Dignity in Data
- Lisa Askins
- Jul 12
- 3 min read
Updated: Sep 2
Honoring the humanity behind every number.
We don’t always think about dignity when we’re working with data. But we should.
Because behind every number is a name. A story. A human life shaped by complexity we may not fully see. And every time we open a spreadsheet, build a dashboard, or publish a report, we're making choices about what matters, what’s visible, and what's left behind.
It starts with how I handle the data in my spreadsheet. Am I in a rush? Am I over-collecting? Oversimplifying? Am I honoring the people behind this information, or turning them into a metric?
The choices we make in quiet moments shape the systems we create. And those systems, in turn, either protect dignity or erode it.
Why Dignity in Data Matters
Data is not neutral. It reflects the questions we ask, the patterns we prioritize, and the narratives we reinforce.
When we treat data as purely technical—detached from the people it represents—we risk reducing human beings to numbers, decontextualizing their experience, and unintentionally reinforcing harm.
Dignity in data means we pause long enough to ask:
What story are we telling? And who does it serve?
Where Dignity Lives in Data Work
Here are some of the everyday decisions that either honor or undermine dignity, often without us noticing.
1. Consent That’s Actually Informed
Many organizations ask for consent, but is it clear, contextual, and meaningful?
Dignity means ensuring people truly understand what they’re agreeing to—and giving them space to say no.
2. Data That Has Context
A chart may show a drop in engagement, but it won’t show the transportation strike, the natural disaster, or the community grief that impacted it. Without context, data becomes judgment.
3. Minimizing What We Collect
Just because we can collect a data point doesn’t mean we should. Dignity asks us to respect people’s right to privacy, even if the system wants more.
4. Reducing Harm Through De-Identification
If our data were leaked or misused, could it harm the people it represents? We owe it to them to treat their information with care.
5. The Language of Reporting
Are we saying “only 45% completed the program” or “nearly half faced barriers we need to understand”? Words carry weight. Dignity means choosing them with care.
6. Who Gets to Interpret the Numbers?
Too often, communities are measured but not included in interpreting what the data means.
Dignity invites people into that process, not just as subjects, but as partners in interpretation.
From Practice to Culture
Individual choices matter, but they only go so far if the culture around data is extractive, performative, or compliance-driven. Dignity in data must be built into how we:
Train staff
Build systems
Report to funders
Define what “success” looks like
We can collect fewer metrics and tell deeper stories. We can ask better questions, not just of people, but of ourselves. And we can shift from control to care in how we handle information.
Questions for Leaders to Ask
If we want to lead with dignity, we need to keep asking:
Am I respecting the humanity behind this data?
Am I open to factors that are unseen?
Could this data point cause harm if misused?
Are we collecting this to serve people, or to satisfy systems?
Who has the power to define what the data means?
Because Dignity Isn’t Just in the Conversation—It’s in the Code
Dignity doesn’t only live in how we talk to people; it also lives in our systems. In our spreadsheets. In our reports, requests, and dashboards.
It lives in what we choose to collect and what we choose to leave out.
Every number holds a name. And every name deserves our respect.
Let’s talk. If you’re navigating change and want to lead with more clarity, confidence, and connection, I’d love to support your next step.
