April 17, 2025

Cost Analysis Case Studies

Dioptra is a cost analysis tool that helps program staff at humanitarian and development agencies to estimate the cost-efficiency of their programs, compare to benchmarks, and identify improvements. Dioptra uses web-based software developed and managed by a consortium of development agencies (including CRS). Dioptra pulls from existing financial information and walks users through a standardized methodology for estimating cost-per-output.

As a result of analyzing costs, project teams have gained valuable lessons learned, for example

Farmer Managed Natural Regeneration is quite cost effective relative to tree planting and more cost effective where land holdings are large than where they are small.
To successfully achieve the long-term objectives of land restoration projects, some income generation opportunities need to be achievable in the short term
Remote teacher training could be more cost-effective than in-person training, but only if quality and effectiveness remains high. If not, scaling will not be cost effective.
It’s more cost efficient to build initial cash readiness capacity compared to marginally improving capacity after some already exists

Teams have used those lessons to

gain additional funding to continue the program
prompt the team to change the training strategy to a hybrid process (virtual and in-person) in certain municipalities. Also, with the Ministry of Education, created a platform where training modules are held that will continue to be used after the award ends.
Phase II of an award eliminated the costly agro-forestry intervention in one country and re-directed funding to more cost-efficient approaches.
One project team used the results of their analysis to revise trainings on commodity management from a workshop setting to a customized supportive monitoring to enhance capacity strengthening in a cost-effective way.
A pilot project was able to determine its economic viability, paving way for a remodel of its design for a scale up.

Although results can be context specific, with enough data points, lessons can be more generalizable. We encourage teams to generate cost evidence from their awards so that their lessons can benefit larger audiences.