1. Governance and policy experimentation for industrial transition: Insights and considerations

For regions in industrial transition, traditional policy solutions – for example, pursuing technology-based innovation and research and development (R&D), channelling resources to large industrial firms, and designing and implementing actions in a sector-driven and/or top-down manner – have not always yielded the necessary results. This is evident in that industrial transition-related challenges, such as generating inclusive growth and improving regional well-being, have not disappeared despite past or present policy actions. This leads to the conclusion that the mechanisms being used to manage industrial transition – from governance arrangements to programming design and implementation – may need to be revisited and recalibrated or alternatively complemented or replaced with a new approach.

The OECD’s work with the European Commission and the regions and countries in industrial transition that participated in the European Commission Pilot Action on Regions in Industrial Transition, beginning in 2018, shed light on how territories can improve their industrial transition processes. One of the lessons learned from the 2018-19 phase of the project was the possibilities offered by experimental governance as a means of managing policy complexity. Experimental governance, which embeds learning-by-doing and trial-and-error processes into the policy design and implementation cycle, can help policy makers identify new ways of approaching the complexity of industrial transition.

The High Impact Actions (HIAs) developed by the eight regions and two countries1 that participated in the final phase of this project, from 2021-23, offer insight into how experimental processes can help territories advance in their industrial transition aims. This pilot action in and of itself was experimental precisely because it encouraged the participants to take a new look at how they tackle industrial transition, the mechanisms used, and the dimensions2 (e.g. jobs and skills, inclusive growth) targeted. It also supported them in the process of conceiving and implementing an experimental initiative, with relevant stakeholders learning as they went along.

The experimental approaches taken by project participants in developing and implementing their HIAs3 can provide initial insights into prospective pathways for managing industrial transition differently, both in terms of the six thematic dimensions that contribute to it and overall governance approaches. These insights, moreover, open the door for further study to identify how widely experimental approaches can be used to help meet industrial transition goals and advance regional development.

With respect to the six thematic dimensions contributing to an industrial transition and explored in this project (i.e. innovation and innovation diffusion, jobs and skills, small and medium-sized enterprises [SMEs] and entrepreneurs, a just transition to carbon neutrality, inclusive growth and smart specialisation strategies [S3s]), the one that was most frequently addressed through the experimental activities was supporting a just transition to carbon neutrality. The focal point of the experiments undertaken in this dimension varied, however. A number concentrated on promoting or generating a circular economy, either in plastics, energy or forestry, for example, or in a specific industrial sector, such as automotive. What also varied was how the experiment was implemented: for example, in two out of the ten cases (i.e. North Middle Sweden and Wallonia, Belgium), a challenge-based (or mission-oriented) approach was adopted.

Advancing innovation and innovation diffusion was another priority area, be it in traditional or artisanal sectors populated by small and micro-enterprises or family firms in remote or rural communities or rather in more R&D-intensive sectors such as hydrogen. Some of these initiatives (e.g. in Cantabria, Spain) experimented with a broader definition of innovation – one encompassing production and process innovations, for example – including as a means to reduce costs and increase competitiveness. The concept of societal innovation was also explored and embedded into the innovation dimension. In such cases, the experiment tested whether it is possible to address broader social challenges (e.g. outward migration or general demographic decline, climate change, the rising costs of energy) that can accentuate industrial transition challenges. One approach was to introduce innovation into less innovative firm ecosystems (e.g. in remote or rural areas or where the firms were predominantly micro- and small enterprises). At times, however, innovation and innovation diffusion were also embedded in other dimensions, such as inclusive growth or a just transition to climate neutrality (e.g. in Cantabria in Spain, Grand Est in France and North Middle Sweden).

A third popular dimension for applying an experimental approach was jobs of the future and skills. Here again, the angle and approach varied. In one instance, in the Great Manchester region, United Kingdom, the focus was on ensuring better quality jobs through soft tools, such as a carrot-and-stick incentive structure to encourage employers to lift their standards in terms of job quality. In Hauts-de-France, France, the focus was on generating incentives to encourage digital upskilling in SMEs, thereby helping them to build their capacity and prepare to carry out jobs of the future. In Centre-Val de Loire, France, the emphasis was on building a stronger managerial talent pool. In all cases, however, the interventions focused on employers and building their capacity to ensure an appropriately skilled and motivated workforce to support the industry needs of a transitioning region.

