Capacity Planning
Demand against real availability, with over-allocation surfaced before commitments are made rather than after they slip.
Capacity is usually planned in a spreadsheet against optimistic availability. This template derives availability from leave, existing allocations and non-project time, so over-commitment is visible at the point of planning.
- Time to deploy
- ~19 min
- Over-allocation
- -57%
- Forecast accuracy
- +38%
- Connected systems
- WorkdayJiraMicrosoft 365
Figures on this page are illustrative modelling, not measured customer results. They will be replaced with substantiated data before launch.
Generated as one application — schema, flows, approvals and reports together.
Four layers, generated in order
Each layer is built against the one above it, which is why the approvals know what they are gating and the dashboards know what they are counting.
- 01
Data model
3 tablesEntities with typed fields, foreign keys, constraints and the indexes the queries below will need.
- 1.1Demand
- 1.2Allocation
- 1.3Availability
- 02
Orchestration
4 flowsSmartFlows bound to those entities — triggers, branches, retries and the calls out to your systems.
- 2.1Availability derivation from leave and allocations
- 2.2Demand intake and skills matching
- 2.3Over-allocation detection
- 2.4Scenario comparison
- 03
Human gates
2 gatesApprovals enforced before anything irreversible. Declared on the flow, not bolted on after.
- 3.1Allocating above 100% capacity
- 3.2Committing to demand without coverage
- 04
Reporting
2 viewsDashboards reading the live records. No export step, no second copy of the truth.
- 4.1Utilisation by team
- 4.2Unmet demand by skill
Deployed together as one application — in about 19 minutes.
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