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The Gender Data Learning Series is an in-depth course that equips financial service providers with the skills to develop or enhance their women-centered strategies using sex-disaggregated data. The Learning Series will feature guest experts with experience developing successful sex-disaggregated data strategies, presentations of use cases and best practice tools, and opportunities for peer learning with fellow participants working at FSPs around the world.
Through a hybrid learning path combining guided self-paced learning modules with live sessions, participants will be able to access tools and develop skills in their own time as well as meet virtually as a group to gain insights from global experts and engage with peer practitioners.
Data use-cases: Practical exam-ples of how financial institutions have leveraged gender data to drive business decisions.
Diagnostic Tools: Tools
and strategies for identifying strengths and gaps in your insti-tutions’ current collection, analy-sis and reporting of gender data.
Analysis and Reporting Best Practices: Best practices for identifying KPIs and reporting out on gender data.
Common Challenges and Solutions: Best practices for de-fining women-owned enterprises, tackling data quality issues, and more.
This series will be of interest if you are looking to:
The program is designed for teams looking to enhance their sex-disaggregated data analytics. This includes data practitioners (i.e. business intelligence team members), as well as women’s market managers and senior business decision-makers. It is recommended that each FSP attending the series nominate at least two staff members to attend: ideally a combination of the business intelligence/ IT team and segment teams.
The series consists of weekly 90-minute live webinars held every Wednesday via Zoom from September 20th through October 11th.
Additionally, business intelligence participants will be required to complete four 90-minute “on-your-own” modules between sessions, which cover in-depth content on the processes of gender data collection and use.
Participation is by invitation only. There is no cost to attend—however, attendees will be selected based on the relevance of the course to their job function and are expected to participate throughout the entire learning journey.
