Workforce analytics for decisions above the team level

Trends, comparisons and drivers across the whole organization, at a resolution that survives being drilled into.

Engagement patterns, workload trajectory and behavioral change combined into a risk indicator, so retention conversations happen before the resignation.

Forecasts of staffing requirements and output trends from historical patterns, which is what makes capacity planning something other than extrapolation.

Dashboards assembled per audience, because an operations lead and a CFO need the same data at completely different altitudes.

Prebuilt and custom reports covering productivity, attendance, capacity and cost, exportable for board and planning packs.

Comparison against internal baselines and industry reference points, which is how a number acquires meaning.

Team performance, collaboration structure and where the organization chart and the actual flow of work diverge.

Connections to HRIS, payouts and business systems, so workforce analysis is not built on one source in isolation.

Software that turns employee and operational data into analysis for planning: productivity trends, capacity forecasts, retention risk and organizational efficiency. The distinction that matters is the audience. Team-level reporting tells a manager what happened last week; workforce analytics aggregates the same measurements across the organization and projects them forward, so headcount, structure and investment decisions rest on measured capacity rather than on last year's number plus a guess.

Productivity monitoring answers questions about teams and individuals now: who is working on what, how much time a project consumed, where activity dropped. Workforce analytics takes the same data, aggregates it upward and projects it forward. The unit of analysis changes from a person and a week to a department and a quarter, which is why the two belong in the same platform but not on the same dashboard.

Worktivity combines its own activity and time data with connected HRIS and payouts sources, applies trend and predictive models, and presents the result as dashboards and reports. Activity comes from the desktop agent, which records how much of a working period was active rather than what was typed. Every aggregate stays openable: you can drill from an organizational figure down to the team and period behind it, which is what makes a number usable in a discussion where somebody disagrees with it.

Productivity trends, retention risk, capacity forecasts, efficiency by team and process, cost per unit of output, and comparison against your own baselines. Each is built to answer a decision rather than to fill a slide: capacity forecasts feed hiring plans, cost per unit of output feeds pricing and staffing, and retention risk gives you weeks of warning instead of an exit interview's explanation after the person has already gone.

It projects from measured patterns, which is more reliable than extrapolating headcount but is still a forecast. Every projection shows the data behind it so you can judge its weight. Forecasts are strongest where the work is steady and the tracked history is long. They are weakest straight after a reorganization, a tooling change or a seasonal shift, because the pattern the model learned no longer describes the team it is describing.

Yes. Worktivity integrates with HRIS, payouts and business applications so workforce analysis is not built on a single isolated source. This matters more than it sounds: activity data alone shows how time was spent, but not what it cost or who left afterwards. Joining tracked time to headcount, compensation and leave records is what turns an activity report into something a finance or people team can act on.

$3.99 per user per month, with a 14-day free trial and no credit card required to start. Analytics is part of the platform rather than an enterprise-only add-on, so the reporting layer is the same whether you are ten people or a thousand, and there is no separate analytics tier to upgrade into before the organizational dashboards turn on.

Encrypted in transit and at rest, role-scoped access, configurable retention and GDPR-aligned operation, with aggregate-first reporting at organizational level. Two things the analytics layer deliberately does not do: it does not record keystrokes, and it does not read the content of the work. Activity is measured as how much of a period was active, and application usage is grouped by application rather than kept as a browsing history.