473. CSCP
474. Supply Chains, Demand Management, and Forecasting
474.1. Introduction to Supply Chain
- Supply Chain
Network of organizations, people, activities, information and resources involvd in supplying a product or service to a customer. Encompasses everything from procurement of raw materials to final delivery of finished product to the customer.
- Suppliers: Providers of raw materials or components
- Manufacturers: Transform raw materials into finished goods
- Distributors: Warehouses that hold & deliver goodsRetailers: Interface with final customers
- Customer: End users of product or service
- Supply Chain Management
Overseeing and managing the entire flow of goods and services, ensuring efficient movement from raw materials to finished products.
- Minimize costs
- Optimize inventory levels
- Improving efficiency
- Ensure timely delivery of customers
- Enhance customer satisfaction
- Meet customer demand
Types of supply chains
- Make-to-Stock (MTS): Products are manufactured in advance and stocked based on demand forecast (Coca-Cola)
- Make-to-Order (MTO): Products are made only after a customer order is received (Boeing)
- Assemble-to-Order (ATO): Products are assembled from pre-manufactured components only after a customer order is received (Dell)
- Flows
- Information: Data exchanged between different parts of the supply chain (orders, inventory levels, product status)
- Product: Physical movement of goods from suppliers to manufacturers, distributors, retails and consumers
- Financial: Payment and credit processes between participants (cost transfers, invoicing, patments)
- Globalization
Challenges
- Longer lead times
- Currency flucutations
- Regulation compliance
- Geopolitical tensions
- Competitive advantage
- Speed to market: Reducing time it takes to get products to market
- Cost efficiency: Reducing production and transportation costs
- Felxibility: Ability to adapt to market changes and customer need
- Customer service: Ensuring timely delivery and product availability
- Technology & Digitalization
- AI/ML: Demand forecasing & predictive maintenance
- IoT: Track shipments & manage inventory
- Blockchain: transactions transparency and security
- Sustainability
Minimize environmental & social impact
- Carbon emissions (efficient transportation)
- Energy efficient processes in production
- Minimize waste
- Renewable / recyclable resources
- Fair labor practices / ethical labor practices
- Risk Management
Supply chain resilience
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Operational risk: Breakdown in manufacturing or distribution process
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Supply risk: Disruption in availability of materials or services
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Demand risk: fluctuation in customer demand
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Environmental risk: Natual disacters / climate change
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Natural disters
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Geopolitical tensions
-
Supplier failures
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Demand fluctuation
- Collaboration
- Supplier partnerships: Building long term relationships with key suppliers
- Shared logistics: Coordinating tranportation & warehousing partners
- Data sharing: sharing real time date, production schedules, dand demand forecasts
- Supply Chain Integration
- Horizontal: Collaboration between different firms at the same level of the supply chain (2 manufacturers or 2 distributors)
- vertical: Multiple stages of the supply chain, from raw materials to final product distribution
- Technology: Shared platforms for operations and communication across supply chain
- Ethical Supply Chains
- Fair wages
- Safe working conditions
- Environmental protection
- Corporate transparency
- Bullwhip Effect
small fluctuations in customer demand at the retail level become larger and larger as you move upstream (wholesalers → distributors → manufacturers → suppliers)
Casuses: information distortion + delayed reactions
- Delays in demand information moving up the supply chain
- Batch ordering (retailers order large quantities irregularly)
- Price fluctuations (order spikes)
- Overreaction to demand signals by upstream suppliers
474.2. Demand Analysis and Patterns
- Demand Analysis
Predict demand for products and services
- Historical Data: Analyzing past sales & trends
- Market Conditions: Understanding current market dynamics & economic indicators
- Consumer Behavior: Identifying changes in customer preferences and buying patterns
- Demand Patterns
- Seasonal: Peaks and trophs (hilodays, summer, etc.)
- Cyclical: Economic cycles (recessions & booms)
- Random: Noise
- Trend: Long term movement (up or down)
- Demand Forecasting Methods
- Qualitative: Expert judgement (e.g., Delphi method)
- Quantitative: Mathematical model, historical data (e.g., time series analysis)
- Factos affecting demand
- Price
- Consumer preferences
- Income levels
- Competition
- Substitute products
- Role of Technology in Demand Analysis
- AI/ML
- Big Data
- Balancing Supply and Demand
- Just-in-Time (JIT) inventory: reducing inventory costs by producing just when needed
- Safety stock: Extra inventory to cushion against demand fluctuation
- Felxible production systems: Quickly adapting production levels based on demand change
- Impact of external factors on demand
- Political: Policy, trade tariffs, international relations
- Economic: Recession & booms
- Social: Societal values
- Environmental: Natural disasters, pandemics
- Measuring demand accuracy
- Mean Absolute Deviation (MAD): Measures average magnitude of forecast errors, regardless of direction
- Mean Squared Error (MSE): Squared errors, giving more weight to larger deviations
- Tracking Signal: Monitors whether a forecast is consistently over or underestimating demand, detecting bias in forecasting methods
- Demand Management and Planning
- Product promotion
- Pricing strategies
- Collaborative demand Planning
- Flexible production
474.3. Demand Management
- Demand Drivers
- Economic conditions
- Market trends
- Technological advancements
- Consumer preferences
- Seasonality
- Marketing
- Forecasting Demand
- Quantitative
- Qualitative
- Hybrid
- Collaborative Demand Planning
Collaborate across
- Internal Units (marketing, sales, production)
- External partners (suppliers, retailers)
- balancing Supply and Demand
Meeting demand without over- or under-production
- Demand Shaping
Influence demand through strategic initiatives
- promotions
- discounts
- advertising
- product bundling
- Technology in Demand Management
- Big Data
- AL/ML
- Inventory Management
- Overstocking: ties up capital & incurs storage cost
- Unserstocking: missed sales opportunities
- Demand Management Chellenges
- Demand variability
- Lead times
- Supply chain disruptions
- Changes in customer preferences
- Risk Management
- Buffer inventory
- Supplier diversification
- Contingency planning (natural disasters, economic downturn, etc.)
