Bypassing clientelism through policy design: generating intelligence for effective social policies

Abstract Can clientelism be designed out of social policies? Much of the literature on social policy would suggest universalism as the best means of ensuring that social services are free of malicious intentions and delivered programmatically. This article builds on the recent attention by policy design studies on inherent policy risks—including clientelism—to elaborate on a second-best reform trajectory of deploying procedural tools to address intelligence distortion. It uses the case of one of Asia’s largest conditional cash transfer programs to argue for the importance of the design of “detecting” tools that collect different kinds of policy knowledge. Clientelism feeds on distorted intelligence about problem scale, policy effectiveness, and the acceptability of policies among the community and target population. Incorporating procedural tools that generate technical intelligence ensures that the program is free of particularistic interest. Building ideological intelligence, however, allowed the program to remain responsive to the political context in which it is embedded, but it runs the risk of making it less programmatic. Designing in procedural instruments to gain intelligence can bypass local clientelistic networks by reducing the need for local tacit knowledge about the identification of the poor and can pave the way for greater state consolidation through surveillance.