I want a detailed MEAL planning tool...
What is it?
The Performance Management Plan (PMP) is the primary tool used for detailed MEAL planning after a project has been funded and approved for implementation. All projects should utilize a PMP regardless of their size, complexity, and value. PMPs are also sometimes called monitoring and evaluation plans.
While they vary in format, all PMPs tell teams specifically what will be monitored and evaluated and how these activities will take place. Specifically, PMPs provide a single location where teams can plan and track:
- Objectives statements and indicators
- Data collection (methods, frequency, responsibilities and respondents)
- Data analysis (types of analysis and sub-groups)
- Data use.
How do I use it?
The format of the PMP should be simple and clear. It is most often a table, like the one shown in the image above. Components of a PMP include:
OBJECTIVES STATEMENTS AND INDICATORS
When completing a PMP, first insert the relevant objectives statements and indicators from the project logframe. This is an opportunity to review these logframe components to make sure they are still appropriate. Also, the PMP can be used to provide further definition for indicators if needed. Detailed definitions are useful to make sure teams and partners have a clear (and shared) understanding of what data they need to collect in order to track indicators properly.
The next section of the PMP helps the team plan for data collection. This means providing information from the logframe about what measurement methods will be used, and also providing details related to the frequency of data collection, who is responsible for collection activities, and what respondents will be targeted.
It is important to consider how often change is expected to occur when determining your data collection frequency. Identifying important change points during the life of the project (such as the provision of a particular resource or training session) will influence your decisions of when data should be collected.
Generally teams will monitor indicators appearing at lower levels of the logframe (outputs and some intermediate results) more often, because change happens more frequently at those levels. Data about indicators at the higher levels of the logframe (intermediate results and strategic objectives) are usually collected less frequently, often as part of an evaluation. Keep in mind that seasonal factors may influence the timing of data collection for sectors like agriculture and education.
Then, identify who is primarily responsible for collecting the data in question. The allocation of responsibilities must be done in coordination with the general project implementation team and with any external stakeholder partners involved in the process.
Finally, identify and list your data collection respondents. These are the people who can give you the most reliable data for each indicator. Implementing partners and local contacts are often most suited to identify the appropriate respondents. They are the ones who are best placed to answer questions like, “Are respondents hard to reach?” “Do respondents provide a balanced, fair and accurate perspective on indicators?” and “What characteristics describe the typical respondent?”
The next section of the PMP identifies how data will be analyzed. First the team needs to identify the type(s) of data analysis they will conduct for each indicator. Generally, data analysis types fall into two categories: quantitative and qualitative.
- Quantitative data analysis involves statistical analysis, such as calculating averages, completing cross-tabulations, and determining whether observed changes in the data are statistically significant.
- Qualitative data analysis requires that teams analyze the notes from focus groups or interviews to identify themes. This can be done through participatory processes with the project team, or by using special qualitative analysis software.
Next, the PMP identifies identifies the sub-groups (also known as strata) that will be compared when analyzing data. Examples of sub-groups a project might compare include male- versus female-headed households; or small versus large families. When you identify these different groups (using your understanding of your information needs) you are then able to disaggregate the data coming from each sub-group.
- Disaggregation is the practice of dividing data collected from a population into groups according to key characteristics: gender, religion, age, etc. Disaggregation allows for the identification of trends, patterns or insights that would not be seen if the data was examined as a whole.
Disaggregation improves your ability to respond to your stakeholder information needs by increasing your ability to make meaningful comparisons across these groups.
Finally, the PMP documents how data will be used after analysis to meet stakeholder needs, comply with reporting requirements and inform project decisions. It is important that the uses for all data collected are identified. This will help ensure that the data collected is truly needed and, conversely, that project decisions and reporting will be based on sound evidence.
When do I use it?
The PMP is most often created just after a project has been approved for funding and given the green light for implementation to begin.
After it is completed, the PMP becomes a very important project management tool that should be referred to often during implementation to make sure the project and MEAL activities are staying on track.
Determine your PMP template
PMP templates vary widely, depending on the organization or donor. Make sure you check the project agreement or with your donor or organizational management for guidance (if any) on how to create your PMP.
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