C4D: Synthesise data from a single study or evaluation

What is it?

Studies and evaluations must, in the end, make evaluative judgments. To do that, there needs to be a process of drawing together data and findings (often from descriptive data and causal analysis); and systematic synthesis and conclusions. In evaluations, this process will often draw upon standards and criteria developed as part of Determining what 'success' looks like. In other types of studies, such as situation analysis, it may use other ways of weighing up and recommending methods. This process is particularly important where there are mixed results from the data, and an overall judgement and weighting needs to be made. Attention to processes to properly synthesise data and make a judgement about the value can significantly boost the quality and usefulness of C4D RM&E.

General information 

There are many methods that can be used for synthesising and valuing. The Rainbow Framework includes relevant methods, such as those covering processes (such as consensus conferences and expert panels), techniques (such as cost effectiveness analysis, numeric weighting, and rubrics), and approaches (such as social return on investment). This page is recommended as background reading before considering options to apply to C4D. 

Applying the C4D principles to synthesising data from a single evaluation


Stakeholders should be meaningfully engaged in the process of weighing up the different outcomes, benefits, and costs (monetary and unintended outcomes). See methods such as a consensus conference, and qualitative weight and sum methods.


Consider whose voices are included and excluded from the process of weighing up findings and making judgements, in order to allow for the collective contribution to the weighing up the extent to which success has been achieved.


By undertaking data synthesis processes we can make findings based on different sources of evidence and voices. This is a useful tool for accountability to partners and community groups, and to donors and managers.

Recommended methods and adaptations for synthesising data from a single evaluation in C4D

Participatory processes

  • There are ways to undertake this process in a participatory manner, in keeping with the C4D Evaluation Framework, so that the perspectives of communities and other stakeholders can be included appropriately. The Rainbow Framework lists several methods for undertaking these processes. The following may be of particular interest:

Balancing costs

  • There are several methods for synthesising from a monitory perspective:

    • These methods are possible in C4D, but it depends on access to relevant, quantifiable outputs and outcomes (such as, numbers of visits to health clinics, number of people wearing helmets). It is also highly dependent on good causal analysis, and where a counterfactual is not created as part of the design, strong analysis of consistency of expected results and ruling out alternative explanations will be vital.

      Of the different available methods, cost-utility analysis is likely to be the most compatible with most types of C4D for the following reasons:

      • Participatory: the approach seeks and consolidates the perspectives of stakeholder groups in deciding on preferences and quality.
      • Critical: the approach is sensitive to the differences among different groups in the ways that different elements might be valued 
      • Holistic: the approach is useful for measuring benefits in non-monetary terms.

    'C4D: Synthesise data from a single study or evaluation' is referenced in: