Our weekly Scorecard shows us what happened last week, but we want to use AI to predict our numbers three weeks out. How do we transition from lagging metrics to AI-driven leading indicators?

Question

Tyler Smith · Accepted Answer

Transitioning from lagging metrics to predictive, AI-driven leading indicators is a powerful way to run a proactive business. However, you must not abandon your weekly Scorecard process. The Scorecard is designed to keep your leadership team focused on accountability and activity.

To make this transition, start by identifying the human activities that lead to your desired outcomes. For example, instead of just tracking closed deals, track the number of outbound calls, discovery meetings scheduled, and proposals sent.

Once you have twelve weeks of clean, historical data on these activities, you can plug this data into a predictive AI model. The AI can analyze the patterns and predict your revenue or operational capacity three weeks in advance based on current activity levels.

This prediction should then be added as a forward-looking metric on your weekly Scorecard. The owner of that seat remains fully accountable for the number. If the AI predicts a drop in capacity three weeks out, the seat owner must bring that issue to the leadership team during your Level 10 Meeting to IDS it before it becomes a crisis. This combines the predictive power of AI with the human accountability of your leadership team.