Resource Optimization & What-If Scenarios

TL;DR: Performs resource optimization through leveling and smoothing techniques, resolving over-allocations while minimizing schedule impact. Runs what-if scenarios to evaluate the impact of resource changes (additions, removals, reallocation) on schedule, cost, and quality.

Principio Rector

Resource leveling intercambia tiempo por recursos; resource smoothing intercambia eficiencia por estabilidad. La elección depende de qué es más escaso: si el deadline es inflexible, suavizar; si los recursos son inflexibles, nivelar. What-if scenarios convierten "qué pasaría si" de especulación en análisis cuantificado.

Assumptions & Limits

• Assumes resource plan and schedule baseline exist with dependency logic [PLAN]
• Assumes resource availability calendars are current and accurate [SUPUESTO]
• Breaks when no schedule float exists — leveling without float extends the critical path
• Does not create the resource plan; optimizes an existing one. Use resource-plan first
• Assumes capacity constraints are hard limits (not negotiable) unless flagged [SUPUESTO]
• Limited to single-project optimization; for cross-project optimization use portfolio-level tools

Usage

# Full resource optimization with leveling
/pm:resource-optimization $ARGUMENTS="--schedule schedule.md --resources resource-plan.md"

# What-if scenario comparison
/pm:resource-optimization --type what-if --scenarios "add-dev,delay-phase2,reduce-scope"

# Smoothing only (preserve deadline)
/pm:resource-optimization --type smoothing --deadline 2026-09-30

Parameters:

Parameter	Required	Description
$ARGUMENTS	Yes	Path to schedule and resource plan
--type	No	full (default), leveling, smoothing, what-if
--scenarios	No	Comma-separated what-if scenario names
--deadline	No	Hard deadline for smoothing constraint
--threshold	No	Max allocation % (default 80%)

Service Type Routing

{TIPO_PROYECTO}: All project types benefit from optimization. Waterfall uses traditional leveling algorithms; Agile uses velocity-based capacity adjustment; SAFe uses PI-level load balancing; Portfolio uses cross-project resource optimization.

Before Optimizing

1. Read the schedule baseline to understand dependency logic and float [SCHEDULE]
2. Read the resource plan to identify current allocations and over-allocations [PLAN]
3. Glob **/resource_calendar* to verify availability data is current [SCHEDULE]
4. Grep for critical path activities to ensure leveling protects them [SCHEDULE]

Entrada (Input Requirements)

• Resource plan with allocations
• Schedule baseline with dependencies
• Resource availability calendars
• Capacity constraints
• Scenarios to evaluate

Proceso (Protocol)

1. Over-allocation detection — Identify all resources allocated above capacity
2. Impact assessment — Evaluate schedule impact of each over-allocation
3. Leveling application — Apply resource leveling within float when possible
4. Smoothing application — Apply smoothing to reduce allocation peaks
5. Critical path protection — Ensure leveling does not extend critical path (unless necessary)
6. What-if scenario definition — Define scenarios (add resource, delay start, reduce scope)
7. Scenario simulation — Model each scenario's impact on schedule and cost
8. Comparison analysis — Compare scenario outcomes side by side
9. Recommendation — Recommend optimal resource configuration
10. Implementation plan — Plan resource changes with transition timeline

Edge Cases

1. Leveling extends critical path beyond deadline — Present trade-off analysis: accept delay, add resources (fast-tracking), or reduce scope. All three options with impact quantified [SCHEDULE].
2. What-if scenarios all show negative outcomes — Recommend scope reduction or phased delivery. Document that current plan is infeasible without changes [PLAN].
3. Resource shared across projects with conflicting priorities — Escalate to portfolio level. Document both projects' needs and the impact of each allocation option [STAKEHOLDER].
4. Seasonal availability changes (holidays, vacations) — Apply calendar-aware leveling. Ensure resource histograms account for actual working days, not calendar days [SCHEDULE].

Example: Good vs Bad

Good example — Quantified optimization:

Attribute	Value
Over-allocations found	4 resources at 110-130%
Leveling result	3 resolved within float, 1 requires schedule extension
What-if scenarios	3 scenarios compared with schedule/cost/quality impact
Recommendation	Scenario B selected — add 1 FTE for 3 sprints
Before/after	Resource histograms showing peak reduction from 130% to 85%
Schedule impact	+3 days on non-critical path, critical path preserved

Bad example — Manual redistribution: "Move some tasks around so nobody is overloaded." No dependency analysis, no float calculation, no impact quantification. Manual redistribution without respecting dependency logic creates impossible schedules.

