The ecology of open innovation units: adhocracy and competing values in public service systems

Abstract There have been concerted efforts to encourage innovation and to foster a more innovative and “open” culture to government and public service institutions. Policy and service innovation labs constitute one part of a broader “open innovation” movement which also includes open data, behavioral insights, digital services, data science units, visualization capabilities, and agile and lean methods. This article argues that we need to step back and better understand these “ecologies” of innovation capabilities that have emerged across public service institutions, and to recognize that as fellow “innovation” traveling companions they collectively seek to transform the culture of government and public service institutions, producing more effective, efficient and tailored policies and services. This article introduces analytic frameworks that should help locate policy and innovation labs amidst these other innovating entities. First, it delineates the various units and initiatives which can be seen as committed to new ways of working and innovating in public service institutions, often relying on “open innovation” rhetoric and approaches. Second, it shows how – despite the diversity among these entities – they nevertheless share similar attributes as “adhocracies” and are located as part of a broader movement and class of organizations. Third, we locate these diverse OI entities amidst broader public service systems using the Competing Values Framework. Fourth, this article situates the challenges confronting OI units developing and sustaining or broadening niches in public service systems. Finally, it identifies future research questions to take up.


Introduction
There have been concerted efforts to bring more innovation and, indeed, foster a more innovative and "open" culture to the government and the public service institutions that serve them. Policy and service innovation labs constitute one part of this movement. Indeed, open innovation can mean different things to advocates inside and outside government, with proponents variously focusing on open data portals, behavioral insight units, digital services units, service and innovation labs, data science units, visualization capabilities, and more. Notwithstanding the particular focus of innovators and those who study them, we need to step back and see that "ecologies" of innovation capabilities have emerged within and across public service institutions, seeking to introduce new ways to develop policy, deliver services, monitor results, engage citizens and clients, and generally become more experimental and agile. Indeed, the goal of open innovation stewards and "activists" is to transform the culture of government and public service institutions in order to take full advantage of the digital era, producing more effective, efficient and tailored policies and services.
The goal of this paper is to introduce analytic frameworks that should help locate policy and innovation labs amidst fellow "innovation" traveling companions and to identify research questions to take up using these perspectives as points of departure. First, we delineate the various units and initiatives which can be seen as committed to new ways of working and innovating in public service institutions, often relying on "open innovation" rhetoric and approaches. Second, we show howdespite the diversity among these entitiesthey nevertheless share similar attributes as "adhocracies" and are located as part of a broader movement and class of organizations (Mintzberg 1979). Third, it seeks to locate these diverse OI entities amidst broader public service systems using the Competing Values Framework (Lindquist and Marcy 2016). Fourth, this article situates the challenges confronting OI units developing and sustaining or broadening niches in public service systems.
This article draws on earlier research focused on locating behavioral insight units (Buttazzoni 2018;Buttazzoni and Lindquist 2019), but our purpose here is not to report on those exploratory empirical findings. Instead, we were asked to share our broader analytic frameworks in the service of this special issue on policy and service innovation labs. Our hope is that this will provide a promising basis for a more nuanced analysis of the strategies that the leaders of different kinds of OI adhocracies use to create and establish niches in public service systems. Even with the launching of a waterfront of several innovation initiatives, it remains that shifting the culture of large-scale public service systems will be difficult given the system's emphasis on control and rules. Despite the recent wave of announcements, pilots, and good intentions in support of innovation in public service systems, the open innovation movement is very much in its infancy and the associated capabilities are relatively small compared to the larger organizations and system in which they have been planted, nurtured, and seek to influence.

New players in public sector open innovation systems
The term "open innovation" (OI) refers to a cluster of techniques and approaches intended to improve the operations, services and policies of the government in the digital era. Most of the lever, in some measure, new capabilities afforded by digital tools, while others, such as service and innovation labs, while assisted by digital tools, have recombined more traditional approaches from various fields. This section sets out the different kinds of OI capabilities found in government or public service systems and identifies some commonalities among them. What follows takes a closer look at eight distinctly different capabilities which are viewed as part of what we call the "open innovation" ecosystem, and yet many observers, when looking at possibilities and challenges in open innovation in the digital era, refer only to one or a few at most. Our purpose here is not to provide a detailed account of each capability, but rather to delineate and distinguish among them, and to show how they relate.
