The University of Pretoria is the second-largest asset owner in the City of Tshwane.

Managing UP Facilities was historically difficult due to data being stored in disparate locations and systems. This creates tremendous systemic, capital expenditure, and operational inefficiencies. To address these issues, a structured approach has been initiated:

• All facilities-related data is currently being centralised in a SQL database.  

The data is planned to be placed in a centralised-UP database and linked together in a common database. Thus supporting live, verified data management and analytics.   The UP ITS department is actively involved, having initiated the process of securing a dedicated development space on UP’s on-prem servers. This enables the engineering consulting company to implement the pilot project for data centralisation.  

• Extensive data cleaning and structuring efforts have been undertaken and continue to ensure that only validated and relevant information enters the central repository. File structure and data workflows planning is 80% complete.  

This process is ongoing and is expected to evolve over the coming years as new technologies and requirements emerge. Setting up a central on-prem server with relevant facilities for data allows UP to stay software agnostic and then have the option to migrate to any software applications for data analytics and visualisation. 

Value proposition 1: 

Campus, building and infrastructure is linked together in a relational database and therefore relational intelligence can be applied. Thus, improving data management, tasks and decision making.

Current Facilities Management Digital Twin operational dashboard 

Reality Capture: Geolocated to scale

Value proposition 2: 

Sensible platform for data collection and consumption. Improving data collection and verification and accessibility.

Mapping of UP Properties and Assets on GIS Software

The integration of GIS software has enabled real-time visualisation and management of UP’s property assets:

•  Title deeds from the Deeds Office have been digitised, ensuring accurate cadastral information and resolving inconsistencies in municipal billing from the City of Tshwane (CoT). Property information is now linked to erf information, municipal account and meter information.

• ESRI software, a widely used solution for managing large-scale properties and precincts, has been adopted as the primary visualisation tool.

• Field workers now have access to mobile applications for mapping key infrastructure, including water meters and electrical meters (both CoT and UP-owned).

• An additional data layer has been introduced, allowing for comparisons between City of Tshwane (CoT) billing accounts and actual meter readings to detect inefficiencies and financial discrepancies.

 Example of ESRI’s field data collection application. Forms were customised in collaboration with UP Technical Services Division.  

Value Proposition 3: 

Improving financial sustainability. 

While full automation has not yet been achieved, with the right resources, this process could be optimised.

Municipal Accounts Information Dashboard

The creation of a dedicated dashboard to compare field-surveyed data from the electrical- and water meter initiatives with the 340-360 monthly municipal accounts from the City of Tshwane (CoT) yielded critical insights into the University of Pretoria’s (UP) billing landscape. First, it revealed the precise total of 347 active accounts. More importantly, the dashboard flagged several anomalies requiring attention, such as accounts that could not be linked to existing property records, accounts already under review or warranting referral to the UP Legal Department, differences in audited meter details versus those on the invoice, and accounts that should be closed.

Additionally, the dashboard identified properties with multiple electricity, water, and waste service bills – some of which do not legally belong to the University yet still appear under UP’s name.

By centralising and visualising these issues, property managers now have a clear overview of required actions, ensuring that the City of Tshwane’s billing is kept accurate, and that the University avoids unnecessary or duplicate payments.

The pilot dashboard was constructed by systematically comparing data from the field surveys with information drawn from the monthly City of Tshwane invoices. It is currently a static system and will become live as soon as the data is moved to the on-prem server. In the future, new invoices will be received, and the dashboard will be continuously updated, ensuring an up-to-date snapshot of utility usage and billing.

During the audit process, it became clear that a more comprehensive and proactive approach was needed to track and reconcile these accounts on an ongoing basis. Although the University has maintained diligent processes historically, this enhanced dashboard now provides a more centralised, user-friendly mechanism for monitoring consumption and billing details.

Originally conceived as an internal progress-tracking tool, the dashboard will evolve into an integral platform that helps the University keep its utility bills in check and promptly address any anomalies.

Dashboard (Municipal Digital Twin) critically gives insights into the University of Pretoria’s property accounts.   

Value proposition 4: 

Improved accuracy of asset information, management of assets and filling in the gaps.

This software is downloaded onto any smartphone and the field surveyors dealing with the equipment daily are then tasked to document the details of the assets, so the information can be placed on the central data server of the University – no longer on the desktops of employees. 

GIS Mapping Initiatives Already Implemented

The field data collection process we have developed and commenced rolling out, using Survey123, a crucial software application that supports efficient, on-site data gathering, plays a pivotal role in the Smart Campus mapping process. The software allows field workers to collect data on site and then the data is graphically reflected on the GIS Software, ESRI – in layman’s terms, the data is accurately placed on a map.

The following assets’ field data collection software has been developed to date: Electrical meters (municipal and UP-owned), municipal water meters, tree surveys, generator asset capture form. Irrigation infrastructure, including boxes and piping. Boreholes. Electrical mini substations (Medium Voltage) Trees – this initiative plays a crucial role in carbon calculations.

Example of the tree capturing form  

Tree Database dashboard, visualising the captured and analysed data. The information is incorporated to provide management insights and reporting. In the future, the ESRI app will be used to update information in the field and push it live to the dashboard 

Value proposition 5: 

Staff optimisation, reskilling and improving customer service and efficiency. 

