6. Adaptive innovation

Adaptive innovation requires realising that things happen which do not fit with what is expected. It starts with the question: How might evolving circumstances change how we do [X]? An organisation strong in adaptive innovation plays with and tests new approaches to a changing operating environment. In this case, the purpose of innovation might be the discovery process itself, driven by new knowledge or the changing environment. When the environment changes (sometimes due to innovation by others, such as new technology, business models or practices), innovation that helps adapt to the change can become necessary. An example is the use of social media by government organisations to interact with citizens, initially through bottom-up initiatives. Sometimes, this type of innovation challenges the status quo and existing missions, which can create internal tension.

Growing interdependencies and fast-paced change characterise today’s globalised world. In the last 15 years, crises such as the economic crisis and global migration crisis demonstrated how systems in place can be challenged by situations with many unknowns. Moreover, technological change impacts the way governments interact with citizens. To date, these are still unforeseeable. More recently, COVID-19 tested governments’ ability to cater to the needs of citizens while trying to bring the pandemic under control (Janssen and van Der Voort, 2020[1]; Moon, 2020[2]). The pandemic also emphasised the need for governments to react quickly and in the face of extreme uncertainty.

In a fast-changing world, government needs to be responsive while providing stability for societies and communities in the face of uncertainty. To deal with a dynamic environment and improve (digital) service delivery to citizens, governments seek agile and adaptive approaches (OECD/MBRCGI, 2020[3])

To understand trends in adaptive innovation, the OECD Observatory of Public Sector Innovation (OPSI) conducted research and invited public servants to discuss their experiences and give examples of adaptive innovation in the public sector. To understand the research themes in this type of innovation, a review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method (Moher et al., 2009[4]).

This section of the report highlights the themes of adaptive innovation in the public sector. Insights are provided on: (1) General description of the facet; (2) Main drivers of enhancement-oriented innovation in the public sector; (3) Enabling factors; (4) Tools and methods; (5) Skills and capacities needed; (6) Policy and public service challenges; and (7) Unanswered questions. The next section describes how adaptive innovation is discussed in the research and how it relates to concepts such as agile governance.

To highlight trends in adaptive innovation, it is necessary to understand the definitions of adaptive innovation used in the literature. The results show that no overarching definition of adaptive innovation exists. Instead, there are three different approaches (Table 6.1) to adaptation: (1) the capacity to be adaptive to change; (2) as an innovation approach to respond to change; and (3) as a governance framework that allows adaptation and innovation to happen.

A large body of research approaches adaptation as the need for public organisations to build adaptive capacity, mainly in the face of extreme events. Here, adaptive capacity is described as the outcome of activities aimed at lowering risk (Reinhardt and Drennan, 2019[5]), reducing vulnerability (Crosweller and Tschakert, 2021[6]; Zhang, Welch and Miao, 2018[7]), and strengthening the resilience of organisations and societies (Drennan and Morrissey, 2019[8]; Van Dooren, 2011[9]). Most efforts to build adaptive capacity appear in reaction to specific issues at hand, such as the need to adapt to climate change.

Moreover, building adaptive capacity can take an organisational and an ecosystems view. The former is connected to the need for public organisations to maintain organisational fit with stakeholder preferences:

“We define adaptation as the organisational capacity to implement changes that restore or maintain a fit with the ever-changing expectations and values of key stakeholders. We thus define adaptation as a goal-oriented activity, and not as the random outcome of small changes” (Boin et al., 2017, p. 665[10]).

Within public organisations, the individual level is important to adaptive capacity. Employees influence the adaptation of public organisations and must be considered in adaptive approaches (Buick et al., 2015[11]; Matthews, Ryan and Williams, 2011[12]; Plimmer et al., 2021[13]). Particularly, when managers show responses that are not adaptive, they are likely to decrease the overall level of organisational adaptation (Matthews, Ryan and Williams, 2011[12]). Moreover, adaptation to build resilience is also discussed on an individual level. Here, it is presented as one component of employee resilience (Plimmer et al., 2021[13]), defined as follows:

“[An adaptable employee] reacts with proper urgency in threatening situations, finds “workarounds” by engaging and building trust within networks, uses specific skills such as stress management and re-prioritisation, turns problems inside-out to find new approaches, [and] can act without having to know the whole picture” (Plimmer et al., 2021, p. 5[13]).

