Defending Dignity A Manual for National Human Rights Institutions on Monitoring Economic, Social and Cultural Rights Quantitative data also allows us to make more specific, precise findings. For example, findings such as “most of the victims were young girls”, “a large number of people do not have access to water” or “the proportion of children underweight for their age rose dramatically” are fairly vague. As highlighted in italics, they use words that are open to different interpretations by different people and are, therefore, quite subjective. Replacing these subjective words with numbers that can be objectively verified gives greater credibility to the findings being made. As discussed further in Chapter 15, quantitative data can also be presented in a visual format. This can be a particularly powerful way to communicate information. Data visualization can provide a clear snapshot of a complex situation, engaging people on the topic and giving them the information they need to understand it and focus on the most important aspects. Quantification is also a language that government officials, public servants and other policymakers understand and use consistently in their work. Using quantitative data in NHRI advocacy can make these groups more responsive to arguments about the need for improvements and reform. 5.3. LIMITATIONS AND CHALLENGES OF QUANTITATIVE DATA As discussed, quantitative data is a crucial type of information for NHRIs to incorporate into their monitoring activities. However, there are a number of limitations to quantitative data. Accordingly, it is important to balance quantitative data with the types of qualitative information that NHRIs more commonly gather and analyse; for example, through interviews and consultations. First, while quantitative data is well suited to diagnosing a situation by answering “how much”, “how many”, “to what extent”, “where” or “when”, it is much more limited in terms of answering “why” a situation is the way it is – which is a key question in any human rights assessment. For this reason, it is necessary to combine data with qualitative information. This issue is discussed in more depth in Chapter 13. Second, the degree to which quantitative data can accurately and objectively measure a particular issue should not always be assumed. What gets measured, how, when and by whom are all political decisions. However, this can get lost in the final number produced. A particular issue in this regard is that women’s voices can get lost in numbers. For example, household surveys are a common method for data collection. However, because data is collected on the household as a whole, dynamics within the household are not reflected. For example, the income of the household may not reflect the resources which a woman in that household actually has access to if a male ‘head of household’ controls the money; it is perfectly possible in this common circumstance for a poor woman to live in a non-poor household. For this reason, intra-household surveys are an important tool to ensure that different perspectives are recognized and represented. By doing the same survey separately, the researcher can create a safe space in which women and men can talk freely and express their perceptions and ideas. In addition, women in many societies might not be comfortable reporting sensitive issues. As a result, even using a robust methodology, the data collected might be poor. Take the issue of sexual harassment, for example. Statistics on this issue are notoriously underreported because being harassed is often associated with a loss of honour and the tendency to “blame the victim” is widespread. 5.4. CONSIDERATIONS WHEN WORKING WITH QUANTITATIVE DATA Incorporating quantitative data into a monitoring activity may be a new undertaking for your NHRI. As such, it is important to consider in advance how you will use the data. This will significantly affect how you collect it and in how much detail. The ultimate goal of a monitoring activity is to collect evidence to advocate for change. This means you should be confident about the potential leverage for change that this quantitative data might provide before devoting scarce organizational resources to collect it. 56