The other three dimensions – SMEs and entrepreneurship, inclusive growth and smart specialisation – were part of several HIAs but they were less frequently the driving objective. Supporting SMEs and entrepreneurship was a thread that ran throughout almost all of the HIAs. This may reflect the firm ecosystems of the participants. It may also reflect the fact that SMEs (as well as micro-enterprises) and start-ups were the categories of firms that needed the greatest level of support in order to be able to contribute effectively to the industrial transition. In this regard, it is notable that in few to no cases were larger firms targeted to participate in the experiments and, in some cases, when they were, the larger regional firms were not interested.

With respect to S3s, in many cases, the HIAs were aligned with the regional (or national, if applicable) S3. Whether or not HIAs were designed to advance the relevant S3 is less clear, as is the impact that the experimental initiatives will have on the S3s. Thus, while an experimental approach to S3 may not have been integrated into the initiatives, the experiments clearly supported dimensions used to advance industrial transition processes. That they do so also can support the value of experimentation with respect to the European Commission’s request that S3s follow a series of enabling conditions in the 2021-27 programming period for Cohesion Policy, among which are actions to manage industrial transition.4 This could be taken a step further with respect to ensuring effective entrepreneurial discovery processes, Enabling Condition 4: Effective functioning of entrepreneurial discovery process. It is not unrealistic to expect that the lessons learned through stakeholder engagement processes linked to experimentation could also build capacity for entrepreneurial discovery processes. Finally, many of the HIAs helped reinforce or increase the variety of firms involved in innovation and/or innovation diffusion, which aligns with Enabling Condition 5: Actions necessary to improve national or regional research and innovation systems.

The diversity of dimensions and actions taken highlights the flexibility of experimentation. Specifically, it can help address more than one thematic dimension of industrial transition at once, whether intentionally or not. An average of four thematic dimensions were addressed in each HIA. There is hope, then, that experimentation is a naturally supportive methodology for taking a more holistic or integrated approach to programming for industrial transition and that experimental initiatives may advance more than one transition objective.

The full pilot action brought to the fore the role that governance arrangements can play in advancing industrial transition. Now, in 2023, through the HIAs, the work reveals the importance of having appropriate governance arrangements for the experiment itself.

Planning and setting up the experiment was often challenging for a number of reasons. Many of the experiments were designed just before the start of the COVID-19 pandemic. In several if not all cases, this led to a delay in launching the experiments and, in other cases, it required a full shift in an experiment’s design. These delays and design adaptations, however, did not appear to affect the experiment’s objectives. Another noteworthy feature of the design phase was that while some HIAs initially targeted one category of firms, such as larger SMEs or SMEs more generally, these were not necessarily the firms that ultimately took part in the experimental process. Rather, on occasion, it was start-ups or micro-enterprises that showed greater interest in the experiment. Ensuring that HIAs are appropriately targeted to meet their beneficiaries’ needs is fundamental and, encouragingly, the experimental approach allowed for the regional project teams to quickly adapt to this new set of beneficiaries. This highlights that while there should be a commitment to the objectives pursued and the transition dimension being worked on, there should also be flexibility – both practical and in terms of mindset – with respect to how such objectives should be pursued.

The need to triangulate between a commitment to clear objectives and flexibility in project design and implementation was also a reality that was imposed by the framework conditions within which each HIA had to operate. In at least one case, regulatory frameworks would normally have made the experiment impossible. East and North Finland was able to work around this because of the experiment’s funding mechanism (a grant from the European Commission).

