External Evaluator Lessons Learned Article 2

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Lessons Learned
External Evaluator Lessons Learned
External Evaluator Lessons Learned Article 2

Introduction

Pull mechanisms are results-based approaches to development that incentivizes private sector actors ("solvers") through prizes to achieve a set of results, paying the solvers only if those results are achieved. Through the $122 million multi-donor AgResults initiative, donors are testing the use of pull mechanisms to engage the private sector in providing agriculture technology solutions to smallholder farmers sustainability, so their engagement in the market continues after the donor support ends. Drawing on early lessons from the AgResults experience to date and the AgResults Kenya On-Farm Storage pilot in particular, this brief provides guidance for development practitioners interested in incorporating pull mechanisms in their own work. It draws on the evaluator’s initial qualitative assessments in each pilot country, which involved interviews with actors in the agricultural sector, key government representatives, and the pilot design and implementation teams. This brief also draws from structured interviews conducted in June 2016 with key AgResults stakeholders to synthesize their collective thoughts on lessons learned thus far. These 13 interviewees included the in-country pilot managers in Kenya and Zambia and representatives from the Secretariat and the Steering Committee.

    

Key Lessons on Designing Pull Mechanisms

  • A starting premise is that pull mechanisms aiming to develop a sustainable market for a technology are best designed for development problems that can be resolved by large-scale adoption of a technology that has already been proven in the field or requires only some tailoring.
  • The solvers should see a clear business case for engaging in the market for the technology. Also, the users of the technology—smallholders—should realize an economic benefit from adopting the technology.
  • The outcomes that trigger payments should be easily measurable, verifiable in a cost-effective manner, and in the manageable interest of the solvers.
  • Finally, and critically, a robust theory of change must clearly articulate how the solvers, motivated by the incentive structure, will address the key constraints limiting the development of a market for the technology.

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