How can we collect high-quality data on climate resilience?

The Building Resilience and Adaptation to Climate Extremes and Disasters (BRACED) programme focuses, among other things, on developing and disseminating knowledge about climate resilience. Just over a year after the start of the programme, projects are beginning to yield research findings. What we can learn from data, however, is only as good as the data we have. So how can we effectively collect high-quality data?

From October through December 2015, the Feinstein International Center at Tufts University’s School of Nutrition Science and Policy teamed up with Concern Worldwide to collect data from 1,420 women in 69 villages around Goz Beida, Chad. We had previously used this exact sample twice, including as part of a Concern programme, Community Resilience to Acute Malnutrition (CRAM).

Four teams of 20 enumerators who were hired locally gathered data, under the supervision of a local colleague. One mobiliser went to each village to give women a heads up before the visits.

Here are three lessons we learned:

1. Do not underestimate the importance of sound logistics. As researchers, we work with organisations whose procedures we may not be familiar with. This can make it challenging to organise a huge logistical feat, such as interviewing thousands of people who are hard to reach. If you cannot get to the field early or if your tablets do not work, you cannot even begin to collect the data you need.

a) Make sure you have someone who knows the organisation’s logistics procedures and can support you and the enumerators. They should be familiar with the research and have dedicated time for it, so you don’t have to enlist already busy people.

b) Co-ordination between the project and logistics managers is key to avoid overlap of research and programming activities in the same villages.

2. Mobilise the survey respondents. We gathered data during the harvest season, when women spend much of the day in the fields, so it was important to discuss our visits with them in advance.

a) Use a well-trained mobiliser to persuade village chiefs to facilitate interviews with the women.

b) Arrive on time.

c) Use a flexible data collection plan so all women can participate. We found that women who were absent during our first visit were often more easily persuaded to complete a survey on a subsequent day.

3. Ensure your enumerators have the skills to collect accurate data. To make the data comparable year-onear, questions need to be asked in the exact same way and follow a rigorous method.

a) Throughout the training, ensure your enumerators are invested in the research. Talk to them about what the information will be used for and share past findings. The more invested your enumerators are, the more care they will take to collect accurate data.

b) Do not assume that people understand a question/answer in the same way that you do. Go through every question and response choice with enumerators multiple times. Give them time to practice with each other and monitor their progress to ensure they understand what they are asking. Local staff can help ask questions in a clear and culturally appropriate way.

c) Anthropometrics – height, weight, mid-upper arm circumference – are crucial for gathering nutrition data. If possible, hire trained professionals to ensure that these measurements are accurate. Otherwise, give your enumerators enough training to do so. Training can be demanding on children volunteers and their families, so spread it out, survey various children, and offer incentives to families.

d) Wealth-related questions are sensitive. Asking a woman in Chad how many cows her family has is like asking me how much I have in my retirement account. Train your enumerators to respectfully challenge responses, and remind respondents that the information they provide is confidential.

e) Before your enumerators start the survey, have them verify they are talking to the right woman. Many women have similar names, so equip your team to verify names in a way that is culturally appropriate.

Of course, context matters. The types of challenges can vary depending on countries, seasons, or organisations. While these lessons are specific to our experience in Chad, I expect some to be relevant in other contexts as well.

Have you faced similar or different challenges? Do you have ideas for how to overcome them?

Anne is a research programme manager at the Feinstein International Center at Tufts University’s School of Nutrition Science and Policy.