00:00:04.480 Welcome back to another episode of Tech
00:00:06.000 Unhinged, where tech gets human. I’m
00:00:07.680 your host Rabia Javeed, and today we are
00:00:09.440 joined by someone who knows exactly how
00:00:11.679 tech companies scale and how they fail.
00:00:13.679 Joffrey is a director at GPBullhound, a
00:00:16.640 global technology advisory firm that has
00:00:18.720 completed over $50 billion in
00:00:20.960 transactions backing category leaders
00:00:22.800 like Unity, Spotify, Slack, and Karna.
00:00:25.760 He spent the past decade advising
00:00:27.279 European B2B software companies, leading
00:00:29.279 dozens of M&A capital deals with some of
00:00:31.760 the world’s top private equity
00:00:33.680 investors. Today, Joffrey specializes in
00:00:35.600 the office of the CFO space and focuses
00:00:37.760 on advising European tech businesses,
00:00:39.920 offering software for finance teams.
00:00:42.079 Joffrey studied engineering and machine
00:00:44.079 learning before specializing in finance,
00:00:46.000 giving him rare visibility into both the
00:00:48.160 numbers and the technology driving
00:00:50.079 modern innovation. Joffrey, welcome to
00:00:51.840 Tech Unhinged.
00:00:52.719 >> Thanks, Rabia. It’s a pleasure to be
00:00:54.160 here. Well, let’s dive into the ice
00:00:56.160 breakers for our audience and listeners.
00:00:58.239 Joffrey, you’ve studied engineering,
00:00:59.920 finance, and machine learning. Which one
00:01:02.079 actually makes you the most dangerous in
00:01:03.920 the boardroom?
00:01:04.879 >> Yeah. Um, finance for sure. I mean,
00:01:07.119 engineering and machine learning are
00:01:08.799 definitely useful skills to um to
00:01:11.040 understand the product, but my job as an
00:01:13.360 investment banker is really to
00:01:14.960 challenge how the road map shows in the
00:01:16.640 numbers. And that’s where board members
00:01:18.400 are really expecting me to translate um
00:01:21.439 you know narrative and numbers into
00:01:23.680 risk, valuation and opportunities for
00:01:25.600 shareholders. So re really the finance
00:01:27.600 skill set is the is the main one.
00:01:29.119 >> Well, you were definitely the one people
00:01:30.880 have to be sort of beware of in the
00:01:32.880 boardroom.
00:01:33.759 >> Absolutely.
00:01:34.640 >> So Joffrey if spreadsheets disappeared
00:01:36.960 tomorrow would the industry collapse or
00:01:39.280 would CFOs finally have a better sleep?
00:01:42.079 >> Oh my god. Uh, first of all, I would
00:01:44.320 probably uh I would probably not have a
00:01:46.560 better sleep if spreadsheets collapse
00:01:48.159 tomorrow. But I would sa,y and this is
00:01:50.240 probably a general feeling that you know
00:01:52.079 still Excel is the glue that ties a
00:01:54.240 lot of systems together. And so even
00:01:55.920 four years after Excel has been
00:01:57.520 introduced to the market. I I I still
00:02:00.000 think we uh we have that as a
00:02:01.520 foundational foundational tool. So yeah,
00:02:03.759 for sure that would be a bad day for
00:02:05.360 finance people everywhere. Yeah, I can
00:02:07.280 imagine what sort of havoc it’s going
00:02:09.199 to break because even to date not just
00:02:12.080 finance people, but many people out there
00:02:14.480 are reliant on spreadsheets.
00:02:16.319 >> Yeah.
00:02:16.959 >> So Joffrey, if we do a bit of a context
00:02:18.800 setting for our topic in hand today from
00:02:20.879 growth at all costs to efficiency first.
00:02:23.599 What fundamentally changed in tech
00:02:25.520 markets that made capital efficiency the
00:02:28.000 new strategic priority?
00:02:29.680 >> Yeah. Yeah. Beautiful way to get into
00:02:31.760 it. I would say two big things have
00:02:33.519 changed uh for sure in the past
00:02:35.519 decade. The first one is, you know, we
00:02:37.360 we were we were in an environment where
00:02:39.280 money was abundant and capital was
00:02:41.280 relatively accessible, which means that,
00:02:43.120 you know, if you could show enough
00:02:44.480 topline growth, then the market would
00:02:46.480 forgive your inefficiencies. But then
00:02:48.319 interest rates went up and you know, the
00:02:50.959 exit markets cooled down and limited
00:02:53.120 partners who are ultimately the
00:02:54.800 investors into private equity funds
00:02:56.560 started to ask harder questions and you
00:02:59.519 know, the growth of cause dynamic kind
00:03:01.360 of stopped. And after a while and you
00:03:03.360 know what we see today is that growth is
00:03:04.879 no longer looked in isolation but in
00:03:06.800 conjunction with other pieces. So
00:03:08.640 obviously if capital efficiency being
00:03:10.400 being an important one. So that’s that’s
00:03:11.920 probably one big leg of it. And then the
00:03:14.239 second one is for sure the level of
00:03:16.879 scrutiny and the level of sophistication
00:03:19.280 that investors have brought to the
00:03:20.800 table. The best private equity investors
00:03:22.560 have data on thousands of B2B SAS
00:03:24.720 companies. they know what good looks
00:03:26.000 like not only let’s say in in the global
00:03:28.480 remit of B2B SAS but also in your
00:03:30.879 specific subsegment for your customer
00:03:32.959 size you know for your industry if
00:03:34.720 you’re um if you’re vertical and so that
00:03:37.200 means that you’re no longer compared as
00:03:39.280 a company to your last quarter but
00:03:41.680 you’re compared to a cohort of your
00:03:43.920 peers which are actually sitting in your
00:03:45.440 peer group. So you know that makes
00:03:46.879 inefficient growth very very visible and
00:03:49.440 very quickly. And so this is what you
00:03:51.920 know has changed fundamentally and and
00:03:53.840 what has made capital efficiency such an
00:03:55.760 important point. It’s not it’s not about
00:03:57.360 becoming conservative just to be clear.
