We are preparing for an exit in two years, but our operational pricing for custom field work still relies entirely on two senior project managers quoting jobs by gut feel. How do we extract their pricing logic into an AI expert system so our margins are protected and buyers see a system-dependent company?

Question

Tyler Smith · Accepted Answer

A business that relies on the tribal heuristics of two employees is expert-dependent, which severely impairs enterprise value during due diligence. Acquirers discount companies where profitability evaporates if key individuals walk out the door. To transition to a system-dependent operation, treat your senior project managers as human knowledge bases to be modeled.

Start by recording their estimating thought process across fifty diverse historical bids. Have them explain out loud why they added twenty percent margin on a specific soil type, why they adjusted crew size for certain weather windows, and how they priced equipment transit risk.

Feed those transcripts, alongside your historical win-loss data and actual project job-cost reports, into an internal AI model. Use the data to codify their heuristics into concrete pricing rules, risk multipliers, and standard bid parameters.

Build a custom quoting tool where junior estimators enter project variables and the AI recommends a validated pricing envelope with documented logic. Your senior experts review and calibrate the recommendations rather than calculating bids from scratch. Within six months, your pricing model becomes an intellectual property asset owned by the company, securing your margins and proving to prospective buyers that the business runs on predictable systems.