Ditch “Data-Driven”: What’s Your Data Moment?
Lately, it feels like you can’t go a day without hearing the phrase “data-driven.” It’s become a kind of shorthand for being strategic.
But in reality, organizations are not “data-driven”, they are driven by people and systems. Because data and information are never neutral, they are created through people’s choices, influence, perspectives, and power. What questions get asked, whose voices are heard, how stories are told, and what is left out all shape the data we use.
Alternatively, when we focus on creating moments with data, the goal shifts from reporting numbers to building shared meaning and understanding. Using data to spark these moments opens space for reflection, conversation, and, most importantly, action. When done with care and intention, data moments center the people who shared their insights, expertise, and, at times, their trauma, and give back ownership over how their data is used.
Stop designing for the numbers instead of the people behind them.
In many reports, the most compelling insights get buried under pages of text, weighed down by dense analysis, and paired with a callout quote that may not even connect to what was just read (we’ve been guilty of this too).
When we prioritize complexity over clarity, we lose the chance to create moments that stay with people. The result is that audiences leave without understanding the findings, no action is taken, and the communities and people who shared their data feel unheard.
Let’s look at some example data from a focus group with African immigrants accessing food pantries:
TO THAT:
“We want them to value our food as their own. Our food is healthy and good. We want them to value our food and have them in their stores.” - Focus Group Member
FROM THIS:
Participants expressed a desire to see these foods integrated into pantries.
Both communicate the same idea, but they work very differently. One tells you what the data is (in the point of view of whoever is creating the report), leaving little room for discussion or shared understanding. The other invites conversation, grounded in the lived experience of the person who shared it. That’s what makes it a data moment — it creates space for people to engage with the insight, question its meaning, and decide together what should happen next.
This Data Moment in Action
The focus group quote above comes from a conversation in Kansas City with African immigrant community members, where we listened to their experiences and challenges in accessing free food. The goal was to create a report of the findings along with recommendations for the future.
Before the focus group: As we’ve shared earlier, data is created. So it is influenced by who writes the questions, who hosts the conversation, and who is invited. For this focus group, we partnered with a refugee service organization that provided trusted translators. They reviewed the prompting questions ahead of time (Spoiler: the group didn’t need much prompting, they had plenty of ideas and feedback) and shared the invite with African Immigrant communities across the metro. This moment built trust both in the data created and in the people sharing it, signaling that their expertise would be honored.
At the focus group: The conversation was fluid. We began with questions about barriers to food access, but participants guided the discussion where they wanted it to go. When a barrier was named, so was a possible solution. Participants were recognized as experts in their own communities and offered direct recommendations to the food bank for improving food access in Kansas City.
After the focus group: Participants were compensated for their time. Notes and direct quotes were shared back with participants to confirm that their words were heard and recorded accurately. The report was shared back with the group, inviting their feedback on whether changes should be made before moving forward.
Designing the insights: We reviewed each quote individually, sorting them into relevant categories. This wasn’t an AI-driven “categorize this text” exercise, it was hands-on. We used a Miro board with every direct quote on a sticky note and sorted each one ourselves. The same process was used for direct recommendations from participants. These sorted quotes became the foundation of the report, highlighting areas the food bank needed to prioritize, such as rising food cost, access, and food choices.
💡 Another way to do this is by bringing stakeholders and community leaders together in-person to do the sorting. Print out each quote and put them all on a table for people to categorize. This approach gives people the time to look at each quote, sit with it, question it, and make sense of its meaning together as they categorize.
By physically placing each quote in a category — whether in Miro or in person — people slowed down, sat with the information, and decided its meaning together. This created “aha” moments and deeper understanding of the data.
Using everything we learned, we were able to organize the report into three clear sections:
Missing: What we learned about communities facing food insecurity who are often underrepresented, missed in public data sources or traditional surveying methods, and missed at charitable food sites.
Meeting: Service design and groceries that meet the needs and desires of people who we’re missing.
Matching: To match the needs and desires of people who we’re missing, the food bank network can add, adapt, accelerate or release these recommendations given by people with lived experience or those who are often missed.
Instead of sharing a litany of facts, the data was organized in a way that helped decision-makers take action in meaningful ways that honored the intent of community members’ feedback. Because data moments aren’t just about accuracy, they’re about authenticity and resonance.
Take a look at the full report here >>
How to Create Your Own Data Moments
Have we convinced you to ditch the “data-driven” mindset yet?
As we focus instead on creating data moments, there are a few values we recommend to keep in mind:
Data should move in feedback loops. Return it to the people who shared their experiences so they can influence the decisions it informs.
Question data and prioritize lived experiences. Numbers alone do not tell the full story. Examine data critically, and ground insights in the experiences of those most impacted.
Name the context. Without naming the conditions that shape data, you reinforce the inequities it reflects.
Acknowledge that data is created. It is not something to be simply collected. Every choice (from the questions asked to how findings are shared) shapes it.
Data should build trust, not break it. If you are not prepared to act on the information you create, do not ask for it.
Clarity over complexity. Complex charts are not always smarter charts. Simple, clear visuals help people see the story faster, ask better questions, and take action.
If you are looking for a way to start, begin with a recent piece of work where people shared their knowledge, experiences, or stories with you (this could include a feedback survey, focus group, or a community conversation). Choose one insight to work with first.
Using the values above, turn that insight into a data moment that keeps their voice intact and grounded in the context they named. This could be a slide deck that tells a story rather than a dashboard of figures, an interactive experience that invites stakeholders to engage with the insights, a video that captures the tone in which the information was shared, or another format that makes the meaning visible without stripping away their perspective. Data moments do not need to wait until you are ready to share a final product — some of the most meaningful moments emerge in the midst of creating, listening, and learning together.
When you create that data moment, share it first with the people who shaped it, inviting them to reflect on how it is represented and what it should inspire next. If you choose to share it with us as well, we will celebrate it alongside you and offer ideas for keeping the story authentic, resonant, and connected to the community at its source.
Meet the Author
Jenna is passionate about using systems and design to connect people to information. In her role as a network development consultant with See What I Mean (SWIM), she helps network leaders, changemakers, and communities explore data in compelling ways to drive change.
Through authenticity, co-creation, and empathy, Jenna helps design stories and engagements that transform data into action. You can often find her in collaborative spaces surrounded by a cluster of sticky notes, supporting organizations to find clarity (while turning those big ideas into tangible actions 😉).
Jenna has worked with a variety of networks in youth development, financial literacy, housing, hunger, and health. She graduated from the University of Northern Iowa, earning a B.A. In Global Studies: Peace, Conflict, and Human Rights. She was a part of a research cluster at the University College Cork understanding migration, mobility, and culture. She is a Certified Nonprofit Professional (CNP) and has an M.P.S. in Data Analytics and Visualization from MICA.
Meet See What I Mean (SWIM)
See What I Mean helps mission-driven organizations and businesses turn bold ideas into meaningful progress. As pragmatic optimists with deep expertise in organizational change, we combine proven theory with real-world experience to navigate challenges, build buy-in, and keep momentum moving. Our collaborative, facilitative approach brings clarity, focus, and energy to even the most complex initiatives, whether transforming a company, strengthening a community, or tackling a global challenge. Drawing on years of leading organizations and consulting with dozens of clients, we share hard-won insights and practical tools to accelerate the work of those making a difference in the world.
Contact our team to see how we can help you transform data into action.