Gender data system is needed for women census

Reference

To effectively collect gender data and integrate it easily into the policy process, it is necessary to ensure that gender is included in every stage of policy-making. These integrations are important to transform understanding and inspire meaningful change towards gender equality.

Current state of the gender gap

• According to the World Economic Forum’s 2024 report, the global gender gap score is 68.5%.
• Only 42% of the gender-specific dimensions needed to monitor the Sustainable Development Goals (SDGs) are currently available.
• Less than half of the health-related SDG indicators are disaggregated by gender. Only 11 of the 28 indicators are adequately disaggregated.

The importance of gender data

• In achieving the SDGs: Gender data becomes extremely important in achieving the target of SDG 5 as the goal of gender equality intersects with 10 other goals.
  • Gender data is important to identify key areas where progress is slow and where targeted investments and projects are needed.
• Addressing inequalities: This can accelerate progress towards gender equality and the broader SDG agenda. If gender data is effectively used to address inequalities, economic benefits will
  • For example, the annual revenue opportunity from reaching disadvantaged women ranges from US$352 million in Kenya to nearly US$1 billion in Bangladesh. These figures highlight the significant potential that comes from having better gender data.
• Inclusive policymaking: Addressing gender data gaps is not just an issue of equality but also smart economics. Gender mainstreaming ensures policies are more effective and inclusive.
  • Gender mainstreaming means incorporating gender aspects into every stage of policy-making.
• Optimize and target resource use: When gender data is used in policy decisions, it enables targeted interventions that directly address the needs and challenges faced by women. This leads to more efficient use of resources and better outcomes for society as a whole.
  • For example, according to a McKinsey study, addressing women’s health gaps could add US$1 trillion annually to the global economy by 2040.
• In economic development: Gender-inclusive economic policies can promote women's participation in the workforce, leading to faster economic growth.

Challenges facing gender data

• Outdated gender indicators: More than three-quarters of gender-specific SDG indicators are more than a decade old and less than 20% of these indicators have been re-collected.
• Lack of reporting on indicators: A United Nations (UN) study found that no country reports on 14 critical indicators. These indicators include the existence of sexual crimes against women and the proportion of women living below 50% of the median income and the national poverty line.
  • Such gaps in data hinder understanding of women’s socio-economic status and experiences.
• Problems with data use: A key challenge in addressing gaps in gender data is understanding and improving the data value chain, where there is a huge disconnect between data producers and users.
• Lack of funding for data: The Data2X report says that US$500 million in annual investment is needed by 2030 to adequately fund key gender data systems to fill existing data gaps. This amount is double the current allocation, highlighting the severe funding gap for gender data.

The way forward

• Need for strong gender data systems and data collection: Addressing gender data problems requires commitment from international donors, governments and private sector stakeholders to allocate the necessary resources.
  • This financial support is crucial to establishing robust gender data systems and ensuring sustained data collection efforts.
• Need for gender representative data: Improving the quality and frequency of gender data collection is essential. This includes addressing biases in the data collection process to ensure that data accurately represents all genders, thereby providing a comprehensive understanding of gender-specific issues.
• Need for cross-institutional coordination: Effective use of gender data requires collaboration between governments, NGOs, private sector institutions and international organisations to share best practices and leverage collective expertise to significantly increase the impact of gender data initiatives and promote more inclusive data collection practices.
• Integrating gender aspects at all levels of policy making: Integrating gender aspects into all stages of policy development is essential to ensure policies are inclusive and effective.
• Investment incentives: Promoting the economic benefits of gender equality can motivate stakeholders to invest in gender data initiatives. 

conclusion

These steps can address persistent gaps in gender data. Addressing gender data gaps can lead to more effective policymaking, spur significant progress in gender equality, and contribute to broader social and economic development, building a more equitable future for all.