Open data platforms Open data units are part of a trans-government movement seeking to take advantage of digital technologies and move the tons of data that governments collect, and make it more available to users inside and outside government (e.g. see "Open Data 101" principle here). This aspect of open innovation is not about manipulating "big data" per se, but rather, creating digital platforms or portals to making different lines of data available to a variety of different users and, where possible, working to ensure that such data is "good data" (Clarke and Margetts 2014). For the government it is about identifying its holdings of data, assessing its quality and sensitivity, and then making it available through a portal and platforms accessible to users. A premise underlying these units and the broader movement is that government collects far more data than it can possibly use at public expense, so it should make it available to outsiders who have the skill and see potential which government may not. It is a means for creating value and innovation.
Innovation, policy, service, and design labs Largely spurred by the success of Denmark's MindLab when it was a government, multi-department sponsored innovation capability, and by the many presentations and publications of its progenitor (Guay 2018;Bason 2010Bason , 2016, innovation, policy, and service labs have proliferated internationally (Gryszkiewicz, Lykourentzou, and Toivonen 2016;Jones 2016;McGann, Blomkamp, and Lewis 2018), as well described in this special issue. The creation of labs and many of the techniques used by them are not new-having been used for decades to develop designs and prototyping in fields such as architecture, planning, and engineering-but seem to be relatively novel in government or public organizations. The techniques used by labs focus on better understanding the needs of users, whether by means of observation or engagement through interviews and workshops and then developing designs and prototypes in collaboration with users and a variety of service delivery partners. It is essentially a bottom-up approach to think about alternative service delivery models and policy frameworks. These units can be located in central agencies, client-serving ministries across public service systems, or in larger departments and agencies with big program delivery systems.
Behavioral insight units Over the last decade, behavioral insight units have proliferated around the world, inspired by the burgeoning field of "behavioral economics" and psychology (John 2014;OECD 2017), interest in the use of "nudges" by firms and governments in various facets of marketing and service delivery, and the pioneering work of the UK Cabinet Office's Behavioral Insights Team during the 2010s (e.g. Thaler and Sunstein 2008;Ariely 2008;Policy Horizons, 2017). Such interventions are dedicated to providing better information, designing better forms, smoothing service provision, identifying different ways to pose questions, reverse onus, and use default positions to encourage users and citizens to move in desirable directions, though leaving choice (Government of Canada, 2017). Behavioral insight (BI) units are usually housed in central agencies but can serve any policy or service delivery domain. Along with the focus on better understanding human decision-making and designing forms and services with that in mind, BI units seek to do so with controlled experimentation (with RCTs as the gold standard). Inherent in this approach are iteration and rapid learning, even with the strong preference for systematic and controlled methods (Haynes, Service, and Goldacre 2012).
Big data/data analytics shops Interest in big data has increased dramatically over the last two decades because of the proliferation of sensors and streams of data available to organizations, the rapid decline in cost of analyzing, storing, and analyzing data, and the arrival of software tools to analyze and display findings (e.g. Davenport 2014; World Bank 2017). The turn toward big data is related to public and private organizations making more data sets available to researchers, and the rise of social media and the need of marketing firms and intelligence agencies to monitor, sift through and find patterns in masses of data. The data that can be analyzed is incredibly varied, including scientific measurements, information packets, representations of concepts and variables (such as social or economic data), images, texts, and documents. Disciplines, textbooks, consulting practices, software companies, and university programs have proliferated to undertake this work, initially developing at the intersection of the fields of computing, engineering, graph analysis, data management, cognitive psychology, software development, human-computer interface, etc. (e.g. Friendly 2007 ;Tufte 1990;Lindquist 2015). Governments have been creating more data analytics capabilities, usually associated with particular program or service delivery areas in government with significant streams of digital data, or contracting out such work to firms and universities.
