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Productivity Task Force Collaboration

The Construction Data Trust in Collaboration with the Productivity Task Force

Who are PTF?

With average productivity levels in the construction industry remaining consistently below the UK average, the Construction Productivity Taskforce was formed in 2020 to identify and trial new ways of making the sector more productive. The group brings together leading figures in the construction industry – clients, contractors, supply chain and consultants – to undertake practical interventions designed to make the sector more productive.

What did they need?

The PTF had several questions that CDT has been able to assist with.

  • Can the PTF members demonstrate the capability of organisations to safely and securely collaborate with data?

  • How can the PTF pilot projects better inform data collection and use?

  • Can members work together to create mechanism to receive data from organisations on an ongoing basis?

  • What insights can we gain from the data received?


How have CDT helped?

To meet these needs CDT has:

  • Drafted and market tested new legal documentation that provide the necessary confidence to organisations wanting to collaborate with data.

  • Onboarded 8 founding participants in the Construction Data Trust (via the PTF membership) and demonstrated the capability of organisations to safely and securely collaborate with data in a structured and repeatable manner.

  • Worked with PTF pilot projects to inform data collection and use, culminating in the PTF Construction Site Productivity Guide.

  • Contributed to PTF Private Sector Construction Playbook, helping to demonstrate the core tenet of trust in the Playbook can operate at the data level

  • Received legacy data from completed projects and demonstrated the need for consistent data standards in order to achieve sector level insights

  • Set up data pipelines to receive new data (defined by Data & Metrics Working Group), advancing the understanding of the need for data quality

  • Developed dashboards to show art of the possible for trend analysis and benchmarking based on data received

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