By Khalim Conn-Kowlessar,

Chief Technology Officer, Domna

The urgent need to decarbonise the UK’s housing stock is well understood, but delivering retrofit at scale remains one of the biggest challenges facing large-scale landlords and property investors. For those with a portfolio comprising thousands (or tens of thousands) of properties, the coordination of detailed, accurate assessments is a daunting task. Where commonalities exist between property groups, archetyping enables more efficient planning, design, and delivery of retrofit projects – but like any data-driven approach – needs to be handled with care.

The Challenge

Individual property visits require technical surveys, data collection, and design coordination, making a one-size-fits-all approach unworkable, particularly for those in the social housing sector operating within constrained budgets. Retrofitting at scale requires a smarter approach, that balances accuracy with efficiency.
Without a clear scope of work or an overarching strategy, projects risk delays, budget overruns, and quality issues. The challenge is not just how to retrofit, but how to plan and execute retrofits strategically, with the confidence that limited resources are being directed where they will have the greatest impact.

What is Retrofit Archetyping?

One solution gaining traction across the industry is retrofit archetyping – the process of categorising properties into groups or typologies, based on shared characteristics – in the same way the healthcare sector groups patients to create treatment pathways, for example. By leveraging clustering algorithms and representative property modelling, landlords can create scalable strategies that reduce time and cost while increasing accuracy and feasibility.

Characteristics for retrofit assessment are normally categorised as physical, thermal, and operational, and may include construction era, property type (e.g. flat, terrace, semi-detached etc.), heating system, fabric and insulation levels, or size and layout.
By identifying representative properties within each group, detailed assessments and retrofit designs can be applied to just a few homes (tweaks may be required for minor home variations such as extensions or repairs) and scaled to the wider stock they represent. Properties from the same era and street can vary significantly in performance due to differences in orientation, materials, or past interventions. However, by accounting for location and key characteristics, these properties can still be grouped meaningfully for efficient planning.

A good example of this in practice was demonstrated at a recent workshop hosted by The National Retrofit Hub at London Councils. The aim was to define 20-30 retrofit archetypes to support Local Authorities bidding for the Warm Homes Social Housing Fund (SHDF 3.0) – a government scheme allocating £1.29 billion to improve the energy performance of social housing in England.

Benefits of a Data-Driven Approach

For landlords or investors managing complex portfolios, the benefits of retrofit archetyping are significant:
• Efficiency: Fewer in-person assessments are needed in the scoping stage, reducing time, resource costs and the need to negotiate access with tenants.
• Scalability: Retrofit strategies developed for archetype representatives can be extended to thousands of comparable homes.
• Accuracy: Better data means better planning, improved cost estimates, and fewer unexpected challenges during delivery.
• Funding alignment: By understanding typologies, landlords can better align retrofit plans with funding opportunities, targeting specific property types or energy performance levels.
• Quality focus: A detailed understanding of the type of works required at scale, means landlords can focus on finding high quality, cost-effective suppliers and installers that best meet their needs

Moreover, standardising retrofit measure packages across archetypes allows for economies of scale in procurement and delivery, and supports the creation of repeatable retrofit delivery models.

Contingency is Key

No two homes are identical, even within a carefully defined archetype. Localised variations, facade treatments, and undocumented refurbishments can impact the feasibility or performance of certain retrofit measures. To manage this, and to take into account any building repair required, landlords should build in cost contingency, recommended at around 26%, and be prepared for onsite adjustments.

Additionally, archetyping should be seen as a living process, updated regularly with new survey data, outcomes, and performance monitoring. At Domna, our software enables landlords to simulate the impact of retrofit measures early in the process – even before surveys have been completed – helping to identify the most cost-effective pathways to meet upgrade targets and build a robust retrofit strategy.

Users can explore a range of cost scenarios, incorporate contingencies, assess funding opportunities, and evaluate the benefits of retrofit not only through traditional metrics such as EPC improvement and energy bill savings, but also through broader measures like asset valuation uplift. All of this is managed in one centralised platform, where clients can bring together internal and open-source property data to support smarter, faster, and more strategic decision-making.

Retrofitting at scale doesn’t need to be a stumbling block for landlords. By using data-driven archetyping, large-scale landlords and property owners can overcome inefficiencies, reduce costs, and deliver impactful decarbonisation strategies with greater confidence. As the UK continues to push toward net-zero, methods such as retrofit archetyping, powered by intelligent data analysis, offer a practical path forward for transforming the nation’s housing stock, one archetype at a time.