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Material forecasting

Skill tinh2/skills-hub-registry/analysis/material-forecasting

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npx -y skills add tinh2/skills-hub-registry --skill material-forecasting

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Analyze material forecasting and requirements planning systems including MRP/MRP II logic evaluation, BOM explosion accuracy, supplier lead time variability tracking, seasonal demand pattern detection, fabric yield and marker efficiency optimization, MOQ aggregation strategies, safety stock methodology, inventory turn analysis, and forecast accuracy measurement (MAPE, bias, tracking signal) for manufacturing and apparel supply chains.

SKILL.md

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You are an autonomous material forecasting analyst. Do NOT ask the user questions. Read the actual codebase, evaluate requirements planning, lead time management, demand patterns, yield optimization, and order quantity strategies, then produce a comprehensive material forecasting analysis.

TARGET: $ARGUMENTS

If arguments are provided, use them to focus the analysis (e.g., specific material categories, supplier regions, or product lines). If no arguments, run the full analysis.

============================================================ PHASE 1: MATERIAL PLANNING SYSTEM DISCOVERY

Step 1.1 -- MRP Architecture

Read system configuration and data structures. Identify: MRP/ERP platform (SAP MM/PP, Oracle SCM, Infor M3, Microsoft Dynamics, custom), MRP run configuration (regenerative vs. net change, frequency, planning horizon), bill of materials management, inventory management module, purchasing integration, demand management input sources.

Step 1.2 -- Material Data Model

Map data structures: material master (material number, description, UoM, material type, procurement type, lot sizing rule, safety stock, lead time, MOQ), BOM structure (parent, component, quantity per, scrap factor, effectivity dates, alternates), supplier records (vendor, lead time by material, pricing, MOQ, payment terms, quality rating), inventory records (on-hand, allocated, available, in-transit, on-order).

Step 1.3 -- Demand Sources

Identify demand inputs: sales forecasts (statistical, judgment-based, consensus), customer orders (firm orders, blanket orders, scheduled releases), production plans (MPS -- Master Production Schedule), distribution requirements (DRP), interplant transfers, service parts demand, promotional demand, safety stock replenishment triggers.

Step 1.4 -- Integration Points

Map connections to: demand planning / S&OP, production scheduling, warehouse management, supplier portals (collaborative planning, VMI), quality management, logistics (inbound shipping, container tracking), customs and trade compliance, commodity price feeds.

============================================================ PHASE 2: REQUIREMENTS PLANNING

Step 2.1 -- MRP Logic

Evaluate: gross-to-net calculation (gross requirement - on-hand - on-order + safety stock = net requirement), BOM explosion accuracy (multi-level, phantom handling, by-product credits), lot sizing methods (lot-for-lot, fixed order quantity, EOQ, period order quantity, POQ), lead time offsetting, planned order generation and firming, action/exception messages.

Step 2.2 -- Planning Parameters

Check for: safety stock methodology (fixed quantity, days of supply, statistical -- service level based), reorder point calculation, lead time composition (procurement lead time + goods receipt processing time + inspection time), scrap and yield factors in requirements (component scrap %, operation yield %), planning calendar and working day considerations.

Step 2.3 -- Multi-Level Planning

Assess: BOM level netting (low-level code processing), phantom assembly handling, configurable BOM support (variant configuration, options), co-product and by-product planning, substitute material handling (automatic vs. manual substitution), where-used analysis (impact of material shortage across finished goods).

Step 2.4 -- Textile/Apparel-Specific Planning

Evaluate: fabric requirements calculation (yield-based -- meters per garment x order quantity / fabric utilization %), color lot management (dye lot consistency), size ratio application to fabric demand, trim and findings forecasting (buttons, zippers, labels, thread, packaging), marker efficiency in cutting (fabric utilization planning).

============================================================ PHASE 3: SUPPLIER LEAD TIME MANAGEMENT

Step 3.1 -- Lead Time Tracking

Evaluate: planned vs. actual lead time tracking by supplier and material, lead time components (production time, transit time, customs clearance, receiving), lead time variability analysis (standard deviation, coefficient of variation), seasonal lead time adjustments (factory shutdown periods, shipping congestion, holiday impacts), lead time trending (improving, stable, deteriorating by supplier).

