by Sreeja Nair
As governments grapple with uncertainties associated with complex policy issues such as climate change, digital transformation, pandemics and Artificial Intelligence, the role of policy piloting and experimentation will be key in shaping policy choices. Designing policies as pilots and experiments “in theory” permits governments a safe space to test new and alternative policy designs and learn from them. There are, however, challenges in realizing the potential of pilots to do so in practice. In my book Rethinking Policy Piloting, I study design features of selected policy pilots that were launched to manage risk and uncertainty in the agriculture sector in India. Despite their technical merit, pilots—just as regular policies—are prone to political influences, which can alter their expected performance on implementation. This is then an interesting departure from a common sentiment, “When in doubt, just pilot.”
Drawing from literature on policy experimentation, scaling-up, and policy change, I develop a theoretical model with four conditions hypothesized to influence a pilot’s outcomes in terms of its policy translation. These conditions are 1) the pilot’s vision to scale-up, 2) stakeholders governing the pilot, 3) semblance of the pilot’s objectives and 4) semblance of the pilot’s instruments (to reach set objectives) to a policy it was designed to improve or replace. Thirteen policy pilots launched by the central Ministry of Agriculture and Farmers Welfare, Government of India to address risks and uncertainties in agriculture production were selected for a comparative case analysis. These pilots spread across 25 years starting from 1990—the decade that saw liberalization and decentralization reforms in India to 2015.
The pilots aimed at increasing crop productivity and reducing risks to agricultural production following a period of demonstration and evaluation and involved testing of different policy elements for guiding national agriculture policy. While some were intended to be incremental measures to support current policy programmes, others proposed new models and innovations to reform and replace the same. Semi-structured interviews were conducted with those involved in design and implementation or evaluation of the pilots. Thick case narratives along with a Qualitative Comparative Analysis helped understand how variations in the four conditions influenced the outcomes of each pilot.
The analysis reveals three key insights. First, pilots can survive in different forms without scaling-up fully and still contribute meaningfully to improved policy design. Second, successful design, implementation, and scaling up of pilots is not automatic and involves a tussle between its technical merit and political appeal. Pilots come with the risk of failure and associated reputational consequences to the policymaker and thus might often be conservative, proposing only marginal changes to current policies. Third, a departure from conservative pilots is seen when non-governmental actors are involved, which could be attributed to risk-sharing in case of failure.
Rethinking Policy Piloting makes an appeal to policymakers to experiment more considering these as opportunities to improve policy design, and to researchers to regulate their enthusiasm around expected outcomes from pilots considering the politics that surrounds them- just as routine policies.
About the Author
Sreeja Nair is an Assistant Professor at the Lee Kuan Yew School of Public Policy, National University of Singapore. She studies how governments manage risk and uncertainty in the policy process, focusing on the interplay of science and politics. Her research examines varied policy tools, in particular pilots and experimentation, for addressing high uncertainty in planning for climate change, sustainability transitions and digital transformation. Follow her on X/Twitter: @Sreeja_Nair01
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