Investing in Innovation: Trade-Offs in the Costs and Cost-Efficiency of School Feeding Using Community-Based Kitchens in Bangladesh

School feeding programs have been a key response to the recent food and economic crises and function to some degree in nearly every country in the world. However, school feeding programs are complex and exhibit different, context-specific models or configurations. To examine the trade-offs, including the costs and cost-efficiency, of an innovative cluster kitchen implementation model in Bangladesh using a standardized framework. A supply chain framework based on international standards was used to provide benchmarks for meaningful comparisons across models. Implementation processes specific to the program in Bangladesh were mapped against this reference to provide a basis for standardized performance measures. Qualitative and quantitative data on key metrics were collected retrospectively using semistructured questionnaires following an ingredients approach, including both financial and economic costs. Costs were standardized to a 200-feeding-day year and 700 kcal daily. The cluster kitchen model had similarities with the semidecentralized model and outsourced models in the literature, the main differences involving implementation scale, scale of purchasing volumes, and frequency of purchasing. Two important features stand out in terms of implementation: the nutritional quality of meals and the level of community involvement. The standardized full cost per child per year was US$110. Despite the nutritious content of the meals, the overall cost-efficiency in cost per nutrient output was lower than the benchmark for centralized programs, due mainly to support and start-up costs. Cluster kitchens provide an example of an innovative implementation model, combining an emphasis on quality meal delivery with strong community engagement. However, the standardized costs per child were above the average benchmarks for both low- and middle-income countries. In contrast to the existing benchmark data from mature, centralized models, the main cost drivers of the program were associated with support and start-up activities. Further research is required to better understand changes in cost drivers as programs mature.