Development actors are embracing the concept and practice of adaptive management, using evidence to inform ongoing revisions throughout implementation. In this guest blog, Heather Britt, Richard Hummelbrunner and Jackie Greene discuss a practical approach that donors and partners can use to agree on what’s most important to monitor as a project continues to evolve.
Causal Linking Monitoring (CLM) is an integrated approach to project design and monitoring. At its heart, the approach consists of cycles of design, monitor/evaluate, re-design repeated over the life of the project. (See the brief for a complete description and case example of the approach.) By fortifying the data-to-design relationship, CLM facilitates the use of data for adapting implementation and ensures that the data collected to steer the project also adapts in line with implementation.
When is Causal Link Monitoring useful?
CLM is intended to be used throughout the life of a project, from the early stages of design through the final assessment. Once a project is underway, there are several key points when the approach may be introduced when:
Developing a theory of change that pinpoints complexity
Designing an M&E plan and making decisions about what to monitor, why and how
Planning an evaluation to inform adaptive management
Conducting a mid-course project or program review with stakeholders
In this blog, we share what we’ve learned working alongside teams designing project monitoring, evaluation and learning (MEL) systems. In future blogs, we will report out on experiences using CLM at other points in the project cycle.
MEL systems are often not designed to inform adaptive management
While reviewing MEL plans and working with project teams, we’ve noticed several recurring challenges to designing MEL systems that perform well in adaptive management:
MEL plans are overburdened with extensive data collection and resource heavy methods. In the face of complexity, teams often attempt to reduce the uncertainty by collecting large amounts of data. The MEL tasks specified in the plan often exceed the time and capacity of the team. Furthermore, plans are designed during project start-up and reflect the information needs predicted to be useful for the life of the project. In a dynamic context, those predictions may break down quickly, which means that MEL teams are soon bogged down collecting data that is no longer useful or relevant.
MEL plans do not support project revision and re-design. MEL plans often pay lip service to adaptive management these days, but often include plans to use data for project redesign. The plans do not specify activities, assign roles, or set aside time and resources for using the data to review and revise the project design in response to new information or changes in the situation.
MEL systems are not prepared to respond to new information needs. Changes made to the project design necessitate changes in the MEL system. Some MEL tasks may be retired because they are no longer relevant; new MEL tasks are needed to track new project activities or evolution in the context. An adaptively managed project requires an adaptively managed MEL system. Most MEL plans do not include operational guidance for adapting in line with the project.
Causal Link Monitoring addresses common MEL system challenges
CLM helps teams overcome these common challenges and launch MEL systems that are well prepared to inform adaptive management over the life of the project.
CLM designs streamlined MEL systems
MEL systems are commonly developed based on the project theory of change. Using CLM, the theory of change is enhanced to pinpoint where a project is uncertain, contested, emergent or dynamic. The resulting “complexity-aware” theory of change describes both how we predict change will happen, as well as where and how our plans are most sensitive to influences outside our control.
Using CLM’s complexity-aware theory of change, MEL planners design ways to monitor and evaluate the uncertain, contested, emergent and dynamic aspects of the project and context. Planners locate data needs on a visual representation of the TOC which helps to ensure adequate coverage at all strategic points of the project and context. This counterbalances tendencies to overburden the MEL system. Teams can make better choices about what data they will need to manage adaptively and when they will need it.
CLM supports project re-design
CLM pinpoints where the theory change is uncertain, contested, emergent and dynamic, and what kind of data is necessary for managing that complexity. As data is collected, it can be analyzed in relation to those specific points in the theory of change to determine whether and how the project design should be adjusted. Using CLM, the MEL plan forecasts when the team should revisit specific points in the TOC, what data will be available, and what resources are needed to support each project review.
CLM facilitates adaptive management of MEL systems
A CLM-based MEL system is explicitly designed to evolve over the life of the project. The enhanced TOC reveals when data is most relevant during implementation. More importantly, project re-design is foregrounded making it clear that initial predictions about what data will be useful are likely to evolve as the project evolves. This prompts MEL planners to specify processes and provide resources to adjust the MEL system to ensure continued alignment with project implementation.
What does Causal Link Monitoring look like in practice?
Using CLM, we’ve developed a 3-day workshop to support MEL system design. We brought together everyone involved in implementing or using information from the MEL system – on both the implementer and the donor side. Together, we enhanced the theory of change by identifying where it is uncertain, emergent, contested, and dynamic. The resulting “complexity-aware theory of change” was a better representation of the interrelationships between the project and the context in which it operates. It revealed where the implementer and the donor needed to anticipate and respond to change, and what information they needed to manage adaptively.
In the workshop, we led participants through an exercise to ensure that all methods included in the MEL plan met the information needs of the project’s primary decision makers in both the donor and the implementer. Extraneous data collection was reduced resulting in a more streamlined MEL system. In addition, the team identified a specific point in the theory of change where new data collection would most likely be needed as the project unfolded in a dynamic environment. They agreed to revisit the MEL plan at that point in project implementation. Participants returned home prepared to implement a MEL system that anticipates and responds to changes.
Is Causal Link Monitoring new?
CLM grows out of decades-long efforts to reform regulatory M&E frameworks based on results-based management (RBM). Many donor monitoring requirements require monitoring of predetermined results along predicted pathways of change. These frameworks are not conducive to adaptive management.
Richard originally developed the approach for addressing monitoring challenges associated with EU Structural Fund programs and it’s still being used in Austria. The approach was described in Systems Concepts in Action as Process Monitoring of Impacts, and Heather included it as one of the recommended approaches in the USAID Discussion Note on Complexity-Aware Monitoring.
The three of us saw the tremendous potential of the approach and we wanted a more practitioner-friendly resource, so we collaborated to write one. We conducted a thought experiment as part of the writing process – applying the approach to an illustrative USAID intervention. We’ve also expanded on several original elements of the approach, so we decided to give it a new name - Causal Link Monitoring (CLM).
Want to know more?
Please contact Heather or Jackie if you are interested in learning more about CLM workshops for complexity-aware project design or MEL system design, or leave a question or comment below!
This brief gives an overview of the Causal Link Monitoring (CLM) approach to iterative project design and monitoring. It outlines the steps involved and provides an illustrative example of how this approach could be applied in practice.