- Sales & Operations Planning (S&OP)
Integrated business management process that bring together sales, marketing, supply chain, finance teams to align demand forecasts with operational plans
474.4. Forecasting
- Importance
Planning supply chain activities to meet future demand while optimizing costs
- Qualitative v. Quantitative
- Qualitative
- Quantitative
- Time Series Forecasting
Predict future demand
- Moving averages
- Exponential smoothing
- Seasonal adjustments
- Causal Forecasting Models
Cause-and-Effect relationship between demand and various external factors (price, economic indicators, marketing)
- Forecasting Tools & Software
- ML
- Data analytics
- Real-time data
- Forecasting Horizon
Time period that the forecast covers
- Short-term (days to weeks)
- Medium-term (months)
- Long-term (years)
Accuracy decreases with longer time horizons
- Seasonal and Cyclical Demand
- Seasonal: Predictable variation in demand (weather, holidays)
- Cyclical: Fluctuations tied to broader economic cycles
- Collaborative Planning, Forecasting & Replenishment (CPFR)
Businesses work with suppliers, customers, & other partners to jointly forecast demand
- Forecasting Challenges
Example
MAPE
Data:
| Month | Actual | Forecast |
| 1 | 1200 | 1250 |
| 2 | 1400 | 1350 |
| 3 | 1100 | 1000 |
| 4 | 1300 | 1200 |
Steps:
| Month | Actual | Forecast | Error |
% Error |
| 1 | 1200 | 1250 | −50 | 4.17% |
| 2 | 1400 | 1350 | 50 | 3.57% |
| 3 | 1100 | 1000 | 100 | 9.09% |
| 4 | 1300 | 1200 | 100 | 7.69% |
Example
EOQ
Data:
Annual Demand (D): 24,000 units
Order Cost (S): $60 / order
Carrying (Holding) Cost: $4/units/year
Steps:
Example
Safety Stock (Service Level)
Data:
Average Weekly Demand = 400
Standard Deviation Demand = 50
Lead Time = 2 Weeks
Service Level = 95% z = 1.65
Steps:
Example
Reorder Point ROP
Data
Average Daily Demand = 60 units
Lead Time = 8 days
Safety Stock = 100 units
Steps
Reorder Point = 580 units
Example
Capacity Utilization
Data
Design Capacity = 10000 units / week
Actual Output = 8500 units / week
Steps:
Capacity utilization = 85%
Plant is operating efficiently below full load
Example
Inventory Turnover & Days of Supply
Data
COGS = $4,800,000
Average Inventory = $600,000
Steps
Example
Total Landed Cost Comparison
Data:
Supplier A: $20 / unit + $2000 freight per 1000 units
Supplier B: $19 / unit + $3500 freight per 1000 units
Steps
Supplier A: cost / unit = 20 + (2000 / 1000) = $22.00
Supplier B: cost / unit = 19 + (3500 / 1000) = $22.50
Supplier A is cheaper by $0.50 per unit
Example
Cycle Time Reduction
Data
Output = 500 units / day
Cycle Time = 1.2 min / unit
Improvement = 15% reduction
Steps
New Cycle Time = 1.2 times (1 - 0.15) = 1.02 min / unit
Available time = 500 times 1.2 = 600 min / day
New output = 600 / 1.02 = 588 units / day
Increase = 588 - 500 = +88 units / day
Example
Cash To Cash Cycle Time
Data
Days of Inventory = 40
Days receivable = 30
Days payable = 25
Steps
C2C = Days Inventory + Days Receivable - Days Payable = 40 + 30 - 25 = 45
Cash to Cash Cycle Time = 45 days
Example
Distribution Network Optimization
Data
Current (1 DC)
- Transportation = $ 300,000
- Facility = $100,000
New (2 DCs)
- Transportation = $220,000
- Facility = $180,000
Steps
Current total = 300,000 + 100,000 = 400,000
New Total = 220,000 + 180,000 = 400,000
Nototal cost change