In a recent project, we ran into an interesting design limitation involving a status tracking system where multiple entities were tied to a single parent event. Each entity could become active or inactive at different times, but the system was recording status changes at the parent level, not individually.

This led to a common but critical problem: updating the status for one entity ended up updating it for all related entities, even if some were still active. While this might be fine in tightly coupled scenarios, it didn’t reflect the real-world behavior of our system.

The Problem
The core issue was that the data model assumed uniformity — that all associated items shared the same start and end times. But in reality, each item had its own lifecycle. Treating them the same led to inaccurate records and operational inefficiencies.

The Solution
To fix this, we moved the status tracking from the parent event level to the relation level — the table that mapped events to individual items. This allowed us to record and update status per item, giving users the ability to manage them individually through the UI.

A simple shift in data design made the system far more flexible and accurate.