Building a Data Engine for Construction – Qflow

Qflow’s digital data trail is cutting costs and reducing waste on construction sites.

As an extraordinarily complex and diverse sector, the construction industry has been slow to digitise. One enduring problem is an over-reliance on a paper trail to track the deliveries of materials and the disposal of waste, leading to major gaps and deficiencies in the data available to contractors and their customers.

To help construction projects improve quality control and reduce costs and greenhouse gas emissions, Qflow is capturing digital data on the materials that arrive at, and depart from, building sites. As many materials suppliers don’t have sophisticated order management systems, Qflow decided the most straightforward approach would be to task on-site staff to take a photograph of each delivery note and upload it to a cloud-based system to be verified and analysed.

Over the past seven years, Qflow has used machine learning to continually improve the accuracy of this system to give its clients “a really rich, very detailed, picture of what was coming onto site and what was going off”. Adopted by major businesses, such as Scottish Power, and major public construction projects, such as the UK’s HS2 rail link, Qflow has now captured more than 75,000 material and waste movements, resulting in an average savings of £221,000 per year per project, while avoiding the equivalent of 9,690 tonnes of CO2 in greenhouse gas emissions.

After expanding rapidly, even during weak years for the construction sector, Qflow is now serving more than 300 construction sites. It is aiming to become profitable within two years, while continuing to grow the business both in its home UK market and abroad. Qflow is now expanding into the US, Australia and continental Europe.