00:03:59.519 It’s about showing that you have earned
00:04:01.760 the right to keep investing and that
00:04:04.080 shows up in every parts of the business
00:04:05.519 and things as trivial as travel and
00:04:07.439 expense. You see it show up because it’s
00:04:09.200 it’s a true test to the company’s
00:04:10.799 ability to be efficient in managing
00:04:12.400 longtail spend. If people hate the
00:04:14.159 process, they don’t record their
00:04:15.680 expenses or at least they find a route
00:04:17.440 around it and then you’re no longer in
00:04:18.880 control of the data and you know if they
00:04:20.798 love the expense process then they just
00:04:22.880 engage with it. It gives you real-time
00:04:24.400 visibility on the business and you know
00:04:26.400 how you deploy cash. So this is the kind
00:04:28.479 of operational discipline that
00:04:30.160 investors are expecting now.
00:04:31.520 >> So if we dive a bit deeper into that and
00:04:33.440 have a historical perspective on this,
00:04:35.759 you’ve seen multiple market cycles from
00:04:37.759 the investment banking side. What
00:04:39.680 mistakes did companies make in the hyper
00:04:41.919 growth era that are no longer survivable
00:04:44.639 today?
00:04:45.280 >> Yeah, absolutely. I mean, I wouldn’t
00:04:47.120 call them mistakes as much as it was a
00:04:49.040 mindset that no longer applies to
00:04:50.639 everything. And just to be clear as
00:04:52.000 well, the there are pockets of the
00:04:53.520 market where this this hyperrowth
00:04:55.680 mindset still works and and AI driven or
00:04:58.560 AI first companies, probably, you know,
00:05:00.639 probably are are part of that. But let’s
00:05:02.400 say if you zoom out and think about uh
00:05:04.720 hypergrowth era, you know, in that
00:05:06.639 moment, you know, your job was to
00:05:08.639 grab as much market share as you can as
00:05:10.320 quickly as you could. And the idea was
00:05:12.160 or the assumption was the you know,
00:05:14.160 next funding round would always be
00:05:15.520 there. And so when you’re in that world
00:05:17.199 as a founder, as an operator, it’s
00:05:19.360 almost like every problem can be solved,
00:05:21.360 right? Like just hire more people or
00:05:23.600 spend more capital and you’ll just solve
00:05:25.520 the problem. that made sense at the
00:05:27.120 time, but now in a very downto-earth
00:05:29.520 way, those same principles and the way
00:05:31.440 it’s cascaded into the organization, it
00:05:33.840 no longer works, right? And one way that
00:05:35.759 you see it happening at a very, you
00:05:37.680 know, basic level is, for instance, if
00:05:39.520 you’re a manager, your team size is no
00:05:41.360 longer um a proxy for your importance in
00:05:44.000 the firm. And this is a very difficult
00:05:46.160 mindset shift because now it’s it’s
00:05:48.080 almost like the bigger your team, the
00:05:49.600 bigger the scrutiny on what it delivers.
00:05:51.360 And so, you know, if you can’t pivot
00:05:53.280 from the mindset of like, you know,
00:05:54.960 building empires and into let’s make
00:05:57.520 sure we know the impact of every euro
00:05:59.600 spend, you’re definitely, you know,
00:06:01.440 going to have a hard time in this in
00:06:03.199 this more uh of a capital tightening
00:06:05.840 era.
00:06:06.160 >> You worked with finance leaders across
00:06:07.919 Europe and then the US as well. Where do
00:06:10.479 you see Europe leading in capital
00:06:12.400 efficiency and governance and where is
00:06:14.720 it still catching up compared to the US?
00:06:17.039 >> It’s always a contrast that that that’s
00:06:18.880 that’s useful to do. um Europe versus US
00:06:21.600 because it’s true that those two
00:06:23.280 geographies have have very different
00:06:24.960 dynamics. Let me start with Europe. I
00:06:26.880 would say in Europe the bar for
00:06:28.319 governance is is quite high. So you know
00:06:31.120 boards are very formal. Uh you have
00:06:33.120 strong regulatory framework. So as a
00:06:35.120 result you have like audit and controls
00:06:36.960 which are very present in the business.