Administrative burdens – which are frequently aggravated by legislation or regulations at a national level – are a common area that many of the HIAs helped smooth over. They did so by finding partners with whom to implement the experiment, as in the case above, or by simplifying procedures or processes over which they had control. Of particular relevance here is the fact that all of the institutions through which the HIAs originated were national, regional or county government bodies. Thus, while there were framework obstacles, the participants found ways to adapt and work within these. For example, in one national case, the administrative burden for accessing funds available or channelled through the government was deemed too high to make the experiment truly feasible, which resulted in a partner being identified who could manage the funding aspect. Occasionally, this has already led to more lasting relevant change. For example, thanks to the East and North Finland experiment, a new way to fund SMEs with higher technology readiness level projects is in place.

Ensuring that experiments are appropriately resourced was frequently voiced by participants as a success factor. Dedicated staff – ranging from an individual to a full team – played a key role in supporting each HIA. Teams were typically guided by a decisive project leader and/or project manager as well as internal and/or external experts with specialised knowledge of the industrial transition dimension(s) targeted by the HIAs. In addition to the importance of policy makers having the necessary skills for project design and implementation, the experiments shed light on the fact that having a clear assignment of tasks and responsibilities, particularly when project teams are composed of individuals from different organisations, is another component of effective human resource support. In the case of the HIAs, clear responsibility assignment supported more co-ordinated action.

Properly funding the experiment seems self-evident. However, there are two aspects to this. The first is funding the institutional structure supporting the experiment, i.e. the individual or team mentioned above, along with elements that may be necessary to ensure implementation, e.g. putting surveys out in the field, hiring experts, travelling to more remote areas, etc. The second is providing funds as an incentive for firms to participate in the experiment. In many HIAs, implementation depended on putting out a project call to firms to participate in the experiment, for which financial incentives were part of the draw for participation. Non-financial incentives were also either explicitly or implicitly used to encourage participation (both explicitly, for instance by promising potential beneficiaries a more streamlined process for accessing funds, as well as implicitly, for instance by offering potential beneficiaries the chance to learn about ways in which they could improve their business performance).

One governance area that was not as well developed in the HIAs was monitoring and evaluation frameworks. In some cases, the implementing region or country would establish clear monitoring and evaluation mechanisms for the projects that supported the experiment. However, it was rarer to see a monitoring and evaluation framework developed for the experiment itself. This may either reflect a gap in the experiment’s design or an oversight. Measuring an experiment’s performance is an important factor in determining its success and whether it should be scaled up. Indeed, it is generally important to take a moment in the design process and establish the criteria that will be used to undertake an ex post evaluation of the experiment when it has reached the end of its lifecycle in order to determine success and scalability. This was frequently missing.

An important element in the governance of an experiment, and one which, notably, is not frequently discussed, is the concept of supported risks. Experimentation is inherently risky. Just as experiments can succeed, they can also fall short of the mark or fail completely. This may be one reason behind their often-limited use. There are ways to manage the risk factor of experimentation and, while these were not explicitly discussed or explored with the project participants, they bubbled up through different elements that shaped this project. First, it is important to ensure that the experiment has political support as well as support from other governmental and non-governmental stakeholders. The more agreement there is around the experimental initiative, the greater its political legitimacy. Second, when designing the experiment, it is important to draw on the collective expertise, knowledge and resources of a diverse range of relevant stakeholders in order to guide the identification of more innovative and effective solutions. By doing so, the knowledge and network supporting the experiment is larger and there is more social capital built around it. Third, highlighting how the experiment can support meeting the goals of higher-level strategies or other sector policies can resonate with other sectors and, at a minimum, gain their support for the proposed concept. Finally, sharing the results of a successful experiment as broadly as possible can help credibility for future experimental approaches and promote learning, which can encourage further experimentation.

While stakeholder engagement is frequently embedded into discussions of governance arrangements or practices, the extraordinarily large role it played in each of the HIAs makes it important to highlight it separately. No participant worked on their experiment alone. They relied heavily on deep and ongoing stakeholder engagement. Stakeholders could be broadly classified into two groups: i) other government stakeholders, usually at the same level of government but active in other sectors that can influence industrial transition; and ii) external stakeholders, including the private sector, civil society and non-governmental organisations, academia, thematic experts, business or trade associations, those implementing individual projects supported by the experiment, and citizens.

