Many initiatives in areas like agriculture, public health, natural resource management, and climate adaptation operate in complex systems—where change is unpredictable, outcomes emerge over time, and different actors value different things.
In these settings, traditional evaluation approaches that focus on attribution and fixed indicators can fall short. Complexity-aware monitoring, evaluation and learning (CAMEL) shifts the emphasis from control to contribution, from proving impact to making sense of change. It helps teams reflect, learn, and adapt as the work evolves—rather than waiting for answers at the end.
Tools like theories of change, outcome pathways, and reflective rubrics still play a role—but they’re used as working models to guide conversation, not as rigid templates. By embedding learning into programme delivery and governance, CAMEL approaches support strategic alignment, stronger relationships, and better decision-making. For a broader reflection on this balance between structure and emergence in real-world programmes, see Working between systems and complexity: a practitioner’s guide. It explores how systems thinking and complexity-aware approaches can work together to support adaptive learning and collective sense-making.
The resources below offer practical insights into complexity-aware MEL—drawing on recent literature and lived experience from collaborative, multi-stakeholder settings.
Evaluation in complex settings: reflections on practice and evaluator roles
This reflective post by Will Allen explores how monitoring, evaluation and learning (MEL) can support adaptation, sense-making, and learning in complex, collaborative initiatives. Drawing on 20+ years of experience and recent literature, it shares five grounded patterns of practice in complexity-aware MEL and considers what this approach asks of evaluators. A useful starting point for practitioners working in areas such as climate adaptation, land use, biodiversity, and systems change.
Monitoring, evaluation and learning for systems change
This new overview paper offers a clear, practice-oriented introduction to MEL for systems change. Written by Lizzy McDonald, Kate Simpson & Carolin Schramm (Wasafiri, 2025) and drawing on the Systemcraft framework, it outlines a flexible, learning-led approach spanning design, delivery, and evaluation. Key concepts include dynamic theories of change, sentinel indicators, rapid learning cycles, and developmental evaluation. An accessible entry point for funders, implementers, and MEL practitioners working in complex systems.
Complexity-aware evaluation for learning
This 2025 paper by Eureta Rosenberg and colleagues examines the design and implementation of a complexity-aware, learning-centred M&E framework within a broad development and environmental programme in the Olifants River Basin. Using a participatory, developmental approach, it explores challenges, adaptations, and learning outcomes. Findings highlight how working with standard M&E elements in new ways—through reflection days, case studies, and novel reporting—supported organisational learning while balancing accountability needs.
Evaluating research for development: innovation to navigate complexity
This editorial by Marina Apgar and colleagues introduces a special issue on how complexity‑aware evaluation is evolving in large, hybrid research‑for‑development programmes. It examines four tensions: accountability versus learning, predefined theories of change versus emergent pathways, internal relational dynamics versus external outcomes, and local versus systems‑level impact. It is useful for evaluators interested in navigating uncertainty, power and adaptation rather than proving linear impact
When evaluation is also design: complexity, place, and continuity in multi-actor work
This LfS post reflects on complexity-aware evaluation as a form of design in long-term, place-based initiatives. Explores how evaluation shapes learning, accountability, and responsibility at moments of transition, particularly when programmes end but places, relationships, and institutional responsibilities continue.
Sensemaking: Framing and acting in the unknown
In this 2011 piece, Deborah Ancona introduces sensemaking as a core leadership capability for working in complex, changing environments, defining it as “structuring the unknown so as to be able to act in it”. She translates Weick’s ideas into practice-friendly guidance, outlining ten steps grouped around exploring the wider system, creating shared “maps” of what is going on, and acting experimentally to learn. The chapter offers concrete examples, leadership implications, and a brief “student manual” that can be adapted for MEL and facilitation contexts.
Complexity-aware methods for health systems learning
This 2024 methods paper, Bringing complexity into causality: Methods for assessing the effects of COVID-19 response on local health system strengthening in five countries, by Yordanos Molla and colleagues, outlines a multi-country learning activity led by the USAID Local Health System Sustainability Project. It applies CAMEL principles through a participatory process that combines Most Significant Change and Outcome Harvesting. A strong, practitioner-oriented example of how to explore emergent outcomes, local perspectives, and ripple effects in complex systems.
