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Big Data: Singapore’s new economic resource


At the Singapore People’s Association Industry Guru Series, public sector and industry experts participated in a panel discussion entitled “Big Data – Think Different in a Changing Business Landscape”.

Data as a new resource

Minister Chan Chun Sing, Minister in the Prime Minister’s Office, highlighted that big data can be harnessed as a new economic resource for Singapore:

“We see data as a new resource. In 1965, Singapore’s basic economic survival question was, how do we transcend our geographic and resource limitations to create a living for ourselves? In 2016, the very same question will still need to be answered. In the past, we survived by having an export oriented strategy. In tomorrow’s world, if we play our cards right, data can be a new resource just like oil and other natural resources,” said Mr Chan.

In the value chain of big data, Mr Chan explained that data processing and analytics, cybersecurity and a brand of trust are domains that play on the natural strengths of Singapore, where it can gain a competitive advantage.

“Increasingly, in the next wave of economic development, you will see that we are going beyond tangible physical resources, into things like data, connectivity, trust, standards, protocols, and that will create new competitive advantages for Singapore,” said Mr Chan.

Data Analytics for Public Transport

Rosina Howe-Teo, CIO and Chief Data Officer of the Land Transport Authority (LTA), said that LTA started data mining of historical fare card data in 2008 to understand traffic patterns.  Today, LTA analyses numerous data sources in real-time, including Singapore’s fleet of 5500 public buses and 60 million data points of bus movement.

Data analytics is used to provide commuters with bus arrival times, to solve problems such as bus bunching, and provides insights into where additional buses should be injected. Analytics also enabled LTA to understand and alleviate crowdedness on train platforms, and these insights were used to improve the design of newer train stations.

“Big data is really about deriving deep insights to what is happening, and coming up with actionable solutions. In LTA, we have a Data Science Group, consisting of data scientists, data analysts and data engineers. They have different skills and specialise in different areas. In the field of data science, there are a lot of skills, not just number crunching. One of our current challenges is on visualization. While we can look at the numbers, visualization is still a very key component of delivery of big data results,” said Howe-Teo.

Data Analytics for Public Healthcare

Dr Chong Yoke Sin, CEO of Integrated Health Information Systems (IHIS), highlighted how Singapore has the most automated public healthcare system in the world today, based on the international HIMMS standard.

“Singapore public healthcare is the most automated in the world today, simply because we have automated every aspect of our practice. Today, all hospitals are at HIMMS stage 6, where in US, only about 8% of US hospitals are at HIMMS 6. The ultimate is HIMMS stage 7, and in Singapore we are glad that Ng Teng Fong hospital has achieved HIMMS stage 7. At stage 7, not only are processes automated, but you are actually making use of big data for healthcare,” said Dr Chong.

The Ng Teng Fong Hospital features a fully digitized paperless environment, with bedside patient information boards that displays real-time data, RFID tracking of patients and medical assets and a fully automated pharmacy. Contraindications are automatically detected and corrected by hospital systems.

“In medicine, it’s about the specifics. The big data is based on the whole body and all the vital signs and signals that it generates. Good medicine is about how to provide the best treatment that is based on the data your body presents, so the more data we have, the better, which is why the effect of analytics is vital,” said Dr Chong.

Dr Chong said that data analytics have enabled Singapore’s healthcare system to go into P4 medicine – Preventive, Predictive, Personalized and Participatory. EMR records capture all the episodes of a patient from beginning to end, personalizing the best treatment for each patient and providing the right care at the right time.

Data Privacy

On the topic of data privacy, the panel was asked the question: with so much data collected, will it become impossible to protect the privacy of individuals?

Prof Mohan Kankanhalli, Provost’s Chair Professor of Computer Science and Dean of NUS School of Computing, said:

“As a computer scientist is see this as a challenge, there is a lot of research going on in privacy, how can you do things like understand computer patterns without actually understanding a particular individual? This is a technology privacy problem and there are a lot of technical solutions to that. One of it is anonymization, how you can anonymize and remove certain identifying data. That is the technology part and people are working on it.

But that is necessary but not sufficient. There also has to be a societal consensus which is expressed in the form of legislation, you have norms and different rules established, like what can be captured, what can be shared, and how you should store that. I think all these aspects can mitigate some of the issues.”

Keith Carter, Visiting Senior Fellow at the NUS Business School and Affiliate Professor of the NUS Business Analytics Centre, said:

“This is so critical, there is no one who has solved this, how to have this balance between privacy, protection and security versus some of the benefits of big data. There is a business side, how do we monetize, what is the importance of the data, and there is a personal side, how do we protect our privacy? We all play a role in deciding how this data will be used. What can it be used for? It is key that we think about it, understand it, and participate in the dialogue.”

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