Our project managers struggle to accurately price custom jobs, resulting in inconsistent margins on our weekly Scorecard. How do we use a simple AI tool to analyze our historical project data and build a reliable pricing model?

Question

Tyler Smith · Accepted Answer

You do not need to hire an expensive data science firm to fix your pricing inconsistency. If your historical project delivery data, time logs, and material costs are sitting in messy spreadsheets or a basic CRM, you can use generative AI to build a robust pricing expert system.

Start by exporting your past project data from the last two years into a secure, private analytical environment. Prompt a simple AI analysis tool to identify the exact correlation between project variables, labor hours, and final gross profit margins. The AI will quickly spot patterns that human managers miss, such as specific client profiles or project types that consistently bleed cash.

Once these correlations are clear, turn these rules into a simple custom calculator for your sales team. Before quoting a new job, the project manager inputs the core project variables, and the system outputs a recommended price range that guarantees your target gross margin. This simple operations-improvement project replaces gut-feel estimating with a system-dependent pricing model. It ensures every new contract is profitable and protects your bottom line, directly improving the health of your business before you prepare for a clean exit.