Public services often depend on and are connected in complex relationships with providers in the private and third sectors. Adaptation as a capacity therefore needs to be looked at from an ecosystems perspective, as services may fail when partners cannot adapt at the same rate. Moreover, in the face of external change, especially environmental risks, vulnerability might not be evenly distributed among actors. Therefore, building adaptive capacity does not end with public organisations but considers different sectors and stakeholders, as adaptation appears differently depending on “the purpose, context, and scale of particular actions, whether at the household, community, sector, region, or country scale” (Va Dany, Bowen and Miller, 2015[14]). Here, research highlights public organisations’ need to consider community-based solutions to adaptation (Drennan and Morrissey, 2019[8]).

Where adaptation is understood as adaptive capacity, the concept is largely a way to reduce harm and strengthen resilience, rather than intending to produce innovations. However, innovation is likely to emerge as a by-product of adaptive measures. Moreover, building adaptive capacity is embedded in an ecosystems view that includes different stakeholders and sectors.

A small body of research (three of 74 research articles, excluding grey literature) understands adaptation as a pro-active approach to innovate. Here, the goal of adaptive innovation is to produce more effective and functional public measures. Moreover, adaptive action links to the entrepreneurial logic applied in international development or to reform processes (Andrews, 2015, Cummings, 2015, Greve et al., 2020). The rationale behind adaptive innovation is to enhance the effectiveness and functionality of reforms and measures (Andrews, 2015[17]; Cummings, 2015[18]; Greve et al., 2020[19]).

The evidence indicates that a body of literature connects adaptation to entrepreneurial logic (Cummings, 2015[18]), understood as:

“Rather than a predesigned programme with a log-frame of expected outputs and outcomes, […], entrepreneurial logic allows iterative learning and adaptation, and for objectives to be adjusted according to experience” (Cummings, 2015, p. 317[18]).

At the same time, results to date show that adaptation as an innovation approach is mainly applied to global development (Andrews, 2015[17]) and reform studies (Cummings, 2015[18]; Greve et al., 2020[19]).

Adaptive governance is characterised by “decentralised decision-making, efforts to mobilise internal and external capabilities, bottom-up (and top-down) decision making, wider participation to spot and internalise developments, and continuous adjustment to deal with uncertainty” (Janssen and Van Der Voort, 2016[21]). The concept is used in system theory, complex systems science and institutional theory, among others, connected to sustainability and climate adaptation research (Chaffin, Gosnell and Cosens, 2014[22]; Rijke et al., 2012[23]). In the public sector, adaptive governance is applied to digital government, notably driven by fast-changing developments in information and communications technology (ICT) disrupting environments and requiring governments to adapt (Janssen and Van Der Voort, 2016[21]).

Adaptive governance provides a framework for studies of governments’ efforts in a digitised environment (Janssen and Van Der Voort, 2016[21]; 2020[1]; Mcbride et al., 2019[24]; Soe and Drechsler, 2018[25]; Wang, Medaglia and Zheng, 2018[26]). In this context, adaptive governance is associated with other approaches to deal with uncertainty, such as agile governance (Janssen and Van Der Voort, 2016[21]; Soe and Drechsler, 2018[25]; Wang, Medaglia and Zheng, 2018[26]). The concepts are sometimes used interchangeably, but they are not the same (Janssen and Van Der Voort, 2016[21]; Soe and Drechsler, 2018[25]; Wang, Medaglia and Zheng, 2018[26]). The next section distinguishes between them.

Research shows an overlap between mentions of adaptive and agile approaches, especially in the digital government context. But few studies argue that they are the same (Greve et al., 2020[19]).

Responding to flaws in traditional approaches to software development in government, agile software development is described as the foundation for discussion of agility in government (Mergel, Gong and Bertot, 2018[27]). In 2001, seventeen software developers from the private sector came together to define the building blocks of the Agile Manifesto (Beck et al., 2001[28]), using the following definition:

“We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value: Individuals and interactions over processes and tools; Working software over comprehensive documentation; Customer collaboration over contract negotiation; Responding to change over following a plan” (Beck et al., 2001, p. 29[28]).

A growing body of research understands agility as a project governance approach that consists of several dimensions and is embedded in organisational change processes (Dittrich, Pries-Heje and Hjort-Madsen, 2005[29]; Mergel, 2016[30]). Within the digital government context, most studies understand agility from a micro-level perspective embedded in a broader adaptive governance framework. Here, agile governance can result in higher levels of adaptiveness (Janssen and van Der Voort, 2020[1]; Mergel, Gong and Bertot, 2018[27]; Wang, Medaglia and Zheng, 2018[26]).

