Building an Organizational Gender Equality Assessment Functionality Using Machine Learning
Equilo is a growing startup with a mission to inspire transformative gender equality and social inclusion by using smart tech to provide a better, faster, and more cost-effective gender analysis and project management.
In this two-month Omdena Challenge, 50 AI changemakers worked to develop a new functionality for an existing app of Equilo. The functionality includes an organizational gender analysis as well as intelligently suggesting specific actions based on comparative data (countries, other organizations, etc.).
Gender equality is both a human right and a precondition for catalyzing development and lifting communities out of poverty. Empowered women contribute to healthy and productive families, communities, and nations. The UN recognizes the importance of gender equality in its Sustainable Development Goals.
Equilo is a web-based application that harnesses comprehensive global data to automate customized gender analysis for 132 countries and soon-to-be 18 sectors, from clean energy and agriculture to health and education. Equilo inspires individuals and organizations to participate and lead – empowering governments, aid agencies, and NGOs to make a difference in communities worldwide. The result is a far more cost-effective, faster route to insights and impactful action. Accelerating gender equality. Amplifying impact. Catalyzing change.
The Project Outcomes
The solution is a new organizational Visualized Gender Equality Analysis and Intelligently Automated Suggested Actions.
The team gathered supplementary data from existing data sources available via databases and the web to integrate into the primary data collected from the survey and integrate into the analytical algorithms, from sources that Equilo provides, such as:
Other possible sources of anonymous/ crowd-sourced data related to gender equality and treatment in the workplace, throughout supply chains, customers
For certain themes or indicators, this may be benchmarked against existing country-level data that Equilo already has
Intelligently Automated Suggested Actions
Also analyzed the strengths and gaps of the Organization in absolute terms, relative to country-level data (if applicable), and relative to peers (where available)
Based on the identified gaps of Organization, the employers should be provided with a prioritized list of suggested actions automatically populated on their dashboard, which will change based on the strengths and weaknesses
The final outcome: New functionality of organizational analysis and Organization-specific suggested actions.