If the IT infrastructure is working properly, it doesn’t mean that users are satisfied and productive. Whether they are, and to what extent, can now be technically measured and, above all, bindingly agreed – in Experience Level Agreements, or XLAs for short.
Traditionally, Service Level Agreements (SLAs) are the benchmark for quality criteria of IT services and support. These agreements define the parameters and metrics that are used to measure the quality of an agreed IT service. But the question remains unanswered: Are employees in the digital workplace satisfied with the service they receive?? Is he productive or is he just annoyed and slowed down? A question that is becoming increasingly important for companies, as also shown by a recent Nexthink study conducted by Vanson Bourne.
XLAs change the view of how good IT services are defined.
Because well-functioning IT infrastructures (from the IT point of view) do not automatically mean that trouble-free and efficient work is guaranteed for end users. This is similar to the weather with the measured and perceived temperature: a supposedly pleasant 17 degrees can be quite uncomfortable with wind and drizzle. In terms of the workplace, this would mean, for example, that a network connection can be good enough for office work or viewing videos over the Internet, but at the same time not good enough for moderating a webinar.
How user satisfaction can be tracked?
In order to be able to understand how an IT service or the use of applications and end devices is actually perceived, it is necessary to have systematically collected measurements from the end user as well as the context of the activity currently being performed. Only this information provides IT with tangible starting points for action.
That is, objective measurements of the work environment need to be promptly related to the subjective IT experience from the user’s perspective (called sentiment analyses). Digital experience platforms (DEX) provide these metrics. Capture performance metrics on endpoints at the hardware, application and network levels, ideally combined with dedicated user feedback. From this data, metrics can be derived that are essential for assessing a productive work environment. Recorded not in SLAs, but in XLAs – experience level agreements.
Which XLAs are critical for a company can best be defined based on concrete use cases. From Nexthink’s project experience, it can be said that a changed view of what constitutes successful IT in relation to the digital workplace can simplify this process. This changed view can sometimes be gained by taking the following steps:
1. Clarify the “why” of one’s XLA strategy
On the one hand, this step raises awareness of the problem regarding the difference between technical and perceived quality of digital workplaces. Second, it helps align digital workplace optimization with business goals. A signal of the need for a new XLA strategy is, for example, when the number of tickets in IT support is high, although hardly any anomalies are recorded in the IT backend. The amount of shadow IT and unofficial workarounds in digital workplaces also shows that end users have to deal with too many compromises or. Act on homegrown solutions.
For example, the following objectives can be listed as possible starting points for manifesting the need for a new XLA:
→ Include employee requirements to the maximum extent possible in digitization initiatives.
→ Better consider the impact on digital work environments in cloud-first strategies.
→ Optimize the transition to hybrid working.
→ Improve evaluation and customization of business-critical software.
2. Set concrete goals
This step ensures that XLA measurements will also lead to concrete, demonstrable improvements for end users. That is, deriving and implementing the right measures from XLA and sentiment analyses in correlation with SLAs. This can address requirements such as:
→ Reduce the number and duration of IT disruptions.
→ Reduce the number of IT disruptions caused by end users themselves.
→ Avoiding an increased ticket volume when introducing new software solutions.
→ Align IT support with different levels of IT skills so that employees with lots or little IT experience receive the appropriate support.
→ Implement strict IT security and compliance policies without compromising productivity and ensuring a positive IT experience.
3. Translating goals into correlated SLA-XLA measures and measurements
The more clearly goals are stated, the better they translate into measurable SLA and XLA metrics – three examples:
- Decrease IT support tickets while improving user feedback to accelerate problem resolution and increase self-service usage rates.
- Decrease in IT support tickets due to improved proactive and contextual IT communication with end users (such as via direct on-screen messaging), verified through feedback analytics.
- Decrease in IT support tickets through the use of predictive tools to proactively avoid IT incidents, verified by appropriate telemetry data from endpoints and feedback analytics.
These examples already make it clear that direct, timely and context-related feedback from end users is crucial for evaluating and adjusting measures – because: The number of tickets also decreases when IT support proves to be unhelpful. In addition: If users experience that their feedback has a noticeable effect, they are also prepared to commit themselves to a continuous improvement process – instead of silently resigning or even quitting.
4. Introduction of an XLA culture
Use cases help to understand how and which XLAs need to be measured for specific goals and supported operationally by appropriate SLAs. This leads to a basic understanding of why there is a disconnect between technical parameters and the actual IT experience. As a result, it becomes easier for IT to define and implement ways to achieve an XLA culture that are unique to their organization. This basically addresses four requirements:
Analyze digital workplace as a whole, not just individual services:
The causes of slow applications or program crashes can be cloud services, local servers, network connections or simply overloaded processors on the user’s PC. Much of this is largely predictable and avoidable through appropriate end user experience management.
But the traditional distributed view of the enterprise network leaves too much room for interpretation about where the causes of a poor IT experience might lie and how to fix them. In addition to an integrated analysis of IT events, it therefore makes sense to use predictive tools to prevent outages from the outset or to warn affected users at an early stage, coupled with workaround instructions as a bridging aid during a disruption.
Communication with Relevance:
Instead of emails or cryptic support tickets, users get more out of receiving targeted IT information relevant to them via on-screen pop-up messages in most cases. This starts with the seemingly small things: a warning when disruptions are imminent, a message on the duration of a disruption, a hint on what is best to do in the case of unstable Internet connections or proactive appointment suggestions to have the laptop upgraded at IT support.
Similarly, with feedback issues. The clearer they are for users in the context of their current situation in the digital workplace, the higher the response rates and the more meaningful the information is.
Correlation of technical with sentiment data:
Comparing data from IT performance management with feedback and sentiment data from user surveys shows the extent to which IT’s view is a realistic picture of the actual IT experience in the workplace. Discrepancies are an important starting point for IT to fundamentally eliminate possible causes of impairment. Second, they help interpret patterns of IT events and proactively prevent disruptions.
Differentiate users and their requirements:
There is a wide field between IT-savvy power users and pure users of standard applications – what bores and slows down some overtaxes others. Taking this into account in IT communication, training, determining degrees of freedom in individual system settings, or troubleshooting procedures is essential for a positive IT experience in the workplace. Here, XLA analyses can make an important contribution to providing and supporting digital workplaces according to individual needs.
Conclusion
Supposedly squishy XLAs should be defined into tangible metrics, as derived from endpoint telemetry data and systematic, bidirectional user feedback. Then the metrics also have the necessary significance to ensure a holistic view of digital working environments through a direct correlation with the SLAs from the IT backend. The result is answers to what the quality of technology in the workplace is really like and where priorities should be set to improve the situation.