Improving in TMT
I'm now a senior associate in M&A (about to be VP soon). I'm at a generalist boutique, but have been largely exposed to TMT deals for the most part.
Despite having completed ~5 deals in the space, I still feel a constant sense of imposter sydrome and it forever feels like I'm trying to catch up on stuff, particularly in 2 aspects:
1) The way people model subscription software has differed completely across each project/client. There seems to be very little standardization to how you go about building a subscription software model. Some shortcut the revenue build (e.g., using ARR-to-revenue % conversion ratio for projections as opposed to modeling out the detail), some shortcut the deferred revenue piece (e.g., assuming a scaling % of revenue), etc. With the rise of consumption models, this has gotten even more complicated. Is there a good resource to keep up with all this?
2) Technology is evolving wayyyyy too quickly. I feel like I barely caught up on the concepts of cloud computing, infrastructure-as-a-service, hybrid cloud, containers, etc. before the GenAI craze came about, and now there's a whole new world to learn. How do you all keep up with these trends?
Can anyone relate? Any advice?
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We need more posts like this instead of ranking banks. Following
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Wait to you hear about everything as a service …
That's exactly what I'm talking about. It used to be straightforward. You either buy a perpetual license or you buy a subscription. Upfront or ratable recognition. That's all fine.
But now you have dinosaur companies like NetApp offering "everything-as-a-service" where their storage arrays are given to customers under a "managed" subscription (so that NetApp still owns the hardware). Fine, recognize some portion as product revenue, then the rest ratably. That's annoyingly complex, but not that bad.
But now there's CONSUMPTION-based "everything-as-a-service", where the revenue isn't even predictable because the amount of revenue is based on how much the customer actually uses.
ARR used to just be annualized recurring revenue. Now you have companies defining it as "annual revenue run-rate" where they pack in completely non-subscription revenue for a quarter, multiply it by 4, and call that ARR. It's infuriating and honestly, should be fucking illegal.
It's just so overly complicated.
RPO / cRPO is the way to go for forward-looking revenue forecasts
These are good insights and agree that many of these "SaaS" companies are increasingly taking aggressive views on ARR. Depending on the situation, it can potentially make sense to model based on a by-customer basis for the top parties, given your context on idiosyncratic contract structure. Of course, none of this is perfect from even the basic definition of ARR to the subsequent impact on deferred revenue, etc. but we should hope that the models we create are directionally correct.
Exactly mate!
I’m currently working on consumption-based XASS in manufacturing and infrastructure … nightmare lol
Exactly mate!
I’m currently working on consumption-based XASS in manufacturing and infrastructure … nightmare lol
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Not specialist tech coverage but lots of exposure and happy to share what works for me.
For #1, I'm a bit detached from the modeling now but I found the SaaS CFO to be quite informative (https://www.thesaascfo.com/). Outside of the modeling bit, helpful to look at things on a unit economics basis
For #2, it's tricky because there are just so many verticals, sub verticals, and the like I find it hard to keep up. Tech / SaaS / enterprise software is so catchall. Even with a broader trend like GenAI, the applications, impact and time horizons vary between the verticals. Plus there is always a flavor of the month/year - ecomm / edtech type things during the pandemic as an example. To your point, the broader industry is constantly evolving so there really isn't a specific piece of literature I think that doesn't age.
Things I track / read in no specific order - obviously M&A / capital flow (who's buying what and why, who's funding what), earnings transcripts / conference presentations for specific sector bellwethers, S1s, Stratechery, Gartner when I'm getting up to speed on a vertical, buyside/sellside literature (Bessemer is a good one, Mary Meeker, Meritech are a few).
Honestly, most of my intel just comes from catching up with people in industry.
I know we have a few tech PE guys here, hoping they chime in. Always looking to sharpen my focus.
Thank you sir. That's very helpful. I actually think I signed up for the SaaS CFO newsletter at one point...Good to hear it validated by someone legit. I'll give it another look.
I totally agree on the unit economics basis, but that's where I find information to be the most lacking. The challenge is not so much in deals when we're under NDA and have the client's model with us, but it's more when trying to model outside in with public information. Companies will disclose so many KPIs (ARR, ACV, TCV, RPO, cRPO, billings, bookings, net retention, net expansion, renewal rate, etc.), but 99% of the time it's not sufficient to fully understand and model the unit economics (e.g., we have ARR and new customer growth, but what was the net expansion?) Not to mention companies often have multiple licensing models at the same time for differing terms.
