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SPRING Singapore shares how it enables a data-driven culture

Kareyst Lin | Jan. 4, 2017
One huge challenge to inculcating such a culture is that employees don’t know if they can trust the system, said Wong Ming Fai, Chief Information Officer, SPRING Singapore.

data-driven culture

When SPRING Singapore first introduced a prediction system to help its officers decide whether a grant should be approved or rejected, there was a lot of suspicion cast upon the system by the employees.

The prediction system leverages machine learning to look at past data — the past applications that were approved or rejected, and why certain things are approved — and gives a recommendation.

"The question people have is, 'is this 100 percent accurate?' People don't know if they can trust this system, and the interesting thing is, people want it to be 100 percent accurate, when in fact, even humans make mistakes," Wong Ming Fai, Chief Information Officer, SPRING Singapore, told GCIO Asia in an interview.

The trust building takes time, and the challenge SPRING faces is how to encourage its employees to trust the systems, Wong said. "We realised that it was useful to build visualisations to explain why the system made a certain recommendation. Instead of putting things into a black box, we open it up and start explaining to employees how we built this engine, why it is making certain recommendations. This was helpful in getting people to understand and gradually trust the system."

Integrating data analytics into SPRING's business community intelligence

The area in which SPRING Singapore is currently focusing their data analytics efforts on is business community intelligence.

"In SPRING's work, we touch base with companies via a number of channels — we conduct regular company visits to find out what they are doing to understand the challenges and plans that they have, and we also work with partners such as the small and medium-sized Enterprise (SME) centres that provide advisory and consultation services. In the process, we collect information. The question is, how do we make these sessions more useful, and how do we use the information that we have collected," Wong explained.

The current process, which is already evolving, involves manually looking back at the reports filed to help the government understand industry trends and challenges of a particular community.

With data analytics and machine learning techniques, SPRING officers can then mine topics that are being touched upon during discussions. This helps them to identify overarching trends or issues shared, ahow SMEs have progressed as well as the impact (if any) through the various government assistance programmes.

"This information also provides a 360 degree view of the companies that we might be visiting. Before the visit happens, the data tells us the different touch points we would have with the company. Other than the reports mentioned previously, the touch points also include information like the grants the companies might have applied for previously and whether they were approved. Also, the companies might have visited some of our SME centres for business advisory, or there might be news on the internet about these companies," Wong said.

 

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