When I perform work, I want my activity to be recorded at the moment it happens,

so I can provide trustworthy evidence of what I did without extra effort.

When I begin or finish a task, I want my time to be captured accurately,

so I can be confident my hours are correct and don’t need to be corrected later.

When I’m doing field work, I want to avoid using complicated tools or devices,

so I can stay focused on the job and avoid interruptions.

When I complete a job, I want to verify that it’s done in a way that reflects my input,

so I can stand behind the result without being surveilled.

When my time or effort is being tracked, I want the record to reflect reality,

so I can trust that what’s shown matches what actually happened.

When I look at our operations, I want to see how work flows from start to finish,

so I can understand where delays or breakdowns occur.

When something slows down the job, I want to see clearly where and why it’s happening,

so I can fix the bottleneck without guessing.

When data flows between systems, I want it to carry its original context,

so I can trace back where it came from if something goes wrong.

When running operations, I want work data to feed into administrative systems automatically,

so I don’t have to manually enter or double-check things.

When I’m being tracked or measured, I want to know it’s to confirm my work, not control me,

so I feel respected and not treated like a suspect.

When I’m working in the field, I want my tools to function without needing constant connectivity,

so I don’t lose data or fall behind if coverage drops.

When our team or workload grows, I want our tools to stay accurate and consistent,

so we can scale without sacrificing trust in the data.

When designing systems, I want them to reflect how people actually work,

so the tools support the process instead of complicating it.

When records are created, I want them to be permanent,

so no one can alter them later without a trace.

When automating something, I want it to start where the work starts,

so the result reflects the real event, not just an observation.

When using a tool, I want to understand what it’s doing at a glance,

so I’m not slowed down by confusion or complexity.

When systems help with decisions, I want to be the one who confirms them,

so I remain accountable for the outcome.

When circumstances change, I want the workflow to adjust smoothly,

so we don’t fall behind or redo work unnecessarily.

When the system collects data, I want it to learn from what actually happened,

so it can improve how work gets done over time.

When managing operations, I want to see how tasks, time, and movement align,

so I can plan more accurately and avoid waste.

When tools are introduced, I want them to support people’s independence,

so users don’t feel micromanaged or disempowered.

When gathering data, I want it to be opt-in and visible,

so it feels respectful and trustworthy, not hidden or extractive.

When a job is done well, I want the system to credit the person who did it,

so recognition and accountability stay aligned.

When building a system, I want trust to be a built-in outcome,

so people don’t need extra justification to believe the data.