Scaling Data Models to Create Transformational Impact
It has never been more necessary to use technology as an enabler to create better systems and processes, and to build platforms to analyze and share data rapidly amongst teams and stakeholders. Through scaling tech solutions and using data effectively, organizations can create differential positive changes within their own communities.
In this one-on-one conversation, Nitin Mathur from Quest Alliance shares the organization’s experience with building data and technology tools, as well as his insights on what is needed for an organization to scale, adopt technology holistically, and act collaboratively.
A little about Quest Alliance’s journey with technology and data: At Quest Alliance, the inherent belief is that people closest to the field know best. This means that decision making is decentralised, and innovation happens ground up. Since the team is also young, they are more open to the use of technology. As such, Quest Alliance was able to bring together teams that were chartered with data or technology. They created a Knowledge Hub which was the coming together of their Research and Advocacy team as well as their M&E and Impact team. This led to them getting nuanced insights because it brought together two different sources/formats of data.
Here are some insights from the session:
In this one-on-one conversation, Nitin Mathur from Quest Alliance shares the organization’s experience with building data and technology tools, as well as his insights on what is needed for an organization to scale, adopt technology holistically, and act collaboratively.
A little about Quest Alliance’s journey with technology and data: At Quest Alliance, the inherent belief is that people closest to the field know best. This means that decision making is decentralised, and innovation happens ground up. Since the team is also young, they are more open to the use of technology. As such, Quest Alliance was able to bring together teams that were chartered with data or technology. They created a Knowledge Hub which was the coming together of their Research and Advocacy team as well as their M&E and Impact team. This led to them getting nuanced insights because it brought together two different sources/formats of data.
Here are some insights from the session:
For digital transformation to happen, we need to look at it holistically. At the highest level, this comprises looking at data, technology, process, and change management.
At Quest Alliance the data aspect was taken care of by bringing together the research, M&E and analytical teams. In addition, to drive technology, they set up the Quest Experience Lab and Innovation Lab that helped accelerate and foster innovations from the ground. Through this, they learned that:
To allow organizations to scale rapidly while also innovation at the same time, we need a supportive ecosystem
A significant part of this ecosystem is providing mentorship and coaching to nonprofits on the:
In terms of funding, organizations don’t need too many resources initially, but this is likely to go up as systems become more sophisticated.
As they scale, organizations will also likely grapple with the following questions:
It would be valuable to foster shared actions – shared platforms and metrics – in the sector. To enable this:
At Quest Alliance the data aspect was taken care of by bringing together the research, M&E and analytical teams. In addition, to drive technology, they set up the Quest Experience Lab and Innovation Lab that helped accelerate and foster innovations from the ground. Through this, they learned that:
- To make sure processes are robust, organizations could consider having a systems and process architect to do an audit, understand the current landscape, and then develop a blueprint for the future of the organization
- How the changes within the organization - with regard to data and technology - are managed is critical. Because once you get the pieces together, it’s the same set of people who have to execute on it. So organizations need to ensure that all voices are heard, and when decisions are made around digital transformation, they are made with buy-in.
To allow organizations to scale rapidly while also innovation at the same time, we need a supportive ecosystem
A significant part of this ecosystem is providing mentorship and coaching to nonprofits on the:
- Cultural aspects of why it is needed. Organizations need help internalizing the adoption of data and technology.
- Necessary skills and expertise needed by the teams delivering on these projects.
In terms of funding, organizations don’t need too many resources initially, but this is likely to go up as systems become more sophisticated.
As they scale, organizations will also likely grapple with the following questions:
- How do you build data and technology into the design so that they become real, usable tools, and part of the way we work? Instead of getting people to just enter data into the trackers and dashboards
- What kind of tools should an organization use? Especially because the landscape changes very rapidly with respect to technology. Should one therefore use tools that are standard, but are likely to become obsolete by the time you build your system in 2-3 years?
- How do we account for the nuances of off-the-shelf technology? Especially because many of these tools have been built for the corporate world where the objective is revenue and profit maximization. But these are not strategic priorities for nonprofits.
- Should one build or buy? For example, Quest Alliance does not build their technology solutions from scratch because they are not an IT or data organization. However, they do work with open-source software and technology because they believe that’s where the world is headed.
It would be valuable to foster shared actions – shared platforms and metrics – in the sector. To enable this:
- Documenting of learnings is critical – capturing what went well, what didn’t. And making it accessible to wider audiences. Because the rich knowledge comes from what one has learnt during the process and experience of designing and working with data; and not just from the data collected.
- It is important to have all the data that is collected in one place – first within a program, then across programs and then across the organization. This way you can discover, identify and draw trends, patterns and insights emerging from all this information.
- The democratisation of data allows different people to look at the same data and draw different conclusions. This allows for the possibility of debate and discussion driven by data.
- It is important to share insights from the data with the wider community and diverse stakeholders – donors, nonprofits, partners, people in academia, etc.
- The data privacy and security concerns on what can be shared need to be taken into account. For example, while individual data cannot be shared, aggregate data can be shared.
- Dissemination via media is critical because the learnings then reach a much wider audience and can get adopted at scale and thereby institutionalized.
Quotes
Key Statistics (from Dasra's D4GX report)
- 7% poorest rural households use the internet vs. 27% richest rural households
- 20% poorest urban households use the internet vs. 62% richest urban households
- 48% males between ages 15-29 can use the internet vs. 32% females
- 64% females are literate in India compared with 80% males
- Scheduled Tribes and Scheduled Castes achieved 59% & 66% literacy vs. 72% of the remaining national population. Of this, drop-out rates among tribal adolescents (especially girls), is particularly high.
- 20% poorest urban households use the internet vs. 62% richest urban households
- 48% males between ages 15-29 can use the internet vs. 32% females
- 64% females are literate in India compared with 80% males
- Scheduled Tribes and Scheduled Castes achieved 59% & 66% literacy vs. 72% of the remaining national population. Of this, drop-out rates among tribal adolescents (especially girls), is particularly high.