Opportunities for Improving Service Delivery in Health, Education, and Social Protection

The chapter concludes with opportunities for data-driven decision-making to improve planning, implementation, monitoring, and accountability of human development service delivery.

Converging technologies have not yet penetrated the human development sectors to the same extent as the agriculture and industry sectors. Within the human development sectors, innovation in service delivery is being driven mainly by information technology applications. The principal trend within each sector is the shift from individual nondigital and digital technology tools to digital platforms and databased technologies using machine learning and artificial intelligence (AI). Within the latter, an important distinction can be made between individual digital technology tools, which are mostly about one-way interactions; digital platforms, which combine interactions across multiple agents; and systems enabled by big data, machine learning, and AI that seek to extract value from data and produce knowledge that can then be reused. Although the distinction between the last two categories is somewhat arbitrary (because the data generated by platforms can also be exploited through machine learning and AI), the idea is to distinguish between digital technologies that allow coordination and delivery of existing knowledge and content and those that generate new knowledge used for commercial or social purposes. In summary, these technologies enable innovations across the entire service delivery value chain that can generate significant benefits or cost savings.

TECHNOLOGY GROUPS

Digital public platforms enable governments to interact virtually with frontline service providers and beneficiaries through web- and mobile-based sites, applications, and software that provide the interfaces for these interactions. First-generation, citizen-facing platforms were developed to provide information (for example, to announce public examination results), but they are increasingly moving to twoway transactional service delivery. As noted in the description of the World Bank’s Digital Economy for Africa diagnostic tool, “Digital public platforms require digitalized systems and processes, shared and interoperable resources, interfaces for internal and external users, digital authentication capability, and online trust. These functionalities are provided through various core components, including digital identification and trust services, interoperability layers, and shared services” (World Bank 2020, 32).

Client-facing services—that is, those in which employees interact directly with customers—can be offered through various digital channels, such as online portals, mobile phones, and social media. Digital public platforms can help improve the cost and efficiency of service delivery and offer beneficiaries ease and convenience. Digital public platforms can be built and run directly by the government or in partnership with private firms. Although the latter approach helps to compensate for the lack of technical capacity within governments, other capabilities are required to define, procure, and manage these partnerships to avoid vendor lock-in and so on.

A special category of digital public platforms for the human development sectors is dynamic social registries that connect people to a range of public services, including social protection, health, education, utilities, and financial inclusion. They help to expand coverage of social services and prioritize the poorest people or targeted groups, while also allowing for scale-up and targeting assistance in the face of crises, disasters, and other shocks. Furthermore, these platforms, by linking to a unique identification (ID), can help to reduce costs associated with inclusion and exclusion errors.

Within human development sectors, the converging technology revolution is most advanced and prominent in the health sector, where it can have immediate impacts on human capital accumulation and welfare. Technology convergence is apparent in the entire global value chain, including digitalization of life science in drug discovery; nonimaging diagnostics based on genomics; nanotechnology in drug delivery; additive manufacturing for medical devices; use of drones for medical supply delivery; the Internet of Medical Things; use of robots in surgery; virtual and augmented reality for remote surgery and training of doctors, nurses, and technicians; and geospatial and epidemiological modeling for disease prediction and surveillance. Portable genomics sequencers allow for diagnosis of diseases in real time in remote areas. AI software, together with sensors and cameras, can turn mobile phones into sophisticated diagnostic tools, which can be used for digital microscopy, cytometry, immunoassay tests, monitoring vital signs, and detection of malaria or cervical cancer. AI has the potential to make medical devices more reliable, and it is helping to decentralize care that can be delivered to those without access to health facilities. Furthermore, genomics, although only a subset of nonimaging diagnostics, is a critical data source for enabling the transition to personalized medicine, especially when combined with AI and other tools.

An equally important shift is occurring toward a whole-of-government approach to digitalization for the delivery of public services and the use of data-driven decisionmaking in the design and implementation of policies and services and to monitor performance and measure impact. Sophisticated systems of data-driven decision-making integrate data from multiple sources, such as geospatial and remote sensing data and household level data, to inform policy making and implementation.

Table 3.1 summarizes the broad groups of technologies and their pathways to improving service delivery for enhancement of human capital.