00:06:38.800 And so and then the next point is also
00:06:41.280 companies are used to operating with
00:06:43.039 less capital compared to their US peers
00:06:44.960 because obviously there’s less capital,
00:06:46.160 less talent available. And so you have
00:06:47.919 to be inherently you’re inherently more
00:06:50.319 constrained than if you were in the
00:06:51.759 US. And so I think um a lot of the
00:06:53.840 businesses that we we advise in Europe
00:06:56.160 have learned to grow with this kind
00:06:58.319 of um mindset that they won’t access the
00:07:00.639 same level of the capital as
00:07:02.479 potentially their US um competitors. And
00:07:05.360 so what the benefit of that is you know
00:07:07.680 they think a lot more of uh they think a
00:07:10.080 lot more about the concept of durable
00:07:12.319 growth how we can make that sustainable
00:07:14.400 over time rather than like how we can
00:07:16.160 make just the next round happen. Now
00:07:17.680 that I’ve said that, I would say that US
00:07:20.319 companies have this feature of, you
00:07:23.039 know, they’ve learned early to use
00:07:24.960 finance as a pivotal tool for decision-
00:07:27.039 making and I’ve seen CFOs of US
00:07:29.360 companies use very sophisticated KPI
00:07:31.759 frameworks and very comfortable making
00:07:34.400 fast calls and you know going after bets
00:07:36.960 uh on the basis of data that’s available
00:07:38.720 even if it’s incomplete and then when
00:07:41.280 you do that you have a better operating
00:07:43.199 cadence right and you’re able to u
00:07:45.680 you’re able to place bets a lot more in
00:07:47.840 a given year then a lot of the US
00:07:49.680 companies also have the discipline to
00:07:51.120 say this is the moment where we cut you
00:07:52.960 know this doesn’t work this is the
00:07:54.160 moment where we cut so this kind of
00:07:55.759 operating cadence is something that
00:07:57.280 European companies are are catching up
00:07:58.960 to now and you know for sure for
00:08:00.800 finance and tech leaders in general it’s
00:08:02.639 it’s a constant learning to
00:08:04.639 kind of be in that uh in that mindset
00:08:06.639 having the constraints in the regulatory
00:08:08.960 framework on one end but also learning
00:08:10.960 to operate with a certain level of in
00:08:13.280 comfort uh to to be at pace in a way
00:08:15.759 >> yeah yeah So if you happen to have a
00:08:18.000 chance, would you move back to the US
00:08:20.720 market or you would want to stick with
00:08:22.400 where you are?
00:08:23.199 >> Definitely would stick in in Europe. I’m
00:08:25.599 sure the US market is exciting. Uh but
00:08:28.800 Europe is probably where uh advisers
00:08:30.960 like like us are are really needed to
00:08:32.799 help you know push the envelope and help
00:08:35.120 transform some of the ambition that we
00:08:37.360 have here. So sticking to Europe for
00:08:39.919 sure.
00:08:40.240 >> We see that historically finance
00:08:42.080 followed innovation. How has this
00:08:44.399 relationship flipped at the moment where
00:08:46.959 finance now is setting the tempo for
00:08:49.200 innovation?
00:08:50.560 >> Yeah. Um I I really like the way you
00:08:53.279 frame that question around you know
00:08:55.440 setting the tempo because I do think
00:08:58.560 that you know a relationship hasn’t
00:09:00.560 flipped as much as as um it seems like
00:09:03.920 it has for one reason which is that you
00:09:06.240 know in tech product always leads.
00:09:08.560 you’re not bunny with spreadsheets for
00:09:10.399 sure. But as you rightly put, it’s um
00:09:13.600 you know the product side now moves a
00:09:15.680 lot more in partnership or in tandem
00:09:17.760 with the finance side. And while the the
00:09:20.800 you know the goals are still very
00:09:22.399 ambitious now the the idea is that the
00:09:24.880 the CFOs are becoming core architects of
00:09:28.080 how we get to those goals, right? And it
00:09:31.040 used to be like finance guys used to
00:09:33.040 show after the fact and say you know
00:09:35.120 it’s the here’s what happened in in the
00:09:37.200 past quarter and now they have to frame
00:09:39.279 the trade-offs of how we make decisions
00:09:41.200 to get to or to deliver that road map
00:09:43.279 because road map needs capital but it
00:09:45.680 also needs clear ROI. In the best
00:09:47.839 companies I’ve worked with I know that
00:09:49.920 CFOs scrutinize very you know very
00:09:52.399 rigorously the impact of an AI
00:09:54.480 investment into for instance, payback. Uh
00:09:57.040 if if that’s if that’s what you’re
00:09:58.640 after. Navan has done a beautiful job
00:10:00.480 when it listed at at you know explaining
00:10:02.480 to investors how it was focusing AI to
00:10:05.279 help increase gross margin by by
00:10:07.279 diminishing the need for support in
00:10:09.600 certain areas of the business. And so
00:10:11.920 if you can have finance that provides
00:10:13.440 that that real time picture of what is
00:10:16.160 the ROI of our investments then you have
00:10:18.160 this real tandem between okay here’s
00:10:20.480 where we putting the effort on the tech
00:10:22.160 side and here are here here’s how it
00:10:23.760 shows up on the finance side and for
00:10:25.839 that you need to shorten this the
00:10:27.200 feedback loop as much as we can I think
00:10:29.440 this is a this is definitely a topic
00:10:30.959 where uh where where there’s a lot to do
00:10:33.760 uh in finance
00:10:35.120 >> yeah and you know we are definitely
00:10:36.640 going to dive into the AI side of the
00:10:38.240 things as well but before that for you
00:10:40.560 know all the leaders listening you
00:10:42.480 today. How can you tell when a company’s
00:10:45.040 financial tools, systems, and processes
00:10:47.680 are actually limiting growth instead of
00:10:49.920 supporting it?
