A story about trial production, three departments, and three versions of the truth.

It's 7am on the production floor.

Three people are standing around a whiteboard.
One is from QA. One is from Engineering. One is from Manufacturing.
They are arguing about a number.

The number is the yield rate for Product A, Batch 7, last Tuesday.

QA says: 87%.
Engineering says: 91%.
Manufacturing says: "Depends on which shift."

All three are holding laptops.
All three are looking at Excel files.
All three are right.

Oran is an orange cat. No CS degree.
He learned to code at night, online, on his own time,
with AI tools and courses he bought on sale.

He got hired anyway. It's that kind of year.

His job title is IT. His actual job is: whatever nobody else wants to do.

This week, his job is to reconcile the production data.

He sits down. He opens all three Excel files.

The columns have different names.
The formulas have different logic.
The defect definitions are different.
QA counts a scratch as a defect. Manufacturing counts it as cosmetic. Engineering doesn't count it at all unless it affects function.

Same scratch. Three categories. Three numbers.

Oran closes his laptop.
He stares at the ceiling for a long time.

Here is what Oran understands, sitting in that chair:

The data problem is not a data problem.

It's a political problem dressed as a data problem.

Each department's Excel file is their scoreboard.
Their evidence. Their alibi.
If QA's numbers are the official numbers, QA controls the narrative.
If Engineering's numbers are official, Engineering does.
If they merge into one system, someone's score gets worse.

Nobody built these spreadsheets to hide information.
They built them to protect themselves.
That's different. And it's harder to fix.

Oran opens a blank document.

He doesn't start with a database schema.
He doesn't start with a system architecture.
He starts with a question:

What would it mean for all three of these numbers to be correct at the same time?

He writes:

• Inspection timing is different. QA measures at end-of-line. Engineering measures at each station. Manufacturing measures at shipment.
• Defect scope is different. Three departments, three definitions, never written down anywhere.
• The data is collected by different people, at different times, with different tools, for different audiences.

One batch. One production run. Six data points that look like contradictions but are actually just context.

The problem isn't that the data is wrong.
The problem is that there's no single place that holds all of it together.

That evening, Oran writes the first three lines of what will eventually become a database schema.

He doesn't know that yet.
He thinks he's just taking notes.

-- What actually happened
-- Who was there
-- When

He looks at the three Excel files one more time.

Then he writes a fourth line:

-- And what "defect" means in this context

There were three versions of the truth.
Everyone was lying. No one was wrong.
The database didn't exist yet.
But the problem did.