My managers keep pitching new AI tools with promises of high efficiency, but I am struggling to track their actual bottom-line ROI. How do we measure the financial return of an AI tool using our weekly Scorecard?

Question

Tyler Smith · Accepted Answer

To measure the true financial return of an AI tool, you must look past soft benefits like employee happiness or vague productivity gains. You need hard metrics that show up on your weekly Scorecard. Start by defining the exact problem the AI tool was brought in to solve. If you integrated an AI tool to speed up your project estimating, your Scorecard should track the average hours spent per estimate, the total volume of estimates produced per week, and the bid win rate. If the AI is performing, you should see the hours per estimate drop while the volume of estimates increases, all without a dip in your win rate. Once you prove the tool is saving time, you must track where that saved capacity goes. If your estimators save ten hours a week, that time must be redirected to high value activities, such as following up on open bids or tackling quarterly Rocks. If your labor cost remains flat and your output does not increase, you are simply paying for software theater. We recommend reviewing these metrics during your weekly Level 10 Meeting. If a tool fails to move its target Scorecard metric within ninety days, it is an issue. You must IDS that issue to decide if the tool needs better training, a process change, or immediate cancellation.