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An Engine for Learning Agendas: World Vision’s Accelerator Fund

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Organization(s)
Authors
Philip Harris, Lauren Van Enk
Description

In 2016, World Vision embarked on a journey to improve operational effectiveness and evidence-based programming. This years-long journey created new mechanisms to realize this vision, including The Accelerator Fund, an internal mechanism designed to expedite research, innovation, and strategic positioning activities. A cross-functional committee annually reviews project ideas from staff and awards grants ranging from $25k to $75k per idea. The Accelerator Fund has played a pivotal role in shaping World Vision's evidence pipeline, particularly through sector learning agendas. It has fostered new partnerships with academics, promoted continuous adaptation to evolving needs, and enabled ventures into new technical areas that align with USAID and other donor priorities. Since its inception, the Accelerator Fund has funded many innovative research activities. Notably, since FY21, it has supported 23 research activities aligned with themes from the USAID Learning Agenda (2022-2026). These investments span multiple sectors and countries and involve partnerships with local and international academics. By linking the Accelerator Fund and learning agendas, World Vision has built an evidence ecosystem that aligns the evidence-building approach used by practitioners with that used by USAID and other donors. This case study demonstrates how a thoughtful use of flexible funds can significantly foster innovation, guide future investments, scale efforts, cease ineffective practices, and enable change within the organization. It demonstrates how learning agendas and their evidence feed into USAID-funded projects and peer-learning initiatives. It also explores how the AF has supported positioning efforts for fundraising and aligned with donor priorities. However, it also candidly shares the challenges of running such a mechanism on limited budgets, managing stakeholder expectations, and navigating organizational dependencies.

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