0

I am trying to make KPI's of a software support organisation performance. We have support requests which are software bugs requiring a new version to be released so the response time towards our customers is quite high (30-45 for most bugs) We have about 30~40 new support requests per month. Most of these are 'Closed' within 45 days. However there are some ongoing requests which can be under investigation for months or even years. The statistics of the support requests have be calculated on a monthly basis

The problem I have is that, because of the few requests have been opened for a year or more, the performance of the many requests which are handled quickly becomes invisible.

The easy solution would be just excluded everything higher than x days, but that would just be ignoring the longer running requests.

Is there any way to calculate the statistics in such a way that would still show the dynamics of the many requests which are handled quickly, but in some way would still show that there are long-running requests which are not yet closed?

I hope this makes some sense, to be honest I have no idea how I would want to represent this data, I'm hoping there is some kind of generally agreed formula to do this in KPI calculation...

Alex
  • 131
  • 1
  • What kind of statistics are you calculating? If it's means of things, then you could simply switch to something more robust e.g. medians, trimmed means etc. – Tim Sep 21 '16 at 14:16
  • Currently it is the average of all requests, from the day they are opened until the day they are closed. I've been thinking about using a median, but had my doubts as it represent one single number in a group of 40-50 support requests... – Alex Sep 21 '16 at 14:24
  • It will represent the number that is exactly "in the middle" - most laypeople would say that it represents the "average" instance. Why is it a problem? – Tim Sep 21 '16 at 14:26

0 Answers0