Workforce analytics
Workforce analytics is the practice of collecting and analyzing data about how employees work, including time spent on tasks, application usage, attendance, and location, so managers can make better staffing, scheduling, and workload decisions. These articles define the terms, explain how each signal is calculated, and set out the decisions the data genuinely supports.
They are written for the people who have to act on the numbers rather than the people who buy the software. Where a metric has a limit, we say so, because most of the damage this category of tool does comes from treating a precise number as a complete answer to a question it was never measuring.
Expect definitions first. Active time is device interaction, not effort. A productivity percentage reflects categories your own organization chose, not a universal standard. Attendance describes a schedule, not a contribution. Once those distinctions are clear, the same dashboard that could be used to rank people becomes genuinely useful for spotting an overloaded team, an under-covered shift, or a tool nobody is using.
If you are new to the category, start with the plain-English guide below, then move to the article on what WorkInsights records specifically and how each number is derived.
What is workforce analytics? A plain-English guide
Workforce analytics explained without jargon: what it measures, how it differs from employee monitoring, what questions it can answer, and where it stops being useful.
What WorkInsights measures, and what the numbers actually mean
A clear guide to WorkInsights active time, idle time, productivity rules, attendance, apps, AI insights, GPS, screenshots, and privacy controls.
Other topics: Compliance and privacy · Responsible management · Enterprise deployment