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Turning cost data into a tool for impact

Kayla Hoyer 27 March 2026

Introducing IDinsight’s Cost-Effectiveness Unit

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Decisions about which programs to fund, design, or scale are rarely straightforward. Leaders must weigh costs against impact often under pressure, with imperfect data. As development sector resources shrink, changemakers are under increasing pressure to maximize the impact of every investment. Yet cost analysis, one of the most powerful tools for making these decisions well, is consistently underused.

Imagine you run a women’s economic empowerment program in five rural villages in a country in Sub-Saharan Africa. You host a workshop with the Ministry of Gender hoping to spark their interest as you have some recent evidence showing the program is impactful. At the end of the meeting, the Minister, who is deeply impressed by the impact numbers, asks what it would take for them to adopt the program and implement it across the country. She tells you they are weeks away from submitting national budget estimates and would like to include your program as a key intervention. Could your team answer confidently, within this timeframe, what it would cost to scale without losing impact?

This is the kind of moment where strong cost analysis can make the difference between a promising pilot and a scalable national policy. IDinsight is launching the Cost-Effectiveness Unit (CEU), a dedicated team helping organizations embed cost thinking into every stage of the program lifecycle from design to implementation and scale.

The problem with how cost analysis works today

The development sector has made real progress in advancing costing methodology. As Senior Economist Jeffery McManus discussed in a recent IDinsight blog post, there are already strong frameworks and resources available, including J-PAL’s guidelines, GiveWell’s approach, and the models I helped develop at the International Rescue Committee. These tools have helped organizations standardize cost analysis usingingredient and activity-based costing, now the most common approach in the sector.

In practice, cost-effectiveness analyses are often conducted after a randomized controlled trial, months or even years after implementation ends. By then, key data has been lost and most operational decisions have already been made, limiting their usefulness for guiding design and scale. Social programs tend to be built incrementally. As new priorities emerge, new components are added, making delivery models more expensive, training heavy, and increasingly difficult to scale over time outside of an NGO context. Without timely, decision-relevant cost data, this organic growth can cause costs to outpace impact. As funding constraints tighten, there is increasing demand to optimize resources and streamline program design around core drivers of impact. While cost analysis tools in the sector are robust, their value is greatest when used proactively to guide design and operational choices, not just retrospectively to evaluate programs.

In reality, leaders often need to make decisions without a perfect set of information or access to the most rigorous evidence. Budgets need to be set, delivery models need to be chosen, and governments or donors may be considering scale early on. Addressing this gap requires employing two complementary approaches: cost-effectiveness analysis, the cost per outcome achieved – which relies on rigorous research; and cost-efficiency analysis, the cost per person or output reached – which helps guide resource allocation.

Building on IDinsight’s history of conducting cost-effectiveness analyses, the newly established CEU is built around supporting decision making on resource allocation. Our work includes:

establish institutional costing systems so teams can track program costs alongside operational data
conducting cost-efficiency analysis to inform program design and make clear recommendations to improve cost allocation to maximize resources
building scenario models to estimate how costs evolve at scale or in new contexts, and
testing program variations to identify delivery models that maintain impact while reducing costs.

A key priority of the CEU is to help organizations use cost evidence as a directional input into design and scale decisions. This means equipping teams to explore tradeoffs, test alternatives, and make informed judgments using tools like scenario modeling, cost-efficiency analysis, and rapid A/B testing.

The goal is not to produce perfectly precise estimates. Instead, it is to provide credible data and transparent assumptions that allow decision makers to compare options and move forward with greater clarity.

Two examples from my own work illustrate what becomes possible when cost thinking is embedded in program design rather than added at the end.

At the International Rescue Committee, I developed scenario models for an intimate partner violence prevention program that a national agency was considering adopting across the country. Rather than presenting a single cost estimate, the model allowed policymakers to test how costs would evolve under different delivery approaches, including potential cost recovery mechanisms. The shift from a static number to an interactive framework changed the nature of the conversation entirely. The question moved from whether the program was affordable to which delivery model would make scale feasible.

A second example comes from education programming in northern Nigeria, where I developed a cost model for integrating social-emotional learning into existing education systems for out-of-school students. The model identified key cost drivers early, well before large-scale implementation began. What it revealed was stark: even if the program proved highly effective, it was largely cost-prohibitive at scale. The social-emotional learning component, priced at roughly a quarter of the full program cost, could not realistically be added to existing budgets without putting scale at serious risk. Rather than discovering this after an expensive research trial, the team used that insight to redesign and minimize costs before moving forward. The resulting product was piloted at a low cost per teacher, and was a promising addition to education systems should it prove effective.

Embedding cost-effectiveness into everyday decision making needs the sector to go beyond tools and think critically about program design. A cost lens encourages teams to ask different questions: Which components drive the largest improvements in our primary outcome? Which activities are most resource-intensive relative to their benefits? Are there alternative delivery models that could achieve similar results at lower cost?

The goal is not to reduce services, but to redesign programs so they deliver the same outcomes more efficiently. This is what separates promising interventions that remain small from ones that scale and reach millions.

As development resources tighten, the pressure to demonstrate impact per dollar will only grow. Governments, donors, and implementers alike will need to make faster, better-informed decisions about what to fund, what to adapt, and what to scale.

IDinsight’s Cost-Effectiveness Unit exists to help organizations meet that challenge by turning cost from a constraint into an actionable input, and by ensuring that insight arrives early enough to inform critical decisions.