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The Brief · Dispatch Nº2: Your Industry's Average Multiple Includes Money-Losing Companies
September 9, 2026·4 min read

The Brief · Dispatch Nº2: Your Industry's Average Multiple Includes Money-Losing Companies

Industry-average EV/EBITDA includes loss-making firms - biotech goes from 15.8x on profitable companies to 51.5x on all of them. Plus what we shipped.

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ValueAlpha Team

Finance & AI Experts

The "average EV/EBITDA multiple" you find for your industry is usually calculated across every company in the sector, profitable or not. Strip out the loss-makers and the number often drops sharply. In biotech, the same sector reads 15.8x on profitable companies and 51.5x once the money-losers are included.

This dispatch is the footnote that belongs under every multiples table, including our own. Last week we published a full reference of business valuation multiples by industry: SDE, EBITDA, and revenue ranges by sector and deal size, with the premium and discount drivers. That guide tells you the working range. This note is about the one question to ask before you trust any published figure: which companies are in the denominator?

The cohort behind the multiple matters more than the sector

Here is the same metric, enterprise value to EBITDA, calculated two ways across six sectors: once on the positive-earnings cohort only, and once across every firm in the sample.

SectorProfitable-firm EV/EBITDAAll-firm EV/EBITDAGapFirms (n)
Biotech / pharma15.8x51.5x+226%496
Subscription SaaS24.5x31.8x+30%309
Wealth management (RIA)38.0x47.1x+24%283
Healthcare devices19.8x23.4x+18%204
Professional services14.3x16.2x+13%155
Environmental & waste services15.6x17.6x+13%53

Source: Damodaran (NYU Stern), January 2025 vintage. n = firms in the sample.

The mechanism is simple arithmetic. These aggregate multiples divide the sector's total enterprise value by the sector's total EBITDA. Add a company with negative EBITDA and it subtracts from the denominator while adding nothing to it, so the ratio goes up. The more loss-makers a sector carries, the more the headline number drifts away from what a profitable business in that sector actually trades at.

That is why biotech is the extreme case at +226%. It is a sector where a large share of the listed companies burn cash by design. But look at the rest of the table: even outside biotech, in mature and profitable sectors, the gap runs 13% to 30%. A professional services firm anchored to 16.2x instead of 14.3x has quietly added about 13% to its expected price before anyone opened a financial statement.

The practical rule for anyone setting an expectation, an LOI range, or a marketing valuation: before you use a published industry multiple, ask which companies are in the denominator. A profitable lower-middle-market business should be compared against profitable companies. If the source does not say, treat the number as an upper bound, not a midpoint. And remember these are public-company benchmarks either way, so a private business still comes down from there for size, owner dependence, and customer concentration. The guide's section on where multiples come from lists the transaction-level sources to use instead of public sector averages.

What we shipped

Three user-facing improvements from the last stretch:

  • Your report saves itself, and keeps every version. The valuation PDF now lands in that company's Data Room automatically on the first run, instead of only when you manually exported it. Every time you save the valuation after that, a new timestamped version is filed alongside the previous ones, so you can see how the number moved over a negotiation instead of overwriting your own history.
  • Quality checks now understand your industry's income statement. Our automatic accounting checks used to test every uploaded statement for a product-style gross margin, which meant a bank, an advisory firm, an insurer, or a biotech got flagged for lines their industry does not report. Those checks now switch off for the sectors where they do not apply. The universal ones, like assets equalling liabilities plus equity, still run on everything.
  • No more asking asset-light businesses for equipment numbers. The data-completeness score used to ding a software or advisory business for missing depreciation and capital expenditure detail, exactly like a factory. Completeness now reflects what your sector actually has on its balance sheet, so an asset-light business is not scored against a checklist written for heavy industry.

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Want to see your own business against the right cohort rather than a headline average? Run a valuation on ValueAlpha and see the comp set behind your range, company by company.

For more on reading multiples correctly, see understanding EBITDA multiples, SDE vs EBITDA, and the valuation gap.

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ValueAlpha Team

Finance & AI Experts

MBA-trained valuation professionals and engineers building the future of private company valuation. We combine institutional finance methodologies with AI to make defensible valuations accessible to every business owner.

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