The distinction between throughput gains versus true end to end automation is critical. HOA management and property managment seem like natural fits because they have repetitve workflows and clearer metrics. Accounting being trickier makes sense given the bespoke nature of each client. I'm curious if the Rule of 60 will hold once we see more data on R&D costs scaling across multiple acquisitions, that feels like it could be the real test of whether these are truely transformative or just well executed PE plays.
Another way to think about this is the "buy then build" vs "build then buy" framework as well. In my opinion, the latter if done correctly should be able to deploy software more effectively across the acquired assets to drive both top-line AND bottom-line, rather than buying first and being tasked with full ownership right away.
One piece that has been stuck to me with some of these roll-ups is the ones going into verticals with large TAMs but structurally slower growth. How do some of these Co's expect to drive HSD growth to Low to Medium DD growth organically? What does higher through-put look like in industries that already have some tech involved but gating factor is human deployment (HVAC, plumbing, etc)?
“take it as given that gifted engineers and M&A types have been making real throughput gains. AI-assisted code has increased their own velocity. Internal tooling, data, retrieval has reduced the time spent on parsing deals.”
This has been my experience. Definitely see you point though. Great post Ty.
Thanks for sharing! Does this feel like a compelling strategy to you, or does it seem more like a product of firms like General Catalyst having too much money to deploy, and pivoting into tech-enabled rollups?
I think it's compelling. Incredibly smart people working across the finance and tech stacks.
It's highly vertical dependent in my view.
M&A is a very valuable tool. But utility in a vertical is subject to a ton of factors that should not really be about AI-infused productivity expectations.
The distinction between throughput gains versus true end to end automation is critical. HOA management and property managment seem like natural fits because they have repetitve workflows and clearer metrics. Accounting being trickier makes sense given the bespoke nature of each client. I'm curious if the Rule of 60 will hold once we see more data on R&D costs scaling across multiple acquisitions, that feels like it could be the real test of whether these are truely transformative or just well executed PE plays.
Completely agree
Absolutely agree.
Another way to think about this is the "buy then build" vs "build then buy" framework as well. In my opinion, the latter if done correctly should be able to deploy software more effectively across the acquired assets to drive both top-line AND bottom-line, rather than buying first and being tasked with full ownership right away.
One piece that has been stuck to me with some of these roll-ups is the ones going into verticals with large TAMs but structurally slower growth. How do some of these Co's expect to drive HSD growth to Low to Medium DD growth organically? What does higher through-put look like in industries that already have some tech involved but gating factor is human deployment (HVAC, plumbing, etc)?
+1. The differences are tangible.
Co-sign and great points.
“take it as given that gifted engineers and M&A types have been making real throughput gains. AI-assisted code has increased their own velocity. Internal tooling, data, retrieval has reduced the time spent on parsing deals.”
This has been my experience. Definitely see you point though. Great post Ty.
Thanks for sharing! Does this feel like a compelling strategy to you, or does it seem more like a product of firms like General Catalyst having too much money to deploy, and pivoting into tech-enabled rollups?
I think it's compelling. Incredibly smart people working across the finance and tech stacks.
It's highly vertical dependent in my view.
M&A is a very valuable tool. But utility in a vertical is subject to a ton of factors that should not really be about AI-infused productivity expectations.