, where we provide value to the business is not in being that spreadsheet jockey.
It's not in, oh, he makes really great formulas.
It is, what do we do with that information?
And I think that as automation gets better and as technology gets better and systems get better and at wrangling this data and that we're not spending all of our time sort of assembling the data and we have it we can lean more into that value.
And you mentioned the storytelling and telling the story, whether it's to investors or internal management.
And I'm wondering with all that information, whatever the state is now where you have to, you still have to spend a lot of time aggregating and consolidating and coalescing data to to get to the numbers you want.
But then you have to shift and be able to convey that to someone in a way that isn't just a wall of numbers and ratios and sort of too much information.
So I'm wondering, how do you connect once you gather all that and have that information?
How do you connect that financial data with narrative to make it resonate with very different audiences between FPA and IR?
Yeah, I mean, it's all about leveraging the data.
I mean, in the FP&A world, we do two things.
We tell the story about what happened last quarter, right?
And so using data and systems to be able to understand what happened in a very granular way, being able to identify outliers like market stage, mode within your mode, mix or things like that where things are going wrong.
Being able to detect that very quickly and easily with data is going to make a whole lot of difference in the way you're going to tell the story about why you missed or beat your quarter.
When we think about how we can use that, when we look forward and when we create forecasts.
Well, the same inputs, the same decisions, the same data points are going to influence the way you shape your forecast.
And so you can just forecast and say, hey, this is what's going to happen.
Or you can use these data points to influence the business and tell them well, if you change this in that market, this is the alternative path and this is the better outcome for the company and for your PL and for your business.
And so, using dashboards that have the right data points, that it is focused on the key metrics, as we discussed earlier, that's going to help surface you know all those issues and all those opportunities and help people coming up with better insights.
Uh, and not just gather data, because one danger for spna is to have, want to own and know everything about everything and then you create, you know, spreadsheets that nobody can use because it's just too much.
And I want to drill into that a little bit more because, as a data nerd, I got to say I'm a little envious of the amount of data you must have access to.
I mean Lyft has to be generating just billions of data points daily.
The quantity and quality of data out there has to be, but to your point it's a lot of.
It can be just noise if it doesn't drive anything that you're looking at.
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Tell me a little bit, what's the makeup of your team between analysts?
Do you have data science people on the team or do you work with the data science group?
What's the internal makeup of your team?
Yeah, so we're a team of roughly 60.
You know, most people are finance people, you know, pure finance people.
But, as I think about our analysts and our senior analysts on the team, they're very curious and very tech-oriented.
They love new technology.
They love data.
They are very interested in the business.
And so they partner with the data science team.
So the data science team is doing all the heavy lifting for us.
I mean, as you said, we have billions of data points every day.
I think about a ride.
We know where you're coming from, when you're going, who you are, you know your spending habits, and then we look at the mode, the price, the demand.
So like it's, it's huge, and so part of the challenges we have as a company is to make sure we really organize this data, make sure it's consistent, it's and it's usable right, and so the team is really it's a team of curious people.
And they keep automating the processes.
And we have a finance hackathon that our CFO got started a couple of quarters ago, which is super fun.
We have all those finance people on the accounting FPA side that are getting together and coming up with new ideas about how they can make us better, more efficient and work in a more automated way.
So I don't have data scientists today on the team, although I think it's coming.
I don't have them today, but I'm fairly sure that if you and I discuss it, in a couple of years we will have more data scientists on the team.
But we have curious people that are embracing those new tech and those new tools.
Some of them are, you know, learning about SQL and, you know, querying.
We have very complex databases and some of them are directly querying them with complex code.
So that's, I think it's the future of FPNA.
Yeah.
And I think you nailed it.
And I've had like a couple of weeks ago, we had two teams.
We had the head of FPA and the head of data science from Wasabi, a big company web hosting company, had them on and talked about how they work together.
And they spoke to the same issue, that curiosity.
And I think that that curiosity is what makes you good at FPA asking why why why, until you dig down to the bottom.
And when you're asking questions like that and you're intellectually curious and you're driven to get the answer, That's going to open up new doors and avenues to you where you're going to figure out how to get the answer.
And maybe it's a stretch and something you haven't done before, whether it's a complex Excel formula or a new way to approach forecasting, or learning about machine learning, or you know.
Whatever the case is that curiosity is going to drive you.
Exactly.
And I've been through a similar revolution of tech disruption 25 years ago.
