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Thinking outside the box, improvisation, and fast learning: Designing policy robustness to deal with what cannot be foreseen
Author(s) -
Capano Giliberto,
Toth Federico
Publication year - 2023
Publication title -
public administration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.313
H-Index - 93
eISSN - 1467-9299
pISSN - 0033-3298
DOI - 10.1111/padm.12861
Subject(s) - improvisation , robustness (evolution) , agile software development , autonomy , politics , computer science , public relations , management science , sociology , knowledge management , economics , management , political science , art , biochemistry , chemistry , visual arts , gene , law
Policies are continually subjected to turbulence and crises. Interest in policy robustness as a fundamental way to deal with what cannot be foreseen is increasing. Thus, there is a flourishing stream of literature suggesting that policies need to be designed to be agile and flexible. However, the associated characteristics remain undeveloped. This article fills this gap by drawing on lessons obtained from the unplanned behaviors that were adopted in the management of the COVID‐19 pandemic. Individual and organizational behaviors characterized by outside the box thinking, improvisation, and fast learning yielded solutions to unexpected problems. In this article, some of these emblematic unplanned behaviors are assessed, and the research builds on the literature on policy robustness, crisis management, and organizational theory to identify three enabling conditions to design more robust policies: coordinated autonomy, training for unplanned responses, and political institutional capacity.