Big data holds “immense promise” for expediting the region’s post-pandemic recovery, the Asian Development Bank said.
According to a 2022 report on the potential of big data in Southeast Asia (SEA), there are vast amounts of information that can be used to optimize public health, education, and social protection.
“Public institutions have turned to big data because of its analytical power to turn voluminous datasets into actionable insights that can help them respond swiftly to crises, improve their services, and enhance resilience to future shocks,” it said.
In the Philippines, where there are 17 health care workers (four doctors, nine nurses, and four midwives) for every 10,000 persons, big data can be leveraged through remote monitoring systems to reduce patient hospitalization and emergency room visits, the report said.
It can likewise be used to analyze job portals to understand skill trends and develop courses that respond to industry needs.
In the social welfare and protection sector, big data can provide an alternative source of poverty estimates to complement traditional statistics such as household-based surveys.
A challenge the Philippine Identification System (PhilSys) encountered when it extended social assistance this pandemic was the lack of identification cards (IDs) among Filipinos, said Emily R. Pagador, an assistant national statistician at PhilSys, in a webinar organized by the ADB on Aug. 17.
The current system, Ms. Pagador said, has multiple records and beneficiary registries, which are siloed.
“PhilSys can connect these different registries,” she said. “With the digital IDs we provide, we can ensure the uniqueness of each beneficiary.”
“The [Philippines’] main challenge is readiness in terms of interoperability — especially in the government sector, where some of our systems are still legacy systems,” she added.
Governments need to calibrate their policies and programs with aggregated data because people’s needs are diverse and ever-changing, said Elaine Tan, advisor and head of the statistics and data innovation unit of ADB’s economic research and regional cooperation department.
“Governments … need timely and future information from which to aggregate and apply algorithms on raw insights with high frequency. Governments can use it to track changes,” she said at the same event.
“We don’t want data insights and policies that are based on data a few years old — especially when we have such fast-moving disasters and global environments,” she added. “We need to take the perspective that data is an asset, and therefore, the costs related to getting these data systems up is an investment.”
In Cambodia, PPP projects seen as key to capitalizing on big data
In Cambodia, public-private partnerships are encouraged to develop big data applications.
“[We don’t have] the human resources able to capitalize that big data into its full potential,” said Nguonly Taing, executive director of Techo Startup Center, a public administrative institution under the guardianship of Cambodia’s Ministry of Economy and Finance.
“That’s why we need entrepreneurs and the private sector to help the government,” he added.
The Cambodia Data eXchange (CamDX), patterned after Estonia’s X-Road, builds an infrastructure that allows for secure data access across government databases, with minimal technical changes in existing information systems.
“We allow each line ministry to have their own system to create and manage data by themselves, with one condition: that they open up their data and share it with others,” Mr. Taing said. “We thought that we could try Estonia’s model, [to be an] information highway for data to flow from one to another … We are providing the experimentation to support this concept.”
The country’s Ministry of Health has also recently partnered with Metfone, a local telecommunications company, to provide digital services for Cambodia’s medical sector. This includes the utilization of a Picture Archiving and Communication System (PACS) to store and share images created by medical equipment such as ultrasounds and X-rays.