Basic Ticketing Systems Data Points

Ticketing systems are great... or at least they're necessary to provide some semblance of order to the chaos..  Having one is a big step in helping better understand what your users need, where errors originate, and how to improve your process.  Just collecting a ticket, however, isn't enough, it also needs to collect useful data points.

Exactly what those data points are will differ based on your needs.  A library, for example, will likely need different data than a startup or a big company.  Regardless of size.or industry, however, there are se basics that everyone should be collecting.  Many of these are done automatically, but others may require setup or configuration depending on your system. The fields you choose to collect may also change over time… this is fine! As organizations change and grow their needs for data collecting will also change and grow. At the start though, it’s very useful to collect the following:

Reporter - this is the person who enters the ticket.  This is needed to get more information, share updates and understand where tickets come from.  This can also generally be used to gather more info, such as location, department and other data points related to the reporter that are useful in analysis.

Assignee - this is the person working on the ticket.  This is necessary both to ensure one individual is actually doing the work, buy also useful in tracking utilization and bandwidth with your team. 

Time entered - the time the ticket was created is useful for several reasons, including tracking response times and SLAs and routing tickets.

Time completed - similar to time entered this is useful in tracking your SLAs and how quickly your team can close specific ticket types.
Type of ticket - this can go by different names such as issue type, case type, etc. Regardless of its name this field tracks what 'bucket' your ticket falls into. Exact values vary depending on need, but examples include things like 'access request' 'training' and 'bug report'. This data is very useful identifying trends in your tickets.