How to Effectively Collect Data on Food & Nutrition Security
How can solid methodologies and smart technologies help you get proper information on food insecurity within households? In this blog I will elaborate on one of those technologies: AKVO FLOW.
Collecting data is crucial to get a better understanding of the impact of your projects. By using data you are able to build a track record which allows you to show your impact to stakeholders. Data are also required to be accountable.
The past years I have supported my colleagues and partners in various countries in Asia and Africa to use AKVO FLOW. This is a mobile device based tool for carrying out field surveys. What makes it so special? With this tool you can collect accurate and real-time data on the ground. The tool enables you to make images and store geo location. By knowing geo location you can easily compare different areas in which you implement your activities. Because the data is collected digital you will have less errors when processing the data. So no more paper interview lists that need to be digitalized. Another advantage of using AKVO FLOW is its real time access. Once collected and uploaded data can be shared all over the world.
You can only use AKVO FLOW if you have a survey. You can make your own survey or use existing standards. One example ICCO has used, is HFIAS*, a readymade methodology to determine the food security status of households.
These are the necessary steps to use HFIAS with support of AKVO FLOW.
- Step 1: Upload the nine HFIAS-questions on your AKVO FLOW dashboard.
- Step 2: Determine additional questions, such as income, gender and household assets.
- Step 3: Add questions on geo location and requests for images that give an idea of the target group.
- Step 4: Determine how many households are interviewed. It’s important to follow the standard sampling methods commonly used in evaluations. We recommend using the practical advice and tools for selection of sampling sizes, elaborated by the Donor Committee for Enterprise Development (DCED).
- Step 5: If you work with different local partners, make sure you align the questions as much as possible to avoid unnecessary data clean up (see step 7).
- Step 6: Train your staff and/or local partners to collect and upload the data.
- Step 7: Clean up your data. This is crucial to correctly analyze the data.
- Step 8: Analyze the data and determine which HFIAS- category is applicable to each household. For example: you might see that the food security situation of the target group has improved, stabilized or deteriorated.
- Step 9: Visualize the most important data. It gives you and your stakeholders a clear over view of the food security situation of the target group.
Does everything go perfect with AKVO FLOW? Of course not. But it’s important to learn from earlier experience. Three years ago I contributed, together with colleagues and local partners, to the AKVO FLOW-pilot in our food security program in Indonesia. In the following years we implemented AKVO FLOW in more than 15 countries. These are our lessons learned.
- It is useful to use multiple choice answer categories as much as possible. For example, if interviewers have to fill in a name of a municipality there is a big risk they will spell these names differently. These mistakes will appear in the dataset. Cleaning this up is time-consuming.
- It’s crucial to think beforehand which type of data you want to report on and which correlations might occur (e.g. by comparing the HFIAS outcomes with levels of education). This might seem obvious but program teams sometimes show a tendency to make extensive questionnaires because the tool makes it so easy to collect data.
- There is a lot of variety in knowledge and experience with smartphones and tablets. Basic trainings in the use of AKVO FLOW are therefore necessary.
In my next blog I will show you possibilities to visualize your data. And if you want to know more on the HFIAS methodology, please read the blog of my colleague Marijke de Graaf.
*Household Food Insecurity Access Scale