Both capture hours. Only one of them gets filled in honestly, and only one tells you anything you didn't already know.
A timesheet records how many hours went to which bucket; a daily task log records what was actually done, with time attached. They overlap enough that teams treat them as interchangeable, and they are not. The task log is filled in daily against real work and produces usable management information as a by-product; the timesheet is usually reconstructed weekly to satisfy billing and produces numbers that look precise and are not.
| Timesheet | Hours allocated to a project or client code, usually per day or per week. Filled to justify billing or costing. Rarely says what was done. |
|---|---|
| Daily task log | One row per piece of work: what it was, for which client and project, time spent, status, blockers, and a link to the output. Filled the day it happened. |
Put concretely — a timesheet row says "Rajvi Packaging: 6h". A task log row says "Rajvi Packaging / Website revamp — rewrote the pricing page and rebuilt the mobile nav, 3h, done, link attached". Both bill six hours across the day. Only one tells you what you got for the money.
The single biggest determinant of data quality is not the tool. It is the gap between doing the work and recording it.
Ask someone on Friday afternoon how Tuesday went and you get a plausible narrative, not a record. The tells are consistent and easy to spot in your own data: everything is in round numbers, days total exactly eight hours, and the split across clients is suspiciously even. Meanwhile the interruption that ate ninety minutes on Wednesday is missing entirely, because it was not memorable — just expensive.
If your time data is full of 2s and 4s and every day sums to exactly 8, you are not looking at measurements. You are looking at a reconstruction.
Daily entry does not eliminate estimation, but it collapses the error. People remember today accurately. The cost of daily entry is around two minutes; the cost of weekly reconstruction is twenty minutes of worse data.
You need a timesheet if you bill strictly by the hour against contracted rates, a client can audit your hours, or a funder requires time allocation in a prescribed format. In these cases the format is imposed and compliance is the point.
You need a task log if you want to answer any of: what did this project actually cost us, where is this person blocked, are our estimates any good, what did the team ship this month, is this retainer profitable. A task log answers all of these and can be aggregated into timesheet-shaped output when someone needs hours by client.
For most small services businesses, agencies and internal teams, the task log is the better default — it is a superset. The exception is a strict hourly-billing contract with a mandated format, where you may need both.
Six, and resist adding a seventh:
Every additional required field measurably reduces compliance. If you find yourself adding a seventh, ask what decision it changes.
Compliance is a design problem, not a discipline problem:
A year of daily task entries is a genuinely valuable asset, and most of the value is in aggregations you get for free:
| Timesheet captures | Hours allocated to a client or project code |
|---|---|
| Task log captures | What was done, client, project, time, status, blockers, proof link |
| Key quality factor | Time between doing the work and recording it |
| Reconstruction tells | Round numbers, days totalling exactly 8h, evenly split clients |
| Target entry time | Under 2 minutes per day |
| Field count | Six — every extra required field reduces compliance |
| Task log is a superset | It can be aggregated into hours-by-client whenever billing needs it |
A timesheet records how many hours went to a client or project code, usually to support billing. A daily task log records what was actually done — the task, its client and project, time spent, status, blockers and a link to the output — entered on the day it happened. The task log can be aggregated into timesheet-style hours, but a timesheet cannot be turned back into a record of work.
Only if you bill strictly by the hour against a contract that specifies the format, or a client or funder can audit your hours. Otherwise a daily task log is more useful: it answers what a project cost, where people are blocked and how good your estimates are, and it still produces hours by client when billing needs them.
Because a week-old day is reconstructed rather than recalled. Reconstructed data rounds to convenient numbers, totals suspiciously close to the expected working hours, and loses the interruptions that were expensive but unmemorable. Daily entry does not remove estimation error but reduces it sharply, and takes less total time than reconstructing at week-end.
Six: what was done in one line, the client and project selected from a list rather than typed freely, the time spent, a status of done, in progress or blocked, any blocker, and a proof link to the output. Each additional required field measurably reduces the rate at which the log gets filled in.
Make it take under two minutes by pre-filling client and project from recent history, fix it to the same point each day, and visibly use the data in reviews and client conversations. Never use it punitively based on hours logged — the moment low hours trigger criticism, entries inflate and the data stops being worth collecting.
Largely yes, for teams that are distributed or interrupted by meetings. The blocker field carries the signal a standup exists to surface, and it arrives on the day rather than the next morning. Keep a short weekly sync for the discussion that genuinely needs conversation.
Merik's task log captures exactly those fields — the work, the client and project chosen from real records rather than typed freely, time spent, status, blockers and proof links — with time suggestions drawn from the employee's own history so most entries take seconds. Filtering by period, client, employee and free text is built in, along with CSV export when someone needs the raw rows.
Because entries carry a client and project, they roll up automatically: a monthly tracker showing who logged what, task insights over the whole log, and project-level intelligence with per-project drill-down. The same entries can ground a monthly performance review, so the review discusses recorded work rather than recent memory. See the task management modules, the feature list, or how it works.