Cost-Effectiveness for Systems Change: Doing More Good with Less

​Event Description

As funding becomes more constrained, the pressure to maximize impact per dollar is growing across the social sector. Cost-effectiveness is often cited as a priority, yet in practice, it remains underused or narrowly applied. Conversations tend to focus on whether something works, rather than whether it is the best use of limited resources, especially in complex, systems-level work.

This discussion explores how to make cost-effectiveness a more practical and meaningful tool for decision-making. How do we account for long-term impact, sustainability, and systems change, not just short-term outputs? What does it take to integrate cost data into everyday decisions across funders, nonprofits, and governments?

We will also examine how approaches like technical assistance, co-creation with communities, and South-to-South learning can support more scalable and cost-effective solutions, particularly in low and middle income contexts. Moving beyond theory, this session will focus on how to operationalize cost-effectiveness in real-world settings while staying grounded in the needs and realities of the communities served.

Speakers

• ​Chris Nicoletti is Chief Impact & Strategy Officer at Splash, leading scalable WASH and menstrual health programmes in urban schools.

• ​Keyur Doolabh is Co-Executive Director of Healthy Futures Global, supporting governments to scale prevention of mother-to-child transmission of HIV and syphilis.

• ​Luan Nio is Senior Director of Partnerships at IDEO.org, partnering with communities and organizations to create a more just and inclusive world through human-centered design.
  

​Discussion Questions
How can cost-effectiveness be used to guide decisions without oversimplifying complex systems change work?
What are the barriers to using cost data more consistently in practice, and how can they be overcome?
How can we balance efficiency with human-centered, community-led approaches to ensure impact remains meaningful and equitable?
What models or approaches are proving both cost-effective and scalable, and how can they be adapted across different contexts?