Big Deal Small Business: Returns Skew
June 15, 2021 | Issue #21
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Buying an SMB can feel like a get-rich-quick scheme. It can feel like you found a winning lottery ticket in the form of a home services company that is willing to sell for 3x EBITDA. All you have to do is find one deal and close it, and you’re in the money.
After a few months of searching, most folks come to the realization that this is not a winning lottery ticket. Any business that trades for 3x has material issues & risk associated with ownership transfer.
In that vein, I want to talk about returns skews, which is a concept that we think a lot about in private equity.
To avoid burying the lede, my view is that any SMB deal inherently comes with significant downside risk. To offset that downside skew, you need a believable upside story that could drive a life-changing outcome.
This post first shows what downside & upside cases can like look in real numbers (so you can imagine it in real life), then looks at returns skew specifically.
Case Set-Up
Set aside a “base case” outcome for now. This post about returns skew, or the range of potential outcomes.
I’ve created two discrete scenarios to illustrate that range:
Downside Case: Two bad years out the gate (but still able to service debt), some multiple contraction
Upside Case: Growth of 5-15% per year and multiple expansion on exit
For the investor / searcher relationship, I’ve assumed the following:
Investors write ~85% of the equity check and get 30% of the common equity and a 10% pref on their capital
Searcher writes ~15% of the equity check and gets 70% of the common equity but no pref
Searcher salary is included in unlevered cash flow, but that really offsets their personal expenses so I don’t include that in “Searcher Cash Flow”
I also made some very simple tax assumptions.
Using that deal structure, I’ve looked at the searcher’s cash flows in each case. Note I didn’t include a case where the business can’t generate enough cash to cover its debt. I’ll touch on that further below.
This results are below, but you can see the simple model for each of these two cases at this link (images didn’t fit in the email body). If you’re on desktop, I’d suggest opening that page up side by side with this post.
Downside Case
Result: Searcher makes ~$40K/year on top of their salary (link to the model if you missed it above)
This is a very easy to believe case. An immediate 25 to 40% cash flow decline could happen if:
You have any kind of customer concentration
Your Seller managed customer relationships and your business is more re-occurring than recurring (link to my write-up on revenue types)
Competitors smell blood in the water after a newbie takes over and they decide to come after your customers
You have operating leverage in your business, so a very small revenue decline (5-10%) can translate to 25%+ decline in unlevered cash flow
In this scenario, the searcher is still able to service debt and earns their common equity after paying back investors on their pref + 10% accrual. In other words, it’s not a very harsh downside case.
Despite that, they only earn ~$40K per year for the stress of managing an ailing business & 5 years of their life. Once you consider the fact that their salary is likely below their market salary in a W2 role, this ends up looking like a really bad deal for the searcher.
You should look at the model and notice how easily this could tip into zero value for the searcher or even negative value in the form of having to pay down debt with personal funds. Another 0.5x lower on exit and there’s basically no equity value.
Upside Case
Result: Searcher makes $675K/year on top of their salary (link to the model if you missed it above)
On the flip side, this case is also very believable. You identify easy wins in diligence and you go execute on them in Year 2. Some level of operational systemization helps grow margins as well. At exit, the business is larger & growing so commands a higher multiple.
This is a life-changing outcome for a searcher as they clear over $3 million in after-tax proceeds, well in-excess of what most searchers could do with 5 years of their life in just about any other career track.
Disaster Case
The last case that I did not model is a “disaster” case where the searcher can’t service debt. They end up getting hit on their personal guarantee for the debt. I didn’t model it because the model breaks. You don’t have to believe a lot more for that outcome to occur.
For example, assume -35% cash flow in Year 1 and then flat from there. You sell for 3.5x. Even though you can still service debt, the searcher ends up being $182K short on debt balance at exit.
You can imagine a lot worse fairly easily. Imagine another -15% year and now you can’t service your debt. For context, that only takes cash flow from $750K to $415K — a meaningful decline in % terms, but easy to imagine 2-3 customer defections driving that outcome.
Returns Skew
Every deal has a disaster case, downside case, base case, and upside case. In my day job in PE, we try to think about the likelihood of hitting each case, or “returns skew”.
For example, compare these deals’ returns skews (% odds of hitting each case):
Deal A: 5%, 20%, 50%, 25% — normal distribution deal
Deal B: 15%, 20%, 40%, 25% — left side skewed deal
Deal C: 15%, 25%, 20%, 40% — high volatility deal
Deal D: 5%, 20%, 40%, 35% — right side skewed deal
My view is that pretty much all SMB transactions have high left side odds (downside or disaster). These are subscale businesses going through a system shock due to the ownership change.
As a result, I believe every SMB deal falls within Deal B or Deal C in the above list.
You can try to find a deal that has more downside protection through recurring revenue, for example, but in practice these deals have structurally high downside risk due to scale, leverage, and ownership transition.
So let’s assume a high likelihood of downside & disaster cases in general. Given that, the real diligence question becomes what the deal’s base case & upside case odds are.
My conclusion is that an SMB search deal NEEDS to have an truly believable upside path. That can be through growth, future M&A, multiple expansion, etc.
If you only think the base case is high probability but there’s limited upside, you’ve ended up in Deal B, a left side skewed deal. That’s likely not an attractive deal to dedicate the next 5+ years of your life to.
Conclusion
My day job tends to have more Deal A archetypes — stable businesses with scale & moat. We push a Deal A set-up into a Deal D set-up by getting cheap leverage with limited covenants / restrictions.
Small businesses are simply too risky to fall into either camp.
Let’s be eyes wide open about the risk profile of these transactions. They are not a winning lottery ticket. The downside risk is meaningful and ever-present.
I’m not saying we shouldn’t try to minimize downside risk, but I think we also need to look for deals with significant upside legs to help offset the downside skew.
Hope you found this interesting — let me know if you disagree with my perspective also. Hit reply to this email or find me on Twitter.
Thanks,
Guesswork Investing
P.S. I’d always appreciate introductions to potential acquisition targets or brokers (primarily targeting $750K-$1.5M+ of SDE or EBITDA, ideally located in the Northeast, West Coast, or Colorado).