Inventory Manager

Workflow 2: Demand Forecasting

Predict future demand to inform inventory decisions

1. Historical Analysis

   • Gather historical sales data (minimum 12-24 months)
   • Identify patterns:
     • Trend: Overall increase or decrease over time
     • Seasonality: Repeating patterns (holiday spikes, quarterly cycles)
     • Cyclical: Longer-term economic cycles
     • Random: Unpredictable variation

2. Forecasting Methods

   • Simple: Moving average (stable demand), last period (very stable)
   • Intermediate: Weighted moving average, exponential smoothing
   • Advanced: Seasonal decomposition, regression analysis, machine learning

3. Forecast Accuracy

   • Calculate Mean Absolute Percentage Error (MAPE)
   • Compare forecast vs. actual monthly
   • Refine methods based on accuracy
   • Segment forecasting by product category/SKU

4. Adjustments

   • Factor in promotions, marketing campaigns
   • Account for market trends, competitive activity
   • Adjust for new product launches, discontinuations
   • Include known events (trade shows, holidays)

Workflow 3: Reorder Point & Safety Stock

Calculate optimal reorder triggers and buffer inventory

1. Reorder Point Calculation

   Reorder Point = (Average Daily Demand × Lead Time Days) + Safety Stock
   

   • Example: Demand = 50 units/day, Lead Time = 10 days, Safety Stock = 100
   • Reorder Point = (50 × 10) + 100 = 600 units

2. Safety Stock Calculation

   Safety Stock = Z-Score × (Demand Std Dev) × √(Lead Time)
   

   • Z-Score based on desired service level:
     • 90% service level: Z = 1.28
     • 95% service level: Z = 1.65
     • 99% service level: Z = 2.33
   • Example: Std Dev = 15, Lead Time = 10 days, 95% service
   • Safety Stock = 1.65 × 15 × √10 = 78 units

3. Economic Order Quantity (EOQ)

   EOQ = √((2 × Annual Demand × Ordering Cost) / Carrying Cost per Unit)
   

   • Balances ordering costs vs. holding costs
   • Example: Demand = 10,000/year, Order Cost = $100, Holding Cost = $5/unit/year
   • EOQ = √((2 × 10,000 × 100) / 5) = 632 units per order

4. Dynamic Adjustments

   • Review reorder points quarterly
   • Adjust for seasonality (higher safety stock in peak seasons)
   • Consider supplier reliability (lower reliability = higher safety stock)
   • Balance service level vs. inventory investment

Workflow 4: Stock Monitoring & Replenishment

Track inventory levels and trigger replenishment actions

1. Daily Monitoring

   • Check current stock levels vs. reorder points
   • Identify items at or below reorder point
   • Flag stockouts and backorders
   • Review slow-moving/dead stock

2. Replenishment Triggers

   • Reorder Point System: Order when stock hits reorder point
   • Periodic Review: Check and order on fixed schedule (weekly, monthly)
   • Min-Max System: Order up to max when below min
   • Just-in-Time: Order based on actual demand signals

3. Purchase Order Generation

   • Calculate order quantity (EOQ or adjusted for MOQ/promotions)
   • Select supplier based on lead time, cost, reliability
   • Generate PO with expected delivery date
   • Track open POs and follow up on delays

4. Receiving & Updates

   • Inspect incoming shipments for quality/quantity
   • Update inventory system immediately
   • Reconcile PO vs. actual received
   • Put away stock and update location data

Workflow 5: Inventory Optimization

Reduce costs, improve turns, and eliminate waste

1. Inventory Turns Analysis

   Inventory Turnover = Cost of Goods Sold / Average Inventory Value
   

   • Target turns vary by industry (retail: 8-12, manufacturing: 4-8)
   • Calculate by SKU and category
   • Identify slow-moving items (low turns)

2. Obsolescence Management

   • Identify dead stock (no sales in 90+ days)
   • Aging analysis: 30/60/90+ days old
   • Disposition strategies:
     • Discounts/promotions to clear
     • Return to supplier if possible
     • Donate or dispose (write off)

3. Carrying Cost Reduction

   • Negotiate consignment or vendor-managed inventory
   • Reduce safety stock for reliable suppliers
   • Cross-dock fast-moving items
   • Optimize warehouse space utilization

4. Stockout Prevention

   • Analyze root causes of stockouts
   • Improve forecast accuracy
   • Reduce supplier lead time variability
   • Implement backup suppliers for critical items

Quick Reference

Best Practices

Data Accuracy

• Conduct regular cycle counts (daily for A items, weekly for B, monthly for C)
• Investigate and reconcile discrepancies immediately
• Use barcode/RFID scanning to eliminate manual errors
• Lock down inventory access to prevent unauthorized removals
• Train staff on proper transaction recording

Forecasting Discipline

• Review and update forecasts monthly
• Track forecast accuracy and refine methods
• Collaborate with sales on upcoming promotions
• Account for lead time in forecast horizon
• Use statistical methods, not gut feel

Safety Stock Calibration

• Set service levels by item importance (A items higher)
• Review safety stock quarterly or after major demand changes
• Don't over-invest in safety stock for slow movers
• Consider supplier reliability in calculations
• Balance stockout cost vs. carrying cost

Supplier Management

• Track supplier on-time delivery rates
• Maintain relationships with backup suppliers
• Negotiate favorable lead times and MOQs
• Communicate forecast visibility to key suppliers
• Develop vendor scorecard (quality, delivery, cost)

Technology & Automation

• Implement inventory management software
• Automate reorder point alerts
• Integrate with POS/ERP systems for real-time updates
• Use demand forecasting tools
• Generate automated reports and dashboards

Key Metrics to Track

Inventory Health:

• Inventory turnover ratio (target: industry-dependent)
• Days inventory outstanding (DIO) = 365 / turnover
• Stock-to-sales ratio
• Dead stock value and percentage
• Inventory accuracy rate (target: 95%+)

Service Level:

• Fill rate (orders fulfilled completely)
• Stockout frequency
• Backorder rate
• Customer order cycle time

Cost Metrics:

• Total inventory value
• Carrying cost (% of inventory value)
• Stockout cost (lost sales + customer dissatisfaction)
• Shrinkage/waste rate
• Ordering cost per order

Forecast Performance:

• Forecast accuracy (MAPE target: <20%)
• Forecast bias (over-forecasting vs. under-forecasting)

Common Pitfalls to Avoid

• Over-ordering: Tying up cash in excess inventory
• Under-ordering: Frequent stockouts and lost sales
• Ignoring ABC: Treating all items equally (wasteful)
• Poor data hygiene: Inaccurate counts lead to bad decisions
• Static reorder points: Not adjusting for seasonality or changes
• Lack of visibility: Not knowing what you have or where it is
• Siloed systems: Inventory data not integrated with sales/procurement
• Emotional ordering: Ordering based on fear of stockouts, not data

Integration Points

• Point of Sale (POS): Real-time sales deduction from inventory
• E-commerce: Sync online and physical store inventory
• ERP/Accounting: COGS, inventory valuation, financial reporting
• Warehouse Management (WMS): Location tracking, pick/pack/ship
• Supplier EDI: Automated purchase orders and ASN (advance ship notice)
• Demand Planning: Import forecasts to inform replenishment