Unlocking hidden insights from helpdesk tickets

When we launched Audiem in 2022, the first datasets weprocessed came almost exclusively from employee surveys. That made sense, because Audiem emerged from the workplace consultancy we offered at the time, and a need to analyse free-text survey responses quickly and accurately.

Since then, we’ve broadened our horizons, helping clients tap into many other sources of employee feedback. We think of this as an organisation’s ‘data ecosystem’ – all the different opportunities available to learn more about workplace experience. One source that consistently sparks interest (and often amazes people!) is good old helpdesk data.

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FM and IT helpdesk tickets are arguably one of the most underutilised sources of workplace insight. Medium-sized and large organisations generate thousands of these tickets, each capturing issues that matter to employees - and that sometimes frustrate or hinder them.

Helpdesk data has other advantages. Tickets are created by employees as part of day-to-day work, so there’s no extra burden of data collection. Your people are used to creating them and you have a robust process in place to capture them – it’s not another ask of anyone’s time. They also contain a timestamp, enabling issues to be tracked ‘longitudinally’ – over weeks, months or years.

But analysing helpdesk data also brings challenges. Even by the standards of free-text data, ticket descriptions are often messy and unstructured. Valuable insights can be hidden beneath layers of ‘noise’ – metadata (supporting data) that’s useful for resolving the ticket but less helpful for spotting patterns.

It can be really daunting to try to extract useful insights from this type of data. Traditional helpdesk systems can report on categorical fields such as severity or time-to-resolution, but they’re not designed to mine the unstructured text in the tickets themselves. That’s where Audiem shines.

Audiem uses algorithms to clean helpdesk text before analysis - for example, by separating routine requests (“Please organise catering for my meeting”) from genuine problems (“I can’t access the room booking app”). This improves the signal-to-noise ratio and makes it easier to extract useful insights.

Because Audiem can analyse helpdesk tickets alongside survey responses and other data sources, you can triangulate findings and get a richer, more reliable picture of your employee experience - all in one dashboard.

Helpdesk tickets are a great example of how you can use Audiem to get more value out of an existing data source, with very little extra effort. As well as being used to administer service requests and manage risks – both important tasks – they can also be used to continuously improve employee experience and performance.

If you want to find out more about how Audiem can make sense of your helpdesk data - book a 15 minute, no strings, discovery call.

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