00:10:50.800 >> Yeah, it’s it’s a it’s a great
00:10:52.320 questions. I’ve I’ve seen um dozens of
00:10:54.640 companies uh in in in my career and I I
00:10:57.920 wouldn’t say there is a single rule, but
00:10:59.760 there are definitely some tail tail
00:11:01.200 signs that you know something in the
00:11:02.959 back end should be functioning
00:11:04.480 differently. So, I’m going to give you a
00:11:06.079 couple maybe one is if you have
00:11:07.839 different version of the truth uh in
00:11:09.839 different teams. So if you ask for an AR
00:11:11.760 number and the go to market and the
00:11:13.279 product teams don’t have or let’s say
00:11:14.640 the go to market and the management team
00:11:16.240 don’t have the same number that means
00:11:17.839 that something isn’t working in the back
00:11:19.839 end and more importantly it means that
00:11:22.320 potentially some decision- making is
00:11:24.800 slower or more political than it needs
00:11:26.399 to be you know go to market has a
00:11:27.839 different incentive on on what AR could
00:11:29.839 be versus what the management uh reports
00:11:32.640 or wants to report. So that’s one um
00:11:34.959 another one that’s that’s relatively
00:11:36.720 obvious is the um the level of attrition
00:11:38.800 in the finance team. I mean, you know,
00:11:40.399 if if you have people who have to build
00:11:42.000 spreadsheet forests uh to reconcile your
00:11:45.040 your your numbers at the end of the
00:11:46.480 month, that’s probably isn’t sustainable
00:11:48.399 and you’re going to see that in in in
00:11:50.240 how people are just remaining or not
00:11:52.240 with your uh with your team. And
00:11:53.920 the last one and probably one of the
00:11:56.640 most fundamental one uh that we see very
00:11:59.040 early is how and this ties back to my
00:12:01.519 previous point around shortening the
00:12:02.959 feedback loop. It’s like how long does
00:12:04.720 it take you to close the books? If
00:12:06.160 you’re a mid-market company and you’re
00:12:07.680 it takes you like more than 15 business
00:12:09.440 days to to get a clarity on what the
00:12:11.200 last month was, then probably something
00:12:13.040 isn’t working well in the in the back
00:12:14.800 end and you know you’re not you’re
00:12:16.480 flying a plane with a fogged cockpit
00:12:18.639 essentially and so uh you have modern
00:12:20.800 tools like CPM which is corporate
00:12:22.639 performance management whose job
00:12:24.560 is essentially to consolidate inputs
00:12:27.120 from different sides of the business and
00:12:28.480 making sure you have one central nervous
00:12:30.160 system that everybody’s looking at
00:12:32.000 regardless of whether you’re in finance
00:12:33.600 or not. these tools are no longer an
00:12:35.360 option uh in mid-market companies
00:12:37.120 because you have to know how you’re
00:12:38.959 navigating otherwise for sure you know
00:12:41.279 your tools and your systems are
00:12:43.040 not delivering what it should do for on
00:12:44.959 the finance side of of things. No, I
00:12:46.800 think that makes a lot of sense and you
00:12:48.399 know this are some good takeaways for
00:12:50.000 our listeners as well and uh no wonder a
00:12:52.880 lot of companies are still you know way
00:12:55.279 back into those old trenches and uh they
00:12:58.000 are not even keeping up with the AI.
00:13:00.720 >> So they’re probably in their own bubbles
00:13:03.200 only that it’s going to burst pretty
00:13:04.720 soon because even um the companies who
00:13:07.600 are at the same scale with AI today they
00:13:10.560 can barely catch up because it’s like
00:13:12.480 every day there’s something new in it.
00:13:14.480 >> Absolutely. You bring up a good point.
00:13:16.240 In all fairness, all of those businesses
00:13:18.480 uh that we see are are so busy kind of
00:13:21.040 building and growing that, you know,
00:13:23.040 when we prepare a transaction for
00:13:25.120 them or with them, you know, we arrive
00:13:27.040 at a point that is at some in some way
00:13:29.839 early in their life, regardless of how
00:13:32.000 big they are, whether they’re 50 million
00:13:33.360 of AR or 200 million of AR, they’re
00:13:35.279 still early in their life. And so, not
00:13:37.279 everything can be perfect or has to be
00:13:39.120 perfect. However, as you bring it up,
00:13:41.440 you know, for sure innovation doesn’t
00:13:43.200 happen if you don’t have that financial
00:13:44.720 discipline. So, you you have to find a
00:13:46.800 way so that the trade-off works in a way
00:13:49.040 so that you know, you don’t completely
00:13:50.560 have a a finance function that doesn’t
00:13:52.399 work uh or or is completely, you know,
00:13:54.720 deprived of resources, but at the same
00:13:56.639 time that you’re you’re not lagging
00:13:58.079 from, you know, trying to catch up on
00:13:59.440 the innovation side. It’s a very valid
00:14:01.120 point.