Visualization Related to big data and data analytics are the fields of "information visualization" and visual analytics (e.g. Chen 2006; Ward, Grinstein, and Keim 2010; Ware 2004), graphics and visual display (e.g. infographics among other things), and visual strategic facilitation, all dedicated to finding ways to capture and display complexity (Lindquist 2015(Lindquist , 2016. All of them have benefited from the emergence of digital tools, but can be traced back decades, if not hundreds of years, in diverse scientific and professional fields. Here we are less interested in the tools per se and more in the new units inside government dedicated to producing different kinds of visual representations. These can be created to assist with conveying particular kinds of data, such as sharing visualizations for big data (i.e. streams of scientific, financial, social media, or website user data), or generating infographics for the purposes of capturing the results of workshops and innovation labs, providing tactile information sliders to sift through information, or even moving more toward assisting with communications of findings. These skills are typically in short supply and difficult to justify for anyone program of ministry, so pockets of skills or small units are located centrally or highly specialized to work on certain kinds of visual representation, or the work is contracted out.
Open government initiatives Many governments, partially in response to new sensibilities generated by the digital era, have been declaring themselves as committed to "open government" and the sharing of data and information, continuing the long-held value that democratically elected governments should be as transparent as possible. In principle "open government" is a broader concept and commitment than providing "open data" though the former is often centered on the latter. A Government of Canada website defined "open government" as a "governing culture that holds that the public has the right to access the documents and proceedings of the government to allow for greater openness, accountability, and engagement" (Canada 2017). The open government movement is international in scope, furthered through the Open Government Partnership, which not only aims to increase access to data and new technologies, but also to further civic participation and access to information in the form of files, documents, and other records which matter to citizens and those who seek to hold the government to account (Open Government Partnership 2011; Canada 2021). The aspiration is that governments should be "open by default," not waiting to be asked but proactively releasing as much data and information as possible. This aspiration, however, challenges and is often constrained by the need to maintain the privacy of personal or corporate records and cabinet or council deliberations.
Digital service units The exemplar for this class of organizations is the UK Digital Government Service, which was established in 2011 and has since been emulated in many national and sub-national jurisdictions around the world (Clarke 2017;Eaves and McGuire 2018). These units are usually established at the center of government to further government-wide initiatives to encourage or force departments and agencies to improve and coordinate the design and roll-out of digital platforms across governments. Such units are dedicated to driving the shift to provide services online developing common protocols and standards, a common look and feel across platforms, and removing overlap and duplication of registration and multiple points of contact for individuals and organizations seeking to interact with the government. Such units can function as cheerleaders for "open innovation" and "open government," beyond simply encouraging and regulating investments in the digital platforms of government, but that depends on the jurisdiction and what other "open innovation" capabilities are sharing the space. So, for example, the Canadian Digital Service operates independently from the Impact and Innovation Unit in the cabinet office of the Canadian government, and other entities such as innovation and service labs and data analytics groups in departments and agencies, but may collaborate with them on certain projects.
Lean units Although many of the principles of lean management have been developed and used over recent decades, and a key handbook in the field was published in 2000 (Pyzdek 2018), these principles and associated tools took on new resonance for governments after the 2008 financial crisis and, more recently, efforts to introduce digital innovation in public sector organizations. Lean principles built off total quality approaches in manufacturing (Ries 2011;Leifso 2021 forthcoming;Marte, Holmemo, and Ingvaldsen 2016). Lean repertoires constantly seek out and implement solutions for reducing costs and reducing service times for clients. Lean units usually have core staff with Lean or Sigma Six credentials who can be deployed as strategic leads and trainers for operational units in departments and agencies (Pyzdek 2018). Fully implanting these approaches in government may have some challenges (Rasmussen and Nugent 2015;Radnor and Osborne 2013;Janssen and Estevez 2013).