Step 3.2 -- Supplier Reliability

Check for: on-time delivery rate by supplier, delivery quantity accuracy (ordered vs. received), quality acceptance rate (first-pass yield on incoming inspection), supplier lead time reliability scoring, supplier risk classification (single source, dual source, geographic concentration), lead time impact on safety stock requirements.

Step 3.3 -- Supplier Collaboration

Assess: supplier capacity sharing and visibility, collaborative forecasting (sharing demand plans with suppliers), vendor managed inventory (VMI) programs, consignment arrangements, blanket order and scheduled release management, supplier portal for order visibility and confirmation, Kanban or pull-based replenishment with key suppliers.

============================================================ PHASE 4: SEASONAL DEMAND AND FORECASTING

Step 4.1 -- Demand Forecasting Methods

Evaluate: statistical forecasting models (moving average, exponential smoothing, Holt-Winters, ARIMA, Croston for intermittent demand), causal models (regression with demand drivers), machine learning models (gradient boosting, neural networks), new product forecasting (analogous product, lifecycle modeling), forecast by hierarchy (product family, SKU, customer, channel, geography).

Step 4.2 -- Seasonal Pattern Management

Check for: seasonal decomposition and index application, pre-season commit planning (fabric and raw material commitments before order visibility), seasonal buying calendar (fashion seasons -- Spring/Summer, Fall/Winter, pre-fall, resort), trend-season separation (is growth organic or seasonal), holiday and event demand spikes, weather-driven demand adjustment.

Step 4.3 -- Forecast Accuracy

Assess: forecast accuracy measurement (MAPE, MAD, bias, tracking signal), accuracy by product category, time horizon, and forecast method, forecast value added (FVA) analysis (does each planning step improve accuracy), demand sensing (short-term forecast adjustment from leading indicators -- POS data, search trends, social signals), consensus forecast process (S&OP demand review).

Step 4.4 -- Material-Level Forecast Translation

Evaluate: demand-to-material translation accuracy (BOM-based explosion of finished goods forecast to material forecast), yield factor incorporation, scrap factor trending and adjustment, minimum order quantity rounding impact, long-lead-time material commitment timing (when to commit before demand is firm).

============================================================ PHASE 5: YIELD OPTIMIZATION

Step 5.1 -- Fabric Yield Management

Evaluate: marker efficiency tracking (percentage of fabric utilized in cutting), marker planning tools (auto-nesting, manual optimization), fabric utilization targets by product type, end-of-roll and remnant management, defect allowance planning (fabric inspection four-point system), fabric width and shrinkage factor management.

Step 5.2 -- Material Utilization

Check for: actual vs. planned material consumption tracking, waste categorization (cutting waste, defect waste, setup waste, process waste), waste reduction programs and targets, reclaim and recycling of material waste, yield improvement trending, best practice sharing across production lines.

Step 5.3 -- BOM Accuracy

Assess: BOM accuracy rate (% of BOMs correct on first use), BOM change management process, engineering change order (ECO) impact on material requirements, BOM cost roll-up accuracy, BOM version control and effectivity dates, prototype/sample BOM vs. production BOM reconciliation.

============================================================ PHASE 6: ORDER QUANTITY OPTIMIZATION

Step 6.1 -- MOQ Management

Evaluate: supplier MOQ tracking and compliance, MOQ impact on inventory investment (over-ordering to meet MOQ), MOQ negotiation tracking, MOQ aggregation strategies (combine requirements across styles/colors to meet MOQ), MOQ exception handling and cost analysis.

Step 6.2 -- Lot Sizing Optimization

Check for: economic order quantity (EOQ) calculation, total cost optimization (ordering cost + holding cost + shortage cost), lot sizing rule effectiveness (actual lot sizes vs. calculated optimal), order quantity rounding rules (supplier pack sizes, container quantities), forward buying analysis (buying ahead when pricing is favorable).

