📈 How can you monitor Checkout Indicators

What are Checkout Indicators?

Checkout Indicators in Visio provide a consolidated, pattern-oriented view of checkout behavior, based exclusively on reviewed events.

They exist to help track trends, recurrence, and the evolution of operational deviations, allowing you to understand whether checkout control is improving or worsening over time.

The indicators are designed to monitor and guide decisions, not to judge individuals or draw isolated conclusions.
 

Main indicators

• Average events — monthly average of out-of-standard events, used to identify trends and recurrence.
• Total events — the sum of all out-of-standard events identified within a specific period.
• Processed days — days analyzed by AI to generate events.
• Reviewed days — days that were effectively reviewed by operators.

In addition to these general indicators, the reports also allow analysis of:

• Event severity 
• Categories of out-of-standard events
• The relationship between severity, category, and the employees involved

This combination helps identify not only how much is happening, but also the type of deviation, its severity, and where it is concentrated.

It is important to highlight the difference between:

• Total events, which shows everything identified by AI.
• Total reviewed volume, mainly represented by reviewed days, which indicates how much of those events were actually analyzed by the responsible user.

This second point also works as a reference for engagement in the review process, bringing transparency to how Checkout is being used.

Indicators table highlighting:

How to interpret correctly

• There is no absolute “good” or “bad” value.
• The analysis is always relative:
  • Between stores
  • Over time
  • Between event types and categories

Use the indicators to ask:

• Is checkout control improving over time? 
• Is the individual performance of employees evolving, or are deviations recurring?
• Where should I focus my attention first?
• Can I trust the reviewed data?

The reports already help answer some of these questions automatically.

For multi-store users, for example, the reports highlight:

• The stores with the highest average number of events
• The most recurring events in those stores

For single-store operations, the focus is on:

• The most recurring operational deviation during the period

The goal is to direct attention to where there is the greatest impact or repetition.

When to return to event review

Volte ao How to review Checkout Tasks (pending, reviewed and archived) when:

• The data appears incomplete
• Employee assignments are missing
• The indicators do not reflect operational reality

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