Theory of change
Community-based change initiatives often have ambitious goals, and so planning specific on-the-ground strategies to those goals is difficult. Likewise, the task of planning and carrying out evaluation research that can inform practice and surface broader lessons for the field in general is a challenge. Theories of change (ToC) are vital to evaluation success for a number of reasons. Programmes need to be grounded in good theory. By developing a theory of change based on good theory, managers can be better assured that their programmes are delivering the right activities for the desired outcomes. And by creating a theory of change programmes are easier to sustain, bring to scale, and evaluate, since each step – from the ideas behind it, to the outcomes it hopes to provide, to the resources needed – are clearly defined within the theory. Within this wider framework logic or outcomes models are very closely related, often being used to take a more narrowly practical look at the relationship between inputs and results.
A good place to start is with this introduction to ‘theory of change’ hosted here on the LfS blog page. Below are annotated links to a number of online ToC resources:
Change theory and theory of change: what’s the difference anyway?
Daniel Reinholz & Tessa Andrews (2020) International Journal of STEM Education
This essay describes the connections between a theory of change and change theory and provides examples of how change theory can inform a project’s theory of change. A theory of change is project-specific and related to evaluation. It makes the underlying rationale of a project explicit, which supports planning, implementation, and assessment of the project. In contrast, change theories represent theoretical and empirically grounded knowledge about how change occurs that goes beyond any one project. Ideally, a theory of change is informed by change theories.
Theories of change in sustainability science: Understanding how change happens
Christoph Oberlack et al. (2019) GAIA
This paper argues that ToCs constitute tools that can and should be applied more extensively to strengthen the relevance, reflexivity, learning ability, and effectiveness of sustainability science. The authors first propose an understanding of ToCs in sustainability science and illustrate their diversity. They then present ten propositions on how to leverage the potentials and to confront the challenges of working with ToCs in sustainability science.
Guidance on how to develop complex interventions to improve health and healthcare
This 2019 paper by Alicia O’Cathain and colleagues aims to provide researchers with guidance on actions to take during intervention development. The authors present key principles and actions for consideration when developing interventions to improve health or other complex settings. These include seeing intervention development as a dynamic iterative process, involving stakeholders, reviewing published research evidence, drawing on existing theories, articulating programme theory, undertaking primary data collection, understanding context, paying attention to future implementation in the real world and designing and refining an intervention using iterative cycles of development with stakeholder input throughout.
Using actor-based theories of change to conduct robust contribution analysis in complex settings
Andrew Koleros & John Mayne (2019) Canadian Journal of Program Evaluation
As interventions have become more complex, the development of ToCs that adequately unpack this complexity has become more challenging. Equally important is the development of evaluable ToCs, necessary for conducting robust theory-based evaluation approaches such as contribution analysis (CA). This article explores one approach to tackling these challenges through the use of nested actor-based ToCs.
Contribution Analysis and Estimating the Size of Effects: Can We Reconcile the Possible with the Impossible?
Giel Ton and colleagues (2019) CDI Practice Paper 20, Brighton: IDS
Contribution analysis starts with a process to depict an intended change process as a sequence of events, with due attention to contextual influences. In analysing and verifying this theory of change (ToC), an evaluation that uses contribution analysis assesses whether an intervention is a contributory cause, and how and why the intervention made a difference. Contribution analysis provides a general framework rather than a detailed methodology, with six steps in an iterative cycle of reflection about and refinement of ToCs.
Refining Theories of Change
Lovely Dhillon and Sara Vaca (2018) AEA blog post
The authors propose: i) propose the essential elements that contribute to robust Theories of Change and clarify the characteristics that distinguish these from other organizational tools and formats; ii) suggest additional elements for inclusion in the ToC; iii) present graphic alternatives that allow for an evolution in representing their complexity and depth; and iv) provide ways to link ToCs to other organizational tools to increase organizational alignment, efficiency, and, most importantly, impact.
The Truth of the Work: Theories of Change in a changing world
2017 paper [PDF] by Doug Reeler and Rubert Van Blerk
This paper provides a powerful commentary on the need to actively involve people (donors, partners and beneficiaries) not just in the doing of projects – but also in the learning and theorizing about what works and what doesn’t. They emphasize the need to concentrate on “the truth of the work itself” – so that with learning and reflection we can, as true partners, meet our shared, complex realities to navigate our ways creatively into the future.
How Decision Support Systems can benefit from a Theory of Change approach
2017 paper [PDF] by Will Allen, Jen Cruz & Bruce Warburton
Illustrates how to use an outcomes-based approach – Theory of Change (ToC) – in conjunction with DSS development to support both wider problem-framing and outcomes-based monitoring and evaluation.
Representing Theories of Change: A Technical Challenge with Evaluation Consequences
This 2018 paper by Rick Davies looks at the technical issues associated with the representation of Theories of Change and the implications of design choices for the evaluability of those theories. Using examples and evidence from Internet sources six structural problems are described along with their consequences for evaluation. The paper then outlines a range of different ways of addressing these problems which could be used by programme designers, implementers and evaluators.
Hivos ToC Guidelines: Theory of Change thinking in practice
Guide [PDF] by Marjan van Es, Irene Guijt, and Isabel Vogel
This guide aims to support Hivos staff in applying a ToC approach as intended and set out in Hivos’ policy brief: ‘Hivos and Theory of Change’. Recognizes that a theory of change approach can be used for different purposes, by different users, and at different moments in the cycle of developing, monitoring, reviewing or evaluating a program or strategy.
Assumptions, conjectures, and other miracles: The application of evaluative thinking to theory of change models in community development
2016 paper [PDF] by Thomas Archibald and colleagues
Unexamined and unjustified assumptions are the Achilles’ heel of many research and development programs. In this paper, the authors describe a ToC approach designed to help community development practitioners work more effectively with assumptions through the intentional infusion of evaluative thinking into the program planning, monitoring, and evaluation process. The authors show how the use of ToC models can encourage individual and organizational learning and adaptive management that supports more reflective and responsive program development.
Related site information: An accompanying page presents links to some older – but still useful – resources on Theories of Change.You may also be interested in links to resources on logic or outcomes modelling, or the related topic of indicator development. Another related page can be found in the knowledge management section with links on how best to develop conceptual models.