00:14:01.600 >> But also, you know, now Joffrey, when we
00:14:03.680 um dive into the um cost-heavy AI world,
00:14:07.120 we see that AI is expensive. be it
00:14:09.279 infrastructure, data or talent. And we
00:14:11.920 also see that you know Europe was
00:14:14.000, probably one of the first regions to
00:14:15.440 have an AI act and companies to sort of
00:14:17.760 act on right. So how successful are the
00:14:20.720 tech companies deciding where to invest
00:14:24.079 and what to say no to in the times of
00:14:26.240 AI? Yeah, it’s it’s a theme that’s
00:14:28.160 that’s started to come up a lot and
00:14:30.320 we see companies um whether that’s our
00:14:33.120 clients or or companies we we talk to in
00:14:35.120 the market regularly um you know putting
00:14:37.199 together frameworks for how they invest
00:14:39.199 in in AI and try to stick to those
00:14:41.760 frameworks. It’s it’s definitely lots of
00:14:44.079 moving parts. I would say that the magic
00:14:46.240 is probably not in the scoring model or
00:14:48.800 the framework itself. I would say the
00:14:51.040 magic ties into um the ability or at
00:14:54.240 least the discipline to you know revisit
00:14:57.519 those those frameworks or or those cores
00:14:59.760 as real data comes in right this is
00:15:01.920 where again finance is very strategic
00:15:03.760 companies are trying to build now a
00:15:06.079 lot of a lot of businesses that we
00:15:07.440 advise they’re trying to build now what
00:15:09.600 I discussed earlier which is
00:15:10.720 self-updating live forecasts a real-time
00:15:13.120 view of the business it’s very hard to
00:15:14.720 do not a lot of companies are doing it
00:15:16.639 we’re probably like two to five years
00:15:17.920 away to do that but in order to do that
00:15:20.000 you have to pull signals from across
00:15:21.600 your organization and get integrated
00:15:23.519 view of everything that updates uh
00:15:25.760 very frequently if you want to get there
00:15:28.160 it’s not all about AI it’s also a lot
00:15:30.399 about infrastructure organizational
00:15:32.639 design and things like that and so I
00:15:34.959 think successful companies now are the
00:15:36.959 ones that are taking stock of what they
00:15:39.199 need to do first in order to then you
00:15:41.760 know fully put a bet on AI when it comes
00:15:44.399 to their internal operations and you
00:15:46.639 know then let alone what happens on
00:15:48.800 the customer-facing side because that’s
00:15:50.639 that’s again a roadmap decision but at
00:15:53.440 least on the internal side you know the
00:15:55.519 best companies are are taking the time
00:15:57.120 to to figure out what they need to do
00:15:59.199 first in order to leverage that AI
00:16:00.880 revolution tomorrow that’s at least the
00:16:02.880 case in Europe probably US is is one to
00:16:05.120 three years ahead of that um you know to
00:16:07.199 your earlier point around the contrast
00:16:08.720 between the two regions
00:16:09.680 >> Joffrey, when today you evaluate B2B
00:16:12.320 software companies right what metrics
00:16:14.959 matter more than the revenue growth
00:16:16.880 >> yeah I love that question as a as a
00:16:18.320 financeier for sure. Uh, you know,
00:16:20.240 metric is metric, metric, metric, right?
00:16:22.320 I could talk about that all day. But
00:16:23.600 you’re right, growth is still the the
00:16:25.279 driver of value. Uh, the biggest one at
00:16:27.440 least in in B2B SAS. And as we as we
00:16:29.600 hinted to earlier, the next question
00:16:31.360 becomes, you know, how efficient is that
00:16:33.519 growth or how expensive it is. And you
00:16:35.680 have multiple metrics that you that you
00:16:37.440 can look at. Uh, but instead of kind of
00:16:40.240 uh, you know, spreading out uh those
00:16:42.079 metrics, I think there are two that that
00:16:43.680 that come to mind that I think are very
00:16:46.240 relevant for two reasons. is one they’re
00:16:47.839 easy to put together. They don’t require
00:16:49.279 a lot of spreadsheets. And two, they
00:16:50.880 they’re hard to manipulate. So the first
00:16:52.720 one is ARR per FTE. So how big is your
00:16:56.079 company compared to the people that you
00:16:57.759 have? This is very telling because it’s
00:16:59.920 a it’s a very easily available
00:17:02.240 benchmark. We know that companies for
00:17:04.240 instance between 20 and 50 million of AR
00:17:06.480 typically run at uh 150 to 250k per
00:17:10.480 employee of of AR. And so someone like a
00:17:13.119 company operating efficiently would be
00:17:15.119 probably above that 250k threshold. It’s
00:17:18.079 something that’s very easy to evaluate.
00:17:19.760 The other one which probably the most um
00:17:22.559 uh you know finance type listeners of
00:17:24.799 your audience have have probably heard
00:17:27.439 of is is the rule of 40 which is if you
00:17:30.080 add together the growth from the
00:17:32.480 last 12 months and the ABDA from the
00:17:35.039 ABDA margin from the last 12 months. add
00:17:37.120 up two percentages that aren’t really
00:17:39.760 comparable, but that somehow make up a
00:17:42.559 benchmark for how the trade-off between
00:17:44.559 growth and efficiency should happen. And
00:17:46.640 I think those two metrics put together,
00:17:48.720 you know, very available in the market.
