We want to use our weekly Scorecard to identify where human labor is being wasted on low-value tasks that AI could handle, but our current metrics only track lag outcomes like revenue and client retention. How do we design activity-based Scorecard metrics to spot these automation opportunities?

Question

Tyler Smith · Accepted Answer

To identify automation opportunities, your weekly Scorecard must track leading operational indicators rather than trailing financial results. Prioritize using AI to increase employee productivity as a starting point, because employees represent your largest P&L item and much of their time is spent on repetitive administrative tasks.

To design these metrics, start by breaking down your core workflows into measurable activity counts. For example, instead of tracking total closed support tickets, track the average minutes spent per ticket or the number of manual copy-paste steps required to process an invoice. When you see a metric consistently requiring high hours for low-value outcomes, you have found your target for AI integration.

Once you identify these cumbersome processes, set a quarterly Rock to automate them. Your Scorecard should then track the transition, measuring the reduction in manual processing time and the shift of hours toward high-value strategic work. By forcing your leadership team to look at activity-based efficiency metrics every single week, you create a direct feedback loop that exposes operational drag and highlights exactly where AI can be deployed to protect your margins.