CAPACITY PLANNING SOC2 Certified
Forecast capacity from real productive hours, not theoretical FTE, and see the gap between demand and available capacity before you commit.
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Six capacity signals tracked continuously, so hiring and reallocation decisions are grounded in data.
Productive hours actually available per team, not headcount on paper.
Upcoming project demand mapped per quarter, per team.
Where capacity falls short of demand, by team and by skill.
Capacity discounted for burnout risk, so plans stay realistic.
Capacity adjusted for approved and planned leave.
A clear call per team: hire, reassign, or re-scope.
Each tab is purpose-built for a different question, so operations and resourcing leaders land on the view they need instead of digging through filters.
Role-based access is built into the module, not a feature you configure after the fact.
Sees capacity across the whole organisation. Default access for operations directors and the COO.
Sees capacity for their assigned teams. The default view for a resource manager balancing project load.
Not applicable. Capacity planning is an admin and manager view; standard users see their own hours elsewhere in the platform.
Why role-based access matters for India BPOs and enterprise HR teams: a Director can't accidentally see another department's leave register, a Manager can't drill into a team that isn't theirs, and an employee can verify their own attendance without an admin ticket. Access lives in the product, not in a separate IT setup phase.
Build the quarterly capacity plan from real data instead of a headcount spreadsheet.
Make pipeline-driven hiring decisions before a deal closes, not after it's already overcommitted.
Balance project load across teams before someone is silently over capacity.
Justify headcount with real utilization data instead of a gut-feel request.
STEP -01
Deploy the desktop agent across the team to start capturing real productive hours.
STEP -02
Pull in pipeline and project demand to compare against real capacity.
STEP -03
Capacity versus demand populates once data matures across a few weeks.
Theoretical FTE and actual productive capacity commonly diverge significantly across teams.
Real capacity replaces theoretical FTE assumptions.
Pipeline and gap analysis justify the hire, not a hunch.
Overcommitment is caught early, before it becomes a burnout problem.
The forecast leads demand instead of trailing a missed deadline.
20+ integrations across HRIS, project tools, and collaboration platforms.
Slack
Google
Salesforce
Keka
Microsoft Teams
Workday
Github
GreytHR
Asana
Power BI
Hubspot
Oracle
Zapier
Trello
Jira
Notion
Tableau
Lattice
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Capacity Planning is the forecasting layer; pair it with the modules below for the signals behind the forecast.
Feeds real projects, tasks, and time estimates in, so demand is grounded in committed work rather than guesswork.
Prices each hour of capacity with cost per productive hour, so plans are weighed in money, not just headcount.
Puts capacity and utilization on executive dashboards, beside attendance, cost, and project health.
Supplies the burnout and overload signal that discounts capacity before you overcommit a stretched team.
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