The method you use to collect data will depend on what you’re interested in learning and the indicator being studied. A distinction can be made between quantitative and qualitative collection methods. Quantitative methods are particularly useful when:
- Precise data should be available
- You want to get a general overview of the situation
- Comparisons between different groups or persons are needed
- Statistical interdependencies between the problem and its suspected causes are to be tested
- Proof that a project is producing (countable) successes needs to be furnished
Qualitative methods help with the collection of descriptive assessments. They convey more detailed, subjective information on attitudes and other constructs. The focus is on the individual. Qualitative data cannot be expressed in figures as they describe a state of affairs, and thus help to deliver a deeper understanding of a situation. This also makes them important for impact-oriented project management: Generally, a full picture of causes and interrelations arises only from a combination of quantitative and qualitative data. Qualitative research methods are characterized by a focus on the how and why of a situation or development. They are particularly suitable when:
- You want to accurately understand a situation in a certain context.
- You want to find out how individuals or groups evaluate their own circumstances, and learn about their expectations and wishes.
- What exactly do you want to find out? Do you want to know the size of the target group being reached, or do you want to determine why the project has achieved no results within a very specific population?
- Why do you need the information? If you want to clarify the relevance of a problem for funders, then quantitative data are particularly appropriate. By contrast, if you want to dig deeply into a problem, or work out details and differences, qualitative methods will be more effective.
The more angles from which you consider your project, the more significant your understanding will be. For this reason, it makes sense to combine various data sources and data-collection methods – quantitative and qualitative alike.