Gleeds is a leading global property and construction consultancy firm. With over 138 years of experience and expertise, they are renowned for providing expert management, advisory, and cost-effective solutions across the built environment. In an industry often plagued by cost overruns and delays, Gleeds identified a pressing need for data-driven decision-making to enhance predictability of budgets and improve time efficiency for its cost managers. To address this issue, Gleeds was keen to develop an advanced data analytics methodology that could offer structured and risk-modelled cost forecasting for new construction projects, enabling the company to remain agile within the marketplace.
Knowledge Transfer Partnerships (KTPs) are a three-way collaboration between a UK-based business or charity, a research organisation, and a qualified graduate known as a KTP Associate who has the capability to lead a strategic business project.
The partnership saw Gleeds paired with data scientist and KTP Associate Alexandra Spencer, who was guided by the academic expertise of Sarah Davidson, Professor of Information Management in the Faculty of Engineering, and Dr Grazziela Figueredo, Associate Professor in Health Data Science in the School of Medicine at the University of Nottingham.
Embedded within Gleeds, Alexandra bridged the gap between academia and the challenges of the real world. Previously dependent on traditional methods of data analysis, the partnership created opportunities for Gleeds to explore advanced technologies used by the university such as machine learning-based extraction, natural language processing, and parametric modelling and apply them to its own practice.
As Alexandra’s contributions started impacting Gleeds’ broader strategic direction, the partnership naturally expanded its scope to include methods for data collection, benchmarking and other data-driven initiatives not originally planned. The university saw the potential for existing machine learning-based extraction tools as a solution.
Applying this advanced technology the collaboration surpassed all expectation, leading to the development of an AI powered cost prediction tool, plus the creation of the Extract app, designed to accelerate Gleeds’ data collection process.
As a result, Gleeds now has a competitive edge, significantly boosting turnover, as well as export potential, thanks to the ability to offer more precise, risk-modelled cost forecasts for construction and refurbishment projects.
The KTP has been a catalyst for a culture of continuous learning and innovation, as well as enhancing Gleeds’ operational capabilities and significantly contributing to its intellectual capital. The new capabilities have given the company the confidence to tackle more complex projects and challenges, creating further avenues for business growth and innovation.
Gleeds formalised the advanced analytics methodology and data collection techniques into comprehensive process instructions for cost managers, ensuring that its team can continue to apply these new methods consistently in future projects. An inclusive staff training programme was conducted throughout the organisation and is now part of Gleeds’ onboarding process for new recruits.
The partnership has put the University of Nottingham at the forefront of data-driven construction prediction research. The project has provided an excellent case study for MSc students and has been instrumental in supporting their learning and development.
Finally, Alexandra went on to win the Future Leaders Category at the National Knowledge Transfer Partnerships Awards in recognition of her leadership capabilities and the impact she made in fostering a collaborative culture during her time with Gleeds. She remains with the company as a Data Scientist, based in Scotland.