In 2022, the CDT was commissioned by the Construction Productivity Taskforce to support its work to identify practical interventions that can be made to make the sector more productive.
The Taskforce was undertaking various activities across two pilot sites. CDT ran workshops and deep-dive sessions to help collate the data from these sites and capture the wealth of insights. This work has been captured within a report, summarising case studies and good practice, called the Construction Site Productivity Guide.
This initial work enabled the Taskforce to surface issues associated with the collection and integration of data, thus shaping its next phases of work. It highlighted the importance of embedding productivity improvements into project plans and provided a 7-step framework for success. This framework focuses on the need for clear understanding of the improvement being targeted, as well as defining the requirements for data that will enable any change to be measured and analysed. Thus, providing the evidence and feedback mechanism to ensure improvements are embedded.
In parallel, the Taskforce Data & Metrics Working Group identified 5 metrics that it saw as potential levers to improve productivity. These high-level metrics have enabled the organisations involved to bring focus to productivity, facilitating several rich conversations which would otherwise have been unlikely to emerge. This created a foundational platform on which to build.
To support the Data & Metrics Working Group, the Construction Data Trust established a legal and technical platform for organisations to share the data they were collecting against these metrics. Together with the Construction Productivity Taskforce, we have demonstrated the industry is ready to pool its data to solve extremely challenging problems. In so doing, we have gained insights into a wealth of conflated problems that must be solved to help the industry improve. What is clear is that whilst we can readily visualise the data received from data providing organisations, for this data to be trusted and therefore useful, there are many further foundations that need to be established.
Everyone involved recognises this as a journey of discovery, delivering marginal gains. Already we have seen, there are many signs of progress and enhanced understanding. Our insights extend, but aren’t limited to:
Benchmarking requirements
Data literacy
Data quality
Analytical techniques
Data volumes
Granularity of data vs metrics
Collaboration and communication
What has become clear is that the high-level metrics provide a starting point for the conversations and need to be accompanied by supporting data. This data will need to be aligned to the problems that we are seeking to solve, with advanced data analytics playing a key role in helping us to solve each puzzle.
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