Every Dataset Tells a Story — But Not All Stories Are Told
- Zeudi Liew

- Apr 15
- 4 min read

Why Data Must Belong to Those Most Affected
Somewhere, right now, a number is being written down.
A child counted. A household surveyed. A need translated into a category that fits neatly into a spreadsheet cell.
It looks harmless. Administrative, even. But this is where power begins.
Because long before data becomes evidence, before it becomes policy, before it becomes funding—it is already a story. A story about what matters, what exists, and what can be ignored.
And like all stories, it has an author.
We like to believe that data is neutral. That it sits outside of politics, untouched by ideology. But this belief is a luxury—one that only exists for those who are not shaped, erased, or misrepresented by it.
For others, data is not neutral at all. It is the difference between being seen and being invisible. Between being protected and being targeted.Between existing in the record—or disappearing from it.
There are places in the world where entire realities are rewritten through data.
Where governments do not simply govern people, but govern the truth itself.
Autocratic regimes understand something very clearly: if you control the data, you control the narrative. And if you control the narrative, you control what is possible.
So they tailor and craft reality.
They suppress inconvenient evidence.They manipulate statistics until they tell a different story.They flood systems with surveillance—not to understand people, but to watch them.They restrict who can speak, what can be measured, and which truths can travel.
In doing so, they do not just hide injustice. They manufacture an alternate reality—one where everything appears stable, justified, even successful.
And in that reality, accountability becomes impossible. Because how do you challenge a system when the evidence itself has been captured?
But the quiet violence of data is not limited to autocracies.
It exists, too, in meeting rooms where indicators are designed far away from the lives they are meant to represent.
In reports where success is measured in outputs rather than outcomes. In projects where communities are consulted, but never truly heard.
It exists in the subtle question: “What data do we need?”
Instead of the more honest one: “Who are we accountable to—and what do they need to know?”
And so data becomes something else. Not a mirror of reality, but a performance of success.
Yet, even within this, something is shifting.
Because data—like power—is not fixed.
It can be hoarded. Or it can be shared. It can be used to control. Or it can be used to liberate.
When communities begin to define their own indicators, something changes. When people say, “This is what matters to us. This is how we know if things are better,” the centre of gravity moves.
A child’s recovery is no longer just a statistic—it becomes “I can sleep through the night.”
A project’s success is no longer just delivery—it becomes “We made this decision ourselves.”
These are not softer forms of data. They are deeper ones.
They carry meaning that numbers alone cannot hold. And they begin to restore something that has long been missing: agency.
But this shift does not happen on its own. Because there is another, quieter imbalance—one that lives within the humanitarian and development sector.
There are those of us who have learned how to navigate data.
We know how to design surveys. How to analyse trends. How to translate complexity into evidence that can influence decisions.
This is a form of power. And like all power, it raises a question:
What do we do with it? For too long, the answer has been: we hold it.
We become the interpreters. The analysts. The consultants. The ones who “make sense” of other people’s realities.
But if addressing inequalities, creating opportunities, empowering and addressing injustice are the goals, then this is not enough. Because knowledge that is held—but not shared—reproduces the very inequalities we claim to address.
The task now is different. It is not to be the voice of others. It is to support communities, local organisations, movements—not just to provide data, but to own it, understand it, and use it.
To build the capacity to ask their own questions. To collect their own evidence. To challenge the narratives imposed on them.
To say: This is what we experience. And we have the data to prove it.
This is not just about skills. It is about shifting power and when data lives only in global dashboards and institutional repositories, it remains distant. But when it lives in communities—when it is discussed, debated, questioned—it becomes something else. It becomes a tool for accountability. Not to donors, but to oneself and to peers and communities.
And yet, there is a danger we must name. In many places, as funding shrinks, the first thing to disappear is not the need—but the data about it.
Local organisations lose the ability to monitor, to evaluate, to document what is happening around them. The work continues, the struggles deepen—but the evidence fades.
A possible data blackout where injustice grows easier to ignore, where what is not measured is easier to dismiss and what is not documented is easier to deny.
This is why building local capacity for data is not simply a technical exercise. It can be an act of empowerment and power shift.
So we return to the beginning.
A number being written down. But now we see it differently.
We see the choices behind it. The power within it. The stories it tells—and the ones it leaves out.
Data is not just information. It is a battlefield.
Where realities are contested.Where narratives are built or broken.Where justice can be advanced—or undermined.
And in this battlefield, neutrality is an illusion.
Every dataset is a decision.Every indicator is a value judgement.Every silence is political.
In the end, data, will always do one of two things. It will reinforce the world as it is. Or it will help build the world as it should be.
And somewhere, even now, that choice is being made.
Future Rights is committed to empower communities and the most affected through data collection and analysis, see the courses
Z. Liew



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