The Smart Nation initiative as policy design

Originating from the seminal work of Harold Lasswell, the fundamental precept of policy design is that the policy process comprises policy means (instruments) and ends (goals) (Lasswell, 1951, 1971). Under this design orientation, policy instruments are essentially the tools, techniques, or mechanisms that governments use to achieve policy goals, usually by giving effect to public policies (Bressers and Klok, 1988; Howlett, 2011; Howlett and Rayner, 2007; Woodside, 1986).

While early policy design studies had sought to build up comprehensive typologies of policy instruments and their varied functions and effects (Bemelmans-Videc et al., 1998;'Elmore, 1987; Grabosky, 1995; Hood, 1986; Howlett, 2000; Woodside, 1986), subsequent efforts would seek to develop a deeper understanding of how instruments tend to be “packaged” within larger “policy mixes” (Doelen, 1998; Gunningham et al., 1998; Howlett, 2004) or “new governance arrangements” (Howlett and Rayner, 2007; Rayner and Howlett, 2009). Often taking a portfolio approach to understanding policy mixes, these studies seek to understand the relationships between policy instruments within a given policy mix, paying particular attention to the dynamics that arise when new instruments arc added to a mix or existing instruments omitted or changed (Howlett and Rayner, 2013a, 2013b). This has allowed for the identification and categorization of the different

Policy Mix Dynamics

Figure 2.1 Policy Mix Dynamics

dynamics that emerge when new instruments and goals interact with existing ones within a given policy mix. Four main dynamics have been identified in the literature, with each dynamic associated with the extent of policy goal coherence and policy instrument consistency within a policy mix, as illustrated in Figure 2.1.

While “policy layering” has been taken to mean the adding of new policy goals and policy instruments onto an existing regime without removing previous ones, “conversion” involves changes to policy instrument mixes without any change to policy goals (Beland, 2007; Rayner and Howlett, 2009: Thelen, 2004). “Policy drift” occurs when policy goals are changed but not the instruments used to attain them (Hacker, 2004; Rayner and Howlett, 2009: 103). Dynamics of layering, conversion, and drift arc fundamentally rooted in the assumption that policy mixes ought to be designed in such a way that policy instruments support, rather than undermine, each other, i.e., to ensure coherence in policy goals and consistency among policy instruments (Howlett and Rayner, 2007: 7). As Figure 2.1 shows, an ideal situation of integration occurs when instrument mixes are consistent and policy goals are coherent. In contrast, the addition of new instruments and goals without sufficient consideration of existing ones may result in mismatches between goals and instruments. Lastly, conversion reflects a more sys tematic attempt to change the policy instrument mix in order to meet new policy goals. These dynamics of policy design can provide a useful framework for understanding new policy initiatives such as the Smart Nation initiative and interactions between components of these new initiatives and the existing urban policy milieu.

Launched in 2014, the Smart Nation initiative aims to harness data and technological solutions to address urban policy issues (Lee, 2014). According to the SNPO, the Smart Nation initiative aims to “support better living, stronger communities, and create more opportunities, for all”, with a focus on “how well a society uses technology to solve its problems and address existential challenges” (SNPO, 2016). The initiative places a strong emphasis on five key domains: transport, home and environment, business productivity, health and enabled aging, and public sector services.

In terms of policy instruments, the Smart Nation initiative relies on a set of “enablers” (SNPO, 2016), which include:

  • • Test-bedding and collaboration with industry and research institutions
  • • An open data portal and a Smart Nation Platform that allow for the consolidation and sharing of government data
  • • Investments in Research and Development (R&D)
  • • Laboratories for the development and piloting of technological solutions
  • • Start-up accelerators to nurture creative start-ups and innovations
  • • Cybersecurity measures for the safeguarding of data, systems, and networks
  • • Building computational capabilities among citizens through educational programs at various levels, including young children, secondary school students, and working professionals.

The policy goals and instruments that the Smart Nation initiative has articulated differ from those of Singapore’s hitherto development-oriented approach to governance or the Asian “developmental state” model (Huff, 1995; Low, 2001; Perry, 1997). The developmental state model generally emphasizes policy goals of economic growth and industry development, with policy instruments typically including subsidies, incentives, government investments in economic and physical infrastructure, and direct market interventions by the state, most notably through state-owned industries and other quasi-governmental organizations.

Although developmental goals are also emphasized in the Smart Nation initiative, there appears to be a clear focus on citizens and communities in the initiative’s policy goals, with these goals broadly emphasizing stronger communities, greater policy collaboration with businesses and citizens, and the nurturing of a culture of innovation and experimentation. As the SNPO emphasizes: “(c)itizens arc ultimately at the heart of our Smart Nation vision, not technology!” (SNPO, 2016). By providing a list of the policy goals and instruments that are associated with the development state model and the Smart Nation initiative, Figure 2.2 highlights the significant differences between the two approaches.

Policy Design Elements

Figure 2.2 Policy Design Elements

These differences are particularly distinct in terms of policy instruments. In thinking about the policy instruments employed by the two approaches, it is useful to think about “developmental” versus “enabling” instruments (Woo, 2015, 2016b). Where the former involves the allocation of state and societal resources toward the attainment of developmental goals (Chang and Grabel, 2004; Murindc and Mlambo, 2011; Stiglitz ct al., 1993), the latter is associated with “the creation not merely of incentives but of those conditions that allow activities to take place” (Baldwin et al., 1998: 4). As Figure 2.2 shows, the developmental state model emphasizes developmental instruments that involve the mobilization of resources toward the stimulation of economic growth and industrial development. In contrast, the Smart Nation initiative favors instruments that establish the enabling conditions and infrastructure necessary for the development and operations of innovation start-ups. Calder (2016: 61) describes this as “minimalist, enabling governance”.

However, it is important to note that the design of Smart Nation policies - or any instance of policy design for that matter - is not a static process. As discussed earlier, policy design tends to be an iterative process that involves the inclusion (or exclusion) of policy instruments from an existing policy mix or portfolio over an extended period of time. There is, in other words, no tabula rasa in policy design - but legacies of urban policies and design processes past. What then, are the dominant design dynamics - whether layering, conversion, drift, or integration - involved in the Smart Nation initiative?

 
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