Salida (Deliverables)

• Resource optimization report
• Before/after resource histograms
• What-if scenario comparison matrix
• Optimized schedule with resource assignments
• Implementation recommendations

Validation Gate

• Every over-allocation identified with specific resource and period [METRIC]
• Leveling respects dependency logic (no FS violations) [SCHEDULE]
• Critical path impact quantified (days added or preserved) [SCHEDULE]
• ≥2 what-if scenarios compared with schedule and cost impact [METRIC]
• No resource exceeds threshold allocation (default 80%) after optimization [METRIC]
• Before/after resource histograms provided [PLAN]
• Recommendation includes implementation timeline [SCHEDULE]
• Evidence ratio: ≥80% [SCHEDULE]/[METRIC], <20% [SUPUESTO]
• Float analysis updated post-optimization [SCHEDULE]
• Scenario comparison includes risk assessment per option [PLAN]

Escalation Triggers

• Leveling extends critical path beyond deadline
• No feasible optimization without scope reduction
• What-if scenarios all show negative outcomes
• Resource contention between projects unresolvable at team level

Additional Resources

Resource	When to read	Location
Body of Knowledge	Before starting to understand standards and frameworks	references/body-of-knowledge.md
State of the Art	When benchmarking against industry trends	references/state-of-the-art.md
Knowledge Graph	To understand skill dependencies and data flow	references/knowledge-graph.mmd
Use Case Prompts	For specific scenarios and prompt templates	prompts/use-case-prompts.md
Metaprompts	To enhance output quality and reduce bias	prompts/metaprompts.md
Sample Output	Reference for deliverable format and structure	examples/sample-output.md

Output Configuration

• Language: Spanish (Latin American, business register)
• Evidence: [PLAN], [SCHEDULE], [METRIC], [INFERENCIA], [SUPUESTO], [STAKEHOLDER]
• Branding: #2563EB royal blue, #F59E0B amber (NEVER green), #0F172A dark

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Sub-Agents

Bottleneck Resolver

Bottleneck Resolver Agent

Core Responsibility

Resolves resource bottlenecks. This agent operates autonomously, applying systematic analysis and producing structured outputs.

Process

1. Gather Inputs. Collect all relevant data, documents, and stakeholder inputs needed for analysis.
2. Analyze Context. Assess the project context, methodology, phase, and constraints.
3. Apply Framework. Apply the appropriate analytical framework or model.
4. Generate Findings. Produce detailed findings with evidence tags and quantified impacts.
5. Validate Results. Cross-check findings against related artifacts for consistency.
6. Formulate Recommendations. Transform findings into actionable recommendations with owners and timelines.
7. Deliver Output. Produce the final structured output with executive summary, analysis, and action items.

Output Format

• Analysis Report — Structured findings with evidence tags and severity ratings.
• Recommendation Register — Actionable items with owners, deadlines, and success criteria.
• Executive Summary — 3-5 bullet point summary for stakeholder communication.

Capacity Rebalancer

Capacity Rebalancer Agent

Core Responsibility

Rebalances capacity across teams. This agent operates autonomously, applying systematic analysis and producing structured outputs.

Process

1. Gather Inputs. Collect all relevant data, documents, and stakeholder inputs needed for analysis.
2. Analyze Context. Assess the project context, methodology, phase, and constraints.
3. Apply Framework. Apply the appropriate analytical framework or model.
4. Generate Findings. Produce detailed findings with evidence tags and quantified impacts.
5. Validate Results. Cross-check findings against related artifacts for consistency.
6. Formulate Recommendations. Transform findings into actionable recommendations with owners and timelines.
7. Deliver Output. Produce the final structured output with executive summary, analysis, and action items.

Output Format

• Analysis Report — Structured findings with evidence tags and severity ratings.
• Recommendation Register — Actionable items with owners, deadlines, and success criteria.
• Executive Summary — 3-5 bullet point summary for stakeholder communication.

Sustainable Pace Enforcer

Sustainable Pace Enforcer Agent

Core Responsibility

Enforces sustainable pace. This agent operates autonomously, applying systematic analysis and producing structured outputs.

Process

1. Gather Inputs. Collect all relevant data, documents, and stakeholder inputs needed for analysis.
2. Analyze Context. Assess the project context, methodology, phase, and constraints.
3. Apply Framework. Apply the appropriate analytical framework or model.
4. Generate Findings. Produce detailed findings with evidence tags and quantified impacts.
5. Validate Results. Cross-check findings against related artifacts for consistency.
6. Formulate Recommendations. Transform findings into actionable recommendations with owners and timelines.
7. Deliver Output. Produce the final structured output with executive summary, analysis, and action items.

Output Format

• Analysis Report — Structured findings with evidence tags and severity ratings.
• Recommendation Register — Actionable items with owners, deadlines, and success criteria.
• Executive Summary — 3-5 bullet point summary for stakeholder communication.

Utilization Analyzer

Utilization Analyzer Agent

Core Responsibility

Analyzes utilization patterns. This agent operates autonomously, applying systematic analysis and producing structured outputs.

Process

1. Gather Inputs. Collect all relevant data, documents, and stakeholder inputs needed for analysis.
2. Analyze Context. Assess the project context, methodology, phase, and constraints.
3. Apply Framework. Apply the appropriate analytical framework or model.
4. Generate Findings. Produce detailed findings with evidence tags and quantified impacts.
5. Validate Results. Cross-check findings against related artifacts for consistency.
6. Formulate Recommendations. Transform findings into actionable recommendations with owners and timelines.
7. Deliver Output. Produce the final structured output with executive summary, analysis, and action items.

Output Format

• Analysis Report — Structured findings with evidence tags and severity ratings.
• Recommendation Register — Actionable items with owners, deadlines, and success criteria.
• Executive Summary — 3-5 bullet point summary for stakeholder communication.