Week 1
Objectives of SC:
1. Cost optimization
2. Service level optimization
Trade-off: by keeping less inventory, we have lower costs but also lower service level and
vice versa.
Two kinds of products:
- Functional (stapler)
- Stable, predictable demand
- Long life cycle
- Low profit margins
- Innovative (fashion)
- Unpredictable demand
- Short life cycle
- High profit margins
Functions of SC:
- Physical function
- Cost to manufacture a product
- Focus on efficient SC
- Market mediation function
- Cost to observe and respond flexibly on the market
- Focus on responsive SC
Kinds of SC (Fisher’s Strategies):
- Efficient strategy
- Focus on achieving low costs
- Responsive strategy
- Focus on achieving high service
Factors that make supply chain management difficult are related to the following concepts:
❖ Development chain which is the set of activities associated with new product
introduction. It affects supply chain strategies, which complicates the alignment of
supply chain strategies with the overall company strategy.
➢ DC consists of:
■ Product design phase
■ Associated knowledge and capabilities that need to be developed
internally
■ Sourcing decisions
■ Production plans
❖ Global optimization is the process of finding the best system-wide strategy.
Minimising total system-wide costs while keeping up service levels increase
exponentially when considering an entire system
➢ Information sharing
■ Bullwhip effects relate to the overestimation of demand due to a lack
of information sharing througout sc.
, ➢ Network coordination
■ Coordination refers to the integration of the individual parts of a supply
chain (coordination = integration)
■ Global optimization vs local
■ No success possible without integration
➢ Avoid conflicting strategies
■ Manufacturers need to adapt to changing customer demand
■ Suppliers seek a long commitment to large quantities with flexible
delivery times
■ Warehouses and distribution centres aim to reduce inventory
❖ Uncertainty and risk
➢ Factors:
■ Matching supply and demand
■ Lead time
■ Fluctuation in back-order and inventory levels
■ Forecasting does not solve the problem
■ Recent trends
■ Natural disasters
■ Politics
❖ One size fits all strategy
➢ Supply chain segmentation
➢ Segmentation can lead to increased complexity, loss of ability to benefit from
economies of scale
Strategic Importance of Forecasting:
❖ Capacity
➢ Capacity shortages can result in undependable delivery, loss of customers,
loss of market share
❖ Workforce Scheduling
➢ Hiring, training, laying off workers
❖ Supply Chain Management
➢ Good supplier relations and price advantages
Forecasting Time Horizons:
❖ Short-range forecast
➢ Up to 1 year, generally less than 3 months
➢ Purchasing, job scheduling, workforce levels, job assignments, production
levels
❖ Medium-range forecast
➢ 3 months to 3 years
➢ Sales and production planning, budgeting
❖ Long-range forecast
➢ 3+ years
➢ New product & capacity planning, facility location, research and development
Seven Steps in Forecasting:
1. Determine the use of the forecast
2. Select the items to be forecasted
, 3. Determine the time horizon of the forecast
4. Select the forecasting model
5. Gather the data
6. Make the forecast
7. Validate and implement results
3 Golden Rules of Forecasting:
1. Forecast is always wrong
2. Longer the horizon, the worse the forecast
3. Aggregate forecasts are more accurate. When an aggregation is made on locations
or products, more accurate forecasts can be made when done individually, as peaks
in different categories will balance each other out
Forecasting Approaches:
❖ Qualitative Methods
➢ Used when situation is vague and little data exist
➢ Involves intuition, experience
➢ Methods:
■ Jury of executive opinion
● Pool opinions of high-level experts, sometimes augment by
statistical models
■ Delphi method
● Panel of experts, queried iteratively
■ Sales force composition
● Estimates from individual salespersons are reviewed for
reasonableness, then aggregated
■ Consumer market survey
● Ask the customer
❖ Quantitative Methods
➢ Used when situation is stable and historical data exist
➢ Involves mathematical techniques
➢ Methods:
■ Time-series models
■ Associative model
, Overview of quantitative approaches:
❖ Time-series models
A time series is where the value of the same variable is recorded at regular time
intervals
Time series Components
- Level: an average around which observations vary
- Trend: a predictable increase or decrease in the level over time
- Seasonality: a pattern of predictable and recurring shifts in the level
- Random Noises: unpredictable variations in the data
Time Series with no trend or seasonality:
Time Series with Trend
Objectives of SC:
1. Cost optimization
2. Service level optimization
Trade-off: by keeping less inventory, we have lower costs but also lower service level and
vice versa.
