This paper argues that many reform initiatives in developing countries fail to achieve sustained improvements in performance because governments and organisations pretend to reform by changing what policies or organisations look like rather than what they actually do. The flow of development resources and legitimacy without demonstrated improvements in performance undermines the impetus for effective action to build state capability or improve performance. This dynamic facilitates “capability traps” in which state capability stagnates, or even deteriorates, over long periods of time even though governments remain engaged in developmental rhetoric and continue to receive development resources. The paper proposes Problem-Driven Iterative Adaptation, based on four principles: 1) solving locally nominated and defined problems in performance; 2) encouraging experimentation; 3) using tight feedback loops that facilitate rapid experiential learning; and 4) engaging broad sets of agents.
Capability traps close the space for novelty since they establish fixed best-practice agendas as the basis of evaluating developing countries and of granting organisations in these countries support and legitimacy. In so doing, local agents are excluded from the process of building their own states while the value-creating ideas of local leaders and front line workers are undermined. Governments adopting such reforms look better for a period—when laws are newly passed, for instance—but ultimately they do not demonstrate higher levels of performance, as new laws are not put into practice.
How can countries escape capability traps? This paper proposes an approach called Problem-Driven Iterative Adaptation (PDIA). It involves pursuing development interventions based on four core principles, each of which stands in sharp contrast with the standard approaches:
- PDIA focuses on solving locally nominated and defined problems in performance (as opposed to transplanting pre-conceived and packaged ‘best practice’ solutions). Focusing on prevailing problems ensures that problems are locally defined, not externally determined, and puts the onus on performance, not compliance.
- It seeks to create an ‘authorising environment’ for decision-making that encourages ‘positive deviance’ and experimentation (as opposed to designing projects and programmes and then requiring agents to implement them exactly as designed).
- It embeds this experimentation in tight feedback loops that facilitate rapid experiential learning (as opposed to enduring long lag times in learning from ex post ‘evaluation’). This allows reformers to learn a lot from the ‘small-step’ interventions they pursue to address problems (or causes of problems).
- It actively engages broad sets of agents to ensure that reforms are viable, legitimate, relevant and supportable (as opposed to a narrow set of external experts promoting the ‘top down’ diffusion of innovation).
