This report presents a case study of applying the OECD anticipatory innovation governance framework to develop and manage anticipatory innovation ecosystems as vehicles for knowledge generation, innovation governance and co-ordinated action to achieve policy goals. Part I establishes the case for anticipatory innovation ecosystems and sets out how they can be governed through a multi-level approach. In Part II, opportunities and challenges for applying this approach in the Latvian context are identified, and recommendations are made for developing anticipatory innovation ecosystems in Latvia.
The Public Governance of Anticipatory Innovation Ecosystems in Latvia
Abstract
Executive Summary
The fast-paced change occurring in domains as different as artificial intelligence, biotechnology and environmental protection presents governments with both opportunities and challenges. While innovations resulting from the rapid development of new technologies have the potential to contribute to prosperity and address grand challenges such as climate change and inequality, their impacts on society, individuals and the environment are uncertain. In this context, the ability of the public sector to proactively govern innovation is increasingly important so that it can be directed towards pathways that are likely to deliver collective benefits, and away from negative consequences.
This proactive shift can be supported by anticipation, a process through which actors use foresight approaches such as futures scenarios to systematically ask questions about plausible futures to inform public action in the present. The leap from asking questions about the future to using the answers they generate can be challenging. The OECD anticipatory innovation governance (AIG) framework sets out mechanisms that governments can use to create the conditions for effective anticipation and proactively steward change though experimentation and innovation.
Informed by research undertaken as part of a two-year partnership between the OECD and the Investment and Development Agency of Latvia (LIAA), this report is a case study of the potential application of the AIG framework to develop and manage anticipatory innovation ecosystems as vehicles for knowledge generation, innovation governance and co-ordinated action to bring about preferred futures. The focus is on the role of government in building the right structures, mechanisms and capabilities to design and develop effective anticipatory innovation ecosystems. In an anticipatory innovation ecosystem, actionable knowledge about the future is created through activities that enable a collective consideration of future needs, opportunities and challenges by ecosystem partners from research, industry, government and civil society. This knowledge can help ecosystem partners innovate and governments become more proactive in their policy design. The relationships established through the ecosystem development process also lay the foundations for co-ordinated action by ecosystem partners to achieve outcomes that would not be possible for them individually, thereby building innovation capacity.
Anticipatory innovation ecosystems can be helpful in a range of policy areas which require transversal coordination, including addressing skills gaps and development and the challenges of aging populations. Given Latvia’s interest in developing innovation ecosystems for ‘Smart Specialisation’ in technological domains where the country has current and potential advantages, the report focuses on the application of anticipatory approaches to inform technological innovation.
Key findings
The report consists of two parts. Part I establishes the case for anticipatory innovation ecosystems and sets out how they can be governed through a multi-level approach. In Part II, opportunities and challenges for applying this approach in the Latvian context are identified, and recommendations are made for next steps.
Part I outlines two nested levels of governance for the development of effective anticipatory innovation ecosystems. The first, ‘micro-governance’ concerns the engagement of relevant stakeholders and the ongoing facilitation of collaboration within the ecosystem. The micro-governance of ecosystems is sustained by four processes: the engagement of diverse stakeholders; an orientation around shared innovation goals; collaboration; anticipation, learning and adaptation. Government can play an important role in initiating and monitoring these processes; guidance on this is provided in Chapter 2. The second, ‘higher’, level, ‘meso-governance’, concerns the functions, practices and structures that facilitate the relationship between government policy and the innovation ecosystem. Seven functions for government in enhancing meso-governance are identified: orchestrating, framing, championing, market building, funding and regulating. Government actors can explore how best to exercise these functions to provide co‑ordinated support to ecosystems.
Part II begins with an exploration of the Latvian context before proposing a three-phase process for developing anticipatory innovation ecosystems in Latvia. The initiation phase sets out an overarching purpose and roles for the government support of ecosystems. During the development and maintenance phase, activities to establish micro-governance processes among ecosystem partners are initiated. The exit phase focuses on the approaches that government can use to determine the ongoing value of their support of an ecosystem and identify opportunities to withdraw.
The report concludes with findings and recommendations to help Latvia improve its governance of anticipatory innovation ecosystems and ensure that its government can benefit from the futures-oriented knowledge they generate to become more proactive in a fast-changing and uncertain world. These are summarised below:
Understanding and expectations of anticipatory innovation ecosystems are not well aligned or communicated. Educating key stakeholders, communication and developing a coherent programme theory of change can help drive engagement and a shared understanding.
The level and type of support provided to anticipatory innovation ecosystems in Latvia is not adequate for their needs: Regular assessment of ecosystem needs through meso-governance functions can help government actors in the Innovation and Research Governance Council identify and co-ordinate support.
The connections among existing resources, initiatives and funding and the anticipatory innovation ecosystem programme are underdeveloped: LIAA and the Innovation and Research Governance Council could consistently work to identify relevant resources and funding opportunities.
Structures and processes for feeding insights generated by anticipatory innovation ecosystems into public sector decision processes are not sufficient: LIAA could analyse ecosystem insights and produce regular reports on future opportunities and threats. The Innovation Research and Governance Council could feed this knowledge back into policy.
The knowledge and capacity of ecosystem partners to facilitate anticipatory innovation ecosystem methods is limited: Latvia could develop LIAA’s capacity to design and facilitate relevant activities that enable the development of micro-governance processes and the generation of anticipatory knowledge.
Ecosystem partners require clarity about the purpose of ecosystem activities: Each ecosystem could collaboratively develop a theory of change so that the orientation of activities around shared goals can be established and success can be monitored.
Resources need to be targeted to support the development of innovation ecosystems: LIAA could prioritise a limited number of ecosystems based on its capacity to support them and engage external and ecosystem stakeholders to provide additional resources.
Key ecosystem stakeholders are not consistently engaged: Latvia could communicate high-level commitment to ecosystem support by assigning an ecosystem leadership function to a senior executive in LIAA, and ensure that engagement plans for stakeholders are developed.
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