What Are Your Odds Of Finding A Company?

And Where Searchers Fail

TLDR: Searching is a volume game. Use the widest possible criteria to increase number of potential companies. Use low cost (time and money) channels like brokered deals, when possible. Searching is a combination of sourcing and closing skills. You get better with reps and by learning from successful searchers.

After understanding how the search fund model works, the immediate next question for most people is: what are my odds of actually buying a company in a 1-2 year time window?

The Stanford Search Fund Primer states that 1 in 3 traditional search funds don’t close an acquisition within 24 months. Note that the study does not include self-funded searches, which are harder to track. Regardless, the risk of not finding a company is large enough to warrant a deeper understanding of what is driving successes and failures.

I think of that question in the framework below, which I will refer to as Search Fund Success Formula for the purpose of this post.

• The Number of Suitable Companies represents the the total number of companies that fit your search criteria (industry, location, size).

• The Sourcing Rate represents the percentage of suitable companies who’s owner is willing to sell and from whom you get enough information to submit a bid within your search timeline.

• The Close Rate represents the percentage of deals you are able to close after to submitting a bid. This reflects aspects like deal structuring, fund raising, diligence and negotiations.

• By multiplying the three factor you can calculate the number of deals you could theoretically close in your search window.

Let’s say your initial Number of Suitable Companies is 1,000, your Sourcing Rate is 5% and your Close Rate is 10%, that means you could theoretically buy 5 companies during your search window. Obviously, you are only buying the first one, but you would have the chance to buy 5. Let’s look at each of the factors.

Number of Suitable Companies: The number of companies that fit your search criteria is the most important predictor of getting a deal done

While you can certainly fail to buy a company by lacking sourcing or closing capabilities, there are plenty of resources, proven approaches and potential mentors that can help you improve in those areas. The combination of the two skills (sourcing and closing) is what makes a good searcher and becoming one is mostly the result of repetitions and learning from other successful searchers.

The number of suitable companies on the other hand is set once you determined your search criteria. There are ~30 million business in the US. For every criteria you apply, the number suitable companies decreases. A common response to that fact is that you can always increase the number of suitable companies by widening your criteria. Many searchers start focused on their favorite industry and city and after failing to find a company, they cast a wider net.

While that is a fine approach for timing / prioritizing your search, it’s not really helpful to determine your actual odds of success. In reality, most searchers have must-haves for size, industry and location beyond which a company is not worth buying. These are the criteria that actually determine the universe of suitable companies and while the number of companies can be quite large depending on how flexible you are, it still represents a finite list of potential companies that you are crossing off throughout your search.

Size is the most limiting criteria. In order to maximize the upside, the ideal range for self-funded searchers is $1.0-$1.5mm EBITDA, while traditional searchers should look for businesses >$3.5mm EBITDA to maximize their upside (I will explain where those numbers come from in the next post comparing the search models). How many of those businesses are there?

While there is no good data on how many companies of each size exist, we can use some approximations to get a general idea. There are roughly 30 million companies in the US, 5 of which are valued at over $1.0tn. Most companies are small and the number of companies of any given size declines as the size of the company increases. Using that framework, we can come up with a rough distribution of companies by Enterprise Value.

Let’s assume half of the companies (15 million) are worth $100k or less and let’s say the number of companies declines by 50% every time enterprise value doubles. Using that distribution we end up with 3 companies in the ~$1.0tn enterprise value bracket, a pretty close match to the 5 companies we see in reality. Just for reference, reducing the decline rate to 40% results in 295 $1tn companies and even a $858tn company, so the 50% number looks about right to me.

This rough distribution gives us ~230k companies in the $1.0-1.5mm EBITDA range (higher self-funded range) compared to only ~60k companies in the $3.0-4.5mm EBITDA range (3x higher self funded range). In other words, the universe of available companies for self-funded searchers is at least 4x larger than the universe of available companies with equivalent upside for traditional searchers.

This discrepancy only increases when you factor in that competition for companies >$2mm EBITDA increases as private equity funds are increasingly buying smaller companies as they try to deploy capital. Additionally, sophistication tends to also increase with company size and off market deals also become less likely as company size increases.

All together, I would estimate that self-funded searchers have at least 5x larger universe of potential companies.

So what does that look like in reality? Say you’re a self-funded searcher and you have a reasonable geographic focus limiting you to 10% of the country (something like a large state CA, TX, FL, or a group of smaller ones) and you only like 10% of the industries (take out the cyclical ones, some overpriced ones like software, etc.). After starting with 230k companies, your Number of Suitable Companies is only 2,300.

Of course there are very wide ranges here depending on your specific criteria, but it’s a good illustration of how quickly the numbers get small for even a seemingly broad criteria like “Texas Home Services”.

Sourcing Rate: It’s easier to find sellers than create them

There are several factors that influence your sourcing rate like, willingness to sell, response rates and ability to access information.

The first hurdle searchers face is that most business that fit their criteria are not for sale. While there are occasional success stories of searchers convincing owners to sell, it’s largely a waste of time.

Obviously the best indication that owners are willing to sell is engaging a broker, which is why self-funded searcher should start there. We started our search by looking at what’s on the market rather than coming up with an industry thesis only to find that none of those businesses were on the market.

Two other questions for sellers that can be helpful in determining how serious a seller are:

1. Have you told your spouse, accountant, etc. about selling?

2. Do you have a number in mind?

If the answer to both is no, they likely have not thought about selling seriously and you might end up wasting time to give them a bid they can brag to their country club buddies about.

Outside of the owners’ willingness to sell, the Sourcing Rate is driven by perceived credibility (website, tear sheet, clarity of pitch), quality of company lists and contact information, quality of the outreach / follow-up program (mass email programs like Gmass, different cadences and mix of phone, email and potentially mail), and perceived trustworthiness (sellers want confidentiality before showing their numbers, always offer to sign an NDA when asking for data). Searchfunder has great posts on how to improve each of these factors.

Close Rate: Tell me the price, I’ll tell you the terms

Negotiations can often appear like a zero-sum game buyers vs. seller. The better approach is “us vs. the deal failing”. One of my professors once told the class he would pay us whatever we asked to buy our laptops, as long as he got to decide the terms. I said, I want a $1bn. He said I’ll pay you $1 a year for a billion years.

The point is by structuring a deal well, you can often create win-win situations. Say a business grew a lot in the past year. The seller wants to get paid off the high number, the buyer wants to avoid paying off a one-time bump. Split the difference in an earn out or a forgivable seller note.

Throughout the closing process these situations come up with the seller, the investors, the bank, etc. Instead of negotiating back and forth on the same point, see if there is a “yes, but” solution.

The Closing Rate is driven by factors like, understanding and management of the deal process, ability to pitch the business to banks / investors, and ability to maintain good relationships (with sellers, bankers, etc.). Similar to the Sourcing Rate, Searchfunder has great posts on how to improve each of these factors as well.

Even for experienced acquisition folks it is common to take several signed LOIs to close a deal. That’s why you have to keep sourcing until the ink is dry.

Conclusion

Given how different searchers and their criteria are, putting a general number on the odds of getting a deal done is a fools game. But the factors outline above can be used as a guidance to understand the three areas that searchers need to be successful in to close a deal.

The tighter the criteria, the better a searcher has to be at sourcing and closing. Given the limited time it’s a good idea to really think about how broad you can make your search. Losing the first year by searching with narrow criteria is a costly mistake.

Lastly, it cannot be understated that luck plays a significant role in searching. One owner picking up the phone one day can make all the difference. But the more deals you source and submit bids one, the more chances you have to get lucky.