In most, if not all cases, stakeholder engagement began early in the experimental process. Internally, stakeholder engagement and communication generally relied on formal or informal conversations with peers or on other co-ordination mechanisms that were established to support the experiment, such as steering and working groups, which frequently mixed internal and external stakeholders. Externally, stakeholder engagement and communication often started with a mapping of relevant actors, followed by a direct consultation, be it through surveys, interviews or other means. This often gave the region an idea as to just how much knowledge and awareness there was regarding industrial transition, its challenges, the dimensions that could help advance it and why engaging in innovation was important. This information helped feed the articulation of experiments’ objectives and ensure they were realistic but still ambitious. It also helped policy makers understand the actual capacity of stakeholders to: i) engage with such a project; and ii) to engage with industrial transition overall. The stakeholder engagement initiatives employed in the different experiments also helped set objectives and priorities, and better target the audience for the experiment. Stakeholders were generally involved in the experiment’s design and implementation. This depth of engagement engendered other innovation opportunities, built new partnerships and helped give project teams an idea regarding scalability. In two cases (i.e. North Middle Sweden and Wallonia), the entire experimental approach was based on stakeholder engagement; in the other cases it was a critical component.

This heavy emphasis on engagement is another reason why it is important to have sufficient resources when undertaking an experiment. It requires a significant amount of co-ordination of different sets of actors as well as expertise in different engagement techniques. This latter point is fundamental as the success of an engagement process can depend on its design and a good understanding of how engagement works, which tools to use and when, and how to build the necessary capacity. It is also valuable for avoiding consultation fatigue and disillusionment.

The potential for scaling the experiments up (to other places) or out (to other sectors) was considered an indicator of whether the experiment successfully introduced a new policy or initiative to support industrial transition. In almost all cases, scalability was identified, mostly scaling up potential and in some cases scaling out. Scaling, however, will clearly require sufficient resources, time and political support. It is also important to recall that determining the outcomes, and ideally the impact, of an experiment on the challenges faced by a region in industrial transition takes time and so a final decision on scaling cannot be made from one day to the next. In addition, the experiments in question ran for a relatively short period (approximately 12 months) – which will have affected project outcomes and, by extension, scaling decisions. Political change may also influence whether an action is continued or scaled and is not to be forgotten.

Below are a series of simple recommendations with respect to experimentation for industrial transition arising from the work. Most are targeted to policy makers, regardless of whether they are regional or national, with a number specifically for higher levels of government and the European Commission.

  • Experimenting is a useful tool for managing industrial transition: It will require supportive framework conditions, sufficient human and financial resources, well-developed planning, monitoring and evaluation mechanisms and a willingness and capacity to engage with stakeholders. If these are not in place, the experiment is unlikely to work or provide any relevant insights for policy makers.

  • Pay attention to scope and scale: While a conclusion of this work is that experiments can be scaled up and/or out and can be a means to support industrial transitions elsewhere, the experiences shared in this report were limited to single experiments in one place. They show that experimentation can work but whether an experimental approach would be appropriate for all initiatives being used to advance transition is less certain.

  • Establish clear, realistic but ambitious goals: This is fundamental to any experiment, as it is the basis against which success will be measured and the future of the experiment will be decided. Moreover, clear goals not only provide direction but can also help to bring together stakeholders around an initiative by creating a shared vision. They can also facilitate effective communication about the experiment, which can help to garner public support for and interest in the results of the initiative.

  • Understand human and financial resource needs: When designing the experiment, it is important to take stock of the expertise that will be needed to ensure implementation and where it can be found. It is just as important to identify the financial resources necessary, the mechanisms that can ensure their availability and the merits of providing financial incentives to prospective participants.

  • Build monitoring and evaluation frameworks: Monitoring the experiment is a continuous process and evaluating its effect can take time. Performance measurement frameworks, however, should be determined at a project’s outset, with appropriate indicators that have been determined following effective stakeholder consultation and are backed by readily-accessible data.