Agile governance is an “organisational culture and methods of collaboration to achieve higher levels of adaptiveness” (Mergel, Gong and Bertot, 2018, p. 291[27]).

The OECD takes a holistic view and defines agility as embracing uncertainty and expecting to continuously learn and improve approaches based on what is learnt in order to prioritise adding value to users as quickly as possible (OECD, 2020[32]).1

By starting small, with phases designed to build understanding through exploration, teams can research, prototype, test and learn about the needs of their users before building a service. This allows them to fail quickly and correct course in response. A service only goes live once enough feedback is gathered to demonstrate that needs are met and the service works. Fundamental to this is a continued understanding of the user’s experience in a cyclical model of delivery. This allows policy and services to reflect needs, based on research conducted with users, considering diverse samples of the population and insights from societal data. Having knowledge of the issues at stake allows policy development to be guided by the needs of the public rather than top-down solutions devised in government offices.

Collectively, evidence suggests that agility, with its roots in software development, is mainly discussed in the digital government context. However, a growing body of literature uses agility as a holistic framework. This development can be observed in practice: Canada, Denmark, Italy, Japan, Singapore, the UAE and UK signed world’s first Agile Nations agreement. The agreement explores agile innovation for the regulatory environment and policy making (WEF, 2020[33]). Moreover, Japan applies agile governance as a holistic framework to keep up with fast-changing technologies and enhance trust in a digitised society.

Characteristics defined as components of agility, such as iteration (Beck et al., 2001[28]; Koski and Mikkonen, 2015[34]; Mergel, 2016[30]; 2021[35]) are also found in studies of adaptation. For example, problem-driven-iterative-adaptation (PDIA) applied in reform processes incorporates features of agile methodology (Andrews, 2015[17]; Cummings, 2015[18]). In more recent studies of public management reform, agility is examined together with adaptivity (Greve et al., 2020[19]).

There is a need for conceptual clarity concerning the differences between agile and adaptive approaches. Further, not all discussion of agile and adaptive methods are related to innovation. As most studies integrate “agile” into “adaptive”, and this report is concerned with innovation, the following sections refer only to “adaptive innovation”.

Three clusters that drive governments’ adaptation practices appear in the literature: (1) environmental; (2) organisational; and (3) individual. Each of these operates at a different level (Table 6.2). Environmental drivers lie outside the public organisation and describe the context in which public agencies operate. Organisational drivers are inherent to the capacities and features of the organisation. Individual drivers provide information about the characteristics of individuals within public agencies that drive adaptation.

Environmental drivers of adaptive approaches lie outside the organisational boundaries of public agencies. Demands – either political, such as the demand to reduce emissions (Liu et al., 2013[36]), or citizen expectations concerning the speed of service delivery (Mergel, 2016[30]; Mergel, Gong and Bertot, 2018[27]) – are the most frequent drivers on the environmental level. Political demands refer to “the power dynamics and incentives that lead bureaucratic and political leaders to authorise or encourage more adaptation […]” (ODI, 2021[37]). Political support, both individual, in terms of individual political leadership (Greve et al., 2020[19]; Ubels, Bock and Haartsen, 2019[38]), and supporting policies, drive the uptake of adaptive approaches (Kalesnikaite, 2019[39]; Mergel, 2016[30]). Fitzgerald and Lenhart (2016[40]) show that political support from higher levels can stipulate local action for adaptation. Moreover, citizen demands play a significant role in the uptake of adaptive approaches in government, such as to restore citizen trust in government and increase responsiveness (OECD, 2014[41]).

Environmental and economic threats, such as flooding (Drennan and Morrissey, 2019[8]), hurricanes (Earle, 2018[42]) or health-related crises like COVID-19 (Moon, 2020[2]), stimulate adaptive action. A large body of literature deals with climate change-related threats that drive adaptation (Juhola, 2013[43]; Kalesnikaite, 2019[39]; Pot, Dewulf and Termeer, 2020[44]; Susskind and Kim, 2021[45]). It shows that environmental threats pose a particular challenge to the local level, as the first line of response usually occurs on-the-ground (Duijn and Van Buuren, 2017[46]; Kalesnikaite, 2019[39]; Reinhardt and Drennan, 2019[5]; Susskind and Kim, 2021[45]).

