When COVID-19 struck in 2020, Singapore responded swiftly with containment and mitigation measures to curb community spread. Underlying the city-state's quick public health response was an all-of-government approach characterised by decisive actions, rigorous surveillance, and prompt adaptation. Additionally, harnessing advanced healthcare technologies, such as artificial intelligence (AI) and data analytics, supported these efforts. Chatbots and automated instant messaging communications, as well as dissemination of information via traditional and social media, helped the public make sense of the uncertainties during the early days of the outbreak. As the pandemic progressed, digital contact tracing and even a robot dog were roped in to complement community surveillance measures as the country fought the war against COVID-19. More importantly, AI-enabled technologies and analytics played a vital role in disease diagnosis and prognosis as well as in supporting the research community in understanding the epidemiology of the novel coronavirus, predicting its evolution, and planning healthcare capacity. In 2023, WHO finally declared the end of COVID-19 as a global health emergency. However, the enduring effects of the pandemic persisted and continued to take a toll on the healthcare sector and on non-COVID-19 patients who had delayed medical care. Part of the burden of endemicity entailed living with the consequences of decisions made to prioritise hospital resources for COVID-19 patients, while non-urgent surgeries were either cancelled or postponed. Addressing the post-pandemic collateral damage became a pressing need. But how? Could AI, data analytics and other advanced technologies contribute to resolving this new healthcare challenge?

In the span of half a century, Singapore's healthcare system had undergone a major transformation along with the country's economic growth. From a developing nation plagued with tropical communicable diseases and malnutrition in the 1960s, Singapore had progressed significantly to become the second-healthiest country in Asia in 2019, according to Bloomberg. Successive reforms had enabled Singapore to transition from providing residents with basic healthcare services in the 1960s to service quality and cost-effectiveness in the 1980s. In the Healthcare 2020 Masterplan, the country prioritised improving accessibility, quality and affordability of public healthcare services to cater to the future needs of an ageing population with longer life expectancies and declining birth rate. To this end, data analytics could play a catalytic role in facilitating the successful implementation of the Masterplan, and by the late 2010s, several data analytics initiatives had been carried out by Singapore's restructured public hospitals. For example, in patient treatment and preventive care, data analytics was used to reduce waiting time for surgery patients, and to forecast diabetic patients at risk of developing serious medical complications respectively. Looking ahead, what would further propel the adoption of healthcare analytics in Singapore?

Andy Smith is the Transport Excellence Manager (Asia-Pacific) at GLC, a leading global logistics services company. In April 2016, GLC inaugurated the GLC Hub in Singapore, which is expected to boost cargo volume in Asia-Pacific. However, Smith faces issues further down the supply chain due to problems with road freight vendors. GLC utilises a hub-and-spoke method to transport cargo. Last mile deliveries are typically outsourced to small local transportation providers in the Asia-Pacific region who would complete the delivery by road. These vendors are usually small companies with only a few vehicles. They do not always make the best decisions about their operations, (e.g., deciding the type and combination of vehicles to be used in the fleet), or the type of resources (such as fuel, equipment on board) to be used. This inefficiency results in vendor bankruptcies and subsequent disruptions to GLC's delivery obligations. Smith wanted to devise a long-term solution to help his vendors manage their operations. He decided it would be best to help address their business needs and enable the vendors to make better managerial decisions. He started collating data in an Excel spreadsheet, but it soon became apparent that the spreadsheet was not ideal. He then considered other solutions such as developing a common platform, using Software-as-a-Service (SaaS) visual analytics online tools or creating a customised application. He wanted a tool that would ideally allow vendors to analyse their financial health over a period of time, and perform scenario analysis to aid their decision-making.

In 2014, Singapore Management University (SMU) undertook the reworking of its ten-year-old legacy intranet web portal eWise, and successfully replaced it with the new intranet, iNet. At lower maintenance costs than eWise, iNet offered modern design, easy consolidation and renewal of content, better integrated core operational functions, vastly improved user interface, and opportunities to collaborate. The case presents an overview of the journey of this transformation at SMU, discussing the key challenges faced by Goh and his team in terms of choice of technology, skills required, resources management and change management, including cultural issues and resistance to change. It discusses the development process and the decisions taken regarding the technical platform, implementation approach, features incorporated, and the taxonomy and topology of the website. Given the sheer size of the organisation and its information and legacy structure, iNet was undoubtedly an achievement. Yet, issues remained: How to accelerate iNet's low adoption rate amongst users? Should the portal be expanded to unify the whole of SMU through a single integrated web portal? Would that bring in synergies across the university or would the different departments continue to operate in silos? What would be the right time for upgrading the intranet portal to ensure future readiness and scalability of the overall IT solution?