Data Is Personality-Driven
I was in a room recently that anyone who works with data for a living would envy.
State government work. A table full of people who actually wanted to use data to inform decisions. Not performatively. Not because a strategic plan told them to. They had real questions, the data existed, and they wanted answers before the next round of decisions got made.
If you have worked in this field for any length of time, you know how rare that is. Usually the hard part is convincing anyone to look at the data at all.
And yet the work stalled.
Not because the data was bad. Not because the questions were wrong. Not because the money ran out. It stalled because one person, positioned exactly where they could stall it, was intent on stalling it. And everything slowed to the speed of that one person’s comfort.
The Reminder I Keep Getting
Here is something my work keeps teaching me, and I keep having to relearn: data is personality-driven.
We talk about data like it is a system. Pipelines, governance, dashboards, evidence-based decision making. The language is all infrastructure, as if information flows through organizations the way water flows through pipes.
It doesn’t. It flows through people.
Personalities decide what gets used and what sits untouched. Which projects go forward and which ones die in a queue. Which partnerships form, because two people trusted each other, and which ones never start, because two people didn’t. How fast anything moves. Whether anyone gets to try something new.
The dataset never decides anything. A person does. And that person’s fears, enthusiasms, grudges, and hopes are as much a part of your data system as any server.
The Stall Is Not Villainy
Now let me be fair to the person holding the brake, because this part matters.
Their concern was data privacy. And data privacy is not a pretext. It is a real thing, and in government it is a deadly serious thing. Government data is people’s lives. Health records. Case files. Addresses. Kids. A breach is not an abstraction; it is a specific harm to a specific person who never agreed to be in your dashboard.
And this is not speculation. Data does get violated. Records exposed. Identities compromised. Information that people handed over to get help with one thing, used for something else entirely. Anyone who has watched that happen, or cleaned up after it, comes by their caution honestly.
Somebody should be worried about that. Somebody should be the person in the room who asks the uncomfortable questions about who can see what and why. Over the years, in other rooms and other roles, I have sat through enough data-sharing conversations that treated privacy as a box to check that I am glad when someone refuses to check it.
So this is not a story about a villain. The person slowing the work down was doing a job that someone needs to do.
The problem is not the concern. The problem is where the concern lives.
One Hand on the Dial
There is a real balance to be struck between using data and protecting the people in it. That balance is the whole question. Use without protection is extraction. Protection without use is a locked filing cabinet that helps no one.
But in this case, the balance wasn’t being struck by a policy, or an agreement, or a shared framework the whole team had hashed out. It was being held by a single personality. One person’s risk tolerance had quietly become the entire agency’s risk tolerance.
And when one hand holds the dial, the cost lands on everyone.
Here is what that cost looked like this time. There was a decision to be made about early childhood education. A real one, with real money and real kids attached. The data that could have informed it existed, sitting in systems the state already owned. But it wasn’t made available in time, so the decision got made without it. Not badly, necessarily. Just blind. And no one will ever write an incident report about that. Somewhere down the line, kids will feel that choice, and nobody will trace it back to a data request that stalled.
That is the trade-off we don’t talk about. On one side of the ledger, the violated data: the breach, the exposure, the harm we can name and fear. On the other side, the decision made in the dark. Both are real. Both have victims. Only one of them ever makes the news.
Decisions get made without evidence that existed and was sitting right there. Partners drift away, because momentum is a resource and you can only ask people to wait so long. Staff stop asking for data, because asking never goes anywhere, and eventually the not-asking becomes the culture. Innovation dies politely, in meetings, without anyone ever saying no.
Data that never gets used also fails the people it describes.
We Are All the Personality in the Room
It would be comfortable to write this as a story about one difficult person. It would also be dishonest.
Because I have been the personality in the room. My enthusiasm has gotten datasets opened that would otherwise have stayed shut. Relationships I happened to have got partnerships signed that a cold email never would have. And I have to assume the reverse is true too, that somewhere along the way my own hesitations, my own fears, my own limits on a given Tuesday slowed down work that someone else needed.
There is no personality-free version of this work. The fantasy of a neutral, frictionless, purely technical data system, where information moves on merit and decisions follow evidence automatically, is just that. A fantasy. Every data system is a group of people, some of whom trust each other, deciding together what they are willing to know and act on.
Once you see that, you can stop being surprised by it. And you can start working with it.
What to Do With This
I don’t have a framework for you. But I have a few things I am trying to practice.
Stop pretending the blocker is technical. If the work is stalled because of a person, then the work in front of you is relational. Find out what they are actually protecting. Sometimes it is the public. Sometimes it is their own liability. Sometimes it is a bad experience from ten years ago that nobody else in the room knows about. You cannot address the fear until you know which one it is, and no amount of better documentation will do it for you.
Move the balance from a person to an agreement. Data-sharing agreements, tiered access, clear de-identification standards. These are unglamorous documents, and they are also how a group takes the dial out of any one person’s hand. Written rules mean the balance between use and privacy gets struck once, together, on purpose, instead of re-struck in every meeting by whoever showed up with the strongest opinion or the most fear.
Make the cost of non-use visible. Privacy risk gets documented, assessed, and reviewed. Stalled decisions don’t. Start naming both. What did we not learn this quarter? What decision got made on instinct because the evidence was locked up? You do not have to be aggressive about it. You just have to make sure the ledger has two columns.
And invest in the champions while they are there. Personality-driven cuts both ways. When someone across the table wants to use data well, that is not a nice-to-have, that is the whole game. Champions leave, get promoted, burn out. The window when the right person is in the right seat is when the agreements get signed and the precedents get set. Do not wait.
The Person, Not the Pipeline
The work I started with is still moving. Slowly. Person by person, which I suppose is the point.
The next time a data project around you stalls, or takes off, look past the pipeline and find the person. There is always a person. The data was never going to decide.
Anthralytic helps mission-driven, resource-constrained organizations with impact strategy, measurement, and reporting. Most of that work, it turns out, is people work. If your data is stuck somewhere between a person and a pipeline, come say hello.
