Impact Data Journeys - Pathways to Success
During the session, the co-facilitators provided a platform for the winners of the D4GX India Empowerment Challenge - a group of passionate and dedicated change-makers who are using data to make a difference - to share their experiences, learnings, challenges, solutions, and best practices from their data journey so far. The discussion was not limited to just challenges, however; the co-facilitators also encouraged exploration of opportunities to scale data-driven programs that could benefit the most vulnerable communities.
Overall, the session served as a platform for all involved to collaborate and learn from one another in the pursuit of creating data-driven solutions that can empower communities and bring about positive change.
Here are some key learnings from the session:
Overall, the session served as a platform for all involved to collaborate and learn from one another in the pursuit of creating data-driven solutions that can empower communities and bring about positive change.
Here are some key learnings from the session:
- Collected data can be used to design and implement programmatic interventions.
- Empowering the community by giving data back to them allows them to own their stories and seek actionable changes. However, data interpretation by stakeholders can be challenging, there can be a lack of ownership of results, and data privacy, ownership, reliability, and cleanliness can be concerns.
- Collected data can also be used as an intermediary for sharing with key stakeholders for building capacity, policy advocacy, etc. This can help devise solutions with some certainty, receive objective results, and create a platform for dialogue. However, challenges with changing capitalistic mindsets about ethical data, data reliability of government data, and making sense of a lot of data can be concerns.
- For both as an intermediary and intervention, data has to be used to keep all stakeholders informed in a collaborative and trustworthy manner.
- Challenges with the type of data used include lack of diversity and consistency in primary data, difficulty accessing secondary data for children/women, and unreliable government data that can lead to a lag in timely analysis and inconsistency among variables.
- Data for good extends to providing access, connecting dots, and demanding action. Deep listening to communities from which data is collected is critical to unlocking systems.