Demographic data plays a huge role in ensuring an equitable scholarship program. As the conversations around equity, diversity, and inclusion evolve, grantmakers must ensure that their programs keep up with emerging best practices. But how exactly does demographic data serve not only grantmakers but stakeholders and students as well?
To support diverse initiatives
Institutions are quickly becoming aware of how their intake programs have previously excluded marginalized communities. As one of the few viable options available to students who need aid, scholarships have a role to play in this too. Typically, a program’s diversity is at risk when one of the following is true:
- There is an assumption that all communities are already catered for equally
- There is a lack of data available to challenge biases in decision-makers
- Meritocracy is prioritized without acknowledging the material conditions of otherwise viable candidates
To provide insights on targeted communities
Test scores don’t always tell the whole story. Demographic data can be a powerful tool in understanding targeted communities when the right information is collected. Information such as location, household income, and racial background often offers insight into an unseen part of an applicant’s life: their support system.
To provide reports to your stakeholders
Most programs rely on stakeholders and scholarship donors to function. These groups need to be included in the process. Demographic data can play a crucial role in attracting donors and sponsors who are invested in supporting a program’s targeted communities.
Demographic data is a crucial metric for programs undergoing an internal transformation as the numbers change over time.
What to avoid when collecting demographic data
Excluding administrative data
Student administrative data and academic reports are vital to creating more equitable programs. They provide the baseline that demographic data can be analyzed against to find the discrepancies between communities and see who is underserved and why.
Not involving stakeholders in data collection
One of the reasons why demographic data collection has been adopted slowly is a lack of understanding of its goals. Misunderstandings here can create hesitancy within stakeholders. Involving them in the data collection process means explaining the goals of the process and how the data is also serving their goals.
Not offering transparency
Transparency in data collection is essential across the board. Without it, there can be no accountability. If a problem comes up in the process, transparency is how issues are isolated and worked on.
Not providing a secure method of data collection
Corrupted data is useless because it’s unreliable. Not safeguarding the data intake process, training administrators, and installing quality checks along the way is a sure way to compromise demographic data.
Not having a plan for how to use the data
Data is only as good as its purpose. Before demographic data can be collected, there should be a clear understanding of what it’ll be used for. This understanding needs to be communicated to both stakeholders and the applicants who will be asked to contribute to the dataset.
Data collection best practices
Continuously collect data
High-quality data is often measured by accuracy and relevance. Accuracy falls under the actual collection process, but relevance speaks to how well data aligns with the interpreted realities. Continuously collecting data doesn’t just bring in new information; it helps to update existing datasets too.
Collaborate with experts
Ultimately, all the data in the world is just that – data. Using it requires an understanding of the people at the source of the data and the outcomes it’s working towards. Bring your data to industry experts. Intra-community experts offer diverse perspectives which can help uncover a program’s blind spots, both in its data and practices.
Work with partners
While scholarship programs provide a financial support system to successful applicants, they may not always have the resources to do everything in-house. Partners help in many ways. Specialized processes can be outsourced to relevant partners, but they help maintain accountability as an external voice.
Partners aren’t always people, either. Scholarship management software providers are a key asset in the fight to create more equitable programs, leveraging technology to overcome issues like budget limitations and automation in the data collecting process.
Remember that data is not one size fits all
Partners and intra-community experts offer powerful new perspectives. Including these perspectives is important because demographic data is about understanding communities in a broad, overview sense as well as the nuances that can get lost in a data stream.
Data is about how it’s collected, analyzed, and used towards certain outcomes. While that can seem daunting, it doesn’t have to be. If you’re ready to simplify your scholarship management process, get started with Scholar’s App today.