Agile movement Like lean and many other OI units and approaches, there have been growing calls for adopting agile methods in the public sector (Mergel, Ganapati, and Whitford 2021). We should recall, though, that early calls for agile methods drew on a variety of well-established approaches associated with product development and manufacturing, focused on getting innovation to market more quickly in a targeted way, rather than awaiting full-scale roll-out of a product (Yusuf, Sarhadi, and Gunasekaran 1999;Guasekaran et al. 2019). Other calls for agile approaches arose from experience with implementing software and hardware IT solutions (see Beck et al. 2001, the Agile Manifesto), focused on rolling out solutions in a more iterative, continuous, collaborative, and user-involved way, rather than relying on established project-management repertoires, informed by timely performance monitoring (Smartsheet 2019). As the government has become more committed to introducing digital solutions, it is not surprising that advocates started calling for agile approaches to be applied to government more generally, to better respond to evolving environments and to more quickly take up new opportunities. This broader view of possibilities beyond digital solutions calls for the government to develop an anticipatory stance to address longer-term trends along with short-term responsiveness, invoking adaptive and scaling up strategies, and relying on collaborative and customized approaches, all with an eye toward the ultimate outcomes (Parker and Bartlett 2008).
Together, these innovation units and OI movements critique traditional top-down, linear, bureaucratic, and risk-averse approaches to developing policy, designing services, interacting with the public and stakeholders, overseeing implementation, and monitoring outcomes and performance. There is some overlap across them and their leaders often see the other capabilities as having a common cause. As change-oriented units, they are usually located in central agencies or larger departments, and often colocated with other units with innovation mandates. Each has distinctive responsibilities, techniques, and capabilities for furthering innovation, with different objectives and repertoires, but organization theorists would see them as sharing similar strategic challenges and structural forms working in many different complex dynamic environments, assembling and mobilizing experts in relatively small units to accomplish specific goals and tailor products on a project basis, requiring flexible leadership and relying on internal and external collaboration as well as flat structures, and deeply committed to innovation.
What follows provides different frameworks for locating and analyzing the challenges and work of OI units in public service systems. Section 3 shows how the concept of adhocracy can illuminate how we think of these units, while section 4 shows how their culture may challenge and be challenged by larger public service systems.

Open innovation units as adhocracies
The concept of adhocracy sprung into the organization theory lexicon with Mintzberg's (1979) seminal The Structuring of Organizations, which identified several generic organizational forms-simple, professional bureaucracy, machine bureaucracy, divisionalized, adhocracy-as well as hybrid forms. Borrowing the notion of "adhocracy" from Alvin Toffler, Mintzberg observed that innovation "of a sophisticated variety takes place in environments not readily understood" (p. 434) and requires a "very different structural configuration, one able to fuze experts drawn from different disciplines into smoothly functioning ad hoc project teams" (p. 432). For Mintzberg, building new knowledge and skills requires recruiting new expertise and artfully combining it with extant expertise, often from different parts of the organization and, in this sense, adhocracies often function as a boundary-spanning entity. The adhocracy form seeks to encourage flexibility, adaptation, and creativity to deal with environments characterized by uncertainty, ambiguity, and information overload, and to produce innovative products, adapt quickly to new opportunities and build emergent strategies (i.e. the need to create new products in the aerospace, software, film, and consulting sectorssee Mintzberg and McHugh 1985).
Mintzberg distinguished between operating, administrative and temporary adhocracies, but it is useful to consider how they manifest in the public administration contexts: Mintzberg and McHugh (1985) pointed to operating adhocracies for film production agencies such as the National Film Board; Lindquist (1993) showed how the transition teams which political parties establish in anticipation of taking power can be understood as temporary adhocracies; and Rourke and Schulman (1989), Desveaux, Lindquist, and Toner (1994) and Lindquist (2005) described how creating new policy and citizen engagement capabilities to launch comprehensive policy innovations, particularly after the failure of existing structures to deliver, can be seen as operating or transitional adhocracies. Although adhocracies must have connections to larger sponsoring organizations and their hierarchical authority structures, adhocracies themselves usually do not sport centralized power or authority relationships, instead opting for flat structures focused on tasks and projects. OI adhocracies differ, though, because they are not focused on designing and implementing "top-down" policy or furthering transitions in government; rather, they focus on improving the operations and services of government with a variety of different methodologies.
