Successful businesses are constantly seeking ways to improve. The only way to stay ahead of the competition is by constantly getting better. This means making changes to discover what works best. The only way to know how changes impact the organization is by keeping close tabs on metrics called Key Performance Indicators (KPIs).
KPIs are metrics that provide valuable insight into your organization’s performance. With constant tracking, you can see the immediate, quantifiable impact your decisions have on the organization’s success. The most important KPIs can vary depending on your industry as well as the specific department being analyzed.
The service desk is one of the most vital departments in your organization when it comes to resource management and overall performance. Measuring the efficiency of your service desk is achieved through the use of numerous KPIs. One such KPI that often goes overlooked is percent resolved level 1 capable.
What does Percent Resolved Level 1 Capable mean?
Percent resolved level 1 capable is a record of all the tickets resolved by desktop support that could have been dealt with by the level 1 service desk. In other words, percent resolved level 1 capable tracks every time a ticket is escalated beyond the service desk when it could have (and should have) been resolved by the service desk itself.
The importance of tracking Percent Resolved Level 1 Capable
From the perspective of the ticket, any time a ticket is resolved, the end result is, well, that the ticket has been resolved. From a resource management perspective, who the ticket is resolved by becomes much more important. If a ticket which can be handled by the service desk is being escalated or bypassing the service desk altogether, then you are essentially spending $50 for a $5 cheeseburger.
It’s no secret that lower levels of support are considerably less expensive than higher levels. The service desk (or level 1) is the first line of defense, so to speak. Any issue that makes it past this line should be one that requires the attention of a more experienced (and expensive) support level. Each time a level 1 issue gets escalated beyond level 1 support staff, it’s like you’re paying extra money for the same result.
Percent resolved level 1 capable tracks issues that are slipping by the service desk that should not be while also tracking what is essentially wasted time by desktop support. Any level 1 issue that gets escalated above level 1 support costs far more than it should because you’re paying the support desk to manage and escalate the ticket and then paying level 2 support to deal with the ticket itself.
A low percent resolved level 1 capable percentage is ideal as it demonstrates that resources aren’t being spent frivolously, it shows that your support desk is doing its job, and it tells you that desktop support is utilizing its time on issues that actually require their expertise. Minimizing your percent resolved level 1 capable is a great way to improve efficiency and resource management in your support hierarchy.
How to manage Percent Resolved Level 1 Capable
The first step to managing percent resolved level 1 capable is tracking it. As we discussed, tracking metrics is the only way to know how your changes are impacting performance. The first step to solving any issue is tracking its related KPIs.
Percent resolved level 1 capable is ideally tracked by desktop support. Each time a ticket is closed out by desktop support, instead of the service desk, a note is made indicating as much. Percent resolved level 1 capable is then calculated by dividing the number of tickets resolved by desktop support by the number of those tickets that were level 1 resolvable.
The next step is discovering the reasons why level 1 issues are being resolved by higher-level support staff. Perhaps these issues are being escalated disproportionately by certain service desk agents. Maybe users are bypassing the service desk and submitting level 1 tickets directly to desktop support. Whatever the reason, identifying the root cause will help you understand the problem so you can better devise a solution.
Once you have a good idea of why your percent resolved level 1 capable is so high, you can begin efforts that target those reasons, thus reducing your numbers. For instance, you may need to provide training to specific service desk agents who are the primary culprits behind those escalated tickets.
Or you may need to put some time aside to train your general staff on the proper methods for submitting tickets so they don’t bypass the service desk. Maybe a combination of the two is necessary or some other approach altogether, depending on the results of your analysis.
Putting an emphasis on using a Single Point of Contact (SPOC) model that requires all service requests to be made through the service desk is a great way to improve percent resolved level 1 capable while also enhancing your ability to track all support metrics. Insisting on the creation of tickets for all service requests will help your technicians avoid being ambushed by support requests that haven’t been run up the flagpole correctly—saving them headaches and you money.
The SPOC model will improve your percent resolved level 1 capable score by drastically reducing the number of tickets that bypass the service desk. It will also help ensure that your organization can more accurately track all service metrics by funneling support issues through the official service pipeline. Doing this also has the knock-on effect of making automation much easier to implement and more effective throughout the service ecosystem.
Additional resources
BMC Blogs has many resources on IT service desk metrics and best practices. Browse our Enterprise IT Glossary or see these articles:
- How to Improve Service Desk Performance
- First Contact Resolution (FCR) for Improved Customer Satisfaction
- Mean Time to Resolve (MTTR) as a Service Desk Metric
- Introduction to Critical Incident Response Time (CIRT): A Better Way to Measure Performance
- Creating a Service Desk Code of Conduct
- Introduction to the Enterprise Service Desk
