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Today we venture into the third step of Monitoring and Evaluation: Planning for Data Analysis.

What is data analysis?

Data analysis is the process of converting raw collected data into usable information. This step is critical in the monitoring and evaluation process because it shapes the information that is reported and also how this information can be used.

Data analysis involves looking for trends, clusters or other relationships between the different types of data,assessing performance against plans and targets, forming conclusions ,anticipating problems and identifying solutions and best practices for decision making and organizational learning.For data analysis to be successful, a series of things have to be done:

  1. Develop an analysis plan:A data analysis plan is a road map of how you’re going to organize and analyze your survey data and it should help you achieve three objectives that relate to the goal you set before the project is started:

    1. Answer your top research questions

    2. Use more specific survey questions to understand those answers

    3. Segment survey respondents to compare the opinions of different demographic groups

    the data analysis plan will also account for the time frame, methods ,relevant tools/templates,people responsible for and purpose of the data analysis. The following points are some key considerations to be observed when planning for data analysis:

    source: https://www.surveymonkey.com/mp/developing-data-analysis-plan/

  • Purpose of data analysis

Data analysis should be appropriate to the objectives that are being analysed,as they are set out in the project log frame and the M&E plan.This is because the data to be analysed will be largely determined by the project/programme objectives and indicators and ultimately the audience and their information needs. 

  • Frequency of data analysis

The time frame for data analysis and reporting should be realistic for its intended use. This states that information should be given in time so that it may be of value. Over analysis of data can be costly and may complicate decision making. Therefore the team should not waste time and resources analyzing unimportant points,instead focus on what is necessary to inform the project management.

  • Responsibility for data analysis

Roles and responsibility for data analysis will depend on the type and timing of the analysis. The analysis of monitoring data can be undertaken by those who collect the data while for evaluation data,the analysis will depend on the purpose and type of evaluation. However,whenever possible it is advisable to involve multiple stakeholders for data analysis.

  1. Follow the key data analysis stages

Data analysis has no one process.in order for it to succeed,five key stages have to be followed.These stages are:

  • Data preparation
  • Data analysis
  • Data presentation
  • Data verification
  • Recommendations and action planning.


We will look into each of these steps in the next blog post. To catch up with us, check out our blogs on  www.considr.in for our previous post on M&E.



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