00:17:50.240 And so they’re easy to evaluate where a
00:17:52.480 company is trading, whether top quartile
00:17:55.039 or kind of average in in those segments.
00:17:57.039 the metrics that if you perform well in
00:17:59.280 it doesn’t guarantee you a premium
00:18:01.120 outcome when you when you do your next
00:18:02.640 transaction but if you have a bad
00:18:04.480 performance in it it almost always caps
00:18:06.400 it
00:18:06.640 >> and it always caps up with the revenue
00:18:08.799 growth as well if you’ve got these
00:18:10.799 right. Yes, absolutely. Growth growth
00:18:13.200 will be the premium driver for sure. But
00:18:14.960 then those two if you look at them uh
00:18:17.360 individually or conjunct with
00:18:19.520 revenue growth will then be the next
00:18:20.960 indicator of okay how good is that
00:18:23.200 company at growing and you have extreme
00:18:25.120 examples of that like we have companies
00:18:27.200 we know we have companies in the rule of
00:18:28.799 40 that are growing 100% but burning 60%
00:18:31.200 of their of their revenues and you know
00:18:33.120 this is the growth at all cost model and
00:18:34.880 you have companies maybe you know
00:18:36.480 growing 20% but doing 20% a BDA margin
00:18:40.000 and delivering that year after year
00:18:41.760 those are two different models and
00:18:43.520 two different ways to evaluate them but
00:18:45.120 they tell you a lot about how growth is
00:18:47.360 being prioritized over efficiency
00:18:49.280 in the business.
00:18:50.240 >> Absolutely. So Joffrey, if we speak
00:18:52.480 about workforce realignment driven by AI
00:18:55.760 automation in particular, we see that
00:18:57.200 it’s reshaping how technology companies
00:18:59.919 manage labor costs alongside financial
00:19:02.400 discipline. So how is AIdriven workforce
00:19:04.640 realignment influencing cost efficiency
00:19:06.960 strategies within tech companies at the
00:19:09.200 moment?
00:19:09.679 >> Yeah, very interesting. Let me tell you
00:19:11.360 what I see from my perspective which is
00:19:13.200 that in Europe we’re probably at the
00:19:15.280 beginning of that curve and the the
00:19:17.360 leaders uh you know CEOs and founders
00:19:19.760 that I speak to are more in a more you
00:19:21.679 know no higher no fire mode right now.
00:19:23.679 They are trying to understand first by
00:19:25.679 experimenting in pockets where you know
00:19:28.240 changes really lies and where they need
00:19:30.320 to essentially put more pressure or put
00:19:32.559 more effort and in the finance function
00:19:34.720 more specifically you see pilots around
00:19:36.880 you know how consolidation and reporting
00:19:38.799 and and forecasting but it’s still at a
00:19:40.960 very small scale and we think that over
00:19:44.000 time the mindset will be let’s see what
00:19:45.840 this does to quality and then let’s
00:19:47.840 restructure teams to make sure that we
00:19:49.360 empower them to no longer do the tasks
00:19:51.600 that should be automated and actually
00:19:53.280 let them operate the business. So my
00:19:55.360 conviction is that we we won’t see like
00:19:57.280 waves of firing but rather waves of
00:19:59.760 reorganizations of like how the teams
00:20:02.320 operate inside the business and how they
00:20:05.120 communicate with the other parts of the
00:20:06.559 business as well.
00:20:07.200 >> All right, Joffrey. So now if we move
00:20:09.039 towards the innovation and how
00:20:10.960 discipline, financial discipline is
00:20:12.720 meeting it. Let’s talk about how some
00:20:14.799 leaders worry discipline kills
00:20:16.720 creativity and there’s a lot of debate
00:20:18.480 around that. In your view, how do high
00:20:20.799 performing companies balance risktaking
00:20:23.840 with financial rigor?
00:20:25.200 >> To your point around discipline kills
00:20:26.799 creativity, in my experience, the
00:20:28.640 opposite is true. Um, the most
00:20:30.320 disciplined founders I’ve I’ve worked
00:20:31.919 with are also the ones who who took the
00:20:34.159 boldest bets. And the difference is that
00:20:36.720 They knew exactly what the
00:20:38.240 parimeter of the bet was um and and the
00:20:40.880 stage they wanted to go and set for it.
00:20:42.799 how that translated in what I’ve seen is
00:20:45.360 um some of the best companies are really
00:20:47.120 good at separating the sandbox from
00:20:49.360 the core. So what is what is your
00:20:51.280 experiments that you’re you’re really
00:20:53.120 trying to figure out whether they can
00:20:54.880 create long-term value versus what is it
00:20:57.039 that you cannot compromise on where you
00:20:59.200 have to scrutinize your business in
00:21:00.880 every in every sense of the way and that
00:21:03.440 discipline on the core is what earns
00:21:05.840 them the right to run experiments
00:21:07.600 elsewhere in the business. So I think
00:21:09.200 that’s that’s really how they get to
00:21:10.640 that that balance between financial
00:21:12.480 discipline but also uh risk-taking.
