In my eight years at Research for Action (RFA), some of my favorite work has been providing technical assistance to education organizations making significant strides in outcomes for students and youth, but who felt overburdened by data or wondered if they could be doing more with it.
Technical assistance involves providing targeted support to an organization or community to help them achieve their goals. It’s a common way to build their capacity. The organizations that come to RFA for technical assistance are passionate about their missions to help students succeed, and they recognize the importance of data in reaching their goals. But the sheer volume and complexity of managing data can be daunting.
I love this work because I believe in the power of data, and I have seen firsthand how it can be leveraged to inform action and improve programs and policies. I also know that data collection and management is time-consuming and often put on the backburner. When education organizations take the time to prepare for data collection, they find that data can help their staff, partners, and youth understand progress, celebrate meeting goals, and make data-informed adjustments.
To overcome some of the challenges of data management, in this blog post I’m sharing the top three issues I encounter when providing technical assistance about data (or when I’m collecting data myself), and why they matter.
Unclear Vision for the Data
Organizations often collect data primarily to satisfy reporting requirements—to the state, funders, etc. However, starting there makes it hard to see beyond those requirements. It’s also important to think about what else the data could be useful for. The time spent collecting required data could be leveraged to better inform programming or decision-making within the organization while also satisfying requirements.
Developing a vision for what data can be used to do helps define what data is important to collect, and it motivates the effort needed to collect it. When team members understand the value that will come of the data, it makes it a lot easier to handle the data entry or fill out that survey. This approach transforms data collection from a mere compliance exercise into a strategic asset for organizational growth and effectiveness.
Inconsistent Definitions and Formats
If deciding what to collect is the first hurdle, deciding how to capture it is the next. Establishing clear and consistent data definitions is crucial for ensuring data quality and usability, especially when data collection involves multiple individuals or departments, or extends over time.
Some examples of standardizations worth clarifying up front include:
- Field Structure: Decide on consistent formats for common fields. For example, determine whether to capture names in a single field or separate first and last names.
- Numeric Representations: Choose between cardinal or ordinal numbers for certain data types (e.g., grade levels as ‘9’ vs. ‘9th’).
- Categorical Variables: Define clear categories at the appropriate level of specificity. For example, if capturing course subjects, do you want to use broad categories like “Math” or specific subjects like “Geometry” or “Algebra?”
- Room for Evolving Standards: While maintaining consistency is crucial, it’s important to acknowledge that some data standards may need to evolve over time. For instance, the shift from binary sex indicators to more inclusive gender identity options demonstrates how data collection practices can and should adapt to societal changes.
By investing time to establish clear data definitions and formats, organizations can significantly reduce future complications in data management and analysis, leading to more valuable and actionable insights.
Difficulty Summarizing or Visualizing Data
Another common challenge is understanding and making sense of large datasets. Organizations may clear the hurdles of defining what data can help them do and collecting it consistently. Then they have a pile of data and are not sure what to make of it.
If the reason for the data exercise is to manage individual case files, staying zoomed on one person might be straightforward. However, we frequently work with partners who want to be able to get the big picture of program impact or progress. This 30,000-foot view often requires summarizing and visualizing data. This step can be particularly useful for identifying trends, measuring progress, or identifying subgroups that require additional support.
Through my technical assistance work, I’ve developed custom tools and strategies to help organizations overcome this challenge and extract meaningful takeaways from their data. Some key challenges we help resolve include:
- Scaling from Individual to Aggregate: Some organizations find it difficult to transition from detailed individual records to meaningful aggregate findings.
- Identifying Trends and Patterns: Without proper summarization techniques, it’s challenging to recognize how programs, offerings, or impacts change over time or vary across different subgroups.
- Actionable Insights: Many organizations struggle to identify key trigger points or thresholds that require follow-up actions, especially when dealing with large volumes of data.
Through data summarization and visualization, organizations can transform raw data into usable intelligence, driving continuous improvement and demonstrating the value of their work more effectively.
As a self-proclaimed data geek, I view these three challenges as exciting puzzles waiting to be solved. While these are the top three challenges I’ve come across, they are by no means all of the challenges I’ve seen or supported organizations in addressing. My passion lies in unraveling the complexities and finding tailored solutions for our partners.
At RFA, our approach to technical assistance is deeply personalized. We believe in meeting our partners where they are and crafting solutions that align with their unique goals and vision. Whether it’s providing expert advice or developing custom tools, we’re committed to guiding organizations not just to where they want to go, but also in helping them define their data journey.
If you’re intrigued by the possibility of leveraging your data more effectively or if you have questions about the insights shared here, I’d love to hear from you. Reach out to explore how RFA’s Technical Assistance team can help you unlock the full potential of your data and drive your agency forward.