It serves as a reference document that contains the targets, definition of each indicator (in the context of the project), the methods of data collection and frequency of data collection for each indicator, who will be responsible for collecting the data and how will the collected data be used. Basically it is required by USAID from the grantee. The grantee has to document and report its M&E system in the PMP. Receiving the M&E performance from all the grantees on one specific format helps the USAID to compare/analyze the performance of grantees with each other.
The PMP is a tool designed to help you set up and manage the process of monitoring, analyzing, evaluating and reporting progress toward achieving your objectives. PMPs enable operating units to collect comparable data over time.
What is the importance of PMP?
PMP is comprised of the following things:
- Indicators Definition
- Unit of Measurement
- Data Disaggregation
- Responsible Office/ Person
- Data Source
- Frequency and Timing
- Data Collection Methods
- Data Quality Assessment Procedures
- Data Limitations and actions to address those limitations
- Data Analysis Issues
- Data Use
- Baselines and Targets
Contents of the Performance Monitoring Plan Explained
1. Performance Indicators:
For monitoring a project, Performance Indicators are already identified and agreed in the "Project Agreement". Each performance indicator requires a detailed definition in the context & scope of the project
EXAMPLE of an Indicator: % increase in Household Income
2. Unit of Measurement:
As it is the basic requirement of an indicator that it must be measureable, thus the measurement will also have a specific common unit. That common unit which is used to measure the change is called "Unit of measurement of an Indicator". As in the above example the Indicator is "% increase in Household Income" hence, the unit of measurement is "%age".
3. Data Disaggregation:
When the indicator measurement is further classified based upon geography, gender, age, education etc this is called data disaggregation. Data Disaggregation is done in order to determine how the project affects people of different age groups, different areas, different gender etc.
Measuring a disaggregated set of indicators (a set of indicators that have been divided into constituent parts) provides important information as to how well government programs and policies are working to support the overall goal. If, for example, it is found that over time, fewer and fewer children have clean water supplies available to them, then the government can use this information to reform programs aimed to improve water supplies, or strengthen those programs that provide information to parents about the need to sanitize water before providing it to their children.
A rationale briefly describes why the indicator was selected and how it will be useful for management. The process of selecting indicators is often based on considering trade-offs. That is, the optimal indicator may not be the most cost-effective. By clearly documenting the rationale for the indicator, an outsider is better able to understand the decisions underlying the selection process. This is helpful when new staff arrive, as well as for auditing purposes.
5. Responsible Office/Person:
For each performance indicator, it is important to identify the specific person and/or office responsible for collecting, analyzing, and reporting the data.
6. Data Source:
The data source is the entity from which data is obtained. Data sources may include government departments, international organizations, non-governmental organizations, private firms, contractors, or other organizations. It can also specify the actual document or report. The same source must be used over time for each indicator. Switching data sources for the same indicator can lead to inconsistencies and misinterpretations.
Example of Data Source: Survey of Pakistan 2012 Report
Example of What can happen if data sources are changed
7. Frequency and Timing:
The frequency and timing for data collection should be based on how often data is needed for monitoring purposes, cost of data collection, and the pace of change anticipated. Data in the PMP is most commonly reported on a quarterly, semi-annual, or annual basis. In some cases, data can be collected more frequently like on weekly or monthly basis and in some cases data might be collected less frequently, e.g after every 5 years.
Examples of data collected on Monthly basis:
Examples of Data collected on annual basis:
Examples of Data collected after every few years:
8. Data Collection Methods:
This section describes exactly how the data will be collected, including the tools or methods used for the data collection. The key is to provide sufficient detail on the data collection or calculation method to enable it to be replicated consistently over time. To ensure full description of the data collection methods, be sure to include atleast the following details:
- Techniques used for acquiring data e.g Key Informant Interviews, Focused Group Discussions etc
- The tools used for collecting the data e.g Structured Questionnaires, Observation Forms etc. It is often useful to include copies of the tool used to collect the data in the annex of the PMP (e.g., structured questionnaires, direct observation forms, templates, etc.) where possible.
- Sampling techniques for selecting cases (random sampling or purposive sampling) based on the Disaggregation (please see point 3 above)
9. Data Quality Assessment Procedures
In this section there should be a complete step by step description of how the quality of data was determined/assessed.
10. Data Limitations and actions to address those limitations:
The situation and scenario in the project area might change from time to time. This might result in increase of some problems in the collection of data. Even if the data was not being collectted from the field, whatever the source of the data previously was, it might not work some times. This is the section where you explain the challenges faced, what are the limitations and scope of the collected data and what steps have been taken to address those limitation. Explain clearly the strengths and weaknesses of the data so that neither you are giving too much of the hopes from the data to the donor nor you are under performing with the collected data.
11. Data Analysis Issues:
12. Data Use:
The data collected and analysed is to be reported to the donors. Moreover, any other organizations, partners or individuals can also receive the analyzed data and can use it. This section defines the scope of distribution of the data. It should tell which organizations, persons or other entities will be recieving the data. This analysis can also be used by higher authorities to make more informed decisions particulalry regarding the project.
13. Baselines and Targets:
Baselines is the status of the indicator when it was measured at the start of the project and the target is the level to which indicator has to be taken by the project interventions. Its the change required of the project to bring about in the indicator.