I mean, I'm that old that when I started my career, people were telling us oh, you're all going to lose your job because of the internet, right?
And look at us, we're still here.
And I think AI is going to be just the same, which is, It's more of a new tool.
We're going to give our teams to be more efficient and do a better job.
It's not something that is replace business acumen.
It's not going to replace business strategy.
And the fact that we need people that are hybrid between finance, data science and business.
You know, advisory that's not going to be replaced by any tool.
It's just going to augment the team capacity.
I want to go down.
I want to get to generative AI, but I'm trying to.
I want to kind of close the loop on this first.
I'm imagining with as much data as you guys have and you talked about, you know, a lot of times it's not the financial metrics that are driving where the company's heading.
It's the operational metrics.
And with the amount of data you have, I would imagine that you guys have probably for years.
Are you using machine learning in your forecasting, not just the traditional statistical models?
So you're using ML to bring in exogenous factors and all these multiple variables and everything in those forecasts.
Yes, all the operational drivers are forecast through a machine learning process, yes.
And is that done?
Is your setup?
Since you don't have data scientists on the team, do you become a customer of the data team that is putting those together?
You work together to sort of build the model?
That's right.
The processes, the RevOps team.
That includes a lot of data scientists.
They are using machine learning to create those very complex forecasts.
And then we translate those data points into a financial forecast.
And then we look at both together and we challenge each other on all the assumptions.
Yeah, that's kind of the perfect setup too.
And you talked earlier about.
A lot of your analysts are learning how to write SQL queries and, I'm sure, dabbling in Python as well.
And with generative AI, everybody's vibe coding now.
If you can't write a SQL query, you could put in the basics of it and have AI write the query for you and save a lot of time.
Which is funny because I always say no one would ever pay me to sit in front of a blinking cursor and write code for a job.
Necessity is kind of the mother of invention.
And through my career, I've had to find ways to get access to systems.
And sometimes that meant writing SQL queries and learning a little bit of Python, or whatever the case was.
But because that wasn't my day job.
It would take me two and a half hours to write a long SQL query to get me what I want, but then it wouldn't run because I left a comma out somewhere or something.
I think about going back then.
If I had generative AI to just QC my code, my query, how much time I would have saved.
And I'm wondering, is anyone on your team right now, are you using generative AI maybe for doing some vibe coding to get some additional kinds of reporting or how are you using generative AI right now across your organization?
Yeah, it's obviously just the beginning, but we are using AI to automate reporting, improve our analysis, so think about variance analysis and then improving our comms.
For example, we use AI to drive some initial variance explanations.
Like you, can dump the entire model and start to get a first pass.
Like I mean honestly, it's not yet something you can just forward to your board of directors, right?
And so it's the beginning, but it's very helpful because it helps you get to this first pass, which saves a lot of time.
And then other things like in on the ir side, lyft has 47 covering banks, the analysts that are covering our stock, and they are producing so many reports very hard for us to digest everything you know.
We now dump all those reports into an AI model and ask all the summaries, the risks, the opportunities highlight the issues, highlight everything we need to know.
And in three minutes you get a very robust AI is really really good with those reports and being extracting the information.
So we use that also for consensus analysis all those models that all those analysts are producing.
You can use that to summarize and show out all the outliers, etc.
For now, it's clearly about augmenting the team.
I'm not reducing the size of the team because of AI.
We're not yet there at all.
And I don't think we'd be there for a very long time.
But clearly, every quarter we see new tools and those tools have new capacities that are helping us, you know, augment and accelerate the way we produce information and insights.
One thing it sounds like you guys have figured out where you know obviously keeping human in the loop, but where you can get benefit.
And I've got to say, I'm right there with you.
One of my favorite uses of generative AI is kind of the.
Even when I was CFO.
The first thing I do, I get the monthly financials and I see the variance analysis and it's all gone through and it's been highlighted with where all those variances are.
But I'm going to go through and do my quick summary of it and make my notes off to the side.
But having generative ai go through and do that first pass and say you know hey, you know revenue's up four percent but cogs are down 16 something's off here or whatever, and you know, highlighting stuff like that and having that first pass, It's pretty amazing how quickly it can do that.
And that's without even tying into pulling in GL data.
And if you've got a system that's in your general ledger can actually tell you oh hey, by the way, we didn't have this big payment.
You know, whatever the variance is, that explains it.
That's where you start seeing real power.