Most OI capabilities seem to be comprised of stable administrative adhocracies, comprised of small groups of core staff with expertise and repertoires for working with different mixes of partners inside and outside government depending on the project at hand, usually facilitating several projects at a time. Every kind of OI unit has its own specific objectives, task structures and expertise, and repertoires not only for carrying out core tasks but also for linking to key stakeholders and partners inside and outside of government. In other words, the work of innovation, policy, or service labs is different from that of behavioral insights or open data platform units, etc. (explored further in Buttazzoni and Lindquist 2019).
Accordingly, different issues and research questions arise when analyzing OI adhocracies, which are distinctive from policy and transition adhocracies in the public sector. The literature tends to focus on producing innovation per se, as opposed to the challenge of relatively small entities trying to develop niches as new entities in complex organizational systems, nor their strategies for establishing credibility, ensuring longerterm survival, and deepening roots and maturing as a set of innovation capabilities in a public service system. The salience of the adhocracy model for understanding open innovation capabilities in the digital era seems clear, especially since a clear aspiration of OI adhocracies is not only to produce innovations in service delivery, engagement strategies, and policy frameworks but also to change the culture of the larger systems of which they are apart.

Adhocracy in public service systems: the competing values framework
Every government and its associated panoply of organizations constitute a complex public service system, comprised of diverse kinds of organizations with different missions, objectives, size, the scope of responsibility, and cultures, often with considerable organizational diversity in the larger departments and agencies. Different organizations and sub-units are designed to further certain goals or protect certain values ranging from control to performance to integrity to innovation, and a much longer list could easily be generated (Wilson 1989). Adhocracies furthering innovation are one class of organizations in public service systems while, by design, others are expected to implement government policies and programs, monitor and audit performance, and provide stability and predictable expertise. The oft-espoused ambition of open-innovation adhocracies is to change the culture of public service systems, but how should we think of this challenge?
Public sector systems, then, can be seen as landscapes filled with packets of competing mandates, values, and culture. Although much has changed in public service systems, many of these capabilities have long existed. For example, "transparency" and "accountability" have long been associated with government entities in democratic systems, even as public servants are to protect the confidences of ministers and cabinets, as well as the privacy of individuals and organizations whose information the government holds. Lindquist and Marcy (2016) argued that the Competing Values Framework (CVF), developed by Quinn (1988) and several colleagues over the years, provides an elegant rendering of this complex reality. Quinn (1988) sets out the origins and rationale for the CVF, which has been published in several books tailored for different levels of leaders in organizations (executives, middle managers, and new managers learning about the fundamentals of leadership and management) (e.g. ).
Quinn enumerated an extensive list of values and competencies essential for furthering the goals of organizations, clustered them into categories of values and competencies which either run together or sit in juxtaposition or tension with other values and competencies, which were grouped according to whether they were internally or externally focused, and whether they were more about stability and control or flexibility and discretion ( Figure 1). From this Quinn and colleagues identified four quadrants describing distinct organizational cultures or "moralities" associated with different value clusters (hierarchy, clan, market/performance, and adhocracy) along with four associated leadership orientations (controlling, collaborative, competing, and creative), summarized in Figure 2. These concepts can be used to describe organizations as a whole, but also illustrate that different parts of organizationseven smaller nonprofit organizations-can have programs and divisions which have distinctive cultures and commitments to more of these values than others.
