Free Team Capacity Planner

The Standish Group's research shows that overcommitment is the leading cause of sprint failures, with teams regularly planning for 100% capacity when actual productive availability is only 60–70% after meetings, support rotations, and administrative overhead. Capacity planning bridges the gap between 'hours at work' and 'hours available for planned work.' Without it, teams face a chronic cycle of overcommitment, missed deadlines, quality shortcuts, and accumulating technical debt — each sprint promising more than it can deliver.

Resource planning (traditional project management) asks 'how many people do I need to complete this work?' — it starts with the work and finds people. Capacity planning (agile) asks 'how much work can this team realistically complete?' — it starts with the people and determines achievable scope. This inversion is fundamental to sustainable delivery. Resource planning leads to overallocation and burnout when demand exceeds supply. Capacity planning forces honest conversations about tradeoffs before commitments are made.

Research and industry practice converge on 70–80% as the optimal utilization target for knowledge work teams. Google's engineering teams famously allocate 20% for self-directed projects. The remaining 20–30% buffer accounts for unplanned work, context switching (which studies show consumes 15–25% of a developer's day), code reviews, mentoring, and the inevitable estimation errors. Teams that plan at 100% capacity deliver less over time due to accumulated shortcuts, burnout, and the compounding cost of never investing in their own tooling and processes.

The estimate is only as accurate as the inputs you provide. Be honest about meeting load, interruption time, and administrative overhead — most teams have 20–30% less truly productive time than their scheduled hours suggest. If you consistently find that actual output falls short of planned capacity, increase the overhead deduction until the estimates match reality.

Yes, always. A common and well-tested practice is to plan work for 70–80% of calculated capacity, leaving 20–30% as buffer for unplanned work (bugs, urgent requests), context switching costs, estimation error (we consistently underestimate how long things take), and necessary overhead like code reviews, documentation, and mentoring.

Enter only the hours each person has allocated to this specific project or sprint, not their total working hours. If a developer splits time 60/40 between two projects, enter 60% of their weekly hours. This prevents the common mistake of planning as if everyone is 100% dedicated when they're actually shared across teams.

Use both together — they answer different questions. Capacity planning tells you how many hours are available (the supply side), while velocity tells you how much work the team historically completes in those hours (the demand calibration). Capacity planning catches short-term fluctuations (holidays, PTO, absences that change available hours this sprint), while velocity provides the long-term baseline of what 'normal' output looks like. When capacity drops significantly below normal (heavy PTO week), reduce your sprint commitment proportionally from velocity.