The Weekly Task Calculator summarizes how a task list moved during the week. Enter starting tasks, new tasks added, completed tasks, and total hours spent to calculate the completion rate, carryover count, and average time per completed task. It also estimates the effort represented by the unfinished queue if future tasks take roughly the same amount of time.
This tool is useful for weekly reviews and workload planning because it separates throughput from list growth. A high number of completed tasks can still leave a growing backlog when new work arrives faster than it is finished. Average time per task is only meaningful when tasks are reasonably comparable; mixed lists containing tiny reminders and multi-day assignments should be interpreted cautiously or divided into separate groups.
1. Enter the opening list
Count tasks that were already active at the start of the week.
2. Add incoming work
Enter tasks created or assigned during the week.
3. Record completions
Count tasks fully finished by the end of the review period.
4. Enter task effort
Use the total hours spent on work represented by the completed-task count.
5. Evaluate carryover
Compare completion rate with remaining tasks and estimated effort.
Estimated carryover effort multiplies carryover by the historical average time per completed task.
The main result is the number of available tasks not completed by week end.
The carryover-effort estimate assumes unfinished tasks resemble completed tasks in size.
Given: 18 starting tasks, 7 added tasks, 20 completed tasks, and 30 task hours.
Calculation: Available = 18 + 7 = 25. Carryover = 25 − 20 = 5. Completion rate = 20 ÷ 25 × 100 = 80%. Average effort = 30 ÷ 20 = 1.5 hours per task.
Result: 5 tasks remain, representing about 7.5 hours if they match the completed-task average.
Count only completed tasks unless you use a consistent point-based system outside this calculator.
The count-based completion rate may be misleading. Split work into more consistent units or use a project estimate.
Yes, but not the starting list plus tasks added during the week.
It shows whether backlog growth came from low throughput or from new work arriving faster than completion.
It is a rough historical estimate and assumes future tasks have similar complexity.