Adaptive management in a dynamic monitoring and evaluation environment: A case of Zimbabwe COVID-19 pandemic (2019–2023)

The COVID-19 pandemic critically disrupted monitoring and evaluation systems in humanitarian contexts, necessitating innovative adaptations to ensure program continuity. This study adopts the adaptive management theoretical framework to assess how remote monitoring and evaluation practices were adjusted during the Zimbabwe COVID-19 crisis. The study examined remote monitoring and evaluation practices implemented during the pandemic in Zimbabwe through key informant interviews with program implementers and development professionals, online surveys of 120 practitioners, and a content analysis of 45 project reports. Remote monitoring emerged as a primary alternative to physical inspections, enabling real-time data collection via mobile platforms (76 % adoption rate). However, challenges such as data privacy risks (reported by 68 % of respondents) and reliability gaps in self-reported beneficiary data (52 % inconsistency rate) were identified. The stratified analysis revealed that programs combining remote tools with periodic in-person verification achieved 89 % data accuracy, compared to 63 % for fully remote approaches. The study proposes a hybrid monitoring and evaluation framework that integrates remote technologies with contextually tailored, participatory methods to balance efficiency and accountability. These findings underscore the urgency of adaptive M&E systems in crisis settings while highlighting the need for ethical and methodological safeguards. Delineating actionable strategies for optimizing remote management, this research advances pragmatic solutions for sustaining humanitarian operations in disrupted environments. • 76 % of Zimbabwe NGOs adopted remote monitoring during COVID-19 restrictions. • Hybrid monitoring methods were associated with 26 % higher accuracy than fully remote approaches. • Data privacy concerns emerged as a key barrier for 68 % of practitioners using remote tools. • Only 32 % used remote monitoring pre-pandemic, showing rapid crisis adaptation. • Local enumerators boosted data quality in 89 % of restricted access cases.