Greenshaw Learning Trust: Achieving Data-Driven Estate Management for Sustainable Growth
21 Academies | 7 Geographical Locations | 12 Years of Strategic Support
All information in this case study is accurate at the point of publication.
Services Delivered
CAD Plans, School Capacity Reports, Condition Surveys.
Outcome
Centralised Estate Management | Enhanced Operational Efficiency | Strategic Decision-Making
The Challenge
Greenshaw Learning Trust has grown rapidly from a single school in South London in 2012 to 21 academies across seven geographical locations by 2024. This growth presented several estate management challenges:
- Centralising Estate Management
With academies spread across a wide geographical area, the Trust needed to centralise estate management processes to ensure consistency and efficiency. Jeremy Pilgrim from Building Spatial Intelligence explains: “Whilst functions such as Finance and HR are regularly centralised, Estates is often left out. But it shouldn’t be.”
- Data-Driven Decision Making
The Trust required accurate and comprehensive data to make informed decisions about maintenance, capital expenditure, and expansion. Without this critical information, it was difficult to prioritise projects and allocate resources effectively across multiple academies.
- Maintaining Educational Focus
As the Trust expanded, there was a risk that estate management issues could distract from the core focus on education. Greenshaw Learning Trust needed a solution that would allow headteachers and staff to concentrate on teaching while ensuring effective facility management.
Our Solution
Building Spatial Intelligence implemented a data-driven approach to estate management for Greenshaw Learning Trust. The solution included:
- Centralising Estate Data and Processes
Providing accurate and comprehensive data through CAD plans, school capacity reports, and condition surveys.
- Developing a Robust Estates Management Shared Service
Ensuring standardised processes across the Trust to maintain consistency, even as the organisation grew.
- Year-on-Year Capital Programme Based on Condition Data
Using up-to-date condition data to inform a rolling capital programme, enabling smarter allocation of resources.
- Tailored and Scalable Approach
The solution was designed to adapt to the evolving needs of the Trust, with Jeremy noting: “Our experience with the London Borough of Sutton, then with Greenshaw High School and subsequently with the Learning Trust shows how we adapt to the needs and requirements of our clients.”
The Outcomes
The data-driven approach provided by Building Spatial Intelligence has enabled Greenshaw Learning Trust to:
- Make Informed Decisions About Expansion and Resource Allocation
Centralised data has empowered the Trust to allocate resources and plan for expansion strategically.
- Prioritise Maintenance and Capital Projects
With a comprehensive view of the estate’s condition, the Trust can effectively prioritise capital projects and maintenance needs.
- Ensure Educational Focus for Headteachers and Staff
By streamlining estate management, the Trust has allowed educational staff to focus on teaching and learning.
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Recommendation
School Property Matters has been invaluable, the data they provide has been intrinsic to managing strategically and effectively from a central perspective.
The SPM team have continuously supported us over the years, working in the background through significant growth in the trust.
