Delays in time tracking directly affect the relevance of all metrics. Monitoring the quality of time tracking helps to assess the amount of delay.
Measuring time tracking quality can provide answers to the following questions:
- How late are people with their time tracking?
- How many hours have not yet been logged by the team?
There are multiple types of metrics in Metric.ai:
This metric shows how many hours have not yet been logged by the team.
Missing Hours is calculated as Capacity Hours - Logged Hours.
The result can be negative to ensure that hours are appropriately summed up on a weekly/monthly basis (one day could be less 8h, while another is more 8h, but the total is 0 missing for the week or month).
Time Delay (Hours * Days)
This metric helps to monitor the delay with which employees log time.
- If time was logged: Time Delay = Hours * Number of days between when it was logged and for which date it was.
- If time wasn't logged yet: Time Delay = Missing Hours * Number of days between today and when the time is missing.
The Time Delay is summed up on a daily basis. For example: 8h were logged three days late, 4h were never logged, and it's now been ten days since the last time input. This gives a total of 8 * 3 + 4 * 10 = 64 Time Delay (Hours * Days).
Time Delay (Days)
This metric shows how long on average people are late with their time tracking.
Time Delay (Days) is calculated as Time Delay (Hours * Days) / Capacity Hours.
For example, if someone had 320 in Time Delay (Hours * Days) and a 160 capacity, this would give two days of delay.