What is an evaluation plan, a protocol and a matrix?

A brief summary of each

Evaluation plan – Typically a stakeholder-facing, overarching guide covering all aspects of the evaluation from project/program objectives to evaluation reporting

A plan provides a high level overview of how the evaluation will be conducted, and is commonly developed for both small and larger evaluations. In smaller size evaluations the plan may be used by evaluators as well as an evaluation operational guide, where development of a full evaluation protocol is not feasible due to resource constraints, time or the inherent nature of the evaluation.

Evaluation protocol – An evaluation team-facing document, providing operational and detailed procedural instructions to the evaluation team as to 'how' the evaluation will be conducted (detailed data collection and analysis methodology and how reporting will be synthesised)

Evaluation matrix – A high level tool which organises and displays the key components of the evaluation in a table/spreadsheet

A matrix provides a visual, easily-read display of the relationship between key evaluation questions, outcomes, data sources, data indicators/themes, data collection methods and timepoints for data collection. Essentially it displays what is being measured, how it will be measured, how it will be collected, and by whom.

How do they differ?

Do I need all three?

The complexity and the size of the program/project will determine how detailed and extensive the evaluation preparation should be. A general guide is as program size and complexity increases so should the evaluation. A more complex and larger-scale evaluation has more potential for things to go wrong or for something to be missed. Involving stakeholders in the development of an ‘evaluation plan’ can reduce confusion and ensure expectations around the objectives and scope of the evaluation are clear.

Generally a quality evaluation plan, accompanied by an evaluation protocol which details high quality evaluation methodology, will better enable evaluators to report on the robustness of the results from the evaluation. Essentially together the 3 tools can ensure the evaluation is set up to succeed, creating for example the ideal of a large enough data sample for the statistical analysis tests desired to answer the key evaluation questions. Such planning can also better avoid data attrition over time, better prove the validity and reliability of the analysis findings, improve transparency and accountability of evaluation approach and generally reduce potential evaluation bias to ensure the evaluation supplies robust intelligence.