We are trying to use a regression-based model like the Ankura framework to justify a premium multiple based on our superior operational margins, but the buyer's broker is stuck on local geographic transaction averages. How do we shift the conversation?

Question

Tyler Smith · Accepted Answer

Brokers often rely on lazy, geographic transaction averages because they are easy to calculate and hard to challenge. However, local averages ignore the reality of businesses that run on high-efficiency, AI-driven operating models. If your margins and scalability are far superior to local competitors, you must shift the conversation from simple multiples to a regression-based valuation model.

A regression-based model, like the Ankura framework, uses a broad dataset of comparable public companies to isolate how specific financial metrics impact enterprise value. It proves mathematically that variables like revenue growth, EBITDA margin, and capital efficiency have a predictable, linear relationship with valuation multiples.

To shift the buyer's perspective, present a data-driven model showing that your operational margins put you in the top decile of your industry nationally. Use the principle of substitution to show that a buyer would have to spend far more capital to build a business with your level of operating leverage than to pay your premium multiple.

By grounding your valuation in objective regression data, you take the subjectivity out of the negotiation. You prove that your business is not comparable to the inefficient local shop down the street. It is an institutional-grade asset, and its multiple should reflect its actual financial productivity, not its physical location.