Singapore's Ministry of Manpower Uses Data Analytics to Target Workplace-Safety Inspections

Singapore's Ministry of Manpower (MOM) has used data analytics since the early-to-mid 2010s to help decide which workplaces to prioritise for safety and employment-compliance inspections, rather than relying solely on complaints or fixed rotation schedules.

Target inspections toward higher-risk construction firms to improve enforcement hit-rates and reduce inspector effort per firm checked.

In 2019, MOM's data analytics work identified 600 construction firms as high-risk. A separate 2018 compliance exercise targeting illegal foreign-worker hiring checked 650 firms while using about 20,000 fewer inspector man-hours than the ministry's previous, non-analytics-driven method. A related workplace-safety trial combined data analytics, behavioural insights and design thinking to target higher-risk companies for inspection.

When the 600 firms flagged as high-risk in 2019 were subsequently inspected, nine in ten (90%) were found to have offenses, including non-payment of salaries and overtime pay. A related workplace-safety trial required six times fewer formal enforcement actions (such as warning letters) and cut ministry resources spent by about 15%, in construction, a sector that accounted for over a third of Singapore's workplace fatalities between 2007 and 2016.

Public reporting on the program does not disclose the underlying model, its variables, or a formal accuracy evaluation, and MOM has not published the methodology for external audit; the reported figures come from journalism describing the ministry's internal data-science practice rather than from an official MOM technical report or peer-reviewed study.