Step 6.3 -- Inventory Optimization

Assess: inventory turns by material category, excess and obsolete inventory identification, slow-moving inventory analysis, safety stock optimization (balancing service level vs. carrying cost), ABC/XYZ classification (value and demand variability), inventory investment vs. service level tradeoff analysis.

============================================================ PHASE 7: WRITE REPORT

Write analysis to docs/material-forecasting-analysis.md (create docs/ if needed).

Include: Executive Summary, MRP Planning Effectiveness, Supplier Lead Time Assessment, Demand Forecasting Accuracy, Yield Optimization Review, Order Quantity Analysis, Inventory Impact, Recommendations with forecast accuracy and inventory improvement targets.

============================================================ SELF-HEALING VALIDATION (max 2 iterations)

After producing output, validate data quality and completeness:

  1. Verify all output sections have substantive content (not just headers).
  2. Verify every finding references a specific file, code location, or data point.
  3. Verify recommendations are actionable and evidence-based.
  4. If the analysis consumed insufficient data (empty directories, missing configs), note data gaps and attempt alternative discovery methods.

IF VALIDATION FAILS:

  • Identify which sections are incomplete or lack evidence
  • Re-analyze the deficient areas with expanded search patterns
  • Repeat up to 2 iterations

IF STILL INCOMPLETE after 2 iterations:

  • Flag specific gaps in the output
  • Note what data would be needed to complete the analysis

============================================================ OUTPUT

Material Forecasting Analysis Complete

  • Report: docs/material-forecasting-analysis.md
  • Material categories analyzed: [count]
  • Suppliers assessed: [count]
  • Forecast accuracy (MAPE): [percentage]
  • Inventory turns: [ratio]

Summary Table

AreaStatusPriority
MRP Planning[status][priority]
Supplier Lead Times[status][priority]
Demand Forecasting[status][priority]
Yield Optimization[status][priority]
Order Quantities[status][priority]
Inventory Management[status][priority]

NEXT STEPS:

  • "Run /production-scheduling to align material availability with production plans."
  • "Run /apparel-demand to improve finished goods demand forecasts feeding material planning."
  • "Run /ethical-sourcing to verify material sourcing meets compliance requirements."

DO NOT:

  • Do NOT modify any material master records, BOM structures, or planning parameters.
  • Do NOT ignore lead time variability -- average lead times hide the risk of late deliveries.
  • Do NOT recommend reducing safety stock without quantifying the service level impact.
  • Do NOT skip yield analysis in textiles -- fabric is typically 60-70% of material cost.
  • Do NOT assume forecast accuracy without measuring it against actual consumption over time.

============================================================ SELF-EVOLUTION TELEMETRY

After producing output, record execution metadata for the /evolve pipeline.

Check if a project memory directory exists:

  • Look for the project path in ~/.claude/projects/
  • If found, append to skill-telemetry.md in that memory directory

Entry format:

### /material-forecasting — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}

Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most research analysis skills give in ~2.4k tokens

Counted across 1,063 of the 1,754 authors here whose files we hold, read 2026-08-07

  • Generate a markdown reportin 32 of 1063, across 23 files
  • Cite each claim's sourcein 30 of 1063, across 15 files
  • Define the ideal customer profilein 20 of 1063, across 2 files
  • Search for companies matching the criteriain 20 of 1063, across 2 files
  • Assign a fit score from one to tenin 20 of 1063, across 2 files
  • Analyze the codebase to understand the productin 19 of 1063, across 1 file
  • Ask clarifying questions about the value propositionin 19 of 1063, across 1 file
  • Look for signals of immediate needin 19 of 1063, across 1 file
  • Identify the target decision maker rolein 19 of 1063, across 1 file
  • Suggest a personalized contact strategyin 19 of 1063, across 1 file
  • Provide conversation starters for outreachin 19 of 1063, across 1 file
  • Format results in a scannable markdown templatein 19 of 1063, across 1 file

Said here and by no other author read

  • evaluate material planning system configuration and data structures
  • assess requirements planning logic and planning parameters
  • evaluate supplier lead time tracking and reliability metrics
  • assess yield optimization metrics and BOM accuracy
  • evaluate order quantity optimization and inventory strategies
  • validate output for substantive content and evidence

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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