There is a growing recognition that many problems facing policies and programmes are complex and need to be treated as such. Implementation must deal with interdependent problems, navigating nonlinear and often unpredictable change processes, involving a diverse range of stakeholders. The first half of this paper therefore aims to give readers the tools to decide in what way, and to what degree, the challenges they face are complex – and sets out the central reasons why complex problems present big challenges for traditional approaches to implementation:
1. Firstly, the capacities to tackle complex problems are often distributed among actors: problems manifest themselves in different ways and at different levels, and rather than one organisation or hierarchy being fully in control of meeting a particular objective, action may rely on differing degrees of collaboration from a variety of actors.
2. Secondly, complex problems are difficult to predict: many social, political and economic problems are not amenable to detailed forecasting. Where causality is not well understood success may rely on adaptation and flexibility to emerging insights, rather than trying to completely fix the shape of policy responses in advance.
3. Thirdly, complex problems often involve conflicting goals: there may be many divergent but equally plausible interpretations of a policy issue, with different groups approaching it from different starting points or assumptions. Implementation cannot be technocratic, but requires a negotiated understanding and synthesis through communicative processes.
Traditional tools tend to be based on inappropriate assumptions for complex problems, and as such, when they are applied in the wrong context, a number of negative side-effects can arise. Formal implementation tools may decrease in relevance, key aspects of problems are hidden from sight, and managers may be presented with perverse incentives. The problem, however, is not (necessarily) intractable problems, or poor application of the right tools, but rather use of the wrong tools for the job. In recent years, the complexity sciences have improved our understanding of complex problems, and have provided concepts and ideas which incorporate both old and new insights to present alternative theories for change, greater understandings of underlying processes and, crucially, better approaches for tackling them in a strategic and direct manner.
Furthermore, the ways in which policy draws on available knowledge becomes one of the central determinants of its success. The difference is that, rather than working in a linear fashion, policy-makers must be mindful of constraints and opportunities as to where, when and how knowledge and decision-making can best be linked. The principles and priorities can be organised as below:
Implementing agencies need to work in a collaborative mould, facilitating decentralised action and self-organisation. This can be done in the following ways:
· Decentralisation and autonomy: One key priority is decentralising policy-making and implementation, distributing power in decision-making and allowing increased autonomy for units lower down the hierarchy.
· Engaging local institutions and anchoring interventions: Implementing agencies may need to work with and through local organisations addressing an issue at different scales; this may be best done through co-management and power sharing.
· Convening and boundary management: Agencies may be able to play a unique role in facilitating processes that build trust and collaboration between key stakeholders. They must act as trustworthy stewards of these processes, including the provision of transparent mechanisms for conflict resolution.
· Building adaptive capacity: Capacity building is likely to be central in efforts to enable actors to capitalise on any autonomy for addressing problems. Supporting adaptive capacity networks is shown to be a central priority for stimulating emergent responses.
· Remove the barriers to self-organisation: There may be different types of barriers and systemic issues which are preventing actors from adapting to emerging problems: these could be related to national legislation or political systems, or issues of power, discourse and social capital.
· Supporting networked governance: Agencies must approach the delivery of their mandate with a networked approach to policy and governance. Accountability structures can usefully focus on holding units accountable for their mission or role description. Relationship management concern and participatory processes should be central focuses.
· Leadership and facilitation: Even where the capacity to act is distributed, leadership emerges as a critical variable in the success of collaborative responses. However, in the face of complex problems this leadership must be facilitative and enabling, working through attraction rather than coercion.
· Incremental intervention: Where a central agency does need to intervene, it should be approached in an incremental manner, starting from existing networks and taking an evolutionary approach to support, looking to ‘seed’ decentralised action and support emerging responses rather than implementing idealistic blueprints.
Implementing agencies need to deliver adaptive responses to problems, building space for interventions to be flexible to emerging lessons. This can be done in the following ways:
· Appropriate planning: Systems around ex ante analysis should be light and flexible, and focus on providing utility, for example by enhancing awareness of the key risks or lessons. Accountability can be tied to clear principles for action rather than to unpredictable results or inflexible activity plans, and rules for the adjustment of plans can be established in advance.
· Iterative impact-oriented monitoring: Continual monitoring of the effects an intervention is having will be critical to its success – and this should be done in order to check and revise understandings of how change can be achieved, rather than simply recording progress. It is therefore imperative to make any evaluation as utilisation-focused as possible, to ensure the requisite feedback is received to allow for timely adaptation.