SMAX Implementation

SMAX (Service Management Automation X), managed by UP ITS, has been integrated into the Smart Campus project as part of UP’s broader digital transformation strategy. Completed SMAX smart forms include Furniture Requests, Signage Requests, Requests for Campus and Building Information and New Project Requests.

The SMAX software uses a ticketing-system that tracks progress on a request and collects the data in a central space.  This ensures transparency and better management by line managers, as well as the protection of institutional knowledge. When staff leave, the data is not stored in a random location on a laptop; rather, it is stored in the central database.

• Automated approvals by line managers and HODs are still to be actioned but are possible. This will eliminate unstructured email chains, approval delays and data being lost and work being redone. 

• New SMAX forms currently in development: License and Permit Management, Fleet Management, Event Booking and Waste removal.

SMAX portal for Facilities Management  

Value proposition 6: 

Improving occupancy and informing future planning and capital expenditure. 

Occupancy Optimisation

An industrial engineering company was appointed to analyse the occupancy levels of various lecture spaces on the Hatfield Campus. They began by consolidating information from the University’s Syllabus Plus and PeopleSoft systems and quickly discovered that 60% are not booked through the central system. This indicates there are numerous micromanaged spaces not accounted for in the centralised venue booking data.

Based on the analysed information, the actual bookings related to the University yearbook, which outlines how many hours of instruction students should receive. This process revealed a range of discrepancies, including both underutilised and overbooked venues. The results were then visualised, plotting the largest venues (on the x-axis) against the total hours they were booked (on the y-axis). Horizontal dotted lines at the 20- and 45-hour marks highlight the discrepancy between scheduled and potential.

A key finding from the data is that, on average, venues are only booked about 50% of the time. Larger venues tend to be booked more frequently than smaller venues, but it is important to keep in mind that these observations are based solely on data from the central timetable. Any additional utilisation from unofficial or micromanaged scheduling may not be reflected in these figures.

• Why are the venues not being fully utilised?  

• Are different configurations needed?  

• How does this inform space planning and balance new pedagogies?  

This information can inform project prioritisation. 

The study further compares the scheduled hours of venue usage with the corresponding Wi-Fi connection records. Since the University can track how many users connect to specific access points, it becomes possible to gain a more accurate picture of actual room occupancy rather than simply relying on how many hours a venue is booked on the timetable. This dual approach provides deeper insight into how spaces are truly being utilised.

The findings, illustrated through data on the Thuto and Chancellors buildings, indicate that real occupancy levels are noticeably lower than what the timetable would suggest. This discrepancy underscores the importance of combining different data sources to obtain a more reliable understanding of campus space usage. By integrating Wi-Fi analytics into occupancy studies, the University can better identify underused facilities, optimise room assignments, and potentially enhance overall resource management.

Scheduled vs Wi-Fi Occupancy Data for Chancellors and Thuto Buildings 

Wifi data per building (Average scheduled time vs Wifi occupancy (averaged determined by Box & Whisker Statistical Process Control method) 

Value proposition 7: 

Cost saving -  new lecture venue is not required.

Looking ahead, the ideal would be to install physical people counters at venue entrances to verify and refine the Wi-Fi-based occupancy data. By thoroughly analysing this information, investigating any anomalies, and continually improving scheduling systems, UP can maximise the efficiency of its existing infrastructure. These insights will not only guide decisions about future space requirements but also highlight available or underutilised areas that may be rented out to external parties – creating possible new revenue opportunities for the University using their existing infrastructure. 

Value proposition 8: 

Improve efficiency and optimising the use of the current property portfolio. 

Contact time discrepancies – Scheduled data and yearbook data 

Although the yearbooks and scheduling are not managed by the Department of Facilities Management, the study included it as it has a direct bearing on the actual use of facilities and utilities expenditure. In the example above, the 100m² lecture venue is overbooked for 375 hours per year.

Conclusion

The achievements detailed above mark a transformative shift in the Facilities Management Department at UP. By centralising data, implementing GIS mapping, and integrating digital platforms like SMAX, the University has enhanced operational efficiency and positioned itself at the forefront of built environment digital innovation. These initiatives have not only improved data accuracy and asset management but also introduced cost-saving opportunities through better oversight of municipal accounts and property usage.

The GIS-based mapping initiatives and the Occupancy Surveys have provided invaluable insights that will support future decision-making, particularly in optimising space utilisation and preventing unnecessary expenditures. Additionally, the SMAX system has introduced a structured workflow that reduces inefficiencies and ensures data remains secure and accessible to relevant stakeholders.

As Africa BEDI continues to evolve, these foundational improvements lay the groundwork for even more advanced digital solutions. The ongoing development of new SMAX forms, further automation of GIS data integration, and refinement of occupancy tracking methods will continue to enhance UP’s facilities management capabilities.

Looking ahead, the seamless fusion of these technologies with future innovations will further elevate the University's ability to manage its vast infrastructure efficiently. With continued investment and refinement, these initiatives will contribute to a more sustainable, cost-effective, and data-driven facilities management strategy that benefits UP in the long term.