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Escaping Capability Traps Through Problem-Driven Iterative Adaptation (PDIA)
Author(s) -
Lant Pritchett,
Matthew Andrews,
Michael Woolcock
Publication year - 2012
Publication title -
ssrn electronic journal
Language(s) - English
Resource type - Journals
ISSN - 1556-5068
DOI - 10.2139/ssrn.2102794
Subject(s) - legitimacy , computer science , set (abstract data type) , adaptation (eye) , process management , business , political science , law , psychology , neuroscience , politics , programming language
Many development initiatives fail to improve performance because they promote isomorphic mimicry—governments change what they look like, not what they do. This article proposes a new approach to doing development, Problem-Driven Iterative Adaptation (PDIA), which contrasts with standard approaches. PDIA focuses on solving locally nominated and prioritized performance problems (instead of transplanting “best practice” solutions). PDIA encourages positive deviance and experimentation (instead of requiring that agents implement policies as designed). PDIA creates feedback loops that facilitate rapid learning (instead of lagged learning from ex post evaluation). PDIA engages many agents to create viable, relevant interventions (instead of depending on external experts).

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