And thanks for the list of what you track / read. I'll definitely follow some of those.
As an engineer, I can answer number 2. The underlying principles around a lot of tech are the same. I’m not saying all tech is the same but if look at what the main purpose of the tech you’re using is doing as opposed to what it looks like or its features, you start to see similarities in things or where things are going. Most things tend to be innovations and not inventions meaning they build upon existing concepts and not create anything entirely new. You just have to build upon that to get a better understanding.
As far as trends goes, read tech news like Tech Crunch, Wired, The Verge, Gizmodo, ArsTechnica and go to tech conferences to stay up to date. You can even read some of the publications from the Big 4 firms and a few other IBs that post monthly industry reports.
Totally, and it's not very hard to understand the actual tech itself at a high-level.
Where it gets really frustrating is trying to figure out what a company does and how it's differentiated from other similar companies at the product level, especially because of the buzzword hell that exists in TMT. Without an engineering background, it takes ages and ages to figure out these distinctions.
I'll give you an example: OpenText and Informatica. They actually do completely different things and are not comparable companies, but if you take a look at their website, as a non-technical person, all you see is, "Oh, they both do some kind of cloud software that helps customers manage their data and information."
So you then look deeper at Informatica, and you see, "Oh wait, they talk a lot about data integration. Maybe that's a separate thing from what OpenText does. Let me check that out."
You figure out it is, in fact, separate. You then look into data integration and you see, "Got it, so data integration is about techniques to get data from source into a central repository."
Now here's the annoying part: Your MD brings up another company, Confluent. You look at your website, and now you're befuddled, "Wait, this company doesn't mention data integration at all, but they do 'data streaming'....which is also getting data from source to central repository. What gives?"
This then just becomes a frustrating rabbit hole where you can't even really confirm if your understanding at the end is correct or not.
That’s a fair point. If you’re trying to get down to the granular level like that you might want to talk to a representative at the company itself to see what sets them apart and their ability to integrate with other software applications. Haven’t been in IB so I wouldn’t know if you guys are allowed to do that. Generally speaking, when you have an engineer on your team, I think most the value add comes from telling whether an idea is bullshit or not but I can see what you’re saying. In an instance like the example you’re using, I’d want to see some sort of spec doc or white paper to get an understanding of how the actual data is being processed and transmitted to get an understanding of what they’re actually doing instead of being tied up in jargon. That might be on their individual websites or you might have to ask a rep for it.
precisely. literally impossible to differentiate and fully understand infra software companies. but i think what's even sadder is like the fact that I don't believe MDs know what they're talking about too. its just a bunch of bs overlapped with bs but at least its probably 60% directionally correct. You can't convince me that MDs truly know what a company like Redhat or Hashicorp do - and i honestly think that this is so sad to think about
as someone with a strong interest in tech and tech businesses, i've found that if you can get in touch with someone at the company (an engineer with a good amount of experience working at that company, a pm, someone who works in finance), they would explain and answer your questions. if not, you can post (almost anonymously if you'd like) a question on some forum like reddit, stack overflow (i think) or something, and if that community has enough activity, someone will give you some answer to go on from. i also think that it helps to go on sites like crunchbase, or to examine the founder/company leader's background, or the things that either the company or founder writes about.
the keywords on a company's landing page might be there just for SEO purposes, or because they've ran A/B tests and realized those words and descriptions of the business, although they may not be the best way to describe the business, usually result in more conversations or whatever targeted KPI. i feel like you have to look outside of the company's landing page, maybe posts from their blog that are really old or really new, or speak to its workers, or long term customers to understand what the business does.
i have to prep for something, but after the evening i'll begin looking into the specific companies you've mentioned
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On point 1 I feel like software is one of the most straightforward P&Ls you can actually have. ARR bridges by product and they convert to revenue on some seasonality assumption and DR is just the difference between EOP ARR and subscription revenues. Compared to a media conglomerate where you're forecasting CPM, impressions, retrans etc. I feel like with software there's only so many ways to skin a cat with SaaS businesses. (I guess occasionally you have some payments)
For traditional software, yes. But nowadays, that is only one of the models, specifically for SaaS software. However, you have new models like infrastructure hardware companies (HPE, NetApp, Pure, etc.) that provide hardware as-a-service, which has different rules around recognition. A portion gets upfront recognized as product revenue and the rest get recognized as subscription revenue. This gets further confounded by the emergence of "consumption-based" subscriptions, where the revenue recognition is actually dependent on how much compute/storage/etc. the customer consumes.
