We just signed up for an expensive AI tool to help our estimating team draft project quotes, but we are struggling to measure the direct return on investment on our weekly scorecard. How do we track the financial impact of this software beyond soft time savings?

Question

Tyler Smith · Accepted Answer

Stop measuring soft hours saved and start measuring hard throughput and capacity metrics on your weekly Scorecard. In EOS, your Scorecard must track activity-based leading indicators that directly influence your profit and loss statement. For an estimating team, the soft time savings from using AI should directly translate into a higher volume of completed quotes or a faster turnaround time. To measure the real return on investment, track two specific metrics. First, measure quotes completed per estimator per week. If the AI tool is working, this number should increase significantly without adding headcount. Second, measure quote turnaround time, which directly impacts your close rate and cash flow. Compare these metrics against your historical baseline. If your estimators are completing twice as many quotes in half the time, you have unlocked massive operational leverage. Translate this leverage into hard numbers by calculating the cost per quote. If your cost per quote drops while your close rate remains steady, your AI spend is directly improving your gross margin. If you do not see these hard changes on your Scorecard within ninety days, the tool is shelfware and should be cut.