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Correlation Between Continual Improvement Needs & Experience Data

Are the IT service desk's continual improvement efforts missing something vital? Maybe it has many IT-support improvement opportunities, but no one knows the leading cause of the issues that needs attention. The article explains how data can measure outcomes and value and delineate issues, better comprehend the root causes, and help form the required solutions.


What is essential for continual growth success

Continual improvement is necessary for IT service management (ITSM), but it needs more than an ITIL book and a heart full of confidence. Instead, continual improvement requires:


Accurate data: Pause for a moment to consider what you are enhancing at the moment? Are you sure that you want growth? Do you have a grip on data that explains this? Plus, do you have data that delves into the issue to comprehend the root cause(s)? Such that it's transparent as to what needs development and how?



The proper focus: Are you enhancing the right things? Of course, it is from a business perspective and not an IT one. You'd be in a daze at how many times the growth of IT operations, say, can sadly have a damaging effect on enterprise operations and its results.

How experience data helps with your continual improvement

Our clients find that experience measurement guides in answering all these issues. As a result, they no longer find it challenging to juggle customer satisfaction (CSAT) feedback levels of less than 10%. Instead, they now possess end-user experience feedback levels above 20%. With that feedback, a constant real-time view of performance can rely on the results as an accurate view of how IT support aids or hinders your company's employees.


For instance, the aggregate client experience data up to the end of May 2021 showed the top three presenting factors to end-user content to be:


  • Fastness of service

  • Attitude of service personnel

  • Service personnel's expertise



The top three contributing factors to end-user dissatisfaction were:


  1. Their issue remains unsolved despite ticket closure.

  2. Inactivity of service.

  3. Explaining the issue repetitively and rendering information again and again, i.e. being fused between people.


Hence, if you were fathoming end-user experience, you'd possess accurate data on what works and what doesn't. Such that you figure out improvement needs and can prioritize and focus effort. For example, the more profound analysis of the third dissatisfaction above delineates that the end-user perceives an extra one point five hours of lost time each time their ticket is assigned again. It is quite a surprise; the happiness score plunges in response!


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