ACatalyst, part 1 of 1
Looking at a company like an owner
Banking asks how to sell a company well. A search fund asks whether you'd want to own it.
Context
In my first year at NYU I interned at ACatalyst, a search fund. A search fund raises money to find one private company, buy it, and then run it.
The problem
The fund was looking for established, profitable small companies, with roughly $1 million to $4 million of EBITDA a year.1 There are a lot of companies like that. Most aren’t for sale, and the ones that are don’t come with clean information. The job was to narrow a long list down to the few worth serious time.
What I did
Screening
I screened more than 50 businesses in that range. About five went far enough to get into real diligence, and I saw the stages a deal moves through: an NDA before any real information changes hands, a CIM2 describing the business, and an LOI setting out the terms of an offer.
Screened
50+
- businesses with $1M to $4M of EBITDA
Diligence
about 5
- NDA signed, CIM reviewed
Up close
1
- a metal products manufacturer, about $8.5M
One deal, up close
The deal I spent the most time on was the potential acquisition of a metal products manufacturer for about $8.5 million. I worked on its financial metrics and market position, and on the inputs that decided whether the numbers held up: demand for steel, swings in iron and other raw material prices, and the assumptions in the three-statement model.
Looking around the deal
To understand the market, I researched more than 15 manufacturing and automotive companies. Later I widened the search to more than 100 potential targets, and helped narrow one area down to towing businesses in Texas as possible bolt-on acquisitions.3
Meetings
I also coordinated more than 40 meetings with more than 50 senior executives.
Five at once
At one point I was working on about five acquisition opportunities at the same time, each with its own pitch book, research and diligence, alongside my classes. I kept it together with a planner and a journal: I broke every deadline into smaller pieces, ranked them, and blocked out separate time for school and for the internship. I got an A in my class too.
The unglamorous part
Not all of it was analysis. A lot of it was data entry, the same fields for company after company. I tried to do it as carefully as the modeling, because everything built on top of it was only as good as those rows.
What I learned
In banking, the question is how to run a deal well. At a search fund, the question was whether you would actually want to own this business, for years, as the person responsible for it.
That question changes what matters. A number that looks fine in a model, like exposure to steel prices, looks different when you imagine being the one who has to absorb it. It was the first time I looked at a company as a possible buyer, not as someone describing it to buyers.
If I could go back to the metal products deal, I would dig further into the customers: how concentrated they were, how often they left, how durable the contracts were, how easily a customer could switch to a competitor, and which end markets they depended on. It came up again at Piermont, where three customers made up about 65% of one company’s revenue.
Footnotes
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EBITDA is earnings before interest, taxes, depreciation and amortization, a rough measure of the cash a business’s operations produce. ↩
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A CIM, or confidential information memorandum, is the document a seller’s adviser prepares to describe the business to potential buyers. ↩
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A bolt-on is a smaller company bought to add to one you already own. ↩