"In the world of Excel geeks, this will be like the Sports Illustrated swimsuit issue," promises Philadelphia investment banker Andy Greenberg, of the formula he and Graham Frazier, partners in West Conshohocken-based GF Data, have put together after seven years of tracking U.S. mid-market company sales.
Greenberg and Frazier say they have crunched 1,600 transactions by more than 200 investment-banking firms -- enough to separate short-term market trends and "identify clear benchmarks" that inject more science into what practicioners have sometimes claimed is the "art" of pricing what a family business or private firm is worth.
Their joint venture, GF Data, has sent their benchmarks and their reasoning to the Private Equity Professional Digest. Greenberg says he expects their model will be published in that journal next week.
Here's the highlights -- a rule of thumb for evaluating mid-market companies:
- A baseline, average-performing business, with management that can be expected to stay in place after the sale, can expect a sale price of about 5.1X its annual profits (measured as EBITDA: earnings before interest, tax, depreciation and amortization).
- If it's a health-care business or in another hot, high-demand sector, add an additional 1.2X earnings.
- If it's a "high-quality" business, with earnings AND revenue growth averaging 10% or better, add another 0.7X earnings.
- If it's a relatively larger ($100M+ annual sales), well-established business within the mid-market sector, add up to an extra 1X earnings.
- An "X factor" or statistical margin of up to 0.2X earnings that doesn't easily reduce to common factors but may be the added juice needed to get the sellers to the table.
In short, a growing, profitable, relatively large medical-device business may fetch a price up to 9X earnings, while a stable but slow-growing, modestly-profitable machine shop or warehouse-and-trucking hub fetches closer to 5X earnings.
Partner Greenberg, a principal at Fairmount Partners, says the model works well with manufacturing, business-services and distribution firms, as well as healthcare firms -- but he also cautions the model doesn't work so well for "retail, tech and other sectors with funky valuations of their own."