In many developing countries the capability of the state to implement its policies and programs is a key constraint to improving human development. Many reform initiatives fail to achieve sustained improvements in performance because organizations pretend to reform by changing what policies and organizational structures look like rather than what they actually do.
To escape the trap of stagnant capability and increasing frustration, new conceptual models of state capability that go beyond the transplantation of the 19th century Weberian state are required. The BSC team is exploring the potential of a new Problem Driven Iterative Adaptation (PDIA) approach, which rests on four principles:
|Local Solutions for Local Problems
Transitioning from pre-determined promoting solutions to allowing the local nomination and articulation of concrete problems to be solved.
|Pushing Problem Driven Positive Deviance
Creating environments within and across organizations that encourage experimentation and positive deviance.
|Try, Learn, Iterate, Adapt
Promoting active experiential (and experimental) learning with evidence-driven feedback built into regular management that allow for real-time adaptation.
|Scale through Diffusion
Engaging champions across sectors and organizations who ensure reforms are viable, legitimate and relevant.
|Table 1: Contrasting current approaches and PDIA|
|Elements of Approach||Mainstream Development Projects/Policies/Programs||Problem Driven Iterative Adaption|
|What drives action?||Externally nominated problems or 'solutions' in which deviation from 'best practices' forms is itself defined as the problem||Locally Problem Driven - looking to solve particular problems|
|Planning for action?||Lots of advance planning, articulating a plan of action, with implementation regarded as following the planned script||'Muddling through' with the authorization of positive deviance and a purposive crawl of the available design space|
|Feedback loops||Monitoring (short loops, focused on disbursement and process compliance) and Evalulation (long feedback loop on outputs, maybe outcomes)||Tight feedback loops based on the problem and experimentation with information loops integrated with decisions|
|Plans for scaling up and
diffusion of learning
|Top-down - the head learns and leads, the rest listen and follow||Diffusion of feasible practice across organizations and communities of practitioners|