· Stimulating autonomous learning: In the face of complex problems, evidence shows that actors are more likely to be responsive to emerging evidence where it emerges in the context of trust and ownership. Monitoring and evaluation functions must be embedded throughout implementation chains, and the autonomy to shape M&E frameworks should be devolved.
· Implementation as an evolutionary learning process: Experimentation through intervention may need to become the central driver of learning. This could be put centre-stage in an evolutionary implementation process, revolving around variation, where a number of different options are pursued, and also through selection, where based on feedback from the environment, some are deemed a greater success and replicated.
· Creating short, cost-effective feedback loops: Judicious use of participatory M&E and transparency may be important because who carries out the monitoring has proven a crucial determinant of effective adaptation. There are a number of local-level methods for citizen involvement in the governance of implementation available, including emerging innovation in systems for beneficiary feedback, and transparency and accountability initiatives.
· Accountability for learning: Measures may need to be taken to ensure policies place explicit value on learning as well as delivery: intervention must be seen as an expression of hypotheses and complex tasks may require learning objectives rather than performance goals. Promoting innovation in service delivery may require valuing redundancy and variety.
Implementation systems and processes must draw on an eclectic mix of sources of knowledge at many different levels and junctures. Of particular importance are tools, which allow for the negotiation between and synthesis of multiple perspectives, for example:
· Decisions from deliberation: Carefully managed and structured processes of deliberation have proven to have wide benefits on both decisions made and their subsequent implementation. These must be embedded in inclusive, face-to-face fora, focusing on eliciting reasoned and legitimate inputs to action.
· Focusing on how change happens: Implementation processes must tie together analytical and management efforts with explicit questions as to how change happens in their context. Ideas and assumptions underlying implementation must be made explicit in order to allow them to be purposefully tested; planning tools such as ‘theory of change’ and theory-based evaluation may assist.
· Realistic foresight: Foresight and futures techniques can be used to provide broad and realistic forward-looking analysis and fix shared structures for ongoing implementation. Tools such as scenario planning have proven invaluable in enabling organisations to be both resilient and nimble, so long as a broad range of perspectives are taken into account.
· Peer-to-peer learning: Rather than focusing on technocratic knowledge-transfer processes, adaptation and learning may often work more effectively through peer networks, such as through study tours or ‘peer review’. Research on communities of practice has shown how the informal dynamics of linkages can be the driver of creativity and reflection.
· Broadening dialogues: Processes of contestation and argument may be important for informing and improving the foundations of policy and action, and implementation should look to build and work with critical voices, rather than avoiding them. Promoting reflexive research is important as is building the capacity of disadvantaged stakeholders to fully articulate their position.
· Sense making for common ground: a shared vision of the problem at hand is often a prerequisite for progress on complex issues. Key stakeholders must jointly negotiate concepts and models, and boundary objects such as shared models or standards can play a key role in anchoring collective action.
· Facilitation and mediation: Efforts to combine different sources of knowledge must tread carefully, and policy-makers must become adept in managing power in the knowledge-policy interface. Power should be shared in both analytical and decision-making processes, with space made for critical reflection and the consensual resolution of impasses and conflicts.
So where are these approaches most relevant? In some sectors, ‘complex’ models of implementation are well-established and proven effective; in other areas, persistent and well-recognised issues with implementation seem to bear the hallmarks of the negative side-effects of traditional tools applied to complex problems. This research has not attempted to specify what problems should be considered ‘complex’, but to give readers the tools to decide for themselves whether an issue faced is complex, and to provide guidance on what to do if it is. The extent to which any one challenge exhibits the characteristics of these three dimensions is likely to be a matter of degrees, and the relevance of the principles and priorities set out above will vary accordingly. Implementation will likely require a mixture of these principles with more traditional approaches and similarly the tools presented above have a domain of appropriate application, and need to be applied well and with sensitivity to context.
What is clear, however, is that complexity can no longer be swept under the carpet. While there is not yet one comprehensive framework, there is a growing collection of models, tools, and approaches to effectively develop interventions in the face of these multifaceted problems. These will allow those charged with implementing policies and programme to be able to more explicitly, systematically and rationally deal with the challenges that are presented. However, taking responsibility for complexity is a double-edged sword. On the one hand, there are a new set of tools to use, and/or more legitimacy given to approaches not previously seen as ‘scientific’ or ‘rigorous’. But on the other hand, this will make areas of practice previously hidden from sight more visible, and actors will find themselves held accountable for aspects of their work which may have previously slipped under the radar. This shift may therefore represent an uncomfortable or unattractive transition. However, what is clear is that it is an essential transition in order to achieve results in the face of complexity.