Briefing papersSeptember 2020Stephanie Buell, Haneen Malallah and Paige MasonLandholders in Tanzania. Photo: Riaz Jahanpour / USAIDAdaptive programmes recognise that certain changes, particularly in behaviours, are complex, non-linear and difficult to measure. This briefing note explores the use of outcome mapping (OM) as a monitoring, evaluation and learning (MEL) approach to track behavioural change and inform adaptation for two programmes: the Pathways to Resilience in Semi-arid Economies (PRISE) research consortium and the Accountability in Tanzania programme (AcT I and AcT II). It discusses the implementation of OM, the ways in which it has enabled adaptation and enabling contexts in order to identify key considerations for MEL specialists and programme managers as they determine whether OM may be the right fit, and how best to use the approach.Key messagesOM has a number of different benefits as a MEL approach, including unpacking different uses of information at different levels of programme implementation; helping to develop a common language around progress markers; and going beyond monitoring to inform adaptation throughout implementation.These benefits are important aspects of monitoring, evaluation and learning for adaptive management (MEL4AM), as they provide richer evidence for decision-making at a frequency that could mean real-time learning and change.OM works best when it is embedded throughout the organisation, and as part of programme and organisational culture, rather than tasked to a MEL unit or individual.Read the research Outcome mapping: learning briefDocumentpdfCorrections and clarificationsCorrected online 29 September 2020: an acknowledgements section has been added.Published online 18 September 2020.Related USAID Wildlife Asia as a case study in adaptive rigour: monitoring, evaluation and learning for adaptive managementA case study of how USAID’s Wildlife Asia programme has operationalised the concepts of adaptive rigour and adaptive management.Briefing papers17 September 2020 Adapting data collection and utilisation to a Covid-19 reality: monitoring, evaluation and learning approaches for adaptive managementA discussion of key considerations for remote collection and the use of data for adaptive management during the Covid-19 pandemic.Briefing papers17 September 2020 Contribution analysis for adaptive managementA discussion of practical learning about the use of contribution analysis for adaptive management.Briefing papers17 September 2020The Global Learning for Adaptive Management initiative (GLAM)GLAM is a global learning alliance that aims to actively identify, operationalise and promote rigorous evidence-based approaches to adaptive management.Projects1 August 2018See more:adaptive developmentmonitoring, evaluation and learningTanzaniaGlobal