Should you use the WG questions in your humanitarian programming? A tool to help you decide.

Written by: Claire F. O’Reilly, Caroline Jagoe, Kavita Brahmbhatt and Oscar Lindow

The Washington Group questions are increasingly used in humanitarian action. However, the practical challenges of humanitarian settings, including sampling constraints, remote modalities, and short timeframes have led to confusion about whether and when these questions can be most effectively used in emergencies. This blog focuses specifically on the Washington Group Short Set on Functioning (WG-SS), which is most commonly used or considered in humanitarian action and is the standardised tool for the UN World Food Programme (WFP), to disaggregate data by disability.

We reviewed data from multiple WFP country offices, and for hundreds of thousands of aid recipients as part of a research partnership between Trinity College Dublin (TCD) and the WFP. Based on this analysis, we developed five criteria to help humanitarian workers make the best decision on data disaggregation by disability in their work. These criteria address the purpose, feasibility, buy-in, quality, and actionability of data disaggregated by disability. They are applied here to the WG-SS only, although this approach may be relevant to any of the WG modules, or decision-making regarding the inclusion of other tools for collecting data for disaggregation.

Answering each of the 5 questions below can help you assess whether using the WG-SS is likely to work for you. It is not necessary to answer ‘yes’ to every question, and a ‘no’ should not be considered as a justification for not disaggregating data by disability. Instead, a ‘no’ may highlight something to address before getting started. 

Will it Work?
Criteria	Questions to ask when considering implementing the WG-SS	Yes/No
Purpose	Is there a clear and shared understanding of why these data should be collected, and how the resulting information can contribute to programmatic objectives?	[Yes] [No]
Buy-In	Are key staff involved in the collection, analysis, and use of data willing to implement the WG-SS?	[Yes] [No]
Feasibility	Is disaggregation feasible in the available timeline and implementation context, using the available resources and modality of data collection?	[Yes] [No]
Quality	Is your data collection process capable of implementing quality checks and adapting as required?1	[Yes] [No]
Analysis & Action	Is there a plan in place to analyze and use the data to contribute to inclusive programming?	[Yes] [No]

Below, we explain the relevance of each criterion, and show examples and outcomes from across WFP’s work when certain criteria where met (a ‘yes’) or not (a ‘no’).

1. Purpose

In emergencies there is pressure to act quickly, but it is important to first understand why you are collecting data for disaggregation. Data should be a means to an end, such as more effective advocacy, or more inclusive programming, rather than an end in itself.

In the Middle East and North African region, for example, WFP used the WG-SS to gather data for disaggregation on callers to an information hotline. At a review, staff noted no analysis had been made of the collected data, as they were unsure if and how the data were intended to be used. WFP re-evaluated their process and decided that disaggregating data during post-distribution monitoring would better achieve their aim of understanding who was able to access their assistance.

2. Buy-In

Getting the buy-in of key staff is important for success. Before starting data collection, address any concerns expressed by involved colleagues, and ensure everyone is in agreement about your purpose for the data, and use of the WG-SS. Involving local organisations of persons with disabilities (OPD) can support buy-in.

When WFP first launched its organisation-wide efforts on disability inclusion, key staff did not understand why the WG-SS is formulated as it is and doubted whether the questions needed to be used as designed. This resulted in multiple adaptations of the questions and approaches to data collection being employed. As a result, some data were unreliable, and it was difficult to compare findings between country offices. To address this, WFP dedicated more resources, including training sessions with technical specialists and OPDs. This increased buy-in, and WFP country offices are increasingly adopting the WG-SS as intended. 

3. Feasibility

Even if you have a clear reason for using the WG-SS to collect data for disability disaggregation, and key staff are on board, the nature of emergency response means that you may still encounter practical challenges. Where disaggregated data are truly unfeasible to collect, it may be better to look for an alternative.

In Zimbabwe, WFP was planning census-style data collection in certain communities, gathering information about all members of each household. This was identified as a good opportunity for gathering data for disability disaggregation, and the WG-SS was successfully integrated. In other settings however, the timing constraints of acute emergencies have meant that it was not feasible to include the WG-SS when rapidly scaling up assistance.

4. Quality

To ensure good quality data, it is important to include a piloting phase and data monitoring. After data are collected, especially if your team is new to using the WG-SS, it is helpful to reflect on the process. Review whether it really was feasible to collect in practice, and whether the data appear reasonable, e.g., given the sex and age distribution of your sample (disability is generally more common among women and older persons) or context (disability is often more prevalent post-conflict).

In Sri Lanka, WFP tried collecting WG-SS data for disaggregation during school feeding activities. Over time, it was clear that the data quality was affected by the fact that WG-SS are not designed for the school settings encountered, and the teachers administering the questions did not always know the students well. WFP looked for alternative opportunities to collect high quality disability data. Through their work with the national department of census and statistics, TCD and the Washington Group are supporting the integration of the WG questions in Sri Lanka’s national census. To ensure quality data, a detailed training schedule has been incorporated into the census preparations, including practice sessions and input from local OPDs. 

5. Analysis & Action

There is no point in collecting data that will not be used! If you have followed the previous criteria, then hopefully it has been feasible to collect quality data with buy-in from your colleagues. Now it is time to analyse and act on those data to achieve your stated purpose. This step may require specific technical support, especially if you are new to the WG tools.

In the Central African Republic, the WFP team identified an annual opportunity to collect WG-SS data for disaggregation, to better understand the links between disability and food security. TCD was able to provide technical support in data analysis, and WFP successfully used the data to advocate among other humanitarian actors for a more inclusive response.

Claire F. O’Reilly and Caroline Jagoe are with Trinity College Dublin

Kavita Brahmbhatt and Oscar Lindow are with World Food Programme