Solution Database / Management
Team capacity planner
Commitments exceed realistic team availability. Declared capacity and explicit estimates with uncertainty visible.
01The offer
For agency resource managers, turn declared availability, estimates and current assignments into capacity scenarios and assignment proposals. Address the recurring problem: commitments exceed realistic team availability. The value hypothesis is a more complete, reviewable deliverable with less repeated preparation; the pilot must establish whether that benefit is real.
- For
- Agency resource managers
- Takes in
- Declared availability, estimates and current assignments
- Delivers
- Capacity scenarios and assignment proposals
- Message
- Team capacity planner for agency resource managers. Declared capacity and explicit estimates with uncertainty visible. Demonstrate the claim through a capacity review for an upcoming delivery period.
- Lead magnet
- A capacity review for an upcoming delivery period
02How it works
- Normalize work estimates
- Account for leave
- Compare commitments
- Flag overload
- Model reassignment
- Capture manager decisions
Workflow
Validate baseline inputs, confirm definitions and constraints, select editable assumptions, calculate feasible alternatives, inspect sensitivities, let the responsible person approve a plan, and compare later actuals with the recorded assumptions. Start with declared availability, estimates and current assignments and finish with capacity scenarios and assignment proposals.
AI and people
Extract input context and explain scenario differences. Use deterministic calculations or explicit optimization for quantities, compatibility, dates and prices. Show uncertain assumptions. Never let generated prose silently change the calculation rules.
Screens
Key screens: Capacity calendar, workload scenarios, assignment review. Place editable drivers and constraints beside a clearly labeled scenario output. Include a baseline view, comparison chart or schedule, and an assumptions history. Let users trace a proposed quantity or date back to its inputs. Keep forecasts distinct from actual results. In this product, the first view is capacity calendar, followed by workload scenarios and assignment review.
Admin
Scenario versions, baseline reconciliation, constraint checks, assumption ownership, reviewer approvals, plan exports and actual-versus-plan tracking.
03Market gap
Alternatives buyers use today
Spreadsheets, planners, specialist forecasting tools and existing scheduling or configuration software. Differentiate on this specific proposed advantage: declared capacity and explicit estimates with uncertainty visible. Test it against the buyer's current method on the same task. Competitor coverage and uniqueness have not been established.
Where this wins
A validated domain model, customer-approved constraints and forecast or decision history that improves practical planning. For this solution, build around declared capacity and explicit estimates with uncertainty visible. This advantage requires execution and accumulated customer trust; the base model alone is not a defensible asset.
04Why now
Management teams are adopting AI for exactly this kind of repeatable work, and the cost of language and vision models has dropped far enough that a narrow, reviewed workflow pays back quickly. The buyer already feels the problem: commitments exceed realistic team availability.
05Proof & signals
Channels where buyers gather: Agency operations advisers. Metrics that prove it works: Overcommitment incidents, forecast error.
Paid pilot
Reproduce a known historical plan, test missing inputs and boundary constraints, then run a new scenario. Compare feasibility, reconciliation and observed error rather than judging the quality of the explanation alone. For this solution, use declared availability, estimates and current assignments and evaluate capacity scenarios and assignment proposals. Agree success thresholds with the buyer before starting; collect a baseline for overcommitment incidents, forecast error. A positive signal is payment and repeat use with acceptable quality and delivery cost, not a favorable demo reaction alone.
06Execution plan
MVP
Begin with agency resource managers and one recurring use case. Build the first two modules: normalize work estimates; account for leave. Provide operator assistance for the third module: compare commitments. Deliver capacity scenarios and assignment proposals through a manual review queue. Perform other necessary full-scope functions manually during the pilot. Include all applicable access, accuracy and professional-review controls from the start.
First 30 days
Week 1: interview five prospective buyers in this segment: agency resource managers. Ask to see a recent example of the problem and their current process. Week 2: prepare this demonstration using authorized or synthetic material: a capacity review for an upcoming delivery period. Week 3: present it through agency operations advisers and seek one narrowly scoped paid pilot. Week 4: review overcommitment incidents, forecast error, total delivery effort and a concrete renewal decision before increasing scope.
After the pilot
After paid pilots establish value, automate the remaining modules: flag overload; model reassignment; capture manager decisions. Add one validated source integration, reusable customer configuration and recurring delivery. Expand to additional teams, document formats or languages only after testing the new scope.
Retention
Refresh inputs, compare recorded assumptions with actual outcomes and refine validated constraints. Expand scenario complexity only when the buyer uses it for a decision.
Integrations
Team updates, calendars, project records and agreed management routines. Read-only operational exports, calendars and finance or inventory records as relevant. Start with plan exports and retain human approval for execution. These are candidate integration categories, not verified supported connectors.
07Investment and running costs
| Phase | Scope | Time | Budget |
|---|---|---|---|
| MVP | One buyer segment, one recurring use case; first modules: normalize work estimates; account for leave. Manual review in the loop. | 5 days | $9,000 |
| Paid pilot | Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers. | 6 days | $11,000 |
| Full product | Remaining modules: flag overload; model reassignment; capture manager decisions. Self-serve onboarding, billing, monitoring and the wider integration set. | 2 weeks | $15,000 |
| Total | $35,000 | ||
| Running | Hosting | AI usage | Total a month |
|---|---|---|---|
| MVP and paid pilot (about 3 customers) | $30–$60 | $50–$100 | $80–$160 |
| Full product (about 50 customers) | $110–$210 | $350–$700 | $460–$910 |
Revenue model to test
Test USD 750-3,000 for a scoped planning setup and review, then USD 200-900 monthly for refreshes within agreed complexity. Data integration and optimization are separately scoped. All ranges are hypotheses.
Cost drivers
Data preparation, domain modeling, validation, scenario computation, reviewer support and ongoing assumption maintenance.
Safeguards
Confirm owners, decisions and commitments. Keep employee discussion notes access-controlled and avoid covert individual performance inference. Validate source access and reviewer availability during the pilot. Maintain customer-level access, data deletion controls and a record of final approvals.
Take it further
Concept proposal expanded from the 315-solution conversation. Demand, pricing, differentiation, build scope and integration feasibility are hypotheses, not verified market findings. Category link is inspiration rather than evidence of business viability.