Leaving that aside, the projection method you describe is certainly one way I've seen it. I've also had clients model at the contract level by detailed term length, with # of customers and mix of 1-,2-,3- year terms as model drivers. I've had clients drive the model off of salespeople and ARR per salesperson assuming a productivity ramp. I've had clients straight up say x% of ARR converts to revenue each year and leave it at that. There are just so many ways of doing this that I wish there was a standardized resource that would lay these methodologies out.
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I don’t think many people fully understand the concept of containerization, kubernetes and infra software well. You literally need to be in the weeds and using these tools to really know how they function. Yes my friends that use docker know how to use stuff like that but they don’t know the macro stuff. But what you can gain is just the macro view - when r they used, why are they useful, and how the space is evolving and yes sometimes it’s even hard to focus on the macro when you don’t understand the fundamentals.
Something for GenAI, now everyone sees AI and just calls it an LLM but little do people know the differentiation between AI, ML, LLMs and how they even work and use many of the words interchangeably. Half the YC companies say they’re innovating with AI while most indoubtedly are just creating a wrapper and using the API. Idk why people care about LLMs hallucinating that much cus I honestly think people hallucinate even more - many times people just say things that are semantically adjacent but not really fully true but we all accept it. What I think investors and advisors r good at is really the macro - I know it sounds stupid but it’s sometimes a gift to not be caught up in the weeds.
Very insightful. Are there any ressources to get better at “macro”? I feel like so much content online is geared towards understanding how something functions vs where it fits in the grand scheme of things.
honestly it's just read more and believe in yourself. VC newsletters are great - subscribe to like 30 off them and read whatever interests you. try to start forming your own perspective and just know that most people in the industry also probably have no idea what they're talking about
I agree with what you said, but I think most people can grasp why things like cloud, containers, GenAI, etc. are useful. You can list use cases forever.
The challenging part is differentiating between products and companies and understanding what specific use case each one fulfills.
Admittedly, public companies are not too hard. There’s a plethora of equity research, investor day presentations, etc. for you to get a sense of their differentiation.
But trying to evaluate private companies is very tough sometimes (for tasks like helping a client investigate a potential acquisition target, coming up with potential buyers, talking about the implications of a competitor getting acquired, etc.)
Like I felt like I was going crazy trying to figure out the difference between Rancher, Portainer, and Platform9 for example lol.
Or even with public companies at times. For example, why Nutanix, IBM, Super Micro, Dell, HPE all sell servers and storage but trade vastly differently from one another. The financials definitely don’t tell the whole story. I do understand it now, but it was incredibly challenging trying to get to the answer AND trying to put it into a nice succinct presentation to my client (without embarrassing myself by accidentally misrepresenting some technical nuance.)
I didn’t realize this was that big of a problem. This gives me more ammo for my answer to how my experience as an engineer would be useful as an investment banker. Thanks.
On #2: Gain a general idea of the high level applications and infrastructure components and typical architecture for some b2c and b2b systems. Understand the terms used to identify each layer/ component, and how they interact with each other. Talk to an IT friend to help you reinforce your understanding. This gives you a limited working but strong foundation.
Next, as and when new terms/ technologies show up on your radar, though we know it rarely happens in IT, update your glossary.
Whatever be the next new flashy thing, remember it provides a b2c or b2b service, whether new or an improvement of an existing service, and the way it does it is by assembling (or developing) software products that line up with the general architecture principles you learned by acting on para one.
Lastly, don't go by page one of these IT service providers. It's meaningless grandiloquence. What their product actually does is less substantive than what the first page claims. An example, that I make up, is: Dropbox can claim "connecting humanity" when their core service is about file swapping.
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You lot struggling with tech? Wait till you see how fucked healthcare is
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