Collaboration often drives adaptive innovation and refers to work with stakeholders, such as NGOs and local communities (Chu, Anguelovski and Carmin, 2016[47]; Kalesnikaite, 2019[39]; Va Dany, Bowen and Miller, 2015[14]; Wang, Medaglia and Zheng, 2018[26]), and among governmental actors (Kalesnikaite, 2019[39]; Soe and Drechsler, 2018[25]). Working with stakeholders on the ground helps pick up signals early and address evolving needs.

Organisational drivers refer to characteristics within public organisations, such as their structure and culture (De Vries, Bekkers and Tummers, 2016[49]).

Financial resources correlate with the adaptive capacity of public agencies (Kalesnikaite, 2019[39]; Zhang, Welch and Miao, 2018[7]). In the case of Cambodia, Va Dany and Miller (2015[14]) show that government organisations reported to not have sufficient funding to implement adaptation activities related to climate change. Moreover, insufficient financial and technical resources appear to pose a particular challenge to local governments (Susskind and Kim, 2021[45]).

Technical facilities also influence the adoption of adaptive approaches. Research argues that ICT systems need to allow integration with other systems and should be aligned with organisational change (Brewer, Neubauer and Geiselhart, 2006[50]; Dittrich, Pries-Heje and Hjort-Madsen, 2005[29]; Gong and Janssen, 2012[51]).

Finally, adaptive approaches require resources in terms of time, as for experimentation with new approaches (ODI, 2021[37]). The lack of time during day-to-day operations is as a barrier to adaptive innovation.

Adaptive approaches require an organisational culture that allows teams to experiment (Fitzgerald and Lenhart, 2016[40]; Pinheiro, Maurer and Sillito, 2008[53]), and incorporates continuous improvement (iteration) and learning-by-doing (Koski and Mikkonen, 2015[34]; Pot, Dewulf and Termeer, 2020[44]). Moreover, as agile and adaptive approaches require collaboration – be it with the user or other stakeholders – an organisational culture that supports teamwork promotes the adoption of adaptive approaches (Wisitpongphan and Khampachua, 2016[54]).

Certain characteristics of leaders are demonstrated to drive the uptake of adaptive innovation. For example, leaders can provide teams the opportunity to experiment with work practices and methods (ODI, 2021[37]; Pinheiro, Maurer and Sillito, 2008[53]). Moreover, they can support bottom-up initiatives of teams who want to experiment with new approaches (Berkani, Causse and Thomas, 2019[55]; Mergel, 2016[30]). Furthermore, leadership provides the overall vision of how these methods can be useful to the team/organisation and their projects (Dittrich, Pries-Heje and Hjort-Madsen, 2005[29]; Wisitpongphan and Khampachua, 2016[54]).

The literature pays less attention to drivers of adaptive innovation at the individual level. Most frequently examined are individuals’ openness and their knowledge/skills. Individuals’ openness to participating in agile and adaptive innovation relates to their willingness to participate (Matthews, Ryan and Williams, 2011[12]; Senapathi and Drury‐Grogan, 2021[56]). For example, individuals’ willingness to participate is challenged when too much change occurs at the same time (Dittrich, Pries-Heje and Hjort-Madsen, 2005[29]; Senapathi and Drury‐Grogan, 2021[56]). In challenging times, personal resources, such as employee resilience can foster successful adaptation to a changing environment (Plimmer et al., 2021[13]).

Several publications also consider the professionalism of individuals related to their job-related knowledge and skills, as in their ability to make fast decisions (Berger, 2007[57]) or manage stress (Plimmer et al., 2021[13]). Whereas leadership is especially important in the initiation process of agile and adaptive approaches, individual drivers were mostly studied after the decision to adopt agile practices had been made. Hence, public servants have an important role once the approach is implemented (see section on skills and capacities for a more detailed discussion.)

Several studies discuss the structures and programmes necessary to support adaptive innovation in the public sector. Adaptive innovation requires (1) tolerant and decentralised organisational structure; (2) infrastructure (3); (4) relationships and partnerships; (5) space for experimentation; and (6) evaluation/feedback.

