Service Level Agreements (SLAs) are rules outlining what services an ITSM must provide to its users and within what timeframe.
Let’s say your users expect to address password resets frequently. If you use GenAI-based chatbots, you must define how effectively they should address a user’s problem through an SLA.
So, SLAs define the target for each service and provide the best practices to fulfill its goals.
Unfortunately, while SLAs aim to set clear performance targets, they often fail to capture the true service experience.
There comes how watermelon effects grapple your service desks. Often handed with wrong data, service desks only get data on the service provided and not on how it works on user expectation.
The watermelon effect highlights this gap: SLAs might appear green (meeting targets) on the surface, but the underlying reality is often red (poor service, dissatisfied customers).
This scenario occurs when employees hide the truth about service quality and continue to receive poor service, resulting in misleading metrics.
To enhance employee experience and drive business value, organizations must look beyond SLAs and focus on delivering exceptional service that exceeds expectations.
A simple example of the watermelon SLA effect
Consider an IT service desk reporting 95% SLA compliance. The dashboard looks healthy because most tickets are acknowledged and closed within the agreed time.
But the employee experience may tell a different story.
Metric | What the dashboard shows | What employees may experience |
|---|
SLA compliance | 95% of tickets meet the target. | Issues may still take several interactions to resolve. |
First response time | Responses are delivered within SLA. | The first response may not actually solve the problem. |
Resolution time | Tickets are closed on time. | Some employees may reopen tickets because the issue returns. |
CSAT | Satisfaction is tracked separately. | Low scores can reveal frustration that SLA compliance does not capture. |
This is the watermelon SLA effect: SLA metrics appear green, while the underlying service experience remains red.
Instead of relying only on SLA compliance, IT teams should also monitor measures such as ticket reopen rates, repeat incidents, employee feedback, and time to effective resolution. Improving IT support automation can also help reduce repetitive requests and move employees toward faster, more complete resolutions.
For teams focused on service-level performance, it is also useful to look at how a Generative AI service desk can help achieve internal SLA targets without losing sight of the employee experience.