operations

What this skill does

# Operations Expert

Comprehensive operations frameworks for process improvement, supply chain management, and operational excellence.

## Operational Excellence Frameworks

### Lean Manufacturing Principles

```
THE 5 PRINCIPLES OF LEAN:
1. Value - Define from customer perspective
2. Value Stream - Map all steps, eliminate waste
3. Flow - Make value-creating steps flow smoothly
4. Pull - Let customer demand drive production
5. Perfection - Continuously improve toward perfection
```

### 8 Wastes (DOWNTIME)

| Waste                   | Definition                        | Examples                           | Countermeasures                   |
| ----------------------- | --------------------------------- | ---------------------------------- | --------------------------------- |
| **D**efects             | Work requiring rework/scrap       | Quality issues, errors             | Poka-yoke, quality at source      |
| **O**verproduction      | Making more than needed           | Excess inventory, WIP              | Pull systems, kanban              |
| **W**aiting             | Idle time between processes       | Queue time, approvals              | Flow optimization, cross-training |
| **N**on-utilized talent | Underusing employee skills        | Manual data entry, routine tasks   | Empowerment, automation           |
| **T**ransportation      | Unnecessary movement of materials | Multiple handling, poor layout     | Facility layout optimization      |
| **I**nventory           | Excess stock/materials            | Safety stock, WIP                  | JIT, demand planning              |
| **M**otion              | Unnecessary worker movement       | Poor workstation design            | 5S, ergonomics                    |
| **E**xtra processing    | More work than required           | Over-engineering, redundant checks | Value stream mapping              |

### Six Sigma DMAIC

```
DEFINE
- Problem statement
- Project charter
- Voice of customer (VOC)
- SIPOC diagram
- CTQ (Critical to Quality) tree

MEASURE
- Data collection plan
- Process capability (Cp, Cpk)
- Measurement system analysis
- Baseline metrics

ANALYZE
- Root cause analysis (5 Whys, Fishbone)
- Statistical analysis
- Process mapping
- Hypothesis testing

IMPROVE
- Solution generation
- Pilot testing
- Implementation plan
- Risk assessment (FMEA)

CONTROL
- Control plan
- Statistical process control (SPC)
- Standard operating procedures
- Training and handoff
```

### Six Sigma Metrics

| Sigma Level | DPMO    | Yield    |
| ----------- | ------- | -------- |
| 1           | 691,462 | 30.9%    |
| 2           | 308,538 | 69.1%    |
| 3           | 66,807  | 93.3%    |
| 4           | 6,210   | 99.4%    |
| 5           | 233     | 99.98%   |
| 6           | 3.4     | 99.9997% |

## Supply Chain Management

### Supply Chain Strategy

| Strategy         | When to Use                               | Key Characteristics                           |
| ---------------- | ----------------------------------------- | --------------------------------------------- |
| **Efficient**    | Stable demand, commodity products         | Low cost, high utilization, minimal inventory |
| **Responsive**   | Unpredictable demand, innovative products | Speed, flexibility, buffer inventory          |
| **Risk-Hedging** | Supply uncertainty                        | Multiple suppliers, pooled inventory          |
| **Agile**        | Demand and supply uncertainty             | All above combined, modular design            |

### SCOR Model (Supply Chain Operations Reference)

```
PLAN
- Demand planning
- Supply planning
- S&OP process
- Inventory planning

SOURCE
- Supplier selection
- Contract negotiation
- Procurement
- Supplier performance

MAKE
- Production scheduling
- Manufacturing execution
- Quality management
- Capacity management

DELIVER
- Order management
- Warehousing
- Transportation
- Last-mile delivery

RETURN
- Reverse logistics
- Returns processing
- Warranty management
- Disposal/recycling

ENABLE
- Business rules
- Performance management
- Data management
- Risk management
```

### Supply Chain KPIs

| Category             | Metric                    | Formula                                                 | Target            |
| -------------------- | ------------------------- | ------------------------------------------------------- | ----------------- |
| **Reliability**      | Perfect Order             | (Complete, On-time, Damage-free, Accurate docs) / Total | 95%+              |
|                      | OTIF                      | Orders On-Time In-Full / Total Orders                   | 98%+              |
| **Responsiveness**   | Order Cycle Time          | Order receipt to delivery                               | Industry specific |
|                      | Lead Time                 | Request to fulfillment                                  | Minimize          |
| **Agility**          | Upside Flexibility        | % increase possible in 30 days                          | 20%+              |
|                      | Supply Chain Adaptability | Time to adjust to market change                         | Minimize          |
| **Cost**             | Supply Chain Cost         | Total SC cost / Revenue                                 | 5-10%             |
|                      | COGS                      | Cost of Goods Sold / Revenue                            | Industry specific |
| **Asset Management** | Cash-to-Cash              | DIO + DSO - DPO                                         | Industry specific |
|                      | Inventory Turns           | COGS / Average Inventory                                | Higher is better  |

## Demand Planning & Forecasting

### Forecasting Methods

| Method                    | Use Case                       | Accuracy    |
| ------------------------- | ------------------------------ | ----------- |
| **Moving Average**        | Stable demand                  | Low-Medium  |
| **Exponential Smoothing** | Trend data                     | Medium      |
| **Regression**            | Causal relationships           | Medium-High |
| **ARIMA**                 | Complex patterns               | High        |
| **Machine Learning**      | Large datasets, many variables | High        |
| **Collaborative**         | Retail, promotions             | Medium-High |

### S&OP (Sales & Operations Planning)

```
MONTHLY S&OP CYCLE:

Week 1: Data Gathering
- Update sales forecast
- Review actual vs. plan
- Identify issues

Week 2: Demand Planning
- Demand review meeting
- Consensus forecast
- New product planning

Week 3: Supply Planning
- Capacity analysis
- Inventory planning
- Resource requirements

Week 4: Pre-S&OP
- Gap analysis
- Scenario planning
- Financial reconciliation

Week 5: Executive S&OP
- Final decisions
- Resource allocation
- Performance review
```

### Inventory Management

| Model             | Formula       | Use Case              |
| ----------------- | ------------- | --------------------- |
| **EOQ**           | √(2DS/H)      | Constant demand       |
| **Safety Stock**  | z × σ × √LT   | Buffer uncertainty    |
| **Reorder Point** | (D × LT) + SS | Trigger replenishment |

```
ABC CLASSIFICATION:
A Items: 20% of SKUs, 80% of value → Tight control
B Items: 30% of SKUs, 15% of value → Moderate control
C Items: 50% of SKUs, 5% of value → Minimal control

XYZ CLASSIFICATION (Variability):
X: Low variability (CV < 0.5) → Predictable
Y: Medium variability (0.5 < CV < 1.0) → Some variation
Z: High variability (CV > 1.0) → Sporadic
```

## Quality Management

### Total Quality Management (TQM)

```
TQM PRINCIPLES:
1. Customer focus
2. Total employee involvement
3. Process-centered
4. Integrated system
5. Strategic and systematic approach
6. Continuous improvement
7. Fact-based decision making
8. Communications
```

### Quality Tools

| Tool                 | Purpose                   | When to Use             |
| -------------------- | ------