The realization of an effective Service Desk should be considered a success. On the other hand, the possibility of increasing efficiency is a necessary benefit for containing infrastructure costs, or for invoicing them to users with a pay-per-use model.
The metrics and KPIs that we already use help us to measure service desk tasks, user satisfaction, and supplier performance. But suppose that we need to improve the effectiveness of a service desk that already has proven efficiency: quick response time, satisfied users, a high SLA rate, and high service levels maintained by external providers.
Even in a less idyllic situation – one more similar to reality – we need to consider an indicator (preferably one already available in EriZone) which is quite often underestimated: AccountedTime.
AccountedTime automatically counts the processing time for each article by summing the time required for each individual action, and keeps that time on the ticket itself. The result is that for every ticket we have the actual working time needed to close the ticket, even when elapsed time between opening and closing a ticket suggests a longer period.
In many circumstances, the only KPI used is the number of open or closed tickets, without any analysis on the effort for each ticket. This value is not sufficient to understand how to improve Service Desk efficiency.
Obviously, AccountedTime will better reflect reality if the Service Desk operator checks the entries and verifies that the daily working time is aligned with the values displayed on the tickets he or she managed. For this reason, EriZone allows the operator to export the working time to Excel or CSV, and if necessary to add or modify data.
If we can analyze the total working time for a ticket (entered either automatically or manually) we can obtain interesting results: we can identify which tickets, services or users are those that require more effort from the Service Desk. This value can help you to modify, if necessary, future contracts with your customers.
This indicator can even anticipate potential bottlenecks and peak periods. In this way, you can decide whether it is necessary to introduce new technologies or procedures to minimize the problem.
By measuring the working time for each ticket, you can find new solutions to continuously improve the efficiency in delivering your services.