Prime Minister Lee Hsien Loong has called Singapore a “nation by design”. “Nothing is by chance”: not the public housing that leaves room for community bonds to forge, not the public transport routes weaving between the city, and not the lush greenery dancing amidst the urban towers.

The nation is now bringing design thinking to its workplace mental health guidelines. It sought the expertise of Co-Lab, an innovation unit in the Ministry of Manpower (MOM) that uses design thinking, behavioural insights and data analytics to improve labour policies. “We did not want it to be just a paper exercise,” says Tan Yi Hui, Co-Lab’s Deputy Director.

Tan shares how her team used design thinking to craft the guidelines, and how her team’s unique approach is shaping Singapore’s manpower policies.

Design thinking and data

Co-Lab spoke with many different types of people in the process of creating the mental health support guidelines. This is an important strategy in design thinking: find ‘extreme users’ to ensure the tool would serve them too.

The team first listed the types of industries and job functions they wanted to speak with, before heading out to engage willing participants. They also looked for people who faced a lot of difficulties finding jobs because of their mental health – the ‘extreme users’ in this case. This gave the team deeper insights to develop more practical recommendations, Tan says.

For instance, Co-Lab found that many employees were concerned about disclosing mental health issues during the job interview. “We wanted to set up a very important point in the advisory for employers to provide avenues for employees to seek support and to give reassurance that the information will be confidential,” she says.

Co-Lab’s approach also came in useful in managing the foreign dormitories’ Covid-19 outbreak in April. The ministry used analytical models to understand factors that affect infection risk, Tan shares.

This complemented on the ground interviews. Officers talked to migrant workers and dorm operators to understand their needs and fears. The conversations revealed that in the beginning, a lot of foreign workers did not understand the situation and weren’t sure where to get information. “There was a lot of confusion,” Tan says.

MOM designed posters and videos in the workers’ native languages to explain the situation. It then sent these through multiple channels, such as dorm operator emails, NGOs and the ministry’s own app for monitoring foreign workers’ health.

While this project was not parked under Co-Lab, many officers involved had been trained in their approach under MOM’s internal academy, shares Tan. The ministry equips officers across departments with data and design thinking skills, so they can be applied to a wider range of projects.

Try and try again

Co-Lab takes an iterative approach to improving policies, and focuses on tackling small parts of a big problem. Eventually, “the uncertain parts become more certain”, Tan says.

Co-Lab is using this strategy to help retrenched workers get back on their feet. Initially, the team thought making information on government support schemes more bite-sized would engage retrenched workers more. But trials revealed “no difference!”, Tan says.

They learned from this failure. “Simplifying information doesn’t mean it will prompt action, it doesn’t mean they will reach out and ask for more information,” she notes. Co-Lab is now testing a new approach of delivering information in a more targeted way, to match retrenched workers’ individual needs.

The team is also working with GovTech to incorporate this service into the LifeSG app, Tan tells GovInsider. LifeSG presents citizens with all the government services and information they need at different milestones, such as the birth of a new baby.

Data literate officials

Given the value that Co-Lab’s approach can bring to policies, should every civil servant be data and design literate? “Definitely,” believes Tan.

“For all our officers, it’s very important to have both approaches: having appreciation of data plus the tools to help understand your user better,” she adds. Data alone doesn’t give the full picture of a user’s emotions and behaviour, and may not help officials design policies and products that truly serve citizens.

Teach data

That’s why Co-Lab holds trainings for MOM staff to teach them behavioural insights, design thinking and data analytics. The unit runs the School of Future Skills within the MOM Academy, which helped to train officers managing the foreign dormitory outbreaks.

The Academy aims to equip public servants throughout the ministry to use these skills in policymaking, so they don’t have to involve Co-Lab in every project. Trainings range from basic appreciation modules to more advanced practicals where officers apply the skills they learned.

MOM also has informal platforms for learning new skills. The ministry holds ‘Analyteach’ sessions, where data analysts across departments take turns to share their knowledge. This is on top of ‘Fridays at Co-Lab’, when members of the unit learn from one another.

In the next year, Co-Lab will encourage its design thinkers and data analysts to learn each other’s skills, Tan says. Combining different expertises could birth new value, she believes.

Start small

What can organisations looking to trial a data and design centric approach do? Start with getting “quick wins” to show its impact to the rest of the organisation, Tan says.

Co-Lab started out as two separate teams of data analysts and behavioural insights experts, she shares. The original vision wasn’t to transform MOM, but to improve the letters they were sending out.

“The letter got a lot of good feedback and reduced the number of iterative processes,” she explains. Employers and officers didn’t have to keep going back and forth to add more information, and the ministry saw the value of this approach.

Co-Lab consciously places people at the centre of every policy they design, and is working to help other public servants do so too. These techniques will be crucial for creating inclusive and effective policies.