00:21:14.799 >> And based on all the tech companies you
00:21:16.640 worked with during M&A and investment
00:21:18.799 deals, what cultural patterns be it
00:21:21.280 behaviors, mindsets or leadership styles
00:21:24.000 you see differentiate resilient
00:21:26.159 operators from those who stall when
00:21:28.480 capital tightens?
00:21:29.840 >> Yeah, I I don’t have like a single
00:21:31.760 answer for that. I would say that um as
00:21:34.400 long as culture works and is deeply
00:21:36.159 rooted uh as long as it’s root deeply
00:21:39.120 rooted but also works for performance
00:21:41.360 then then I think you have a you have a
00:21:43.200 system that can manage regardless
00:21:45.039 of the values themselves. But one
00:21:47.760 combination that I’ve I’ve learned to
00:21:50.080 observe and like over the years is
00:21:52.480 is a is a combination of having brutal
00:21:55.600 honesty uh not just between ourselves
00:21:58.240 but also you know everyone with
00:22:00.799 themselves and at the same time
00:22:02.799 empowering talent. So let me let me kind
00:22:05.360 of break that down. If I think about
00:22:07.200 companies that are brutally honest, they
00:22:09.120 don’t hide behind vanity metrics. They
00:22:11.039 publish the numbers, and you know they’ll
00:22:13.520 they’ll look at eroding cohort
00:22:15.120 profitability. They’ll take stock of you
00:22:17.039 know growing segment level churn and
00:22:18.720 they’ll don’t they won’t treat that as
00:22:20.320 bad information or bad news. They’ll
00:22:22.000 treat that as actual information and
00:22:25.120 they won’t move into blame. They will
00:22:26.960 move into solution. That’s point number
00:22:28.640 one. And to move into solution I find
00:22:30.960 that if you if you have a culture that
00:22:32.559 really empowers people at the local
00:22:34.320 level to make decisions raise the hand
00:22:37.520 you know really operate within your
00:22:39.440 business then that creates a good soil
00:22:41.360 to then move into the solution you know
00:22:43.840 into the solution process. And I find
00:22:45.760 that combination when I’ve seen it to be
00:22:47.360 to be very powerful.
00:22:48.640 >> So another quote that goes by Joffrey,
00:22:51.039 finance leaders are becoming the new
00:22:53.120 product leaders. Would you agree
00:22:55.520 strongly agree or is that
00:22:57.760 oversimplifying this entire shift?
00:22:59.840 >> I would say no. It’s it’s a nice it’s a
00:23:02.720 nice phrase to coin. I wouldn’t be the
00:23:04.960 one coining it. I would say um in the
00:23:07.760 sense that I think where the statement
00:23:09.679 is right is that what’s changing is that
00:23:12.400 CFOs are are becoming the co-designer of
00:23:14.640 the strategy. They’re not the product
00:23:16.960 like they’re not the driver but you know
00:23:18.960 they’re no longer just the reporter of
00:23:20.480 outcomes either and because they have
00:23:22.080 this bird’s eye view on the business
00:23:23.760 they can definitely shape the agenda in
00:23:25.600 a very powerful way but for sure they’re
00:23:27.600 not the ones uh you know defining that
00:23:29.919 agenda themselves. So my my position
00:23:32.559 would probably disagree
00:23:34.799 overall but agree to the to the spirit
00:23:37.919 of of where the question is is headed.
00:23:40.400 >> Well, you were you were agreeing to
00:23:42.720 disagree.
00:23:43.440 >> I think where the where the question
00:23:45.360 makes sense is uh is you know finance
00:23:47.840 now has has a say in road map where it
00:23:50.400 didn’t have one in you know five years
00:23:52.559 ago I would say at least in most
00:23:54.080 companies. So
00:23:54.799 >> yeah because you know you see from an
00:23:56.559 outsider’s perspective it took me sort
00:23:58.880 of a while to understand that how
00:24:01.200 important finance departments are you
00:24:03.600 know they might be the people with the
00:24:05.679 most introvertish personality but they
00:24:08.320 are the big guns. I um I heard this this
00:24:10.720 beautiful quote um a while ago which was
00:24:13.600 you know 30 years ago finance had the
00:24:15.760 power and now it feels like data has the
00:24:18.159 power but what happened in the meantime
00:24:20.400 is that data ended up as you know
00:24:22.720 flowing a lot through finance. So it
00:24:24.960 ended up having this circle back to the
00:24:26.799 finance team who ultimately unbeknownst
00:24:29.039 to them became again the the some
00:24:31.440 somehow the central nervous system of
00:24:33.120 the organization. you know moving
00:24:34.720 towards the last theme of our podcast
00:24:37.360 which is you know um what is it that we
00:24:40.000 look forward to and what is winning in
00:24:42.640 the next decade ahead of us. So AI is
00:24:45.279 automating decisions humans used to make
00:24:47.600 slowly or rather at their own pace but
00:24:50.320 what does this mean for the speed and
00:24:52.400 structure of financial leadership?
