Operational Models: Accountability to affected people

The last 18 months have seen exciting and rapid developments around operational models and collaborative approaches to programming and delivering CVA, including the growth of the Collaborative Cash Delivery platform and the announcement of the UN Common Cash System.

What are the key issues these and other emerging models are facing as they design to deliver better for people in crisis? What are the opportunities and challenges presented by working together differently?

By bringing together experts from across the CALP Network in a series of webinars we aim to collate the state of the evidence in a number of key areas – what are the best ideas and considerations which emerging operational models and approaches should seek to integrate, and how can we learn from these models as they develop? These webinars will culminate in a major event in the CALP Network’s Cash Week.

The second webinar in this series covers the critical issue of increasing accountability to aid recipients. What are the opportunities presented by emerging models to build on everything we’ve learned and to radically increase recipients’ agency in and influence over cash assistance? Join panellists from Ground Truth Solutions, CAMEALEON, IFRC and Oxfam to explore the state of the evidence and key recommendations.

As cash and vouchers become and increasingly important part of humanitarian assistance this brings the potential and promise of shifting power and agency from humanitarian actors to recipients. In reality we are seeing very little progress in this direction. While many humanitarian actors claim to take AAP seriously, recent research finds that current efforts to seek recipients’ feedback and increase the voice and agency of crisis affected people in programme design are falling far short. The emergence of new operational models provides an opportunity to work differently: building on what we’ve learned to date and radically increasing accountability to recipients. We cover the state of the evidence and propose recommendations to emerging models.