Construction has no shortage of data. Programmes, BIM models, labour records, progress reports, site images and digital applications are now routinely generated across major projects. The challenge is turning that information into something project teams can use to understand productivity while work is still being delivered.
That is one of the issues being addressed by the Cambridge Framework for Construction Productivity: Measure · Benchmark · Improve, developed by researchers at the University of Cambridge Laing O’Rourke Centre. The framework draws on data collected from more than 25 projects over three years and looks at productivity at project, work-package and activity level. It is also being supported by Camentis, a software tool currently being piloted on live construction projects.
London Construction Magazine asked Dr Danny Murguia, Assistant Research Professor at the University of Cambridge Laing O’Rourke Centre and lead author of the Framework, what needs to change if construction productivity measurement is to become a practical project-control tool rather than another reporting exercise.
What are the biggest weaknesses in the way construction productivity is currently measured across UK projects?
At sector level, measures such as GVA per hour worked are useful for understanding long-term economic trends, but they offer very little insight into what project teams can actually change on site. At project level, organisations often report progress rather than productivity, and labour metrics are fragmented and inconsistently defined. The result is a lack of comparable, granular benchmarks across projects, work packages and activities. We need measures that answer practical questions: how fast are we building, how efficiently are resources being used, and why does performance vary?
If productivity data were embedded into procurement requirements, what would clients and main contractors need to do differently in practice?
Clients would need to define minimum productivity data requirements to the supply chain from the outset. Contractors would then need to ensure that those requirements flow through to trade contractors and are captured consistently during delivery. The key is not collecting more data for its own sake, but ensuring that information from programmes, BIM, progress records, labour systems and site reports can be integrated and compared. Over time, clients could build portfolio-level productivity databases that support benchmarking, more realistic planning and better risk allocation.
“The key is not collecting more data for its own sake, but ensuring that information from programmes, BIM, progress records, labour systems and site reports can be integrated and compared.”
How can project teams avoid productivity measurement becoming another reporting burden rather than something that genuinely improves delivery?
The starting point should be to use data that projects already generate rather than creating parallel reporting processes. Much of the information already exists in programmes, BIM models, labour systems, progress records, site images, and digital applications. The value comes from structuring and integrating those datasets so that useful metrics and visualisations can be generated with minimal manual intervention. Most importantly, the information must feed directly into project-control conversations. If teams can see emerging deviations, understand the likely causes and take corrective action, productivity measurement becomes a management tool rather than an administrative exercise.
What have the live demonstrator projects shown so far about the types of interventions that can make the biggest difference to productivity?
The demonstrators suggest there is rarely a single intervention that explains high performance. What matters is creating a stable production system. That includes reliable handovers between trades, timely material availability, good logistics and access, appropriate crew sizes, effective batching, sufficient crane capacity and rapid resolution of recurring blockers. Our data also show that simply adding more labour or equipment does not necessarily produce proportional gains. The most useful interventions are therefore those based on understanding the specific cause of variability and adjusting the production system accordingly, rather than applying generic productivity targets.
How do you see Camentis developing alongside PAS 4010:2026, and could it eventually become part of standard project controls across major UK construction programmes?
PAS 4010:2026 creates an important opportunity because it places greater emphasis on having a structured productivity management strategy and on continuously measuring and improving performance. Camentis is designed to operationalise that kind of approach by bringing together project data, calculating consistent productivity metrics, visualising production flow, capturing blockers and enabling benchmarking. It is now being tested on live projects. The longer-term ambition is that this type of capability becomes embedded within routine project controls, so productivity is monitored alongside programme, cost and risk. Whether Camentis itself becomes a standard tool will depend on adoption, but the underlying approach is increasingly aligned with where the industry needs to go.
From Measurement to Project Control
The Cambridge Framework is intended to move construction productivity measurement away from fragmented and retrospective reporting towards a more consistent approach that can influence decisions during delivery. For project teams, perhaps the most significant point is that improving productivity does not necessarily mean adding people, plant or additional reporting.
As Murguia’s comments highlight, performance can instead depend on the stability of the production system itself: trade handovers, logistics, materials, crew configuration, crane capacity and the removal of recurring blockers. The longer-term question is whether productivity data will ultimately become as routinely embedded within construction project controls as programme, cost and risk. With PAS 4010:2026 placing greater emphasis on structured productivity management, that transition may already be beginning.