supply-chain-analyzer

name	supply-chain-analyzer
description	Tedarik zinciri analizi: Bottleneck tespiti, stok optimizasyonu, tedarikçi risk yönetimi ve lojistik iyileştirme.
triggers	{"keywords":["supply chain","bottleneck","stok optimizasyonu","tedarikçi risk","logistics","inventory"],"contexts":["supply chain optimization","vendor management","logistics planning","demand planning"]}
auto_load_when	Kullanıcı tedarik zinciri analizi, bottleneck tespiti veya stok optimizasyonu istediğinde
agent	researcher
tools	["Read","Write","Bash","Grep","Glob"]

Supply Chain Analyzer — Tedarik Zinciri Uzmanı

Odak Alanı: Tedarik zinciri optimizasyonu, bottleneck tespiti, stok yönetimi ve tedarikçi risk değerlendirmesi.

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Pattern Bölümleri

1. Tedarik Zinciri Haritası

End-to-End Supply Chain
├── Suppliers (Tier N → Tier 1)
│   ├── Raw material providers
│   ├── Component manufacturers
│   └── Sub-assembly suppliers
├── Inbound Logistics
│   ├── Transportation
│   ├── Customs/import
│   └── Warehouse receiving
├── Manufacturing/Production
│   ├── Production planning
│   ├── Quality control
│   └── Work-in-progress (WIP)
├── Outbound Logistics
│   ├── Finished goods storage
│   ├── Distribution centers
│   └── Transportation to customers
├── Distribution Network
│   ├── Regional warehouses
│   ├── Retail/fulfillment
│   └── Last-mile delivery
└── Customer
    ├── B2B customers
    └── B2C customers

2. Bottleneck Tespit Yöntemleri

Bottleneck Analysis Methods
├── Throughput Analysis
│   ├── Identify slowest step
│   ├── Calculate cycle time per step
│   ├── Find lowest capacity point
│   └── Compare to demand rate
├── Root Cause Analysis (5 Whys)
│   ├── Why production slow?
│   ├── Why machine slow?
│   ├── Why maintenance delayed?
│   ├── Why parts not available?
│   └── Why supplier delayed?
├── Constraint Theory (TOC)
│   ├── Identify constraint
│   ├── Exploit constraint
│   ├── Subordinate everything
│   └── Elevate constraint
└── Visual Analysis
    ├── Value stream mapping
    ├── Gantt charts
    ├── Kanban boards
    └── Throughput dashboards

3. Stok Optimizasyon Modelleri

Inventory Optimization Models
├── Safety Stock Calculation
│   ├── Formula: Z × σ × LT
│   ├── Z = Service level factor (95%=1.65)
│   ├── σ = Demand standard deviation
│   └── LT = Lead time
├── Economic Order Quantity (EOQ)
│   ├── Formula: √(2DS/H)
│   ├── D = Annual demand
│   ├── S = Ordering cost
│   └── H = Holding cost per unit
├── Reorder Point (ROP)
│   ├── Formula: (D × LT) + Safety Stock
│   ├── When to reorder
│   ├── Automatic triggers
│   └── Continuous monitoring
├── ABC Analysis
│   ├── A items: Top 20%, 80% value
│   ├── B items: Middle 30%, 15% value
│   └── C items: Bottom 50%, 5% value
└── Vendor-Managed Inventory (VMI)
    ├── Supplier manages stock levels
    ├── Automated replenishment
    └── Consignment model

4. Tedarikçi Risk Kategorileri

Vendor Risk Categories
├── Financial Risk
│   ├── Company stability
│   ├── Payment history
│   ├── Credit rating
│   └── Bankruptcy risk
├── Operational Risk
│   ├── Production capacity
│   ├── Quality consistency
│   ├── Lead time reliability
│   └── Capacity utilization
├── Geographic Risk
│   ├── Political stability
│   ├── Natural disaster exposure
│   ├── Transportation routes
│   └── Port/infrastructure
├── Compliance Risk
│   ├── Labor standards
│   ├── Environmental
│   ├── Certifications
│   └── Legal/regulatory
└── Strategic Risk
    ├── Dependency level
    ├── Switching cost
    ├── Competitive position
    └── Technology roadmap

5. Demand Forecasting Methods

Demand Forecasting Approaches
├── Qualitative Methods
│   ├── Market research
│   ├── Expert opinions
│   ├── Sales team input
│   └── Delphi method
├── Time Series
│   ├── Moving average
│   ├── Exponential smoothing
│   ├── Seasonal decomposition
│   └── ARIMA models
├── Causal Models
│   ├── Regression analysis
│   ├── Econometric models
│   └── Market factors correlation
├── Machine Learning
│   ├── Neural networks
│   ├── Ensemble methods
│   └── Demand sensing
└── Collaborative Forecasting
    ├── Vendor input (S&OP)
    ├── Customer order history
    └── Consensus planning

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Key Patterns

Pattern	Açıklama	Uygulama
End-to-End Visibility	Tam zincir görünürlüğü	Data integration
Demand-Supply Balance	Talep-üretim dengesi	S&OP process
Safety Stock Optimization	Optimal güvenlik stoku	Statistical models
Lead Time Reduction	Tedarik süresi kısaltma	供应商 improvement
Multi-Sourcing	Birden fazla tedarikçi	Risk diversification
VMI Implementation	Vendor-managed inventory	Automated replenishment
Continuous Improvement	Sürekli iyileştirme	Kaizen, lean

