- In 2022, CORE launched the Data for Change program in partnership with seven community-based organizations and Providence Community Health Investment.
- CORE's Technical Assistance (TA) coaches and data experts collaborated with cohort members to grow their capacity to use data to drive positive change.
- Our experience highlights important lessons that other organizations should consider when working to better use data for change.
In 2022, the Providence Center for Outcomes Research and Education (CORE) launched the Data for Change program with the goal of helping community-based organizations (CBOs) better use data in support of their efforts to advance health and equity. In partnership with Providence Community Health Investment and a cohort of seven CBOs, our Technical Assistance (TA) coaches and data experts collaborated with cohort members to grow their capacity to use data. It was a fantastic experience for the CORE team, and participants came away with new skills, strategies, and confidence to take control of their data and harness it for good.
As we reflect on year one, it's clear that CBOs of all sizes can leverage data and analytics to advance their missions. The cohort also learned valuable lessons that other organizations should consider when working to grow their capacity to use data for change.
Here are 7 key takeaways from our experience so far:
1. Remember that your data is primarily about people: When working with quantitative data, it is essential to humanize those numbers. Behind the metrics and statistics are people whose lives are far more complex than the numbers we examine. That's why it is essential to focus on ethical data collection and use, consent, confidentiality, and security, and consider how data can cause harm. Many resources exist to help think about how to use data responsibly (we'll share a few at the end of this blog post). But one of the most valuable data skills is ongoing reflexivity throughout the entire data lifecycle. From interrogating assumptions and potential bias built into the initial project design to carefully considering your approach to data storytelling, think through how you can use data to showcase community assets and remember to use people-first language.
"Our ongoing question is always going to be: how do we use data as a way to build solidarity, trust, and relationships?" - participant
2. Engage both leadership and frontline staff: Data for Change participants found that engaging leadership and frontline staff in data initiatives was vital to building a collective vision and co-ownership of new processes and tools. This work often requires new thinking and structures, making change management an essential part of any effort to grow organizational data capacity. Organizations should take the time to build buy-in and understand the motivations and current challenges of all stakeholders.
"It's easy for staff to be left out of the conversations leadership is having about the data collection process, so making sure we're communicating across positions and programs is super important." - participant
3. Create dedicated time for data: Time and capacity are two of the most significant barriers to developing a strong data culture, data strategy, and high-quality data. According to participants, one of the most valuable components of Data for Change was the time dedicated to working with CORE's TA coaches. This protected time provided motivation and space for cohort members to advance their data-related objectives. By establishing time for data entry, quality, analysis, and usage, we were able to improve data initiatives and support staff.
"Interpreting or making use of our data is not linear; it's a continuous process. You might go to the next step but then go back two steps. We went through that quite a bit throughout our journey. Learning to be flexible has been one of the biggest things for us." - participant
4. Celebrate and build on small wins: By modeling the use of data with all staff and building on small wins, participants built confidence and skills over time. This helped break down barriers and build a sense of success. Furthermore, recognizing and celebrating the fact that everyone has a role to play in data collection and data storytelling, regardless of their perceived data literacy, proved valuable in helping build a more robust data culture within the organizations.
"We sent out a survey to our membership with a very long letter explaining why we were asking for everything. Thus far, we have a 60 percent return rate. We've never had a 60 percent return rate on anything." - participant
5. Value qualitative data: For many organizations and staff, being a "data person" may be associated with complex quantitative figures and burdensome tools and reports. CORE's work with cohort members to expand their definition of data to include qualitative information led them to uncover skills within their organizations that help center the experiences and needs of community members. By valuing qualitative data, we were able to gain insight into participants' experiences and understand the "why" and "how" behind program successes and challenges. This also reinforces our first takeaway: remembering that data is about people.
"What we're taking away from this process is that there are many ways of collecting data. Our data collection is often rooted in relationships, and it's nice to be firm about that being a valid way of collecting and integrating data." - participant
6. Provide customized support and training: The Data for Change year one experience made it clear that while content-based workshops may seem more efficient, it was more effective to begin with individualized TA that organizations can apply to their specific situations and projects. After a few individual TA sessions, participants were better equipped to come together with shared language and context and to share their experiences and learnings with other cohort members.
"While the toolkits and reference materials are useful on their own, the TA sessions–with their active thinking partnership and collaboration--have been profoundly impactful" – participant
7. Define your own data needs and outcomes: As participants worked to inventory the “what, why and how” of their existing data collection efforts, some pointed to funder reporting requirements as the main reason for certain data activities. This prompted crucial conversations about whether that data collection is an efficient use of resources and the ethics of seeking information from community members when it’s not necessarily being used to directly benefit them. Ultimately, when organizations can define their data needs, goals, outcomes, and ways of measuring those outcomes, they are better equipped to use that data in service to the communities they serve.
"We need to keep asking ourselves why we are doing things the way we're doing them and looking at our data and what can we learn from it to make our work stronger and be more effective in the way we deliver our services." - participant
The first year of Data for Change was a valuable learning experience for our team and the cohort. As we move into year two with the recently announced 2022-23 cohort, the CORE team looks forward to using these learnings to improve the program and support our other partners' data initiatives.
That includes expanding our Data for Change offerings to provide additional flexibility for partners. Organizations can apply to participate in the Data for Change cohort, a nine-month commitment including three convenings and a small participation stipend. Or they can opt for a more flexible request-based TA bank. In 2022-2023, four CHI grantees are participating in the cohort, and seven additional CHI grantees will receive individualized TA from the Data for Change team.
To learn more about Data for Change, get in touch!
- Q&A with CORE's Lisa Angus & Lizzie Fussell: Translating data into action
- Blog post: CORE announces 2022-23 Data for Change cohort
- Learn more about Providence Community Health Investment
- Data ethics resources: Data Feminism, Urban Indian Health Institute, Chicago Beyond's "Why am I always being researched?", Data Justice Lab, and Urban Institute's Principles for Advancing Equitable Data Practice