The data-driven transformation of Singapore

Singapore burnished its global brand eight months ago by hosting the first-ever meeting between a US president and a North Korean leader. As preparations for a second meeting between Donald Trump and Kim Jong Un get underway in Vietnam, I am reminded of the logistical challenges that the Singapore summit posed.

Airlines and pilots were notified of temporary restrictions on flights in and out of the country, causing travel delays that could have blemished Singapore’s reputation as a leading air hub. Instead of the usual barrage of complaints from travelers, however, the Internet was lit up with listicles such as “Ten things to do in Changi Airport if you are delayed by the Trump-Kim summit.” Many even touted getting stuck at Changi as a rather pleasant experience – from enjoying a visit to the butterfly garden at Terminal 3 to shopping at over 350 retail outlets and being mesmerized by a kinetic art installation comprising 1,216 bronze droplets in Terminal 1.

Passenger data flows

Changi’s reputation as a global air hub is well recognized. What is less known is the airport’s ability to track and analyze data flows generated by over 60 million passengers and about 100 airlines flying to 300 cities in more than 70 territories worldwide each year. Every 90 seconds, a plane takes off from Changi, while over 40,000 staff from over 200 companies serve over 140,000 travelers daily, many of them able to make swift decisions based on these data. Even front-line staff are equipped with tablet computers to view data dashboards and make intelligent calls for any service recovery.

Steve Lee, Changi Airport Group’s (CAG) chief information officer, describes the group’s role as the “orchestrator” of the service ecosystem surrounding the airport. CAG integrates its various channels and backend data sources that underpin everything customer-related. The platform channels and consolidates feedback collected from airport customers via touch-points, including websites, emails, the contact center and instant feedback systems located across Changi’s airport terminals. Data is also shared with airport partners and tenants, allowing them to process feedback related to their own operations, track their own service quality standards and rectify issues such as shop floor cleanliness to meet service-level obligations.

Changi has succeeded as an air hub in spite of the odds. Aviation experts have, for instance, deemed Bangkok’s Suvarnabhumi International Airport as geographically preferred over Singapore. Yet it has been consistently conferred the accolade “‘world’s best airport.”

Interestingly, the success of  CAG can be attributed to its business and service model, found also in some of the world’s most valuable enterprises such as Apple, Amazon and Facebook, which thrive on seeing and understanding data in a superior way, according to a 2016 McKinsey study titled “The Age of Analytics.”

In the broader context of Singapore, a mastery of data among its workforce and enterprises can help it remain relevant in the global economy.

While Singapore’s investments in advanced infrastructure such as 5G (fifth-generation) telecom networks will bolster its status as a data hub, what is equally important is how the country taps this tsunami of data to fuel innovation with frontier technologies such as pattern recognition, machine learning and automation for the benefit of its enterprises, government agencies, and workforces.

In this week’s national budget announcement, Finance Minister Heng Swee Keat spoke about a slew of measures to ensure that Singapore’s industries continue to transform – and create good jobs – in three key areas. They are: building deep enterprise capabilities; building deep worker capabilities; and encouraging strong partnerships within Singapore and across the world. The budget will provision around $3.6 billion for the Singaporean worker and $1 billion for Singaporean enterprise.

Data-driven global competitiveness 

In helping workers to thrive in the digital age, training and professional conversion programs should not only focus on technical skills but also analytical thinking abilities.

The truth is, advances in natural language processing like Tableau’s Ask Data in its latest release will enable more non-IT-trained workers to ask questions of their data in plain language. This will lower the barriers for a broader segment of the workforce to perform complex tasks like data analytics easily. Therefore, beyond the technical aspects of data literacy, Singapore should focus on cultivating a data-driven cast of mind. This can augment the inherent reflexes of the Singaporean worker with what the World Economic Forum describes as higher cognitive abilities and enable him or her to do well in the global marketplace.

For example, many will remember the major disruptions plaguing Singapore’s public subway system two years ago. Perfectly functioning trains were found to lose signal with base stations and come to a halt just as a rogue train on the other side of the track passed them.

Instead of seeking validations to pre-conceived suspicions, such as finding faults in the carriages that had broken down, a team from Singapore’s Government Technology Agency harnessed data visualizations to explore creatively the possible causes of the disruptions. They were able to arrest the rogue train quickly, pull it out of service, and resolve the disruptions that had been plaguing riders for months.

Second, Singapore can capitalize on its advantages as a data hub to spur its enterprises on to acquire deeper digital and data capabilities.

Since Singapore’s founding in 1965, the country has always made a virtue of necessity with the resources that it has been afforded. Fresh from a painful separation from the Malaysia Federation, founding Prime Minister Lee Kuan Yew rallied a nascent and fearful population to transform Singapore: “Over a hundred years ago this was a mud-flat swamp. Today this is a modern city. Ten years from now, this will be a metropolis.”  Today, Singapore can enable a new generation of Singaporeans to make our own transformation from mud-swamp flats to metropolis, by harnessing for ourselves a limitless resource of the 21st century – data.

The problem? Leading corporations seem to be failing in their efforts to become data-driven, according to a 2019 Big Data and AI Executive Survey from research firm NewVantage Partners. The survey participants comprised 64 C-level technology and business executives representing very large corporations such as American Express, Ford Motor, General Electric, General Motors, and Johnson & Johnson. The percentage of firms identifying themselves as being data-driven has declined in each of the past 3 years – from 37.1% in 2017 to 32.4% in 2018 to 31.0% this year.

Fortunately, Singapore is in a favorable position to enable its enterprises and workers to become more data-driven. The country’s hunger for data talent is not abating. Jobs that require data skills recorded 17 times the rate of growth between 2013 and last year, reported Linkedin’s 2018 Emerging Jobs in Singapore. One explanation for this could be the increasing number of Singapore-based firms that are harnessing data to give themselves a competitive edge. Ride-hailing company Grab is one of them. From the onset, Grab needed to act as a disruptor that believed in enabling a broad spectrum of its workforce to help its various business units make better decisions around app development, new business opportunities and overall user experience. This led to significant productivity gains, more strategic product launches and ultimately a “super local” app experience, which was instrumental in Grab out-competing US-based Uber in Southeast Asia, a company that is reportedly 12 times its size by market valuation.

To enable local firms to benefit from the experience of data-driven companies like Grab, Singapore could pioneer a “data-driven scorecard” to gauge the state of readiness of organizations across the Asia Pacific. A scorecard of this nature should enable enterprises to examine parameters such as data governance, access, culture, and the ability to take meaningful actions for greater productivity with data. Both large enterprises – like Grab and CAG – as well as local small and medium-sized enterprises will find this scorecard useful in identifying what are some gaps preventing them from becoming more data-driven while yielding recommendations for benchmarking against the very best in the region.

Making out-sized contributions to the international community through such benchmarks is not new for Singapore. For instance, Singapore in 2010 spearheaded the City Biodiversity Index (CBI) in partnership with 30 other cities to measure the progress of their biodiversity conservation efforts. Singapore’s CBI – like a data-driven scorecard – offers thought leadership in an area that is projected by the United Nations to impact more than two-thirds of the global population who will live in cities by 2050.

Against the prospects of looming headwinds, it was thus apt for Prime Minister Lee Hsien Loong to visit workers at Changi Airport on the first day of the Lunar New Year to encourage them to continue innovating and staying ahead of the competition. With data mastery, workers should feel confident of helping to secure Singapore’s status as a leading air hub and, by extension, our continued relevance in the world.