Two kinds of products:
- Functional (stapler)
- Stable, predictable demand
- Long life cycle
- Low profit margins
- Innovative (fashion)
- Unpredictable demand
- Short life cycle
- High profit margins
Functions of SC:
- Physical function
- Cost to manufacture a product
- Focus on efficient SC
- Market mediation function
- Cost to observe and respond flexibly on the market
- Focus on responsive SC
Kinds of SC (Fisher’s Strategies):
- Efficient strategy
- Focus on achieving low costs
- Responsive strategy
- Focus on achieving high service
Factors that make supply chain management difficult are related to the following concepts:
❖ Development chain which is the set of activities associated with new product
introduction. It affects supply chain strategies, which complicates the alignment of
supply chain strategies with the overall company strategy.
➢ DC consists of:
■ Product design phase
■ Associated knowledge and capabilities that need to be developed
internally
■ Sourcing decisions
■ Production plans
❖ Global optimization is the process of finding the best system-wide strategy.
Minimising total system-wide costs while keeping up service levels increase
exponentially when considering an entire system
➢ Information sharing
■ Bullwhip effects relate to the overestimation of demand due to a lack
of information sharing througout sc.
, ➢ Network coordination
■ Coordination refers to the integration of the individual parts of a supply
chain (coordination = integration)
■ Global optimization vs local
■ No success possible without integration
➢ Avoid conflicting strategies
■ Manufacturers need to adapt to changing customer demand
■ Suppliers seek a long commitment to large quantities with flexible
delivery times
■ Warehouses and distribution centres aim to reduce inventory
❖ Uncertainty and risk
➢ Factors:
■ Matching supply and demand
■ Lead time
■ Fluctuation in back-order and inventory levels
■ Forecasting does not solve the problem
■ Recent trends
■ Natural disasters
■ Politics
❖ One size fits all strategy
➢ Supply chain segmentation
➢ Segmentation can lead to increased complexity, loss of ability to benefit from
economies of scale
Strategic Importance of Forecasting:
❖ Capacity
➢ Capacity shortages can result in undependable delivery, loss of customers,
loss of market share
❖ Workforce Scheduling
➢ Hiring, training, laying off workers
❖ Supply Chain Management
➢ Good supplier relations and price advantages
Forecasting Time Horizons:
❖ Short-range forecast
➢ Up to 1 year, generally less than 3 months
➢ Purchasing, job scheduling, workforce levels, job assignments, production
levels
❖ Medium-range forecast
➢ 3 months to 3 years
➢ Sales and production planning, budgeting
❖ Long-range forecast
➢ 3+ years
➢ New product & capacity planning, facility location, research and development
Seven Steps in Forecasting:
1. Determine the use of the forecast
2. Select the items to be forecasted
, 3. Determine the time horizon of the forecast
4. Select the forecasting model
5. Gather the data
6. Make the forecast
7. Validate and implement results
3 Golden Rules of Forecasting:
1. Forecast is always wrong
2. Longer the horizon, the worse the forecast
3. Aggregate forecasts are more accurate. When an aggregation is made on locations
or products, more accurate forecasts can be made when done individually, as peaks
in different categories will balance each other out
Forecasting Approaches:
❖ Qualitative Methods
➢ Used when situation is vague and little data exist
➢ Involves intuition, experience
➢ Methods:
■ Jury of executive opinion
● Pool opinions of high-level experts, sometimes augment by
statistical models
■ Delphi method
● Panel of experts, queried iteratively
■ Sales force composition
● Estimates from individual salespersons are reviewed for
reasonableness, then aggregated
■ Consumer market survey
● Ask the customer
❖ Quantitative Methods
➢ Used when situation is stable and historical data exist
➢ Involves mathematical techniques
➢ Methods:
■ Time-series models
■ Associative model
, Overview of quantitative approaches:
❖ Time-series models
A time series is where the value of the same variable is recorded at regular time
intervals
Time series Components
- Level: an average around which observations vary
- Trend: a predictable increase or decrease in the level over time
- Seasonality: a pattern of predictable and recurring shifts in the level
- Random Noises: unpredictable variations in the data
Time Series with no trend or seasonality:
Time Series with Trend
