M&E

ProMise: M&E Module

This provides the user with an option of creating an M&E framework depending on the structure of the project.

Indicators are also defined by the user and the data collection tools are created and linked to indicators for the process. Secondary data resources are also catered for. Organizations can also setup sub-grantees or other organizations to provide data that will be aggregated for the high-level reporting.

Key benefits;

  1. Richer Data: PROMISE M&E provides for collecting data in multiple formats
    which opens up immense potential in getting richer data from your
    development project’s monitoring and evaluation.
    a). Location and GPS data has become more accessible with the use of
    location tracking on cell phones. This makes it easier to collect follow-up
    data, helping you to make connections and draw insights better, and verify
    the source and credibility of your data.
    b). Multimedia data means adding images, video, and sound to your
    traditional data. Collecting M&E data in such a form not only makes verification easier, but it also increases the quality of your data.

  2. Better Insights: Using analytics, visualization, dashboards, and mapping can
    enhance the ability to make sense of all the data that is collected.
    a). Visualizations of M&E data can help you understand and consume your
    data more efficiently and convey important data points and help you arrive
    at the right conclusions about your M&E process.
    b). Geospatial mapping your development project helps to understand its
    geographical footprint and also helps to gauge patterns and develop
    deeper and better understandings of your target audience.
    c). Analytics can help you measure your results and make you more
    data-driven. Depending upon what your project goals are, you can optimize
    your program to achieve those results. Analytics can help you plot the
    roadmap to that end goal by helping you realize what inputs will get you
    that result.

  3. Increased Accuracy: The measures for data accuracy are validity, reliability, precision, integrity, and timeliness.
    a). Real-time data validation helps to weed out measurement errors and
    increases accuracy significantly. In-built data validation prevents erroneous
    data from entering the system. This helps to ensure that data is valid and
    reliable.
    b). Data entry errors occur at the time of data collection or when it’s being
    transcribed. PROMISE allows single-point data entry to reflect across the
    system. Provision for the ability to track where inaccurate data is coming
    from, flag it, and have it collected again. This makes data more precise and reliable