Community engagement is an essential component of successful program implementation. It elevates the assets and challenges of a community to support the creation of responsive programs, policies, and practices. CMHIS identifies community engagement and mental health needs assessment as critical first steps in implementing mental health care practices.  

Data can help organizations understand community needs, identify service gaps, and guide implementation decisions. However, numbers alone rarely explain how people experience a program, practice, or system—or what the findings mean within a particular community context. Data storytelling brings together evidence, clear communication, and community interpretation to help people make meaning from data and use it to inform action. 

One participatory data-storytelling approach is a data walk. A data walk is a community engagement approach that helps introduce a wide range of community members to data, gather their input, and make sense of what they are seeing. This approach pairs impactful data storytelling with facilitation tools to move from data to action. Getting community input can reveal missing context, help you identify priorities, and inform implementation decisions. 

 This process can make complex information easier to engage with, incorporate lived experience into data interpretation, surface assumptions or gaps, and support shared decision-making. 

Consider the following scenarios and how the data is shared:  

Imagine walking into a community planning meeting as a participant and someone hands you a 40-page report on community needs. The report is mostly text, with a few graphs and charts. Everyone is asked to read the report and share their feedback. After 20 minutes, the floor is open to discussion. You would likely feel overwhelmed.  

Without providing the data through visuals and accessible language, participation would be limited. Now imagine if the data is presented through a data walk.  As you enter a community space, a “data curator” greets you and explains that you are invited to explore the displays throughout the rooms. The displays are visually appealing and don’t overwhelm you with too much information on each image.   

Participants are invited to view the displays, ask questions, make statements, or affirm the data. After exploring and reflecting on the information, community members come together for a welcoming discussion about what they observed.  Participants share insights, ask questions, and connect the data to their own experiences.   

In the second scenario, you leave feeling heard and valued, having contributed your lived experience and knowledge to the conversation.  

A highly effective data walk is well designed: it considers the purpose of the event, the needs of the audience, and the outcomes it aims to achieve. Taking the time to plan can greatly improve the effectiveness of the data walk. 

Start with Purpose 

Purposeful planning is key to ensuring your data walk is accessible to participants and informative for program delivery, research, and communications. Begin by defining a purpose. Understanding what you are trying to achieve sets the foundation for everything else. Ask yourself: 

• What is the outcome we are trying to achieve? 

• What do planners need to walk away with? 

• What could happen during the data walk that would demonstrate success? 

Consider Your Audience 

Next, consider your audience. Think about which community members’ perspectives are essential to the process.  Also think about who is often overlooked or historically excluded from planning and decision-making, and how you can engage them. From there, consider what each of these audiences needs to actively participate. This will help you think through what data to present and how to present it. 

Understanding your audience also helps you determine the “when,” “where,” and “how” of your data walk. Think carefully about the logistics that will lead to the most participation. Consider timing, location, and other potential barriers that would impact participation. This could mean hosting the event outside traditional 9-to-5 hours or on a weekend, providing food and childcare, getting materials translated and hosting discussions with simultaneous interpretation (where applicable), and choosing a trusted location within the community. 

Outreach and Participation 

After you understand the audience you need to reach, how will you get them to participate? This is why marketing and recruitment are important. Consider which channels will be most effective for your recruitment. Prioritize trusted outreach channels to recruit people whose perspectives are needed. Besides traditional communications channels, include trusted community organizations or leaders to reach the community. 

In your messaging, being clear about what the data walk is (and isn’t) will help potential participants understand their role and expectations. Also highlight any incentives that could engage potential participants. These incentives can strengthen recruitment. 

Design the Data Walk 

Your next step is to design the data walk. Design decisions should be guided by the purpose, audience, accessibility needs, and data.  Consider which information you most want feedback on. Are there any pieces of data your team needs help making sense of? Prioritize those. Take the time to ensure your data is clear and choose the image or visual that represents the data most accurately.   

Alongside the data you display, add questions for the audience to consider. Some ways to encourage community interpretation are to provide sticky notes or invite participants to jot down what they observe. You could also offer stickers or instructions (e.g., draw a star or +1) so participants can indicate when they agree with a comment. Some other ideas for participants to contribute might be sharing verbal responses, including facilitated small groups, or offering audio responses. 

Facilitate the Discussion 

After giving participants time to review the data and add their comments and questions, the group comes together for a facilitated discussion. A facilitator then guides the group through observations and questions while making space for different perspectives and areas of disagreement. 

Once the discussion wraps up, define next steps so participants understand how their input will be used, what decisions it may inform, what continued participation in the project might look like, and when they can expect an update. 

Community Engagement: Share Findings and Next Steps 

Data walks are a way to connect with your community in a well-designed, engaging, and accessible way. While the steps outlined above are useful for planning a data walk, the most important factor is to consider your specific community context and what will—and will not—work for the people you hope to engage. 

A data walk can also serve as a connection point for building strong, responsive community partnerships. By adding community context to the findings, data walks can help move data toward action, identify priorities, and inform implementation decisions.  

Closing the feedback loop by sharing a summary of the data walk, related materials, or findings from the broader evaluation with participants and the community is also an important part of community engagement. Doing so demonstrates accountability, supports a more inclusive engagement process, and helps build trust with the communities you engage. 

 

References: 

Murray, B., Falkenburger, E., & Saxena, P. (2015, November 10). Data walks: An innovative way to share data with communities. Urban Institute. https://www.urban.org/research/publication/data-walks-innovative-way-share-data-communities