We are hitting our volume metrics on the scorecard every week, but customer complaints and rework are quietly climbing. How do we build quality safeguards into our weekly data?

Question

Tyler Smith · Accepted Answer

When teams focus solely on volume and speed, quality is often the first casualty. If your operations scorecard only tracks units produced or projects closed, your team will hit those numbers, potentially by cutting corners.

To counteract this, you must pair every volume metric with a corresponding quality safeguard metric. This creates a healthy tension on your scorecard. If you track speed, you must also track accuracy.

Pairing Volume and Quality Metrics

Here are some examples of how to pair metrics effectively:

• Operations Seat: If you track weekly projects completed, pair it with:
• First-time resolution rate, or
• Customer satisfaction score.
• Sales Seat: If you track outbound calls, pair it with:
• Lead-to-opportunity conversion rate to ensure calls aren't just random dialing to hit a target.

This approach ensures that while teams pursue high output, they are simultaneously accountable for the standard of their work. For guidance on selecting the right metrics, consider [how to choose five-fifteen scorecard metrics](/qa/how-to-choose-five-fifteen-scorecard-metrics).

Addressing Quality Issues

If quality issues are rising, you should address them systematically:

1. Drop the Problem to Your Level 10 Meeting Issues List: This makes it a priority for discussion.
2. Use IDS (Identify, Discuss, Solve): This structured problem-solving method helps you identify the root cause of the issue. You might find that your goals are misaligned, forcing employees to choose between hitting their weekly scorecard target and doing the job correctly. Properly balanced scorecard metrics prevent this internal conflict. To manage your Level 10 Meeting effectively, see [how to review our weekly scorecard in under five minutes](/qa/how-to-review-scorecard-under-five-minutes).

The Role of AI in Scorecard Management

While AI can assist significantly with data preparation and tracking, the core of these discussions remains human-centric.

• AI works before the Level 10 Meeting to prep the data.
• AI works after the meeting to capture and track decisions.

The 90 minutes of the meeting itself should remain human-focused, involving your leadership team, the scorecard review, the issues list, and the IDS conversation. To explore more about how technology can support your data efforts, consider [AI in optimizing EOS scorecard metrics and accountability](/qa/ai-in-optimizing-eos-scorecard-metrics-and-accountability).