Fundamental insights from the CVF are that all of these values and competencies are material to the health and performance of organizations, that striking new and creative balances across existing and new value and competency mixes is an essential responsibility of leadership (as Selznick argued in the 1950s), and that leaders and reform movements focusing only on select values and objectives do so at their peril, especially where complex public service systems are concerned. OI adhocracies can be seen as the latest wave of effort, using new analytic tools and social technologies, to promote innovation in public service systems.
OI methods and capabilities are dedicated toward innovation, experimentation, and agility, dedicated to introducing new approaches for doing the work of government. As summarized in Figure 1, the CVF would see such proclivities as consistent with the open systems quadrant, attaching value to insight, adaptation, innovation, external orientation (including levering outside talent), and influencing other parts of the larger organization. Furthermore, as noted in Figures 1 and 2, and consistent with our earlier discussion, the CVF depicts the associated leadership and animating values of open innovation groups as consistent with the adhocracy form from theories of organization, including finding new ways to secure necessary resources.
The CVF does more than assign OI adhocracies to the innovation space; it also serves to locate them amidst other competing value clusters and suggests that different organizationsand, indeed, different parts of organizationswill have different organizational cultures built around them and the specific tasks they carry out. 1 This is particularly relevant for public service systems, which are large-scale, multi-organizational institutions serving duly elected governments and larger societies. In democratic systems, elected governments oversee authorities and responsibilities that are distributed throughout the system. Indeed, that public service systems have significant Weberian hierarchical structures is not simply a matter of scale; they also derive from Westminster governance principles that assign authorities and responsibilities to elected governments at the apex. With responsibilities, budgets, and accountability distributed from the top of the system, hierarchy values and organizing are predominant features of the system. Moving away from the bottom-left quadrants in Figures 1  and 2 toward the clan, performance, and adhocracy quadrants will always be an uphill battle-in the words of Bakvis and Juillet (2004), it will be like "pulling against gravity." Likewise, governments have huge investments in and cultures built around human resource systems aligned with hierarchical structures, not to mention performance systems build on enacting approved policy and programs, as opposed to doing something different. To succeed, OI adhocracies must establish themselves against considerable odds and find ways to co-exist, survive, secure support from, and influence leaders and organizational capabilities associated with the other quadrants.

Open innovation adhocracies: building niches, influencing environments
Locating OI adhocracies in larger public service systems and usually more proximately in specific departments and agencies, puts the matter of how these kinds of organizations establish themselves in these broader organizational contexts. Mintzberg (1979) noted, "perhaps the most important single role of [its] top management … is that of liaison with the external environment" (p. 448), and, even though innovation cannot be predicted and has limited yields (i.e. genuine breakthroughs may occur only with a relatively low percentage of projects), OI adhocracies must forge relationships, secure resources, build credibility, reduce barriers to innovation, and demonstrate value in broader performance-oriented and budget-constrained environments. Here we identify strands of literature with the potential to further frame and provide the basis for further lines of research.
First, organization theorists, using ecological metaphors, have long thought about how organizations develop and deepen niches, build credibility and legitimacy in broader organizational domains (domain consensus), and find ways to secure resources and reduce dependency (Stinchcombe 1965;Thompson 1967;Meyer 1975;Van de Ven 1976;Pfeffer and Salancik 1978;Hannan and Freeman 1989;Singh, 1994a, 1994b). Meyer (1975) cast an organization's domain essentially as a "claim," which can be narrow or broad, and not only asserted but defended over time through consistent service and acquisition of resources. The relevance for OI adhocracies is that not only do executives in public service contexts have to authorize the establishment of such entities, but the leaders of OI adhocracies also have to launch and build niches for their new organizations as "start-ups" and then sustain them.
