Lead the implementation of specific WASH assessments or train partners to do it

The coordination platform is sometimes responsible to lead WASH assessments and is frequently in charge of delivering training for partners on assessment methodologies.  WASH coordination platform staff must be competent to carry out WASH assessments, from design and data collection, to analysis and reporting.

A WASH assessment cycle typically involves the following steps: 

Set the objectives and scope

Define in a TOR (see Assessment TOR template in the Key Guidance and Tools section) including the research questions, the geographical areas and population groups to be covered. Detail your information needs, focusing generally on the needs and vulnerabilities of affected people, but also on aspects related to access, operational feasibility and response modalities, etc. Set the timeframe of the assessment and the information products that will be produced.

Develop indicators and questions

Develop a list of indicators that will allow you to meet the information needs identified in the previous steps. In any case, remember to include the WASH core indicators. The GWC has developed an indicator and question bank that you can use to develop your own list.

For each indicator, explain how it will be aggregated/disaggregated, and what type of analysis you want to run. This process is usually done by building a matrix called Analysis plan. This matrix will help making sure that all data required for the analysis are collected, that no time is wasted in collecting unnecessary data, and will guide the analysis process. See analysis plan template in Key Guidance and Tools section.

Once you have set the indicators, formulate the questions that will be asked to the respondents to gather the data. Remember that questions should be as brief as possible, simple-worded, and not leading towards pre-defined answers. Again, you can use the GWC indicator and question bank to develop relevant questions.

Data is more and more collected through mobile data collection systems, such as Kobo and ODK: this allows easier data management. In the Follow up on data collection / Mobile data collection folder on top of the page, you will find guidance on how to set up and use mobile data collection systems.

Design the methodology

To design the methodology, consideration should be given to both the objectives of the assessment, and constraints such as time, resources, access, etc.

The main dimensions that need to be addressed are:

• Unit of measurement, which is the level the data is collected at (e.g. individual, household, institution/infrastructure, community, area). This will have an influence on the type of data collected: the higher the level, the less reliable is the answer of the interviewee.
• Data-collection methods (e.g. direct observation, key informant interviews, focus group discussions, community discussions, key-informant interviews, household interviews, etc.): in the Design the methodology folder above can be found a table detailing pros and cons of the different data collection methods.
• Sampling methods, or in other words the criteria you will use to select the respondents. There are two main types of sampling: probability sampling – in which respondents are selected randomly and every person in the sampling frame has the same chance of being selected, and non-probability sampling – in which respondents are not selected randomly. Probability samplings are much more resource-intensive but can generate statistically significant findings, while non-probability samplings are often lighter in terms of resources but generate findings that are indicative only. For this reason, there is always a tradeoff between representativeness of findings and cost/time constraints.

Follow up data collection

Ensuring close follow up during the collection phase will improve the quality and timeliness of data. It is key that progress and challenges of data collection is regularly monitored. To achieve this, a matrix can be set up to track the number of forms that have been submitted, the areas that have been completed and the issues hampering progress. You need to check and clean data as soon as they come through to spot inconsistencies and follow up with the enumerators.

In the Follow up on data collection folder above you will find templates of tracking matrices and data cleaning tools.

Analyze the data

Once data has been collected, analysis can start. This process should be guided by the analysis plan, as the indicators chosen must help answering the research questions of the assessment.

Analysis should aim not only at describing the situation (for instance, where and who lacks safe water), but also at explaining the causes (for instance, lack of improved water points), interpreting the effects (for instance, linking presence of AWD with lack of safe water) and anticipating possible evolutions (for instance, the potential increase of child mortality rate in certain areas). Another key aspect is the implementation of cross-sectorial analysis based of WASH data or data from other relevant sectors, such as nutrition, health, education, etc.

In the Analyze the data folder above can be find documents that describe possible approaches towards these different levels of analysis.

Share information

Findings should be disseminated in a timely and effective way. Different types of information products can be considered, including factsheets, maps, web-platforms, reports, etc. depending on the audience and the resources available.  In the Share information folder can be found templates as well as example of information products from past assessments.

Information products should be shared both with the primary audience through the coordination platforms channels (coordination meetings, MailChimp, SendinBlue, social media, etc.), and the broader humanitarian community, thought platforms such as HumanitarianResponse.info, ReliefWeb (see key external weblinks at the bottom of this page), etc. It is important to share the anonymized, cleaned dataset on the Humanitarian Data Exchange (HDX, see key external weblinks) – the main humanitarian online data sharing platform, so that other people can have access to data and run their own analysis.