Task Analytics involves reviewing and studying past historical data about certain tasks to analyze effects of certain decisions or events on these tasks, research potential task changes and trends, and evaluate task performance within a given scenario or environment. The purpose of task analytics is to reach optimization in future task performance through gaining knowledge and making improvement decisions which contribute to implementing desired changes in task life-cycle.
The term "task analytics" is often used to define a software module or tool intended for analyzing and improving task performance. Task management software may include task analytics functionality that helps measure and visualize task performance. Such functionality gathers statistic task data (task attributes) and then uses math algorithms to perform calculations on this data. Consequently, task attributes inserted in math formulas generate key performance indicators (KPIs) that serve as the input data for task decision making and problem solving.
As a process, task analytics can be presented as a series of the following steps:
- Task data gathering
- Task monitoring
- Task reporting
Managers carry out these steps to solve many problems and make decisions relating to employee tasks and task performance. For example, some of the problems and decisions are:
- Optimize employee workload
- Remove performance gaps
- Mitigate job failure risks
- Ensure workflow integrity
- Accomplish goals on time.