5 Hidden Costs of Underutilised University Buildings and Spaces

Yet many estate decisions are still based on timetables, assumptions, or periodic surveys rather than objective evidence of how buildings and spaces are actually used. 

Underutilised buildings create hidden costs that extend far beyond wasted space. They increase energy consumption, inflate facilities management costs, contribute unnecessary carbon emissions, weaken capital planning decisions, and negatively impact the student experience. 

Working in partnership with SmartViz, North helps universities address these challenges through occupancy intelligence – combining IoT infrastructure with AI-powered analytics to provide a continuous, real-time view of estate utilisation. 

This article explores five hidden costs of underutilised university buildings and explains how occupancy intelligence enables estate teams to make more informed, evidence-based decisions. 

Hidden Cost #1: Energy Wasted Heating and Powering Empty University Buildings 

Energy is one of the most visible and controllable costs in university estate management – yet it remains one of the most poorly aligned with actual demand. 

Buildings are typically heated, cooled and ventilated according to timetables and schedules rather than occupancy. A lecture theatre booked for 9am that sits empty until 11am will still consume energy from the moment the building management system activates. A seminar room that runs to 30% of its scheduled capacity generates the same energy cost as one that is full. 

At sector level, the AUDE Higher Education Estates Management Report 2025 is unambiguous: the higher education sector “almost certainly occupies too much space,” with estimates of over-provision ranging from 10% to 40%. The report notes that “as a sector we simply can’t afford the running costs associated with space we aren’t using properly.” 

For a large research university, energy alone can account for tens of millions of pounds each year. Even modest reductions in wasted consumption – achieved by aligning building operations more closely with real demand – translate into material savings. One leading research-intensive university found that occupancy data enabled it to reduce energy use during low-demand periods, adjusting heating, ventilation and lighting in line with how spaces were actually being used rather than how they were theoretically scheduled. 

The hidden cost: Energy spend driven by booking data and assumption rather than actual occupancy. 

Hidden Cost #2: Cleaning and Facilities Costs That Don’t Reflect Actual Occupancy

Cleaning, security and facilities management are typically contracted or scheduled on fixed cycles – daily, weekly, or based on the academic timetable. They bear little relationship to whether a space has actually been used. 

A building that sees minimal footfall on a Friday afternoon receives the same cleaning resource as one that has been intensively used all week. A floor of offices that empties by mid-afternoon is secured and serviced as if it were occupied until close of business. 

When occupancy data is available, these schedules can be rationalised. The same research-intensive university referenced above was able to adjust cleaning and maintenance schedules based on real usage patterns, and to close buildings during weekends and quieter periods outside term time – reducing operational costs without compromising service quality. 

The principle is straightforward: services should follow people, not timetables. Without the data to know where people actually are, that alignment is impossible. 

The hidden cost: Facilities services deployed at fixed cost against variable and often lower actual demand. 

Hidden Cost #3: Capital Investment Decisions Based on Incomplete Space Utilisation Data 

When a department requests additional space, or a faculty argues for a new building, what evidence underpins that case? In most universities, the honest answer is: not enough. 

Historically, understanding space utilisation relied on periodic manual surveys – snapshots taken at a point in time, often by observers counting heads in rooms. This data is easily challenged. It does not reflect how space performs across a full academic term, across different days of the week, or in response to changing teaching patterns. 

The result is that capital investment decisions – which can run into tens or hundreds of millions of pounds – are often made on the basis of perception, advocacy and incomplete information. Requests for new space go unquestioned because no one can reliably demonstrate that existing space is being used well. Equally, consolidation proposals are resisted because no one can prove they are safe. 

Occupancy intelligence changes this dynamic. When investment decisions are supported by continuous, objective data on how space actually performs, the conversation shifts from debate to evidence. 

The hidden cost: Capital investment misallocated or delayed because utilisation evidence is too weak to support or challenge it. 

Hidden Cost #4: Avoidable Carbon Emissions from Underutilised Buildings 

Net Zero is no longer an aspiration for most UK universities – it is a strategic commitment, increasingly tied to regulatory expectation, funder requirements and institutional reputation. Yet the pathway to Net Zero runs directly through the estate. 

Buildings are the dominant source of carbon emissions for most universities. Heating, cooling, lighting and power consumption in underutilised buildings generate emissions that have no corresponding educational or research benefit. They are, in the most direct sense, avoidable. 

The challenge is that without occupancy data, it is difficult to know which buildings, which floors, or which time periods represent the greatest opportunity for reduction. Energy management systems can tell you how much energy a building uses. Occupancy intelligence tells you whether that energy use was justified. 

When a university can correlate energy consumption with actual occupancy patterns, it can identify where emissions reductions are achievable without compromising the student or staff experience. It can make the case for building closures, consolidations or operational changes with confidence rather than caution. 

The hidden cost: Carbon emissions from buildings operating beyond the level that actual demand justifies – creating a measurable gap between Net Zero ambition and estate reality. 

Hidden Cost #5: Poor Student Experience Caused by Limited Occupancy Insight 

The student experience is shaped, in part, by how well campus spaces serve the people who use them. Spaces that are too crowded, too noisy, too cold or simply too hard to find erode satisfaction and wellbeing. Spaces that sit empty while students struggle to find somewhere to work represent a failure of planning rather than a shortage of provision. 

Most universities have limited visibility into how students actually move through and use the campus. Which areas are consistently oversubscribed? Which are avoided? Which spaces work well for independent study but poorly for group work? Which rooms are too warm in the afternoon to be comfortable? 

Without this data, space design and allocation decisions are driven by assumption. A room that is technically available may be consistently underused because of its location, its environment, or its configuration – and no one knows. 

The hidden cost: Student satisfaction and wellbeing affected by space provision that does not reflect actual need or behaviour. 

The Common Thread: Decisions Made Without the Right Data 

Each of these five costs has a common cause. Universities are managing complex, expensive estates with limited visibility into how those estates are actually performing. The data they have is incomplete, periodic and easily challenged. The decisions they make as a result carry more risk than they need to. 

Occupancy intelligence does not change what decisions need to be made. It changes the quality of evidence on which those decisions are based – and, in doing so, changes the confidence with which they can be made and defended. 

The sector is at a point where the financial, environmental and reputational pressures on university estates are converging. Doing more with existing space is not optional. The question is whether estate teams have the visibility to know where the opportunity lies. 

Learn How Universities Are Using Occupancy Intelligence to Reduce Costs and Carbon 

If the challenges described in this article resonate, we would  invite you to watch our on-demand webinar: 

Using Occupancy Intelligence to Cut Costs, Carbon and Complexity 

In this session, North and SmartViz are joined by estate leads from the University of Oxford and University of Glasgow to explore how universities can use real-time occupancy data to make smarter decisions about space utilisation, reduce operational costs, support Net Zero ambitions and plan their estates with greater confidence.