
TABLE OF CONTENTS
This company has multiple development teams, and they all work in sprints. These are fixed blocks of time (usually one or two weeks) in which a set amount of work is planned and completed. Planning a sprint means estimating how long each task will take. Those estimates only improve over time if the team looks back at the previous sprint and compares what they predicted against what actually happened.
With several dev teams running projects at once, the company couldn't get a clear picture of where sprint time was going. Developers forgot to log hours. This happens when logging is a separate job from the work itself, and managers ended up checking entries by hand.
The tool they had wasn't helping. It cost more per user than a team this size wanted to pay, came with complexity they didn't need, and still left the manual cleanup in place.

Apploye runs in the background and tracks time automatically against the project it belongs to, and it can be read at the level engineers actually work in; specific tickets and modules, not whole sprints.
That's what makes the data worth having. A sprint total tells you the team was busy. Time against a module tells you which tasks are taking the most time.
Sprint time is now visible where the decisions get made, on a tool that costs less and asks less of the people using it.