The cycle of good impact practice: Analyse your data

What’s the best way to make sense of the data you’ve collected?

Data analysis is the process of making sense of the data you have collected. It involves examining your data to find patterns and themes, and drawing conclusions about what it is telling you.

How to analyse your data

Data analysis should start with what you need to know. By agreeing your goals and deciding what data to collect, you will have already identified the research questions you want to answer. These should frame your analysis.

The focus of your analysis is guided by your particular needs. For example, if your programme model is similar to others, and evidence on the effectiveness of your particular approach already exists, you may choose to focus on your reach and the quality of your service (user, engagement and feedback data).

The way you go about analysing your data will depend on the type of data you have collected:

  • Quantitative data – Quantitative data is numerical – for example, responses to multiple choice or rating scale questions in a survey. Learn more about analysing quantitative data.
  • Qualitative data – Qualitative data is not numerical. It may include open-ended responses to questionnaires, data from interviews or focus groups, or creative responses such as photographs, pictures or videos. Learn more about analysing qualitative data.


The cycle of good impact practice defines what impact practice is and articulates a clear path to success. It follows a four-step cycle. This page is part of Assess, the third step in the cycle.

Other resources from this step in the cycle

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This webpage has been adapted from the Inspiring Impact programme, which ran from 2011 until early 2022 and supported voluntary organisations to improve their impact practice. More information about the Inspiring Impact programme.