Many studies mention organisational factors as barriers to the adoption of adaptive approaches. Berger (2007[57]) argues that hierarchy and a command-and-control structure hinder the adoption of adaptive approaches in government. Organisational structures such as public procurement (Russo et al., 2018[58]; Wisitpongphan and Khampachua, 2016[54]), processes (Gong and Janssen, 2012[51]; Mergel, 2016[30]) and organisational responsibilities (Clarke, 2020[59]; Liu et al., 2013[36]), as well as project orientations (Maccani et al., 2020[60]; Strojny, 2016[61]) need to be aligned with adaptive approaches. In contrast, Janssen and van der Voort (2020[1]) argue that organisational structures provide the stability decision makers need to carry out adaptive approaches. Hence, tension exists between the needs to act adaptively and maintain stability.

Adaptive governance is described as a framework that allows adaptation and adaptive innovation to happen. It is characterised by “decentralised decision-making, efforts to mobilise internal and external capabilities, bottom-up (and top-down) decision making, wider participation to spot and internalise developments, and continuous adjustment to deal with uncertainty” (Janssen and Van Der Voort, 2016, p. 4[21]). Adaptive governance is supported by decentralised governance structures and processes in public organisations because decentralised governance structures emphasise public servants’ autonomy in their day-to-day work (ODI, 2021[37]).

Research refers to the technical and organisational features of infrastructure needed to support adaptation. Technical infrastructure enables an organisation to sense demands (Chen, 2009[69]) and provides authorities with the information necessary to act (Chatfield and Reddick, 2018[70]; Mackay et al., 2019[71]). For example, based on their case study of small island states, Mackay et al. (2019[71]) provide insights into the relevance of information infrastructure for climate change adaptation, as access to high-quality information is crucial.

In the face of external changes, especially environmental risks, vulnerability might not be evenly distributed among actors. Therefore, building adaptive capacity does not end with public organisations but considers different sectors and stakeholders.

Network arrangements are thus a support structure for adaptation, serving varied purposes. On one hand, members of networks can actively collaborate to improve their collective adaptive capacity (Juhola, 2013[43]). On the other hand, they can benefit from knowledge and/or best practices from other network members (Fitzgerald and Lenhart, 2016[40]; Kalesnikaite, 2019[39]). In her study of sea-level rise adaptation efforts of US governments, Kalesnikate (2019[39]) finds that “institutions of higher learning can help plan local action, while city-to-city collaboration can help in later stages, such as the implementation process” (Kalesnikaite, 2019, p. 880[39]). The author finds that building relationships as a support structure is particularly important to enable adaptive innovation at the local level:

“In the absence of financial support and technical advice from higher levels of government, collaborative action provides an alternative route for city governments to serve their communities. Because solutions to adapt to sea level rise are site-specific, cities can take advantage of local knowledge by working not only with other municipalities, but with nonstate stakeholders as well” (Kalesnikaite, 2019, p. 881[39]).

Another support structure for adaptive innovation is the space and permission for experimentation in public sector organisations when it comes to piloting new practices. Governments are adopting laboratories as new approaches to policy and service design (Fuller and Lochard, 2016[72]; McGann, Blomkamp and Lewis, 2018[73]). One type, innovation labs, are publicly funded units that reside outside the formal institutional boundaries of government (Timeus and Gascó, 2018[74]), and can be rooms for experimentation. Following successful experimentation, approaches can be transferred to the practice of government (Tönurist, Kattel and Lember, 2017[75]). McGann, Blomkamp and Lewis (McGann, Blomkamp and Lewis, 2018[73]) show that user-centred approaches such as design thinking and agile methods are frequently observed in innovation labs.

The literature examines the concept with a focus on digital government (Soe and Drechsler, 2018[25]). However, laboratories as units where measures are tested before being adopted on a large scale are also discussed in other contexts, like eco-districts in urban planning (Fitzgerald and Lenhart, 2016[40]).

New organisational units, such as digital government units, introduce new work practices into government, like Agile, which were not part of the standard toolbox of public administrations (Clarke, 2020[59]). Introducing flagship projects important for the public sector organisation’s field of work can be a way to test how adaptive innovation could be better supported in existing organisational structures. Some countries try to support experimentation more structurally, with varying levels of success (Box 6.8).

Governments learn from experience to develop adaptive capacity. Earle (2018[42]) reports that the US government’s response to Hurricane Sandy in 2012 was more efficient than to Hurricane Katrina in 2005. The government was able to act more quickly and coordinate more efficiently with stakeholders such as volunteer groups. Previous challenges were incorporated as learning to adapt to future disasters.

