We are launching a brand-new business unit that uses AI-driven workflows to deliver services, but we have no historical data to set realistic weekly targets on our Scorecard. How do we establish meaningful Scorecard metrics for a startup division without guessing?

Question

Tyler Smith · Accepted Answer

Launching a new business unit requires a different approach to data. When you do not have historical benchmarks, setting arbitrary targets can frustrate your team or lead to false complacency. You need to focus on learning velocity and activity inputs rather than mature output targets.

First, start by tracking activity-based leading indicators. In a new division, focus on inputs that you can control. Track the number of client demos delivered, workflow tests run, or customer feedback loops completed each week.

Second, set short-term, flexible targets. Instead of committing to a target for a full quarter, review and adjust your targets every two to three weeks. This allows you to build a baseline of historical data without locking yourself into unrealistic goals.

Third, measure the time it takes to deliver your service. In an AI-driven model, tracking the time from input to output helps you optimize your workflows.

By focusing on inputs and learning velocity, you can build the baseline data you need to set mature, long-term targets in the future. This keeps your new team focused on execution and helps you scale the division with confidence.