How Singapore is using tech to save infrastructure $

Interview with Chia Ser Huei, Executive Director, Centre for Public Project Management, Ministry of Finance, Singapore.

Singapore has distributed nearly S$100 billion (US$ 73.7 billion) to help citizens tide through the Covid-19 crisis, The Straits Times reported. The nation’s prudence over the years has prepared them for a stormy, pandemic-stricken day.

Singapore has been careful with its infrastructure spending in particular, as it takes up a quarter of the annual national budget, shares Chia Ser Huei, Executive Director, Centre for Public Project Management (CP2M) in the Ministry of Finance. The government set up the Centre in 2011 to manage its spending on publicly funded buildings. Over the past five years, it has saved about S$3.5 billion on infrastructure projects, Second Minister of Finance Lawrence Wong shared.

GovInsider spoke with Chia to find out how virtual tech and data analytics will help Singapore continue to manage infrastructure spending, and how the Centre works with agencies and experts to create the most value for money.
 

Digitalising design

Singapore will use a digital platform to improve how infrastructure is built. It will use Building Information Modeling (BIM) and virtual design tech to digitalise design.

Architects can test designs and adjust them digitally, avoiding costs to change them physically. Construction teams can simulate the building process to improve the accuracy of their plans, and better coordinate the production, delivery and installation of building modules.

Chia is excited about the potential the platform has for improving Singapore’s buildings. “A fully digital process can make it easier to test alternative designs and construction methods virtually,” and can help teams design more cost-efficiently, he says.

This platform will be shared with everyone involved, from architects and construction teams all the way to building management. This can help project managers understand how to maximise cost savings at every step of the way, Chia says.

For now, government agencies conduct feasibility studies to find potential problems before they embark on major construction projects. For example, before the designs for underground public train tracks are finalised, teams conduct extensive advanced engineering studies to find potential site constraints early. This helps project planners better estimate costs, Chia says.
 

Analytics to plan and predict

Government agencies also use data analytics to plan the city’s public infrastructure network. “Vehicular traffic and commuter patterns guide us on where roads and public transport infrastructure are needed,” Chia shares. Population distribution also helps agencies decide where to place facilities.

Analytics can be helpful even after the building has been constructed. Data collected from a building can help managers anticipate when problems might arise, and proactively address them, he explains.

“In future, maintaining buildings can be like maintaining passenger aircraft or jet engines,” Chia says. Building managers can monitor the performance of ventilation systems or lifts in real-time with sensors, predict when they might break down, and schedule timely maintenance. This saves money on repairing more serious problems, and reduces inconvenience to building occupants.
 

Balancing trade-offs

One of CP2M’s key roles is to manage trade-offs. “We need to ensure the infrastructure is designed and sized sufficiently to stay relevant for many years,” Chia says. But will the extra costs for a nicer design or future-proof features truly pay off?

These are the hardest decisions to make, Chia says. For instance, what is a reasonable passenger capacity public train lines should be designed for? “Catering too much becomes wasteful, but catering too little may require us to spend much more in future to raise its capacity,” he explains. “While we seek to be prudent, we want to avoid becoming penny-wise, pound-foolish.”

In an upcoming public train line project, developers originally planned for the train depot to be underground to save land space in tiny Singapore. But the soil condition of the site meant higher engineering risks and costs. After weighing the factors with other government agencies, the decision was made to build the depot at ground level instead.

The pandemic has shown us just how quickly urban needs can change. Cities need buildings that will shelter and serve citizens for years to come. In Singapore, virtual models and data analytics will help ensure this.