LBO LEGENDS #6: Your favorite data scientist pulled 300k LBO deals. I profile them. Thoma Bravo had to make an appearance. TB's acquisition of Kofax is the stuff of legends. They bought it for 1.5b in 2017. Sold it for a rumored 3b+ in 2022. lets dig into it @OrlandoBravoTB🧵
If you all aren't sensing a theme here, there is (maybe was) massive IRR in carving out legacy techcos from large techcos and improving them. This deal is no exception. In 2017, Thoma Bravo senses a theme:
Robotic Process Automation is going to take off. What exactly is RPA?
Robotic Process Automation is rly just the use of software to automate manual processes. A wide variety of industries have manual processes that need to be automated via code. In 2017, Kofax has RPA footholds in: Finance, Insurance, Healthcare, Logistics, and government.
'Digital Transformation' was really gaining momentum in 2017, and it looks like @OrlandoBravoTB was looking to capitalize. They approach Perceptive Software about a spinoff. They convince Perceptive to spin it off, and acquire the company for 1.5b.
What's next? Thoma bravo uses its WIDE network of companies to push and bundle the RPA solutions. They also make some very interesting add on acquisitions:
Top Image Systems: This one is brilliant. The company makes image / document recognition systems. Easy RPA integration.
Next they buy lexmark: lexmark makes document imaging technology. Give your RPA software access to better images, and eliminate the middle man. You can also bundle these services and create synergies. Another interesting move by @OrlandoBravoTB
Finally, they buy Psigen. Sensing a theme? Another very fancy document / data processing company servicing the financial services industry.
In RPA, garbage in garbage out. There was probably a thesis that they should own the entire 'data value chain'. Doc process -> rpa.
So how'd it turn out? They sold the business to ClearLake and TA for a rumored 3b+. This deal won @thomabravo the DEAL OF THE YEAR from the private equity awards in 2021. Warren Buffet: eat your heart out! Everyone tag @OrlandoBravoTB to get him to chime in.
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M&A / leveraged buyout legends continues 🤝
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Want to see how a data scientist at a private equity fund breaks down a business and helps a portco change their pricing? I'm going to keep things hypothetical but this is closely related to a real story. Watch how you can use analytics to improve your business 🧵🧵🧵
Portco XYZ is a service provider. Each service has a rate associated with it, an amount of money exchanged for the service, and an amount of time associated with the service. Leadership at the fund has a weird feeling the portco could be doing better.
We pull all the pricing agreements, price customer actually paid, and the amount of time the service took to render. We have almost 30,000 transactions to work with; not a small service provider! We pull this data and plot the amount of time it took to render the service + price
PREDICTION/HOT TAKE: every PE fund will have a 'Chief Data Officer' or 'Chief AI Officer' in the next 5 years. The ROI on these roles SHOULD be large. As the head of ai at a large pe fund, I will explain my reasoning 🧵🧵🧵
AI has already permanently changed the way a variety of my portcos function. Each week AI seems to be getting more and more advanced. Some of these applications have very high ROI, and the CAIO will have the ability to go port co by portco and identify low effort high roi apps.
The first task at the fund of a CAIO will be learning more and more about each business. After years, this role will have a solid gut feeling about where/if AI ROI can be derived. Each week these ROIs get easier to achieve. Combo of vendor + custom solutions.
SAM ZELLS INVESTMENT THEMES: Sam's death hit me weirdly hard. Idk why. Followers told me I should pull his last 30 investments and look for themes/thesis. Watch a PE data scientist break down his firm's 6 investment themes (other than real estate). RIP to a GOAT. 🧵
I pulled the last 30 LBO/PE deals Sam did. There's actually some obvious themes here (other than his real estate plays). Sam's funds seem to have invested across: Logistics, Clean Energy, Health Care Infra, Energy and Waste management. Brilliant themes abound. Keep reading.
Logistics and Supply Chain Services (East Coast Warehouse & Distribution, Able Freight Services, Lanter Delivery Systems, The Pasha Group, International Rail Partners, RailUSA): The man loved logistics. We have warehousing, OTR carriers, and railroads.
Sam Zell was a legend. I thought about doing a quick profile on the last 50 deals his fund has done and any themes. I'm not sure if this would be considered content baiting as I'm new to twitter. If I should do it, lmk
alright i'm doing it. stay tuned and retweet for one of the goats!
Just dropped the analysis; feel free to like / retweet gang
@StevenACohen2 has turned bullish! The famed Hedge Funder was quoted as saying he's officially long term bullish on the market thanks to increased efficiency due to ai. Does a head of AI in finance agree? 🧵🧵🧵🧵
ChatGPt has created a generational opportunity. people on this platform think we are over hyping it, but I vehemently disagree. I have gotten chatgpt to do things I didn't think would be possible for 10 years. If you aren't bullish, you simply haven't pushed it hard it enough.
Which things you ask? I can't share its most impressive capabilities because frankly, I want them for myself and the fund I work for. They are truly alpha. Now, how do I see it shaping the economy? In radical ways.
CONSUMER SPENDING FREAK SHOW: Most of the people who follow me are in PE, so I'm going to touch on something that is getting lots of attention and telling two different stories: CONSUMER SPENDING. Interesting data below 🧵🧵🧵
Bloomberg published this head line : "US Retail Sales Increase in Sign of Steady Consumer Spending" On its surface, not so bad. Value of purchases rose 0.4% in first advance since January. However, this data doesn't tell the whole story AT ALL.
Goldman Sach's Scott Feiler (consumer discretionary trader) published a note highlighting some better data: earnings at public cos. Although some of these consumer spending indexes are fine, looking at public companies with exposure to consumers is another important data point.