I could see that being a huge time save for IR kind of reporting.
Yeah.
Yeah.
Yeah, it's it's it's clearly I think gonna change the game.
By the way, when I discuss with analysts, they are also mentioning they are using it more and more on their side as well.
I think it's just making everybody more efficient.
Yeah, 100%, 100%.
And I'm sure, obviously with all the reporting requirements and compliance and all that, making sure that the models aren't hallucinating is a very important part when you're doing that.
So you keep a human in the loop.
Are there any things that you've found or any ways to sort of combat or identify when they do hallucinate?
And are you seeing it?
The models getting better just because of whether it's the way the models are built or the way that your team is using them?
Are you, uh, How do you deal with hallucinations when you're dealing with LLMs?
Yeah, I don't think we are seeing too much of that, but that's the big reason why we need the people that are using those tools to be the experts in their field and domain first right.
And so I think it's going to be a challenge for the coming generations is you have to learn the basics, because you have to be able to spot the issue in whatever the AI tool is spitting back at you.
And so that's why people are not going anywhere.
It's because you still need this expertise.
Being able to understand the fine print and adjust whatever the answer is based on your own knowledge and expertise is super key.
It happens to all of us.
Like you ask a question to AI, you know, like sometimes I ask, are you sure?
And you're like, oh, good point.
It's very interesting to see.
Even on the GPT models et cetera, we say it will spot their own mistakes.
But if you don't ask, they won't.
So again, very important to keep experts in the loop for sure.
100%.
Yeah.
It's interesting right now because I really thought I am seeing more companies today that have budget for big implementations of generative AI, you know, integrated into workflows, not just the employees using whichever tools they're using.
And I think the year started.
So last year, people wanted to learn about AI and how it might work.
And then, with all the pressure from leadership and boards and investors OK, we're going to lean into AI now.
And I think they're starting to be budget.
But you're also seeing a lot of studies that some of these projects aren't working.
And you know the kind of the big, massive projects are.
There was that MIT study that there are faults with, you know, but it showed something like 95 of AI projects fail.
And I think It's interesting right now because I think at the senior, at the leadership level, there are kind of two fears that are dictating what happens.
One is we're hearing about competitors, how they're using AI.
There's this FOMO of we better do AI. or we're gonna get left behind.
And then there's the other one that is that fear of hallucination or fear of what could happen to your data and all that.
But then and I think that that all kind of sits in sort of these top down big AI projects.
But then there's the bottom up, where employers are putting the tools in the employee's hands and they're getting more and more comfortable with how to use them.
We're really starting to see efficiencies and maybe it's a software expense.
It's not a big capital investment, sort of labeling those efficiencies and understanding them.
Maybe it's hard to see if there is ROI on a recurring user-based software expense or whatever.
But how have you seen, even on your team, employee usage and adoption?
Are there Do you get feedback?
Are there still some holdouts who are don't want to use AI, or is everybody kind of now starting to see it?
What's the kind of the mix there between excitement and there may be an existential threat?
To have like this is really cool.
It's probably going to take my job.
I don't perceive anyone being scared about it.
I think people are very excited.
What's interesting is everybody's curious and excited.
Many, many people get back to their Excel model five minutes after they started.
You know they are experimenting with AI.
And then they're like oh, now I need to do my real job and I'm back in Excel.
I mean, Excel is very deep in the FP&A culture.
It's actually very surprising to see Even people that are very tech savvy.
They're like oh, don't take my Excel away from me, right.
And so I think it's going to be a journey.
I think the worst thing we could do as leaders is to choose the tools for our teams and then tell them now you're going to use this.
I think that's the recipe for failure.
I mean guilty.
I've done it, i'm seeing it.
Today we have a lot of success with a workflow automation tool and you know the team is adding more and more processes to this tool, leveraging a tool to cut a lot of the processing time.
You know, when we have complex spreadsheets, you have 20 spreadsheets.
You need to put everything in one table.
Now, all of that is being automated as we speak at the list.
And there's a team behind it.
And trust me, they are the people that are doing the work.
They are not the VP coming in and saying, just because their boss put pressure on them on, you have to use AI or you're going to be irrelevant.
That never works, right?
What works is when the team comes up with ideas.
And so I think our challenge as leaders is to empower our teams and foster a culture where You know they're going to try and test things that are not necessarily expensive.
But again, at least we have this finance hackathon.
And honestly, the best ideas we had over the last two years are coming from that specific event.