Evaluation insights from the Living Water programme
This collection of 2024 evaluation resources documents the Living Water programme, a ten-year partnership between DOC and Fonterra to improve freshwater ecosystems while supporting sustainable farming. Led by Will Allen and Viv Sherwood, the evaluation used a Complexity-Aware Monitoring and Evaluation (CAME) approach, incorporating systems thinking, adaptive management, and developmental evaluation. Resources include a national programme evaluation summary, five site evaluation reports, and a place-based impact tool to guide collaboration and engagement.
Navigating system change evaluation
This 2023 white paper by Social Finance delves into the complexities of evaluating system change initiatives. Recognizing that traditional evaluation methods often fall short in capturing the nuances of systemic transformation, the report offers practical guidance for practitioners, funders, and evaluators. It emphasizes the importance of embedding evaluative thinking into strategic planning, maintaining a clear ‘North Star’ while allowing for iterative learning, and understanding the emergent nature of outcomes in complex systems.
Advocacy brief: Complexity-aware monitoring, evaluation, and learning
This 8-page brief by Anna Martin and Katrina Mitchell (CORE Group, 2021) introduces CAMEL approaches in global health and development contexts. It advocates for flexible, systems-aware MEL that supports real-time decision-making, tracks emergent outcomes, and centres stakeholder perspectives. The brief outlines practical benefits across programme stages—from design to outcome assessment—and provides guidance for implementers, MEL staff, and donors. A high-level complement to more detailed methodological guides.
Complexity-Aware Monitoring and Evaluation
This 2021 paper by Tilman Hertz, Eva Brattander, and Loretta Rose explores the elements of a complexity-aware M&E system for sustainable development programmes. The authors argue that traditional M&E approaches relying on rigid Theories of Change fail to capture dynamic, unpredictable systems. They propose an iterative, real-time approach that fosters flexibility, experimentation, and innovation, helping donors and implementers track emergent change rather than rigid pre-determined plans.
Twinning “Practices of Change” With “Theory of Change”: Room for Emergence in Advocacy Evaluation
This 2017 paper by Bodille Arensman, Cornelie van Waegeningh, and Margit van Wessel argues that Theories of Change (ToC) often oversimplify complex interventions like advocacy. Instead, they propose focusing on “practices of change”, which centre on human interactions and emergent outcomes. The paper advocates for strategies-as-practice and recursiveness to better reflect the reality of complex, adaptive change.
Performance monitoring’s three blind spots
This 2013 presentation by Ricardo Wilson-Grau highlights three common blind spots in performance monitoring: unintended results, alternative causes, and multiple pathways. It emphasises that linear models often fail to capture how change happens in complex systems, making alternative evaluation approaches essential.
Contribution analysis: A new approach to evaluation in international development
This paper by Fiona Kotvojs and Bradley Shrimpton explores AusAID’s shift to contribution analysis, which moves beyond attribution-based evaluation. Using the Fiji Education Sector Program as a case study, it examines how contribution analysis helps assess programme impact while addressing causality and complexity.
Complex adaptive systems: a different way of thinking about health care systems
This 2004 paper by Beverly Sibthorpe and colleagues provides a brief introduction to complex adaptive systems (CAS) thinking in healthcare. It underscores the importance of M&E frameworks that account for feedback loops, tipping points, and emergent change, rather than relying on linear models.
Appreciating the recursive and emergent nature of Complex Adaptive Systems
Strategy-as-Practice: Taking Social Practices Seriously
This 2012 paper by Eero Vaara and Richard Withington explores strategy-as-practice (SAP) and how it explains strategy-making within broader social and organisational practices. The authors propose five directions for further development: recognising macro-institutional influences, focusing on emergence, considering material influences, and promoting critical analysis.
Using programme theory to evaluate complicated and complex aspects of interventions
This 2008 paper by Patricia Rogers outlines how programme theory can help evaluate complex interventions. It highlights methods for representing recursive causality, reinforcing loops, disproportionate relationships (tipping points), and emergent outcomes, making it a valuable tool for complexity-aware evaluation.
For further insights into complexity-aware monitoring, evaluation, and learning, explore related Learning for Sustainability site pages on planning, monitoring & evaluation, Theory of Change, and logic models. You may also find rubrics useful for assessing complex initiatives. These resources support adaptive management, learning-based evaluation, and outcome-focused planning, helping to navigate complexity and enhance impact.
[* Image: Can Stock Photo / alphaspirit]