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KPI Watchdog

Once automation is running, it needs watching, around the clock. This dashboard compares every reading with its forecast, catches problems in minutes, and fixes or escalates them while your team sleeps.

Simulated readings from a fictional operation, one per simulated minute.

Industry
Watching

An online store, a streaming app and 120 stores

Simulated time02:00
  • Orders per minute

    Normal

    424

    Forecast 376–464

  • Checkout errors

    Normal

    0.86%

    Forecast 0.68–1.04%

  • Page load time

    Normal

    1.87 s

    Forecast 1.65–2.10 s

  • Top sellers in stock

    Normal

    97.6%

    Forecast 96.0–98.3%

  • Video start failures

    Normal

    0.61%

    Forecast 0.49–0.75%

  • Support chats waiting

    Normal

    17

    Forecast 15–24

Incident response

No incidents yet. Cause a problem above, or keep watching: a demo problem starts on its own.

Shift report

Incidents
0
Fixed automatically
0
Escalated to a person
0
Average time to detect
–
Average time to resolve
–

What this means for your business

  • Problems surface in minutes, not when a customer complains or the morning report comes in.
  • Routine failures fix themselves, with a ticket and a record; people are paged only when judgment is needed.
  • Every incident leaves a timeline, so reviews start from facts.

How it works

  • Each metric has a forecast for the time of day. A reading more than three standard deviations from it, in the bad direction, flags the metric as unusual; two in a row open an incident.
  • Each kind of incident has a playbook: diagnose, then apply the known fix or page the right person with the diagnosis attached.
  • An incident closes once readings are back inside the forecast and stay there.
  • The data is simulated, with one reading per simulated minute, from a fictional operation.

Want this working in your operations?

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