Second, the business of OI adhocracies is innovation, and over many years scholars have identified no shortage of organizational characteristics associated with successful innovation. One early and widely cited review (Damanpour, 1991) found that successful innovation often coincided with internal skill specialization, functional differentiation, technical knowledge, "slack" resource availability, and administrative intensity. Other research has suggested that fewer hierarchical approvals, decentralized decisionmaking, and informal processes were common among innovative firms (Moon, 1999). Other studies shifted focus toward understanding environmental and partnership factors like leadership skills, perceived credibility, and mission clarity in building trust among members from partner organizations (Gabris, Golembtewski, & Ihrke, 2000). Collaborative, inter-organizational innovation processes have been described, interestingly, as "open innovation" (Wernerfeld 1984;Mowery 2009;Gassman 2006). These newer open innovation paradigm models the components of multi-stakeholder innovation projects typically pursued by open innovation adhocracies in the public sector.
Third, there is the matter of how OI adhocracies, once created, demonstrate their value to executive sponsors and central agencies, as well as the partner they work with, which often fund their projects. As set out above, in public service systems this has to be done in culturally unreceptive and tough fiscal environments, particularly when the "outputs" of OI adhocracies really constitute policy ideas or pilots, candidates for possible conversion in broader public policies. Assessments of OI adhocracy performance should be proximate: at one level, demonstrating that specific projects have been completed and, at another level, monitoring the proportion of which actually get converted into bona fide public policies. Bearing in mind the rhetoric and aspirations of many OI adhocracies, there is yet a third level of performance and value to consider: whether and to what extent OI adhocracies manage to influence larger organizational cultures in public service systems (see Buttazzoni and Lindquist 2019).

Conclusion: suggestions for future research
The literature on the variety of new organizational entities seeking to bring new ways to design and deliver public policy and service delivery for governments has typically focused on specific kinds of entities, such as policy or innovation labs, lean units, or behavioral insight units. This paper has drawn on Henry Mintzberg's insight to suggest that these entities should be considered as a broader class of organizations -OI adhocraciesand it has sought to locate them in larger public service systems by drawing on Robert Quinn's Competing Values Framework. We have suggested that these diverse entities share similarities in organizational form and they confront similar challenges in starting up, surviving, and furthering innovation in public service systems dominated by hierarchical values and practices. These new perspectives also suggest there might be very different levels at which these entities are located and their performance or success within government should be appraised.
These new ways of framing and locating OI adhocracies suggest several promising questions: What are the strategies used by OI units and their leaders to establish credibility and to survive in the public service systems? What have been the barriers to securing recognition, acceptance, and resources to ensure the OI unit is sustainable? Do we have the right expectations and metrics for gauging the success of these organizations in public sector contexts? What are the implications and impact of OI adhocracies arriving in public service systems as a group? How might these new OI adhocracies compare to what might now consider "old" OI adhocracies, such as policy analysis, systems analysis, evaluation, and foresight units? The view of executive sponsors, the leaders of partner organizations, and other units within public service systems could be elicited to get a more rounded perspective on OI adhocracy leadership and unit performance, as well as their impact on the culture of their larger sponsoring organizations. The fortunes of these units could be tracked over time to ascertain their survival rates, whether their strategies and organizational repertoires evolved, whether different funding models emerged and whether these units have begun to change the culture of the larger organizations and systems of which they are a part.
Finally, Buttazzoni (2018) very interestingly suggested that, because of their differing core missions, OI adhocracies might further the dominant values of different quadrants when innovating. This suggests that innovation can occur in any of the quadrants, particularly in complex public sector systems with often large-scale organizations comprised of multiple program and corporate services sectors. It also suggests that another fruitful line of research could emerge from elaborating the Competing Values Framework to delineate where different OI adhocracies are located and how they further innovation in different department functions and contexts.

Disclosure statement
The views contained in this paper are those of the authors only and do not reflect the views of the larger institutions of which they are a part.  Moore's (1995) framework and strategies for increasing public value might relate (Talbot 2011;Williams and Shearer 2011;Moore 2014;Bozeman and Johnson 2015). Likewise, we are not trying to ascertain which values are associated with different eras and approaches such as traditional public administration, new public management, and public value and network approaches (e.g. Stoker 2006;Bryson et al. 2014;Torfing et al. 2020). We are more interested in the intersection of espoused values, organizational form, and strategic leadership in larger public sector systems.