Either evaluation mechanisms or learning facilitate building adaptive capacity. Evaluation mechanisms help organisations keep track of successes. Learning happens through evaluation, for example when a new work practice is introduced bottom-up (Berkani, Causse and Thomas, 2019[55]), when strategies need to be readjusted (Fitzgerald and Lenhart, 2016[40]), or for overall project governance (Crawford and Helm, 2009[83]). Learning as a principle can also be part of a broader framework of adaptation that enables institutional learning. Drawing on environmental and ecological studies, Carrey and Harris (2015[84]) discuss a double-loop-learning process2 as part of the adaptive management cycle, where learning is fostered by evaluating instruments (technical learning) as well as the incorporation of constant evaluation into the overall monitoring process (institutional learning).

The literature on adaptation highlights two groups of tools: tools for collaboration and tools for anticipation. Much literature focuses on methods and tools for collaboration, such as agile and design thinking. Knowledge about the application of these methods in the public sector is largely based on studies that deal with public services, particularly in the digital government context, and less in literature that deals with environmental challenges. Moreover, as there is an overlap between literature on adaptive and agile approaches, studies have focused on agility as a methodology. Agile methodology refers to a project-governance approach that centres on collaboration and iteration, and on tools that incorporate agile principles, mostly developed in the private sector.

User-centricity lies at the core of agile and design thinking approaches (Bason and Austin, 2021[85]; Beck et al., 2001[28]). It aims to develop services and products that serve their users and take their needs into account through research. The agile methodology provides constant feedback from users concerning the result, aiming for “radical collaboration with the client in each phase” (Mergel, 2016, p. 516[30]). In design thinking, a human-centred approach is applied broadly to public service and policy issues (Bason and Austin, 2021[85]), whereas agile methodology focuses on the specific user at hand.

Agile practices and their underlying principles gained considerable interest in research and practice. They promise higher levels of adaptiveness (Janssen and van Der Voort, 2020[1]; Mergel, 2016[30]; Soe and Drechsler, 2018[25]; Wang, Medaglia and Zheng, 2018[26]). With roots in software development, agile practices have become established in non-software projects as well (Mergel, Gong and Bertot, 2018[27]; Strojny, 2016[61]).

The traditional approach to governmental projects has been the waterfall approach. But this mode of planning – where one project phase is strictly executed after another and project outcomes are predefined – is not suitable to governments operating in a dynamic environment, such as digital government (Janssen and Van Der Voort, 2016[21]). In contrast, agile practices’ focus on “user involvement, iterative and incremental development, [and] constant adaptation to the situation at hand” provide an alternative to waterfall project governance (Koski and Mikkonen, 2015, p. 41[34]). A common area where agile practices are applied is public procurement (Mergel, Gong and Bertot, 2018[27]; Soe and Drechsler, 2018[25]).

Several methods apply the principles established in the Agile Manifesto (Beck et al., 2001[28]), including Kanban3 (Senapathi and Drury‐Grogan, 2021[56]), Lean4 (Mcbride et al., 2019[24]) and Scrum (Strojny, 2016[61]).

Design thinking is a frequently observed approach in the public sector (Clarke and Craft, 2018[88]; Mintrom and Luetjens, 2016[89]). Bason and Austin (2021[85]) identify three dimensions in which design thinking is applied as an innovation approach in the public sector: They find that public administrators apply design thinking to (1) explore the problem space, (2) generate alternative scenarios and (3) enact new practices (Figure 5.5). In essence, design thinking centres on user perspectives and aims at “radically new solution paths” (Senapathi and Drury‐Grogan, 2020[90]). Therefore, it challenges existing approaches to public service delivery and public governance (Bason and Austin, 2021[85]).

Clarke and Craft (2018[88]) describe the underlying principles of design thinking (Clarke and Craft, 2018, p. 112[88]):

Designs should not be envisioned as static outputs, but rather are best crafted with an appreciation for the reality that they will need to adapt and adjust over time;

Designers and the targets of design are not strictly rational actors, and that behavioural insights into each of these players’ worldviews, practices, and rational constraints produce more robust policy solutions; and

Design is often a pluralistic activity, involving a diversity of actors within and outside government.

