3. Innovation portfolios in policy making systems

Differences in public administrations account for differences in the quantity, quality and type of innovation in a country (OECD, 2021[1]; 2021[2]). However, the nature of a country’s public administration is only one factor affecting the quantity and quality of innovation. Many economic, legal, cultural and historical factors determine the kind of innovation that is initiated, implemented and scaled up.

This chapter asks which systems-level factors are important for investing in different innovations, and if and how a country's public sector innovation portfolio can be studied or steered. In private sector innovation research, many streams look at the systems level and its influence on innovation, with some also outlining a role for the state. For example, the National Innovation System concept (Lundvall, 2007[3]) sees innovation as the outcome of co-creation, with the state as part of a broader system. Similarly, the Quadruple Helix framework (Carayannis, Goletsis and Grigoroudis, 2018[4]) sees the state as one actor alongside universities, industry and the public. The most pronounced analysis of the connection between the state and innovation is spearheaded by Mazzucato’s (2013[5]) work on the “entrepreneurial state”. This analysis acknowledges that states are not merely part of an innovation ecosystem but rather active drivers and promoters of innovation and economic change. Their institutional set-up influences what types of innovation processes are possible and likely, even in the absence of directed state action. At the same time, political-institutional structures can also be barriers to successful innovation. Connected research on ‘technology innovation systems’ (Hekkert et al., 2007[6]) and ‘sociotechnical transitions’ (Geels et al., 2017[7]) connects state action, investment and structures to specific types of innovation – either technological or transition-oriented.

These perspectives are largely missing in the public sector. As argued in Chapter 1, research on public sector innovation tends to look at innovation as a bundle and analyse systemic barriers to innovation without differentiating between innovation types or strategic intent (Cinar, Trott and Simms, 2019[8]; 2021[9]; Scott, 2020[10]). At most, studies distinguish between radical or incremental innovation, usually from a measurement angle and need to differentiate outcomes (Bugge and Bloch, 2016[11]; Fuglsang, 2010[12]). Newer studies look at the need to balance exploration and exploitation activities (Cannaerts, Segers and Warsen, 2019[13]), but usually from an organisational perspective (Chapter 2) rather than a policymaking or systems level. Alternatively, research concentrates on a singular type of innovation, usually based on the process or inputs applied, and analyses how it interacts with broader structural elements (e.g., collaborative, technology-enabled, co-creation, experimentation (Misuraca and Viscusi, 2015[14]; Torfing, 2018[15]; McGann, Blomkamp and Lewis, 2018[16]).

To establish what influences innovation intensity in a system, it is important to analyse how innovation capabilities emerge in a policymaking system and what supports them (Clausen, Demircioglu and Alsos, 2020[17]; Vivona, Demircioglu and Raghavan, 2020[18]). However, it is also crucial to bridge the gap between the intent to create public value through innovation (Chapter 1) and the types of innovation the government system supports. Namely, it is important to examine policy intent as a part of public sector innovation portfolios to see if innovation activities and purpose line up.

One might argue that most innovation activity in the public sector is undertaken by organisations, teams and “hero” innovators going against the system. But the practice of public sector innovation has been professionalising and institutionalising in recent years. Strong signals of this are the adoption of the Declaration on Public Sector Innovation (OECD, 2019[19]) by OECD member countries in 2019 and the emergence of formal public sector innovation networks and strategies in many countries (Box 3.1).

The responsibility to develop and coordinate the public sector innovation system lies with various central government entities – prime minister’s offices (e.g., Germany); line ministries with horizontal coordination functions such as finance, treasury boards or ministries of interior (e.g., Canada, Iceland, Ireland, Korea, Finland, Norway, Slovenia); central innovation labs and units (e.g., Estonia, Denmark, Portugal) – or is shared between actors (e.g., Latvia, New Zealand, Sweden). Their coordination can be either centralised or decentralised (OECD, 2018[20]; 2021[1]) and they can have diverging functions, mandates and roles. For example, many central innovation units have purview over specific aspects of the innovation process (e.g., human resources and training, innovation diffusion, experimentation), but do not control all the relevant factors. They might also not be tasked with removing systemic barriers or creating drivers for public sector innovation.

When countries start to work on innovation strategies, it allows them to look at the agenda more systemically, connect strategic aims to public sector innovation, establish collaboration with stakeholders in the system and address desired aspects of the innovation portfolios (OECD, 2021[1]). While rudimentary, these functions supporting public sector innovation already exist in OECD countries and are becoming more systemic. This indicates a need to understand how innovation is happening across the public sector and how to steer its execution in practice.

OECD work on the systems level includes the Innovation Determinants model (OECD, 2018[20]) and its second-generation iteration: the Innovative Capacity Framework (Box 3.2). The latter includes a state-of-the-art overview of innovation barriers and drivers in the public sector, and is an evolving tool the OECD aims to test in country contexts through surveys and studies. The aim is to create more robust empirical evidence around these concepts and measure the effects of different variables that influence public sector innovation in different country contexts. (To date, the model does not outline how these variables influence the four facets of innovation, leaving another research gap to fill.) In parallel, the OECD is looking into anticipatory innovation governance and mission-oriented innovation through the recently created Mission Action Lab (MAL), which conducts facet-specific, system-level analysis, as in Finland (Tõnurist, 2021[21]) and through mission simulations and boot camps.1 As research in this area is still emerging, the following discussion is based more on hypothesis than empirical evidence.

