Decoding Student and Staff Comments at Heriot-Watt University with Explorance MLY

About Heriot-Watt University

Heriot-Watt University, the UK’s eighth oldest higher education institution and now a global institution, has five campuses located in Edinburgh, Orkney, Scottish Borders, Dubai and Malaysia. It has over 26,000 students from 172 countries, with 65% taught on campus and 35% off campus; and over 2,800 staff, with 82% in Scotland, 10% in Dubai and 9% in Malaysia. With a fully integrated academic model, students can transfer to any of these campuses and graduate with a Heriot-Watt University degree

The Challenge: Making Better Use of Open-ended Feedback Data

The University needed to find a way to provide comprehensive analysis of free-text comments from its Early Experience Survey, National Student Survey (NSS), Postgraduate Taught Experience Survey (PTES), Postgraduate Research Experience Survey (PRES), Annual Student Survey, Course Experience Surveys, and Mid-Semester Check Ins. In particular, manual approaches to analysis of open comments were time and resource intensive, and an opportunity was also identified for getting richer insights.

“In our current university strategy, we have a performance indicator on student satisfaction, and this will also be at the heart of our next strategy,” said Kirsty Scanlan, Director of Strategic Planning, Performance & Projects. “We have made commitment that feedback is listened to, acknowledged, and utilised, and student experience is at the heart of process development. Heriot-Watt is unique in that we have the same academic provision in Dubai and Malaysia as we do in the UK, and student surveys are also truly global.

“One of the areas that unite all the areas under my wide and broad remit is that we are all about delivering data to the University. However, it is not just data, it is the insight that is really important. We have a very healthy provision of data from these surveys, but have lacked the software to make the most of it. Open comments are a rich source of information yet extremely time-consuming to process. Our teams have been internally reviewing qualitative data, manually cleaning this as it would include personal details of staff or students themselves, and then getting that feedback to appropriate staff members.”

The Solution: Student and Staff Experience Insights Through Explorance MLY

In September 2024, Heriot-Watt implemented Explorance MLY to analyse qualitative student feedback from its Welcome Week Survey, Mid-Semester Course Check-in Survey, and End-of-Semester Course Survey.

“This equates to 225 hours of time that it takes to process. And this assumes that somebody is sitting there for six weeks doing nothing but looking at open comments. As a university we want to embrace AI in appropriate and sensible ways, to support what we cannot provide, and we thought that MLY would help us to make better use of the data we are collecting.”

She continued: “So, having started to push MLY at the start of the 2024-25 academic year, we soon began to really utilise the data. As well as the obvious speed and time efficiencies, through MLY’s depth of analysis we felt we would be able to better identify local challenges, ensure that subject/discipline areas are targeted, and provide insight to local leaders more swiftly to make staff and students’ lives easier.”

Heriot-Watt also used MLY to analyse staff comments. “There is a real correlation between staff experience and student experience,” Kirsty stated. “If you have got unhappy staff, are the students then going to have a good experience? You cannot disaggregate the two, and have to look at both.”

In April 2025, the University ran a staff Health & Wellbeing Pulse Survey with a requirement for a quick results turnover, drawing on three quantitative engagement questions and two open-ended questions with over 1,000 responses each. “We were tasked with delivering the qualitative analysis within three working days, ahead of our Global Operations Executive meeting, where results were to be discussed,” Kirsty reflected.

“This also included developing a way to make the free-text insights visible, accessible, and actionable for leaders across the University in their respective areas. The MLY platform enabled fast and effective topic analysis of the 2,000+ comments as well as streamlined export of the analysis – including all relevant data fields – for immediate use and implementation into Power BI as a reporting mechanism. Within one week of survey closure, 45 leaders across the global institution received their reports. This methodology also allows us to effectively plan turnover timelines for future surveys.”

The Outcome: Fast, Flexible and HE-specific Solution = Time Savings and Better Insights

By summer 2025, MLY had become “one of the key instruments to enable us to deliver insight to the community”. “For Student Surveys, Explorance MLY software has reduced the time required to process comments from 225 hours to just 4.5 hours,” Kirsty revealed.

This represents a staggering 98% reduction in processing time, allowing us to allocate resources more efficiently and focus on higher-value tasks. And, for me, this is what has made MLY a no-brainer for us. “MLY substantially reduces time and effort, releasing staff capacity; provides objectivity and accuracy, and is easily repeated. It delivers topic-specific sentiment analysis, recommendations on what to stop, start, continue or change, including alerts to any areas requiring immediate attention.

Another advantage is MLY has been trained on millions of points of data over several years before reaching the market and continues to improve, and through its ongoing innovation is scalable and customisable.

In summary, MLY has led to faster identification of areas of low satisfaction and faster insights into improving the student and staff experiences, the ability to process and analyse feedback in real-time, facilitating timely responses and interventions, and has freed up staff time from manual data processing, allowing them to focus on more strategic tasks and initiatives.

Kirsty concluded: “We now have the capability to efficiently provide leaders across the institution with valuable qualitative data, making it more accessible and actionable than ever before. By embedding the link to the relevant MLY analysis in our existing Power BI models, users have access to valuable quantitative and qualitative data in one effective location.”