It's coming from the team themselves.
And I do want to dive into your leadership a little bit more in a second.
But one last question around AI.
And I think I love to hear the way that you guys are using it and the way that you're approaching it.
Because I do...
In my day job, I'm doing implementations of AI to help office the CFO.
I always groan when somebody comes in and their mission with AI.
I understand it's technology, it's automation and it is going to be more efficient.
And if we can find ROI by doing more with fewer people, that's great.
But I always hate it when people lead with We need headcount reductions out of this.
It just feels not right.
And I don't mean from a philosophical standpoint.
I mean, it's a big ask right now if you think a robot is going to fully take over the entirety of someone's job.
Now there are tasks and we could find efficiencies there, but maybe look at your crystal ball right now.
And I think we're both using generative AI in very similar ways, where it's a tool for efficiency in what we're doing right now.
But if you look out in the future, do you think, does it fundamentally reshape?
And I'll say this about FPA and about IR, since you're over both.
But do you think it reshapes?
I know they're going to stick with the Excel, but maybe, whether it's the time to deliver, the amount of delivery, the depth of the analysis, do you think it reshapes how they formulate and deliver insight?
A hundred percent.
I think over time, we're going to cut the processing time in half.
I mean, I'm just making up those numbers, by the way.
I don't have any data to back that up.
But my intuition is over time we're going to cut the processing times for the forecast or the reporting.
We're going to do a better job at detecting patterns earlier and bring that insight to the business teams.
So, yes, I think it's going to impact our work in a very meaningful way.
But I think it's just going to grow the business as opposed to just shrink the teams, right?
The biggest, the most important part of the FP&A job is to sit next to a business leader.
And that's not going to go away, even if we have all the AI tools in the world.
Yeah, 100%.
Well, I do.
Before we start wrapping up, I do want to talk about leadership, because You've been with a couple of great companies at Electronic Arts and at Lyft and leading a large team right now I'm wondering.
That's why I just love finance because you have to have this domain expertise.
You have to have the technical expertise, you have to have the data expertise now more and more, but you also there's still that soft skill.
These are still people we're dealing with.
We have to manage teams.
So I'm wondering Do you have a philosophy on sort of building and developing your FPA organizations, whether it's your approach to how they're set up, to what their sort of training path is?
And I know you mentioned at EA having a great development path and maybe that's carried through and I'm sure Liv does something similarly.
Could you talk a little bit about your team structure and your philosophy around that?
Yeah.
Yeah.
So we operate in a very competitive environment, right?
Hiring SPNA teams in the Bay Area is very challenging, right?
There's a lot of competition, many great companies, compensation can be very high in some companies.
And so, for a company like List, it's all about what we can offer in terms of environment to our team members.
And so when we hire, we really look for curious people that are going to be able to adapt and that are going to surface the problem pretty early.
We are trying to foster a great environment in terms of safety, people feeling safe about raising issues, challenging the business assumptions, having healthy debates with the business.
Then they need to understand the impact of what they are doing.
Asking the same people to prepare the same reports, on and on and on.
Then they don't know what's done with it, doesn't help.
And so we have fairly flat structure here at Lyft.
And so we promote direct access from the analyst to the CFO, trying to make sure everybody has exposure to the management team.
We are also promoting rotations. which is always challenging, but something we really like to do.
This week we had someone from my business FPA team going into my corporate FPA team, and that, to me, is what success looks like, right?
Because when you think about a career, If someone wants to stay in the corporate world, there's maybe five levels right.
And so it's not about being promoted.
It's about learning different things, learning about different parts of the business.
And so that's what we offer at Lyft.
And it's this career path.
And then, you know, our challenge is to give them the right tools.
And so we discussed about AI.
It's part of it.
That's the culture we're trying to foster.
That's great.
And, as you're thinking about the team and developing your team and hiring people, new members to the team, thinking about the skills that we have today.
When you and I were coming up, I used to always joke that the reason I was able to move up in finance was because I was really good at Excel and PowerPoint.
And I didn't realize until later that being good at PowerPoint meant I was able to actually tell the story.
And the Excels do the numbers and PowerPoints tell the story.
And if you'd asked me at the beginning of my career, or even in my first CFO role, what skills people starting out in finance needed to focus on and hone in, it would have been one thing.
And I know we all love Excel, and I don't think Excel's going anywhere.
And having that ability to do what we need to in Excel to get to the numbers is important, but there are new ways that people can get to those numbers now.