  • Be willing to take risks and have a flexible mindset: The risk of failure is inherent to any experiment. Experiments do not always work out as planned and it may be necessary to shift and adjust the experiment in response to rapidly changing circumstances. This need not lead to failure and it may also, in fact, lead to success. However, any readjustment to the experiment should be conducted in close consultation with relevant stakeholders while ensuring that a clear line of sight on the pre-agreed objectives is maintained throughout.

  • Be able to actively engage with stakeholders: Engagement is a capacity in and of itself – be it on the part of the engager or the stakeholders. Engagement is also a commitment to act based on its outcomes and should be part of the full design, implementation and evaluation process of any experiment. This includes being transparent with stakeholders about what has or has not worked while communicating successes, however modest or incremental.

  • Experiments are an investment that can pay dividends: A successful experiment for industrial transition can build government capacity, spread innovation, advance inclusive growth and contribute to achieving a range of strategic and sector objectives (e.g. in climate, digitalisation, energy, labour markets, skills), including the priority objectives linked to EU Cohesion Policy. Moreover, experiments are a cost-effective way of generating information on whether a policy intervention can achieve a specific objective, and/or whether it is desirable or even possible to scale up or out.

  • Use experiments to reconsider framework conditions: Often, framework conditions and administrative processes hold back innovation and innovative governance. Since experiments are limited in time and scope, policy makers can use their results to assess the potential benefits of adjusting framework conditions (such as laws or regulations), as well as the risks of doing so. For instance, experimentation can provide pathways to test whether minor legislative or regulatory adjustments for the express benefit of specific groups, such as micro- and small enterprises or start-ups, may promote their participation in the economy. Such experimentation can be done, for example, by:

    • Working with a region wishing to implement an experiment where specific framework conditions or administrative burdens have been perceived by stakeholders as negatively affecting success.

    • Establishing a defined period of time or a specific funding opportunity to which framework or administrative requirements could be adjusted for a targeted group of potential project beneficiaries while measuring the results.

  • Tackling territorial divides improves trust in government: Further analysis of and support for regions in industrial transition can lay the foundations for tackling the geography of discontent, which in turn can help to improve trust in government.

  • Welcome experimentation as a viable lever for policy design and implementation: Continue to promote and facilitate experimentation that reinforces the various dimensions supporting industrial transition, for example by:

    • Establishing regulations that support (or do not discourage) experimentation as criteria for responses to innovation project calls funded by EU Cohesion Policy or other funds.

    • Emphasising the need for and facilitate the development of robust monitoring and evaluation mechanisms to track the effects of policy experiments effects, including the core challenges facing regions in industrial transition (e.g. relatively high levels of unemployment, low gross domestic product, low labour productivity, low life expectancy).


← 1. The regions are Cantabria (Spain), Centre-Val de Loire (France), East North Finland (Finland), Grand Est (France), Greater Manchester (United Kingdom), Hauts-de-France (France), North Middle Sweden (Sweden) and Wallonia (Belgium). The countries are Lithuania and Slovenia.

← 2. The nine dimensions are divided into two sets. One set is for governance arrangements that are particularly important to industrial transition and experimentation: framework conditions; strategic programming, implementation and evaluation; and stakeholder engagement. The second set is dedicated to thematic dimensions that support industrial transition, namely: innovation and innovation diffusion; jobs (of the future) and skills; SMEs and entrepreneurs; a just transition to carbon neutrality; inclusive growth; smart specialisation.

← 3. Chapter 5 of this report highlights the main findings and provides links to case studies of each HIA.

← 4. In the 2021-27 programming period for Cohesion Policy, the European Commission requested that S3s be updated and respond to the seven “enabling conditions”: i) Up-to-date analysis of bottlenecks for innovation diffusion, including digitalisation; ii) Existence of competent regional/national institution or body responsible for the management of the smart specialisation strategy; iii) Monitoring and evaluation tools to measure performance towards the objectives of the strategy; iv) Effective functioning of entrepreneurial discovery process; v) Actions necessary to improve national or regional research and innovation systems; vi) Actions to manage industrial transition; and vii) Measures for international collaboration.

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