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Anti-Patterns

❌ Yanlış Uygulamalar

# SINGLE SOURCING
Tüm parçalar tek vendor'dan
- Risk集中
- Tedarikçi sorunu = üretim durması
- Negotiation gücü yok

✅ Multi-sourcing strategy

# EXCESSIVE INVENTORY
"Stok olsun, eksik olmasın"
- Yüksek holding cost
- Depo maliyeti
- Obsolescence risk
- Cash flow problem

✅ Optimize: Just-in-time, safety stock

# NO SAFETY STOCK
"Sıfır stok ideal"
- Herhangi bir kesinti = üretim durması
- Müşteri memnuniyeti düşer
- Emergency ordering pahalı

✅ Risk-based safety stock hesapla

# IGNORING LEAD TIME VARIABILITY
Vendor: "3 hafta" dedi
- Always exactly 3 weeks değil
- Variance yok sayıldı
- Buffer yok

✅ Lead time distribution analiz et

# REACTIVE SUPPLY CHAIN
Problem olduktan sonra çözüm
- Proaktif değil
- Kesintiler önlenemiyor
- Müşteri memnuniyeti düşer

✅ Predictive analytics kullan

# SILOSED OPTIMIZATION
Her departman kendini optimize ediyor
- Purchasing: Min price
- Production: Max utilization
- Warehouse: Min space
- Overall: Suboptimal

✅ End-to-end optimization

✅ Doğru Uygulamalar

# BOTTLENECK ANALYSIS ÖRNEĞİ
Production Line Analysis:

| Station | Cycle Time | Capacity/hr | Status |
|---------|------------|-------------|--------|
| A: Cutting | 45s | 80 units | 🟢 Available |
| B: Welding | 60s | 60 units | 🔴 BOTTLENECK |
| C: Assembly | 50s | 72 units | 🟢 Available |
| D: Testing | 40s | 90 units | 🟢 Available |

Bottleneck: Welding station
- Demand: 65 units/hour
- Current: 60 units/hour
- Gap: 5 units/hour

Solution Options:
1. Add second welding station
2. Overtime to increase capacity
3. Outsource welding
4. Improve cycle time through training

Recommendation: Option 1 (long-term)

# SAFETY STOCK CALCULATION
Item: Widget-X
- Annual demand (D): 10,000 units
- Daily demand: 33 units
- Lead time (LT): 14 days
- Demand std dev (σ): 8 units/day
- Desired service level: 95%

Safety Stock = Z × σ × √LT
= 1.65 × 8 × √14
= 1.65 × 8 × 3.74
= 49 units

Reorder Point = (Daily Demand × LT) + SS
= (33 × 14) + 49
= 462 + 49 = 511 units

Policy: Reorder when stock reaches 511
Order quantity: EOQ = 632 units

# SUPPLIER RISK SCOREBOARD
Q2 2024 Supplier Risk Assessment:

| Supplier | Financial | Ops | Geo | Compl | Total | Risk |
|----------|-----------|-----|-----|-------|-------|------|
| Supplier A | 3 | 4 | 2 | 4 | 13 | 🟡 Medium |
| Supplier B | 5 | 3 | 4 | 5 | 17 | 🔴 High |
| Supplier C | 4 | 5 | 5 | 4 | 18 | 🔴 High |
| Supplier D | 4 | 4 | 4 | 4 | 16 | 🟡 Medium |

Risk Actions:
- Supplier B: Quarterly financial review
- Supplier C: Backup supplier qualification
- Supplier D: Continue monitoring

# SUPPLY CHAIN METRICS
Key Performance Indicators:
| Metric | Formula | Target | Actual | Status |
|--------|---------|--------|--------|--------|
| Perfect Order | (On-time × Complete) × Accuracy | >95% | 92% | 🟡 |
| Lead Time | Avg supplier delivery | <14 days | 16 days | 🔴 |
| Fill Rate | Orders filled complete | >98% | 96% | 🟡 |
| Inventory Turn | COGS / Avg Inventory | >6x | 4.2x | 🔴 |
| Stockout Rate | Out-of-stock / Total SKUs | <2% | 1.5% | 🟢 |
| Supplier On-time | On-time / Total deliveries | >90% | 85% | 🟡 |

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Quick Reference

Bottleneck Türü	Belirti	Çözüm
Equipment	Machine down time	Preventive maintenance
Labor	Operator shortage	Cross-training
Material	Part shortage	Safety stock, supplier improvement
Process	Slow cycle time	Process improvement
Quality	Rework rate	Quality management

Stok Türü	Tanım	Yönetim
Raw Material	Ham madde	Supplier coordination
WIP	Yarı mamul	Production smoothing
Finished Goods	Mamul	Demand matching
Safety Stock	Buffer	Risk-based
Consignment	Tedarikçi sahipli	VMI

Forecasting Horizon	Yöntem	Accuracy
0-3 months	Time series, ML	High (MAPE <10%)
3-12 months	Causal, consensus	Medium (MAPE 10-20%)
1-3 years	Market research, ML	Low (MAPE >20%)
3+ years	Scenario planning	Very low

Risk Mitigation	Yöntem	Etki
Multi-sourcing	Birden fazla tedarikçi	Tedarik kesintisi riski ↓
Safety stock	Buffer inventory	Stokout riski ↓
Vendor development	Performans iyileştirme	Kalite ↑ lead time ↓
Contracts	Long-term agreements	Fiyat dalgalanması ↓
Insurance	Risk transfer	Financial exposure ↓

🌍 Universal Language Support

• Turkish Native: This skill natively supports Turkish. If the user prompt is in Turkish, all analysis, formatting, and output MUST be entirely in Turkish. You do not need explicit "write in Turkish" instructions.