Wonder Woman

Wonderwoman is a machine-learning supported platform that enables mothers to return to the workforce in decent jobs. Wonderwoman offers personalized development plans to boost self-esteem and maintain competitiveness while on maternity leave (0-5 years).

The problem our solution solves is low participation of women in the labour force in Asia-Pacific post-childbirth. Women in Asia-Pacific are on average 70% less likely than men to be in the labour force. The gap persists despite economic growth and increasing education levels. Low self-esteem experienced by new mothers, or mothers who have been out of the labour force, is not given adequate attention as a cause for low labour participation. Combined with technological advancements and the shortening lifespan of skills, there is a greater need for women to maintain their relevance to the labour market.

Sheryl Sandberg shares in Lean In that women keep themselves from advancing because they don't have the self-confidence to do so. She says, "We lower our own expectations of what we can achieve." As every woman experiences maternity differently, our theory of change relies on machine-learning to create personalized programs by empathizing, motivating, and incentivizing the user to develop habits that can facilitate their re-entry into the labour market.  

1. Increase women participation in the workforce post childbirth
2. Women continue to be competitive in the workforce during maternity leave 

Backend data on the application - 75% of women on the platform achieve their plan in returning to the workforce

Backend data on the application - 80% completion rate of personalized development programs

Before and after self-assessment tool on a specific list of characteristics - 85% of the women self-assessed to having higher self-esteem after using the platform

Our solution is unique because the issue of low female labour participation is not commonly tackled by addressing low self-esteem. When analyzing gender-based disparity, we have identified childbearing and rearing as the keystone difference in women’s career trajectory. Other solutions in the field tend to focus on access, volunteering, and job placements. The use of technology is novel in our solution because it challenges traditional forms of initiating behavioural change by pushing the boundaries of technology-human interfacing. The digitization of emotional intelligence has immense potential for customized-servicing of women’s needs.

Our technology is human-centered because it is based on the premise that no two individuals are the same and the approach to each user is done in a personalized way. The platform will collect data input from the new mothers and elaborate on them through an algorithm that can use logic to model human-like responses.

The solution will primarily be an application and people can access through smart phones, tablets, and desktops. In the long run, the business model has the potential to set up physical spaces, such as community centers, based on demand and membership across markets. The platform will be at a competitive rate to guarantee access and inclusivity. 

The members of the team have all full-time jobs. We plan to research and pilot the idea alongside our existing responsibilities. 

A limiting factor of the solution is in the user’s adoption. Our target users may not believe that tech solutions can support or influence them. For this, we need to research and test the interface, and identify early-adopters to champion the movement. Another factor that could limit our success are other variables that play into the problem of low female labor participation, such as access to opportunities and heuristics biases. We anticipate building features into the platform to address various facets of the issue in the future, but will focus on self-esteem and competitiveness as the solution’s unique value.

We are applying to Solve because we want to learn from a novel community of thinkers and doers. With experience in the development industry, we are driven by the desire to tackle some of the world’s most pressing problems but we also believe that we need to instill new perspectives and tools through cross-sector collaboration. By becoming a Solver, we hope to primarily tap into cutting-edge research around behavioral science and artificial intelligence to develop a solution that gets to the core of the identified problem, and delivers real value to women.

There are no partners at the moment. 

Most of them are based in India: JobsForHer, Avtar I-Win, Pubic programs, Sheroes and HerSecondInnin