Delays to large-scale construction projects more than double since start of pandemic

Research by machine learning startup nPlan found that the median delay for projects completed before the pandemic was approximately 100 days, while pandemic-era projects have a median delay of more than 200 days.

These figures have been compiled by amassing a dataset of more than 500,000 construction schedules provided by clients and contractors including Network Rail, Shell, Kier and Google.

Analysis of pre- and mid-pandemic projects in the nPlan schedule dataset suggests that nearly nine in 10 large-scale construction projects (85.5%) are delivered late; nearly two-thirds of them (59.4%) by at least two months.

Meanwhile, nearly a quarter of projects (22.7%) are delivered more than 250 days late, and more than one in 10 (13.4%) are delayed by at least a year.

nPlan chief executive Dev Amratia said: “In construction, as in so many other sectors and areas of public life, the pandemic hasn’t just created new problems, it has highlighted and exacerbated existing problems - in this case the costly project overruns which are endemic to the industry.

“Because this issue was not dealt with before the pandemic, we are now in a situation where projects have suddenly become much riskier.

“This will pile pressure on contractors and may mean clients bring forward fewer projects. On the other hand, the salience the pandemic has given this issue means we now have an unparalleled opportunity to get better at anticipating and preventing project overruns using advanced forecasting and risk management techniques.”

Cost hikes and time overruns have been recorded on some of the country’s biggest construction and engineering projects in the last two years.

Earlier this week, Crossrail Ltd revealed that shutting down construction sites during the first lockdown cost £13M.

Meanwhile, Speaking at NCE’s Tunnelling Festival in December, Tideway chief executive Andy Mitchell revealed that decisions made in the first three months of the Covid-19 pandemic cost the Super Sewer project promoter around £100M.

According to Amratia, the majority of construction projects that fail to complete on time have been hampered by poor forecasting and risk management.

He claims that one of the most effective ways to solve these problems is to remove human bias from the planning process:

“Time and time again we see forecasts marked by optimism bias, and risk management skewed by availability bias - that’s why we’ve developed a machine learning engine which turns our customers’ historical schedule data into a model which reflects the way they actually deliver projects.

“This unbiased model is then used to create super-accurate forecasts and discover risks and opportunities which would have remained hidden during the traditional planning process. This leaves planners free to get on with the important work of actually mitigating the risks and seizing the opportunities flagged by our system.”

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