00:24:54.559 Basically to me the change is like
00:24:56.799 finance team is no longer going to be
00:24:58.880 expected to produce answers and more and
00:25:01.120 more to design systems at least for the
00:25:03.360 next 5 years and you know if you think
00:25:05.840 about it yes for sure until now and and
00:25:08.000 and probably for for a couple more years
00:25:10.080 finance team spend a lot of time
00:25:11.600 assembling data trying to make sense of
00:25:13.520 it reconciling it and hopefully with AI
00:25:15.760 and and better tooling you know you can
00:25:17.600 automate a lot of those workflows to
00:25:19.440 accelerate your decision-m process and
00:25:21.600 the bottleneck will move from can we get
00:25:23.840 the numbers which is still the you know
00:25:26.000 bottleneck for for many companies today
00:25:27.600 and and rightly so to you know do we
00:25:30.159 trust the numbers and can we act fast
00:25:32.000 enough based on that and and to me
00:25:33.600 that’s the that’s the frontier that a
00:25:35.440 lot of companies will have to to cross
00:25:37.360 uh in the next two three years
00:25:38.640 >> if you had to pick Joffrey what will
00:25:40.720 separate these survivors from the
00:25:42.559 winners in tech space over the next 5
00:25:45.440 years
00:25:46.320 >> the winners will be the ones who um are
00:25:49.120 able to rearchitect themselves around
00:25:51.600 this new AI parading just like just like
00:25:53.760 It happened when software kind of
00:25:55.520 exploded and started eating the
00:25:57.120 world. And you know what that means and
00:25:58.880 and this will also kind of lean into
00:26:01.600 this theme of of organizational
00:26:03.279 design I mentioned earlier is how can
00:26:05.360 you have the proper team structure? What
00:26:07.120 is your data strategy? What are the
00:26:09.039 operating rules? What are the workflows
00:26:10.799 that you need at a very fundamental
00:26:12.480 level to to operate with very clean data
00:26:16.080 and foundations in order to take
00:26:18.480 advantage of this very big wave that’s
00:26:20.320 coming. That means for many companies
00:26:22.320 that they’ll need to learn to
00:26:24.080 capture more signals uh to capture them
00:26:26.480 faster uh to organize around I would say
00:26:29.600 you know being able to create this
00:26:31.279 instant feedback loop so that they can
00:26:33.520 allocate capital at the greatest
00:26:35.039 velocity possible because ultimately
00:26:37.200 this is what’s going to be a surviving
00:26:39.039 game against your competitors for every
00:26:41.200 point of margin your competitor can win
00:26:43.600 you know against you because they’re
00:26:44.960 more efficient is a point on pricing or
00:26:47.200 a point on go to market velocity or a
00:26:48.960 point on something else that they will
00:26:50.159 be able to take and so slowly create an
00:26:52.159 advantage uh for you.
00:26:54.159 >> So um Joffrey, moving towards our last
00:26:56.559 question of the podcast. If you had to
00:26:58.559 leave our listeners with one piece of
00:27:00.240 advice or a hard-earned lesson, what
00:27:03.120 would it be and why?
00:27:04.480 >> That’s a tough question, but I guess a
00:27:06.159 great way to finish. Look, I say this,
00:27:07.919 if you’re a CEO or a CFO right now, you
00:27:10.720 probably have a 6 to 12 month breathing
00:27:12.799 space right now uh that you can use and
00:27:16.880 you shouldn’t waste it. And perhaps the
00:27:20.559 best use of it is to not push another
00:27:22.480 round of AI projects or cosmetic cost
00:27:24.799 cutting and to quite rebuild the engine
00:27:27.600 from the inside that you need to
00:27:30.080 leverage the you know the data tools and
00:27:32.400 the AI tools of tomorrow. So you want to
00:27:34.880 make sure you project what your future
00:27:36.640 state for data architecture is going to
00:27:38.400 be. What your key metrics that are going
00:27:40.480 to be the different line drivers of your
00:27:42.320 P&L are uh what you want your decision-m
00:27:44.799 cadence to be and then get the financial
00:27:47.200 and operational plumbing to a point
00:27:49.279 where you can actually see what’s going
00:27:51.440 on close to real time in your business.
00:27:53.840 And I would say in two to three years
00:27:56.399 this will not be something that’s nice
00:27:58.960 to have. It will be more and more
00:28:00.320 something that you must have. And so I
00:28:03.120 would say the lesson from the past
00:28:05.120 few cycles is don’t try to force your
00:28:07.520 organization into a level of discipline
00:28:09.520 or innovation that it’s not built
00:28:11.679 for or architect for yet. Build the
00:28:13.919 foundations first and then you know you
00:28:16.480 you’re going to be in a you’re going to
00:28:18.000 have an edge against your peers when the
00:28:19.440 when the AI boom unfolds.
00:28:21.120 >> Well well what a beautiful way to um you
00:28:23.600 know end this conversation on such an
00:28:25.919 important note. Joffrey, thank you so
00:28:28.159 much for such a grounded and insightful
00:28:30.399 conversation. Thank you, Rabbi. It was a
00:28:32.559 pleasure to discuss.
00:28:33.520 >> Thanks a lot. And to everyone listening,
00:28:35.279 thanks for joining us on Tech Unhinged.
00:28:36.960 And we’ll see you next time.
