Stig
You seem to have the technical extraction ok assuming that
change_time is a reliable indicator of a ticket close event.
You would naturally want to be sure that nobody had changed
the system clock during this period. ;)
However, before the suits get ready to "do" something with
this statistic, allow me to make an impassioned plea:
"Average" is very unlikely to be a valid measure of "answer
times", and unless you first analyze what the data distribution is, using
"average" would be no more reliable than reading chicken
intestines.
You will be VERY sensitive to outliers and abnormal events.
First study the distribution and check for skew and kurtosis.
Other measures less sensitive to skew and variation are:
95- percentile, i.e the time taken for 95% of cases to be handled
The percenage of cases that were solved within a target timeframe.
These are far better measures than "average"
P.S. I wrote an article on this for S-Business magazine that appeaed in the
Q1 edition.
Kind regards,
Matthew H. Loxton
----- Original Message -----
Sent: Friday, June 04, 2004 8:37 AM
Subject: [otrs] Statistics: calculating
avarage answer times for tickets
The suits from
management in my company want statistics showing the avarage time it takes to
handle tickets in the help desk. That is the avarage time span from ticket
creation to the ticket is closed.
I do that by
firing the following sql-statement in the Select Box (Admin
Area):
select
sec_to_time(avg(unix_timestamp(change_time) - unix_timestamp(create_time)))
from ticket
where
unix_timestamp(create_time) > unix_timestamp('2004-05-01
00:00:00')
and
unix_timestamp(create_time) < unix_timestamp('2004-05-31
00:00:00')
and
ticket_state_id = 2
The example shows the avarage answer time for may
2004 (the result is in: hh:mm:ss)
I am intersted in knowing if anybody is dealing with the same kind of
statistics and hearing if there is a better way to retrieve the same
information.
Elsewise I just want to share my endeavour with whoever is
interested.
Regards
Stig
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