Customer story / Ambitious Impact (AIM)
How Ambitious Impact's Operations Team Replaced Timesheets with Automatic Time Tracking
AIM's three-person operations team tracked 1,853 hours over 22 weeks with DoneThat, and found the answers to questions it had been arguing about for months.
Senior Operations Manager, Ambitious Impact (AIM)
Challenge
Clockify only recorded what someone remembered to start. Fragmented tasks and constant context switching went unlogged, leaving a record the operations team could not plan from.
Solution
DoneThat tracks automatically in the background, with no timers and no per-person monitoring, reconstructing how the team's work actually divides.
Results
- 1,853 hours tracked with no timers
- A hire decided on measured evidence
- Automation ranked by cost, not annoyance
Ambitious Impact (AIM) is a London-based nonprofit incubator that researches, funds, and launches new high-impact charities. Its three-person operations team supports AIM and the organizations it incubates, often across several legal entities in one afternoon.
In early 2026 they swapped Clockify's manual timers for automatic time tracking built for teams, and logged 1,853 hours over the next 22 weeks without anyone starting a timer.
Timers only record what you remember to start
Manual tracking asks for a deliberate start and stop on every task. For one project that is annoying. For a team running payroll cycles, hiring pipelines, and urgent compliance work across several organizations, it stops working.
"You start a timer, something urgent lands, and you remember three hours later. What we filed on a Friday was a story about the week, not the week."
The short, fragmented tasks that make up most operations work never got logged at all, so the record leaned toward whatever felt memorable. DoneThat instead runs in the background and reconstructs the day on its own. Screenshots are processed and deleted in real time, and the team sees how its work divides rather than what any individual did.
"Clockify told us what we remembered to log. DoneThat tells us what actually happened."
Sizing a hiring decision properly
The team had circled the same conversation for months. People operations was clearly the heaviest area, so did it need another person?
The record sharpened the question before it answered it. Part of what made that area look so large was temporary: a one-off policy project and an active hiring push were both running inside the window. Setting those aside gave a truer view of the load that would still be there afterwards.
"It tempered how big we thought people ops was. It is still a chunky piece, and the conclusion was that we are genuinely capacity-constrained."
That load was still substantial, and the team hired. What changed was the basis for the decision: a measured baseline rather than a sense of how the last quarter had felt.
Temporary projects turned out to be taking a share of capacity nobody had priced as a project. It is the kind of work described afterwards as "a busy quarter" rather than as a cost. Seeing the cost changed how the next one got scoped, and made the capacity returning at the end of each project something to plan for rather than discover.
From arguments to evidence
The same shift reordered automation. The usual tiebreaker is which process annoys someone most; knowing what each one cost moved cheap irritations down the list and quiet, repetitive admin up it.
"Anything where we need to automate, that is what I am looking for now. DoneThat shows me which processes are actually expensive, not just which ones are annoying."
After 22 weeks the questions the team had been arguing about had stopped being matters of opinion. None of it required anyone to remember to press a button.
"Having an honest picture of hours and time is worth far more than clocking in. It is the difference between a record we file and a record we use."