To make a program meaningful and worthwhile, you will need to measure its progress and impact. In order to do so, you will need to develop data collection tools that will help you gather information on some or all of the following:
How these data are collected and how changes are measured is part of the Study Design.
Data will need to be collected at several points:
- The first step is the collection of baseline data, which are gathered before a program is implemented. This step is essential in order to be able to measure progress and impact. It is also referred to as collecting "pre-intervention" data.
- Once the program has been delivered, you can begin to determine changes in the relevant dimensions that are listed above. This will require a second round of data collection, immediately after the program or intervention has concluded. The information to be compiled should be the same as that collected for the baseline measurement.
- Ideally, you will also want to determine whether any changes have been sustained beyond the period during which the program was implemented. In order to assess these changes, you will need to collect data at multiple points of time beyond the intervention.
There are two methods, or study designs, for collecting data that can help you to assess program impact:
- Longitudinal, or panel, design; and
- Repeated cross-sectional design.
In a longitudinal design, the same individuals are followed from baseline throughout the follow-up period. In a repeated cross-sectional design, the same population, though not necessarily the same individuals, is sampled repeatedly at baseline, post-intervention, and each follow-up time point.
Both methods include collecting data at different points over a time period, which can be decided by the research team based on the program objectives.
The following steps will guide you through the data collection process.
More information on different approaches to collecting data, whether through surveys, key informant interviews, or other means, is provided under Data Collection.
1. Determine what data need to be collected, from where, and when they should be collected.
Refer back to your program objectives, program timeline, and your workplan. Using the measurable outcomes stated in your objectives, determine what data will be needed to inform each objective, the best source of those data, and when and how often the data will need to be collected.
2. Develop guidelines on how data should be collected.
If you are using a survey method, you need to ensure that all questionnaires are disseminated and all interviews are conducted under the same conditions and following the same procedures. The Training page provides more information.
3. Determine your sample size and sampling procedures, if applicable.
The Sampling Note under Issues to Consider includes a discussion about sampling methods and a link to a sample size calculator. Consulting with a statistician to help you determine the minimum sample size needed to measure your objectives is recommended.
4. Manage the logistics of collecting and storing data in preparation for analysis.
Maintaining the security of your valuable data is a critical consideration in planning and implementing your program. Where will the data be stored and who will be responsible for data maintenance? If you are collecting any sensitive or personally identifiable information about program participants, the data need to be maintained in a secure location with restricted access.