Adaptation requires picking up signals to prepare for the future. Hence, it is not surprising that adaptation is closely linked to anticipatory practices and tools (Chapter 7). Scenario approaches, which are one of the most common strategic foresight tools, are particularly linked to adaption.

In addition to tools that aim for collaboration with clients and stakeholders, scenario-planning helps public administrations build anticipatory capacity in the face of climate change (Rickards et al., 2014[91]). Based on a study of projects for climate change adaptation in Australia, Rickards et al. (2014[91]) discuss scenario-planning as an approach that recognises the uncertainty that comes with climate change adaptation. In contexts of high uncertainty, scenario-planning enables decision-makers to incorporate a range of possible futures (Rickards et al., 2014[91]).

The literature on adaptation reveals the skills needed from leadership and public servants, however, no systematic approach is observable.

In hierarchical systems, such as government, leadership plays a significant role creating space for new approaches like adaptive innovation (Andrews, 2015[17]; Fitzgerald and Lenhart, 2016[40]; Mergel, 2016[30]; ODI, 2021[37]). Beyond this formal role, leadership styles shape employees’ adaptability to change (Buick et al., 2015[11]). Evidence shows that, to build commitment, leaders must communicate a clear vision of what is ahead and how new approaches will influence the practices of the organisation (Chatfield and Reddick, 2018[70]; Dittrich, Pries-Heje and Hjort-Madsen, 2005[29]; Janssen and van Der Voort, 2020[1]; Matthews, Ryan and Williams, 2011[12]). Furthermore, leadership must be willing to take risks (Bishop and Savoury, 2004[93]; ODI, 2021[37]).

Moreover, adaptive approaches require a participatory leadership style (Brewer, Neubauer and Geiselhart, 2006[50]). Crosweller and Tschakert (2021[6]) suggest a relational leadership model that incorporates compassion and empathy in the face of extreme events such as disasters. The authors argue this can be supported by a communitarian, rather than an individualist approach to strengthening resilience. In the public sector, one manifestation is the growing acknowledgement that “hero-innovators” rarely exist and “distributed heroism” is required to realise and sustain innovation (Meijer, 2013[94]).

Managers’ behaviour is decisive as to whether adaptive approaches such as design thinking can be sustained. In some cases, leadership turnover can lead to a departure from an innovative approach (Bason and Austin, 2021[85]). The case of France’s Central Bank (Box 6.13) describes how leadership at different levels (middle management and directorate) sustained agile approaches in the organisation. Middle managers provided space for experimentation and were responsible for making sure that teams evaluated their successes. The evaluation results were then presented to the director of the Central Bank who decided they should become part of the core practices of the organisation.

Employees’ influence on a public organisation must be considered in adaptive approaches (Buick et al., 2015[11]; Matthews, Ryan and Williams, 2011[12]; Plimmer et al., 2021[13]). On a personal competence level, individuals must show willingness to participate in adaptive innovation practices (Matthews, Ryan and Williams, 2011[12]; Senapathi and Drury‐Grogan, 2020[90]). On a professional competence level (i.e., where adaptation is linked to job-related tasks), design thinking and agile approaches require short cycles where decisions are made by cross-functional teams. This poses a challenge to public servants as it shifts hierarchical decision-making (Berger, 2007[57]).

Programmes are emerging in different countries as part of innovation management support (Table 6.4). Moreover, a mindset change is necessary to move from traditional approaches to new approaches that favour adaptation (Rose and Cray, 2010[95]; Senapathi and Drury‐Grogan, 2020[90]). Plimmer et al. (2021[13]) show how adaptability connects to employee resilience. They conceptualise employee resilience based on three components: network leveraging, learning and adaptability. Adaptability is defined as a combination of job-related skills, such as stress-management and building trust with different networks.

All the studies reviewed suggest a role for skills in relation to adaptive approaches. Moreover, the evidence suggests that adaptation requires new competences for leadership and public servants. However, research has paid more attention to the skills and capacities of leadership than those of public servants.

While adaptive innovation occurs in public administrations around the world, the challenge is balancing adaptation and stability/resilience, and building a bridge from knowledge to practice based on experiences and conditions for success, as well as on the pitfalls when introducing approaches to adaptation.

