Research by Chan and Hoffmann (2013, 2016) showed that people can estimate task times with reasonable accuracy.
Following their suggestion, we therefore calculate a corrected measure of overconfidence by regressing the estimated task-completion time on the traditional calculation of overconfidence.
This overconfidence score cannot be explained by the estimated task-completion time that the participants listed for any piece of furniture, so this procedure eliminates the distorting effect.
In each case, a linear relationship was found relating subjective estimates of task time and actual task times.
We use part of the algorithm for the Critical Path Method [22] to estimate the entire task time for a new delivery position.
In the first half of the re-plan module C, a robot iterates to estimate the entire task time when a new delivery position is set to each position.
They then procrastinate, and the actual time for the task takes far longer than they estimated (because it's task time + procrastination time).
PERT logic assumes probabilistic estimates for each task time, with pessimistic, realistic, and optimistic estimates for the completion times of each task.
In a series of studies, the new metrics were compared with the only other published metric of lostness, the optimal path deviation measure formulated by Smith [P.A. Smith, Towards a practical measure of hypertext usability, Interacting with Computers 4 (1996) 365 381], and with other measures including self-report estimates and task times.
This simple example is based on CPM logic; it uses single-point task time estimates and assumes that the completion time for the project is the simple sum of the task times along the critical path.
Even though it is a time-consuming job to work out arrow diagrams, precedence relationships, task time estimates, and so on for large projects, CPM or PERT is an invaluable aid to planning and control.
