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Globally, women perform 76.2 percent of all unpaid care work hours—more than three times as men. This disparity directly affects their ability to engage in social, cultural and economic activities. The gender gap is especially prevalent in Mexico, where men dedicate the second least time to unpaid care work globally, behind only Chile. Meanwhile, women in Mexico City spend an average of 10.8 hours more per week than men on unpaid household and care work. The COVID-19 pandemic further exacerbated this issue, as women took on additional domestic responsibilities, limiting their opportunities for paid employment. While there is evidence that a better care ecosystem can enhance women's economic participation, policymakers often lack concrete information—such as infrastructure requirements—to develop such an ecosystem.
The Government of Mexico City, in collaboration with the Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ), ProsperIA, and the White Ribbon Alliance (WRA), developed an intelligent map platform. This platform combined various data sources, including data processed by Natural Language Understanding (NLU), administrative records related to the care system, information on economic opportunities, and enablers of women's participation such as transportation and childcare. The approach also incorporated crowdsourced data from women in Mexico City, who reported that care responsibilities limit their economic participation. Using NLU, these insights were transformed into data points. The final output was a map of Mexico City that identified areas where care centers could benefit the most women.
Policymakers can use this platform to make more informed decisions about resource allocation that prioritize the needs of underserved and under-resourced communities. Women and children, in particular, benefit from these data-driven policies. There are also several advantages for the government. The map, which leverages both crowdsourced and administrative data, is cost-efficient. Furthermore, the NLU model saves policymakers time by using advanced Artificial Intelligence (AI) techniques. This model can also be scaled to include additional data sources or expanded to other Spanish-speaking countries. The initiative significantly contributes to SDG 5 (Gender Equality) by promoting women's economic empowerment, SDG 8 (Decent Work and Economic Growth) by providing women with the care infrastructure necessary to participate in paid employment, and SDG 10 (Reduced Inequalities) by directing resources to the most vulnerable communities.
In Mexico City, women dedicate an average of
more per week than men to unpaid care and household work.
Mexico City is the fifth largest city in the world and the largest Spanish-speaking city globally. Despite systematic data collection by the city's government, the size and diversity of the city mean that not all community needs are fully captured, particularly those of women. Additionally, Mexico faces significant gender equality challenges, as women spend considerably more time on unpaid domestic and care work than men. On average, women in Mexico City spend 10.8 hours more per week on unpaid labor than men.
This gender gap highlights the urgent need for policies and infrastructure that support women. Specifically, access to childcare centers remains a challenge for many mothers in Mexico. According to social policy expert Dr. Martha Merlo, the primary issue is the lack of childcare centers, rather than the quality of existing services. Nationally, only 3.1percent of children under six attend public childcare centers, further indicating the pressing need to increase care infrastructure.
Accessible, affordable, and high-quality domestic and care services can shift these tasks into the paid sector, increasing social, political, and economic participation for both those providing and using these services. The lack of such programs, on the other hand, can severely limit women's choices and opportunities. In urban areas like Mexico City, where nearly 40% of women have children, access to childcare could greatly increase their participation in social and economic activities.
To address these challenges, the Women’s Ministry in Mexico City partnered with GIZ and WRA to better understand and identify gaps in the city's current data ecosystem. Through consultations, the team identified available data, especially at the level of urban blocks in Mexico City. Datasets such as the 2020 Population and Housing Census were combined with satellite imagery and existing data on childcare and care centers. The project also utilized the Federal Women’s Ministry Care Map (MACU in Spanish).
To assess demand for care services, the team incorporated results from an NLU-processed, crowdsourced survey conducted by WRA. The survey, targeting women in Mexico City, asked about employment and health issues. Respondents could answer multiple-choice questions such as: “Which factors have contributed to your inability to find a good job or access quality healthcare?” and self-identify with statements like “I provide care for a dependent person.” By mapping these responses based on participants' zip codes, the team was able to estimate where care responsibilities were most limiting women’s participation in economic activities.
After gathering and integrating various data sources, the platform enabled the Government of Mexico City to determine the best locations for expanding care infrastructure. It overlaid socio-economic, demographic and administrative data with crowdsourced input and existing infrastructure data. Using deep learning and spatial intelligence, the platform—named IncluIA—made data-driven recommendations for where to increase care services based on the needs of communities that would benefit the most.
By doing so, the platform equipped policymakers with the tools to make cost-effective decisions and allocate resources more efficiently. The video below demonstrates how the platform operates in practice.
The borough of Álvaro Obregón has some high-income areas and many economic opportunities, mainly in the southern part of the city. However, it is also a borough with strong inequalities with some low-income areas and few labour opportunities, particularly in the western and northern region. The platform recommended two new childcare centres be built in this neighbourhood. Although women in Álvaro Obregón dedicate more hours to paid employment compared to other boroughs, they still only work around 20 hours per week.
Through its initial analysis of the top 15 locations in need of care infrastructure in Mexico City, the platform recommended two new facilities in Álvaro Obregón. The following figures show how the map accounts for multiple dimensions to assess the granular needs of the communities.
The map initially provided the Women’s Ministry with recommendations to construct15 new childcare facilities. The locations of these facilities were determined based on need, using data such as income distribution, labor opportunities, paid hours worked by women, and the ranking of “Caring for a dependent person” as a barrier to employment, alongside the current distribution of childcare centers. The platform also considered how many children each new childcare center could potentially serve by estimating the area’s infant population density and providing an estimate of the capacity each center should accommodate. The platform identified four boroughs most in need of childcare infrastructure, recommending the placement of ten centers in Iztapalapa, two in Gustavo A. Madero, two in Álvaro Obregón and one in Iztacalco.
Policymakers can now use the platform to make informed, data-driven decisions regarding childcare infrastructure that empower women. The platform's layering feature also enables policymakers to gain deeper insights into the city and the communities they serve, incorporating women’s voices on employment and health needs through the WRA survey.
The outcome of this use case provided three key recommendations for policymakers in Mexico City. These recommendations prioritize the needs of low-income women and children while addressing the current demand for childcare. GIZ, along with its platform partners, call for the following actions:
The platform is easily accessible to policymakers, enabling them to quickly absorb and utilize the data to improve childcare infrastructure in Mexico City.
Additionally, the platform is highly adaptable for new areas of policy. By leveraging the same data and NLU model, Mexico City and the national government can continue using the platform to make spatially aware, need-based decisions across various sectors. Furthermore, the platform is replicable in other Spanish-speaking countries. making it highly scalable. Mexico City has already embraced this approach and expanded the platform to include new datasets, which you can learn more about here.
