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<p>Despite the growing emphasis on evidence-based management, the strategic role of demand forecasting in nonprofit organizations remains theoretically underexplored and empirically neglected. This study investigates how forecasting models can function as low-cost governance mechanisms that enhance operational efficiency and strengthen accountability in resource-constrained nonprofit contexts. Drawing on a case study of a major Brazilian nonprofit healthcare organization, the research applies a structured five-stage forecasting framework. Five linear models: Simple Exponential Smoothing (SES), Holt Exponential Smoothing (HOLT), Simple Moving Average (SMA), Weighted Moving Average (WMA), and Autoregressive Integrated Moving Average (ARIMA), were evaluated using MAE, MAPE, and RMSE as accuracy criteria. Results reveal that the SMA model consistently outperformed more complex approaches, achieving a 24.93% cost reduction in inventory management. The findings challenge assumptions that advanced statistical sophistication is necessary for operational impact, demonstrating that replicable and straightforward tools can deliver significant efficiency gains and amplify social value. The study advances theory by extending demand forecasting research into nonprofit governance and resource management, providing a framework for integrating quantitative tools with mission-driven strategies. Practically, it offers managers an accessible pathway to strengthen financial prudence, transparency, and alignment with ESG principles and Sustainable Development Goals (SDGs). Socially, it underscores how data-driven planning can expand outreach, reduce waste, and enhance trust in nonprofit institutions. This is among the first empirical studies to test and validate linear forecasting models in a nonprofit setting. By bridging operations research and nonprofit management, it contributes to reconfiguring the discourse on efficiency in the Third Sector, illustrating how technical tools can reinforce legitimacy, accountability, and long-term sustainability.</p>

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Enhancing operational efficiency in nonprofit organizations through demand forecasting

  • 期刊论文

  • 发表日期：

    2025年9月13日

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  • Felipe Mendes Girotto,
  • Cássia Rita Pereira da Veiga,
  • Zhaohui Su,
  • Claudimar Pereira da Veiga

摘要

Despite the growing emphasis on evidence-based management, the strategic role of demand forecasting in nonprofit organizations remains theoretically underexplored and empirically neglected. This study investigates how forecasting models can function as low-cost governance mechanisms that enhance operational efficiency and strengthen accountability in resource-constrained nonprofit contexts. Drawing on a case study of a major Brazilian nonprofit healthcare organization, the research applies a structured five-stage forecasting framework. Five linear models: Simple Exponential Smoothing (SES), Holt Exponential Smoothing (HOLT), Simple Moving Average (SMA), Weighted Moving Average (WMA), and Autoregressive Integrated Moving Average (ARIMA), were evaluated using MAE, MAPE, and RMSE as accuracy criteria. Results reveal that the SMA model consistently outperformed more complex approaches, achieving a 24.93% cost reduction in inventory management. The findings challenge assumptions that advanced statistical sophistication is necessary for operational impact, demonstrating that replicable and straightforward tools can deliver significant efficiency gains and amplify social value. The study advances theory by extending demand forecasting research into nonprofit governance and resource management, providing a framework for integrating quantitative tools with mission-driven strategies. Practically, it offers managers an accessible pathway to strengthen financial prudence, transparency, and alignment with ESG principles and Sustainable Development Goals (SDGs). Socially, it underscores how data-driven planning can expand outreach, reduce waste, and enhance trust in nonprofit institutions. This is among the first empirical studies to test and validate linear forecasting models in a nonprofit setting. By bridging operations research and nonprofit management, it contributes to reconfiguring the discourse on efficiency in the Third Sector, illustrating how technical tools can reinforce legitimacy, accountability, and long-term sustainability.