As outlined in the in-depth analyses of each innovation facet (Chapters 4-7), different drivers, support structures, tools and methods, skills and capacities, and challenges spur and influence different types of innovation (Table 3.1). As described by Kaur et al. (2022[24]), the capacities and conditions required of public sector systems depend on the innovation facet. For example, creating an environment for enhancement-oriented innovation will likely be favoured by austerity, focus on service delivery, attention to behavioural insights, digitalisation and the like. In contrast, adaptive innovation could have strong environmental drivers, such as global crises and economic shocks experienced by the entirety of a public sector system, but might need legitimacy to create the structures and funding mechanisms for continuous testing and iteration. Mission-oriented innovation, meanwhile, will require both structural change in public sector organisations and cross-government coordination, as well as revamping procurement, budgeting and other systemic factors. Finally, anticipatory innovation is likely to demand the largest appetite for risk, dedicated spaces and creative evaluation mechanisms. Yet these different facets can all exist at the same time in the same system.

Supportive elements, such as performance reviews that include innovation, innovation funding rules, regulation, auditing and evaluation practices, influence different types of innovation in different ways. It is also possible for path dependencies and feedback to be so strong in certain organisational contexts that they override systems-level factors. For example, organisations in data-rich environments, like tax offices, have developed dynamic capabilities and lead in enhancement-oriented innovation through digitalisation (Lember, Kattel and Tõnurist, 2018[25]). Further, technology and digitalisation can create their own support measures and legitimatisation (Mergel, 2019[26]).

The assumption is that a diverse innovation portfolio is likely to deliver the best public outcomes in the short, medium and long terms.2 The challenge is to steer public sector innovation on the systems level without creating biases for innovation that does not align with the system or organisational need to innovate.

This means understanding which factors support one innovation facet or another. It also means deciding whether that crowds out needed innovation or favours practices the government wants to invest in for political reasons. However, innovation goals at the government level are rarely clearly defined or linked. This makes it difficult to compare the importance of one innovation facet over another, for example weighing up mission-oriented innovation against adaptive innovation. Environmental signals, such as crises and immediate threats, are therefore likely to bias the innovation portfolio, as shown in the effect of the COVID-19 crisis on innovation investments (OECD, 2020[27]).

One way to overcome this is to analyse the systemic factors and measures in place, and qualify their effect on innovation facets as potentially positive, negative or neutral to see if these can be balanced in some way. However, a lack of evidence around these assumptions make this analysis difficult. Furthermore, even on an organisational level, innovation portfolio tools and methods are lacking to help organisations make sense of their innovation portfolios and link them to factors that influence them on an individual, organisational or a systems level. This becomes more evident at the level of organisations/units that coordinate public sector innovation activities. With the Public Sector Innovation Facets model, OPSI works with countries to develop tools that organisations and public sector innovation coordinating bodies can use to make sense of innovation portfolios and the reasons behind them (Box 3.3). However, this work is only in its early phases and more evidence is needed to make the approaches actionable and draw conclusions.

The Public Sector Innovation Facets model provides a framework for considering whether an innovation system is aligned with its needs and goals, and offers ways to start building on the strengths and address the weaknesses of a policymaking system. It allows system stewards to draw on the approaches and capacities reflected in each organisation’s facets maps to support policy development and outcomes.

If public sector innovation is professionalising and becoming more institutionalised, it is not yet ingrained across policymaking at large. Most innovation in the public sector is not classified as such (e.g., under reforms, policy innovations and development projects) because its usual channels – labs, innovation units, etc. – rarely participate in bigger reform efforts (McGann, Blomkamp and Lewis, 2018[16]). Rather, links between innovation and government action are more apparent in bottom-up approaches where the gap is smaller between designers, citizens, service improvement and creative teams (Lewis, McGann and Blomkamp, 2020[29]). However, that does not mean innovation is unimportant in strategic policymaking or that the use of innovative tools and methods would not improve the quality of policy and its implementation.

Policymaking is a discrete, stage-gate process where bureaucrats tend to solve ‘known problems’ using policy analysis and formulation, decision-making, policy implementation, and monitoring and evaluation (Cairney, 2016[30]). While research generally describes it as a technocratic process, this assumption has received a lot of criticism (Cairney, Oliver and Wellstead, 2016[31]; Howlett, 2009[32]; Bogenschneider and Corbett, 2011[33]). Real life processes are much messier, from problem framing (based on evidence or emotion) to the ways policymakers learn or how feedback lags behind decision-making (Considine, 2012[34]; Head, 2013[35]). Nevertheless, rationalist and technocratic assumptions about policymaking and evidence-based agendas can make it difficult to integrate innovation into policymaking practices.

Nonetheless, there can be windows of opportunity for integrating adaptive, anticipatory, mission-oriented and enhancement-oriented innovation. The COVID-19 crisis raised interest in adaptive and anticipatory processes, although the specifics of how these can work in policymaking structures without the legitimising need of a crisis remain vague. Complex societal challenges and future-oriented policymaking break the mould of policy, expanding beyond organisational mandates both conceptually (into adjacent policy areas) and temporally (into possible future scenarios). They therefore present structural challenges for governments organised around mandates and grounded in public accountability. To address them, governments need commensurate governance supports for policymaking in these spaces.

Complex, horizontal societal challenges are the easiest area to make the case for integrating facet-specific innovation. The climate crisis and socioeconomic transitions call for systemic change in policymaking towards transformative policy design and appraisal (Mercure et al., 2021[36]). They require a holistic, whole-of-government approach, recognising that problems are interrelated and depend on both bottom-up and top-down innovation. This means, for instance, that countries’ climate goals can serve as a test case for a mix of enhancement, adaptive and anticipatory innovation: optimising the efficiency of existing power sources, looking to grassroots ideas and technological changes, and exploring uncertain but plausible scenarios. This requires, more alignment and coordination in policymaking and implementation, allowing governments to also enhance their innovation portfolio approaches. Some tactics connected to this are outlined in Table 3.2 below.


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