Public administrations deal with adaptation in different ways and contexts. Some of these link to strengthening resilience and building adaptive capacity in the face of challenging situations, while others aim to produce innovation. Adaptation research and practice apply interdisciplinary knowledge to adjust to new policy and public service challenges. Public agencies that deal with environmental challenges bring knowledge about building strong communities, partnerships and adaptive capacity, and strengthening the resilience of systems in face of threats. Meanwhile, public agencies that apply adaptive innovation work practices provide experience with how methods such as agility, user-centricity and human-centred design can be incorporated into government practices to enhance public service delivery.

But adaptability can sometimes come at the price of stability in public administration practice, especially when there is a need to act quickly (Janssen and van Der Voort, 2020[1]). Adaptive governance is characterised by “decentralised decision-making, efforts to mobilise internal and external capabilities, bottom-up (and top-down) decision making, wider participation to spot and internalise developments, and continuous adjustment to deal with uncertainty” (Janssen and van Der Voort, 2020, p. 4[1]). One way to balance adaptability and stability is to introduce an adaptive governance framework that incorporates fast processes and avoids fragmentation at the same time.

Adaptation can generate many different responses and approaches to experimentation and testing. However, it can be challenging to incorporate successes and lessons learned back into broader organisational practice. Practice and research show that adaptive innovation is often contained within specific remits (such as digital units, innovation labs, or one-off projects) rather than forming part of core practices in public sector organisations. Cycles are a challenge for practitioners. To avoid over-generalising some sort of evaluation mechanism at the instrument level, the institutional dimension has been discussed in the literature (double-loop-learning process). Here, adaptive management has been applied as a possible approach as it provides a basis for organisations to apply a double-loop-learning process (Rickards et al., 2014[91]).

There is no common definition of ‘adaptive’ innovation observable in the literature. Adaptation is understood as (1) the need to build adaptive capacity and strengthen resilience, (2) an approach to produce innovation, and (3) a governance approach that allows adaptation and innovation to happen. Not all these are connected to innovation: whereas innovation can occur as a by-product to adaptive capacity, it appears as a goal of public measures and policies in innovative governance. Literature that deals with adaptation as an innovative practice shows an overlap with mentions of agile methods (for example, in the digital government context and in reform studies). Adaptation is discussed in several contexts of the public sector, such as environmental studies, global development and digital government. These areas have in common that many public services are dependent on providers in the private and third sector and are often connected to these in complex relationships. However, much of the research in the different research streams (up to now) appears disconnected. Further research is needed to disentangle existing terminology and research, and provide a clearer definition adaptive practices and relation to innovation in the public sector context.

Drivers for adaptive innovation in the public sector appear on different levels: environmental, organisational and individual. Little research has focused on individual success factors of adaptation in the public sector. More precisely, little is known about the skills and competences of public servants who are not in a leadership role. An open question for further research concerns the types of skills and competencies public servants need for adaptive innovation in the public sector to thrive.

Several studies discuss structures and programmes needed to support adaptive approaches in the public sector. The results show that no overarching understanding of these exists for each approach. Moreover, some structures – such as units that allow for experimentation, and relationships and partnerships – lie outside the formal boundaries of public organisations. In contrast, organisational structures inherent to public organisations appear as barriers to adaptive innovation. An open question for further research concerns how public sector organisations can support adaptive innovation structurally.

Literature on adaptation notes two main tool groups: tools for collaboration and tools for anticipation. Much literature focuses on methods and tools of collaboration, such as agile and design thinking. Here, collaboration refers mostly to public sector efforts to produce design innovations. Knowledge of these methods in the public sector is largely based on studies that deal with public services, particularly in the digital government context and more research is needed on the tools and methods that are applied for adaptation purposes in other areas, such as environmental challenges.


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← 1. This is reiterated in the Recommendation of the Council for Agile Regulatory Governance to Harness Innovation (OECD/LEGAL/0464) and Practical Guidance on Agile Regulatory Governance to Harness Innovation (C(2021)99/ADD1).

← 2. “Double-loop learning occurs when errors are corrected by changing the governing values and then the actions” (Argyris, 2002, p. 206[97]).

← 3. Kanban principles “Start with what you do now, agree to pursue improvement through evolutionary change, respect current processes, existing roles, responsibilities, and job titles, encourage acts of leadership at every level – from individual contributor to senior management” (Senapathi and Drury‐Grogan, 2020, p. 3[90]).

← 4. “The core idea behind the lean development cycle is that the organization should be able to learn as quickly as possible about whether or not their product will be well received […]” (Mcbride et al., 2019, p. 7[24]).

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