I want to ask this.
Maybe this is a two part question.
One is on the technical sort of hard skill side and the other is on the soft skill side.
Other than the basics that they're getting in their core domain expertise education, what skills should people be focusing on to make themselves kind of future-proof and to be prepared for the coming, whatever evolution happens in FPA?
Yeah, so there's things that will never change.
So, as you said, the core, the foundational skills around like, if you're a finance professional, you have to understand accounting.
You have to understand the statements of cash flow.
You have to understand all those things.
Maybe you have to do it, even if you're only focusing on FP&A.
That's very important.
Then the half-skills, well, they depend on your role and what you want to do, but clearly tech, Data manipulation, complex formulas, all of that, super important.
It was important 20 years ago.
It's still important today.
It's just the tools are different.
But this mindset that you're going to leverage technology to do your job is super important.
But then I think when I look at who's successful over a career versus who's not really successful, I mean it's all about communication and business acumen, right.
So being curious. understanding the business, and then being able to tell a story.
You know I've been, you know I've seen so many of my colleagues when I was, you know, more junior.
They were like spreadsheet nerds and they could.
You know those people that are doing all those very complex formula without even looking at their keyboard and you know everything moves on the screen and looks super cool and you're like oh, am I behind?
But then you realize that over time, that's not very important, right?
Because that's what's really important is your ability to connect with the business teams, understand what they are doing, what's important to them, how you can help them grow their business and then how you can communicate those challenges and those opportunities.
Clearly, number one, focus on your communication skills.
How do you interact with leaders?
That's number one.
It's sometimes easy to forget.
When you get very good at Excel, you know what is going on under the hood where you're building all this stuff, but it's the outcome that you're being hired for.
Is not the really cool formula?
It is the insight that you provide from it.
So I do think as, Automation moves on the ability.
It really shifts your focus to what am I doing here?
Why do I work for this company?
What do they want from me?
Being able to provide that value rather than just building them a cool nested if statement or whatever in an Excel sheet.
Yeah.
Okay.
Well, now we're going to get to the part of the show where we bring it home with our two standard questions that we ask everyone.
And the first one is, what is something that not many people know about you?
Something that we couldn't learn from your LinkedIn profile or online presence?
No, that's a good question.
I mean.
So my family knows about it very well because I'm pretty obsessed, but I think in the work environment a little bit less.
But I'm passionate outdoor guy so i do a lot of uh very long you know running uh races 100 up to 100 miles.
So I'm very big about you know going out there in the woods seven, eight hours every Sunday.
And, you know, I'm kind of this weekend wire with my very modest abilities.
But I'm very passionate about pushing myself out there.
So something is very important part of my life.
That's great.
What a great balance too, from being just so focused on finance and all the accounting and being able to get out in the woods and go do a long, long trail run.
That's awesome.
So any events coming up that are on your calendar?
Any ultras?
Yeah, so I just completed my first triathlon ever.
And so that was super awesome in Santa Cruz.
And we have a marathon with my wife in December.
So very excited.
Oh, that's awesome.
Which marathon?
In Sacramento, the California Marathon.
That's great.
That's great.
Well, good luck to you on that.
And are you guys going to run together?
Yes, that's absolutely.
We are training together.
It's pretty awesome.
Very cool, very cool.
Okay, now everybody's favorite question to close this out.
What is your favorite Excel function and why?
Oh, wow.
So before I answer that specific question, let me tell you that my team hates when I'm in their Excel models.
I'm kind of at a point where I'm not using Excel that much, but I mean index match is probably the obvious.
You know, it's kind of a... more sophisticated version of the VLOOKUP.
I had been using that a lot in the earlier part of my career.
But yeah, that's pretty amazing what you can do with Index Match.
A hundred percent.
And I'm really dating myself now because my first CFO role was back in 2007.
I'm VLOOKUP till I die.
But if somebody's relying on me to get into an Excel spreadsheet at this point, there's probably a problem.
They've probably come to the wrong person at this point at this point.
But yeah, i know and i've heard all the wonderful things about index match, but uh, until i have to use it, i just vlookup is one of those things you just quickly do because i was doing it back when i had to.
Well Aurelien, I really enjoyed having you on the show and hearing about Lyft and electronic arts and your experience and just really appreciated all your insights today.
Thank you, Glenn.
Appreciate it.
And I hope we'll discuss again soon.
