Data to Policy

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“We manage what we measure—and, in turn, what we measure affects what we do”
The Istanbul Declaration, Global Human Development Forum, May 2012.

 

What we choose to measure matters.  So we need to make sure that we measure what matters.

 

Data helps to make the nature and scale of issues visible. If issues or groups are not measured in a way that makes them visible, they are effectively hidden. If you don’t have data that confirms the extent of an issue, or who is most affected, it’s difficult to develop targeted, effective policies and programs, and track their impact.

It’s no surprise, then, that political advocacy for recognition and inclusion of issues and social groups is often combined with demands for better data.  Data and policy are inextricably linked.  If you don’t have data it’s harder to argue that an issue or problem is a priority and needs to be addressed – whether you are a civil society advocate, a policy maker or a political leader.

The lack of attention to gender inequality over many years has left a legacy of significant gender data gaps.  This makes it harder to see the nature and scale of problems, assess priorities, argue for action and implement policies and programs to benefit individuals, communities and economies.

 

Image of a woman in Nepal, standing and looking at the camera. She is wearing a red sari and necklaces.
If issues or groups are not measured in a way that makes them visible, they are effectively hidden. Photo: Alice Floyd/IWDA

“We can’t close the gender gap without closing the gender data gap.”
Melinda Gates, Women Deliver Conference, Copenhagen, May 2016, announcing a commitment of $80 million from the Bill and Melinda Gates Foundation to help reduce the gaps in data on women and girls

 

The gender and poverty data gap

One key gender data gap is in relation to poverty data. Historically, poverty data has been collected about households. This makes it impossible to accurately assess whether some household members are poorer than others, or whether and how poverty varies by sex, age, disability and other factors. This limits our understanding of poverty and the factors that shape it. It also means that in 2018, we don’t know if women, overall, are poorer than men, or if poverty is feminizing.

Measuring poverty at the household level is like looking at a picture without your glasses on – everything is a bit blurry, a bit imprecise, details are hidden.  To see clearly who is poor, in what ways, to what extent, we need to assess the poverty of individuals.

Closing this gender data gap matters. Poverty data is used to advocate for scarce resources, to allocate resources to priorities, to design policies and programs to address those priorities, and to assess what is changing, for whom.

The Sustainable Development Goals agreed in 2015 and the commitment ‘to leave no one behind’ has increased the need for data that can be disaggregated by sex, age, ethnicity, caste, urban/ rural location, disability and more, to see who is affected by what issues in what ways.  To know if ‘no one’ is left behind, we need to measure the poverty of individuals, and assess the factors that poor people say define poverty.

Image of a woman in Timor-Leste, looking at the camera. She is wearing a green top.
Gender data can be used to allocate resources to priorities, to design policies and programs to address those priorities, and to assess what is changing, for whom. Photo: Anna Carlile/IWDA

Better data is critical – but it’s not sufficient

Data needs to inform action. By measuring the situation of individuals, in relation to 15 key areas of life that poor people say characterise poverty, and need to change if they are to escape poverty, the Individual Deprivation Measure can highlight priorities for particular groups or in specific geographic areas, supporting efforts to focus on the most important issues.

 

Seeing what matters, for whom

When we undertook a study of deprivation in Fiji with the Fiji Bureau of Statistics, using the IDM, we found that some 91% of women reported exposure to fumes related to cooking and heating, compared to 65% of men.

Women on average were exposed to 105 minutes per day of fumes related to cooking and heating, compared to an average of 24 minutes per day for men.  Women in informal settlements spent most time exposed to fumes, compared to women in rural or urban areas.

Graphic, showing a woman standing next to a tall flame with 105 min at the top, and a man standing next to a tall flame with 24 min written at the top. This references the average time per day men and women in Fiji are exposed to unclean cooking and heating fuel.
In the Fiji IDM study, women on average were exposed to 1 hour, 45 minutes per day of fumes related to cooking and heating, compared to an average of 24 minutes per day for men. 

Women also reported that they suffered health problems linked to unclean cooking and heating fuel at twice the rate of men (25% compared to 12%), and these problems were more likely to be severe.

Detailed information such as this can help NGOs and social enterprises promoting safe cook stoves to know where to focus, to advocate for resourcing, and establish a baseline to assess how reducing exposure to dangerous fumes is changing lives and reducing health costs.  It can help government health bodies to inform public health messages and support health staff to have conversations with women about the risks of smoke exposure. It can assist energy authorities to pinpoint priority areas for extending electricity provision, and social ministries to develop social protection measures that target the groups who are most deprived.

 

Seeing connections

Image showing the 15 IDM dimensions: food, water, shelter, health, education, energy/fuel, sanitation, relationships, clothing, violence, family planning, the environment, voice, time use and work.

Because the IDM collects data about all 15 dimensions from each individual (it’s not an index that brings together data from different surveys), it can highlight where deprivations are related, which has the potential to assist advocates and policy makers to tackle deprivation more effectively.

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