Information as an Enabler to Supply Chain
Download
Report
Transcript Information as an Enabler to Supply Chain
Information as an Enabler
to Supply Chain
Value of Information
“In modern supply chains, information
replaces inventory”
Why is this true?
Why is this false?
Information is always better than no
information. Why?
Information is the supply chain driver that
serves as a glue allowing the other drivers to
work together to create an integrated,
coordinated supply chain
Types of Information
Supplier information
Manufacturing information
Distribution and retailing information
Demand information
Characteristics of good information
Information must be accurate
Information must be accessible in a timely
fashion
Information must be of the right kind
Value of Information
Information
Helps reduce variability
Helps improve forecasts
Enables coordination of systems and
strategies
Improves customer service
Facilitates lead time reductions
Enables firms to react more quickly to
changing market conditions
Information for Coordination of Systems
Information is required to move from local to
global optimization
Information is needed :
Production status and costs
Transportation availability and costs
Inventory information
Capacity information
Demand information
Increasing Variability Upstream the Supply
Chain –Bullwhip Effect
Bullwhip Effect
Increasing propagation of variability
upstream through the supply chain
We Conclude ….
Order variability is amplified up the
supply chain; upstream echelons
face higher variability.
What you see is not what they face.
What are the Causes….
Demand forecasting
Min-max inventory level
Order-up-to level
orders increase more than forecasts
Long cycle times
Long lead times magnify this effect
Impact on safety stock
Product life cycle
Batch ordering
Volume & transportation discount
What are the Causes….
Price fluctuation
Promotional sales
Forward buying
Inflated orders
Orders placed increase during shortage
periods
IBM Aptiva orders increased by 2-3 times
when retailers thought that IBM would be out
of stock over Christmas
What are the Causes….
Single retailer, single manufacturer.
Dt
Retailer observes customer demand, Dt.
Retailer orders qt from manufacturer.
Retailer
qt
L
Manufacturer
Consequences….
Increased safety stock
Reduced service level
Inefficient allocation of
resources
Increased transportation costs
Ways to Cope with the Bullwhip Effect
Reducing uncertainty
Centralizing demand information
Bullwhip inherent in use of various forecasting techniques
Reducing variability
Use of EDLP strategy (Payless)
Lead time reduction
Order lead time (time to produce and ship)
Information lead time (time to process order)
Efficient network distribution design
Strategic partnership
Vendor managed inventory (VMI)
Sharing of customer information
Collaborative forecasting
Coping with the Bullwhip Effect
in Leading Companies
Reduce uncertainty
POS
Sharing information
Sharing forecasts and policies
Reduce variability
Eliminate promotions
Year-round low pricing
Reduce lead times
EDI
Cross docking
Transmitting POS data upstream
Strategic partnerships
Vendor managed inventory
Data sharing
Information for Effective Forecasts
Pricing, promotion, new products
Different parties have this information
Retailers may set pricing or promotion without
telling distributor
Distributor/Manufacturer might have new
product or availability information
Collaborative Forecasting addresses these
issues.
Locating Desired Products
How can demand be met if products are not
in inventory?
Locating products at other stores
What about at other dealers?
What level of customer service will be
perceived?
Lead-Time Reduction
Why?
Customer orders are filled quickly
Bullwhip effect is reduced
Forecasts are more accurate
Inventory levels are reduced
How?
EDI
POS data leading to anticipating incoming
orders.
Information to Address Conflicts
Lot Size – Inventory:
Inventory -- Transportation:
Lower transportation costs
Improved forecasting
Lower order lead times
Product Variety – Inventory:
Lead time reduction for batching
Information systems for combining shipments
Cross docking
Advanced DSS
Lead Time – Transportation:
Advanced manufacturing systems
POS data for advance warnings
Delayed differentiation
Cost – Customer Service:
Transshipment
Impact of the Bullwhip Effect
Performance Measure
Impact on Performance
Manufacturing Cost
Inventories
Lead Time
Transport Cost
Shipping & Receiving Cost
Customer Service Level
Profitability
Bull Whip Effect - Operational
Obstacles (Batching)
Contributing factors
High Order Cost
Full TL economies
Random or correlated ordering
Counter Measures
EDI & Computer Assisted Ordering (CAO)
Discounted on Assorted Truckload, consolidated by 3rd
party logistics
Regular delivery appointment
Volume and not lot size discounts
State of Practice
McKesson, Nabisco, ...
3rd party logistics in Europe, emerging in the U.S.
P&G
Bull Whip Effect - Pricing
Obstacles
Contributing factors
High-Low Pricing leading to forward buy
Delivery and Purchase not synchronized
Counter Measures
EDLP
Limited purchase quantities
Scan based promotions
State of Practice
P&G (resisted by some retailers)
Scan based promotion
The Bullwhip Effect: Information
Processing Obstacles
Contributing factors
No visibility of end demand
Multiple forecasts
Long lead-time
Counter Measures
Access sell-thru or POS data
Direct sales (natural on web)
Single control of replenishment
Lead time reduction
State of Practice
Sell-thru data in contracts (e.g., HP, Apple, IBM)
CFAR, CPFR, CRP, VMI (P&G and Wal-Mart)
Quick Response Mfg. Strategy
Bull Whip Effect - Operational
Obstacles
Contributing factors
Proportional rationing scheme
Ignorance of supply conditions
Unrestricted orders & free return policy
Counter Measures
Allocation based on past sales.
Shared Capacity and Supply Information
Flexibility Limited over time, capacity reservation
State of Practice
Saturn, HP
Schedule Sharing (HP with TI and Motorola)
HP, Sun, Seagate
Managerial Implications of the Bull
Whip Effect - Behavioral Factors
Contributing factors
Lack of trust
Local reaction
Counter Measures
Building trust and partnership
State of Practice
Wal-Mart and P&G with CFAR
The Bullwhip Effect:
Managerial Insights
Exists, in part, due to the retailer’s need to estimate
the mean and variance of demand.
The increase in variability is an increasing function of
the lead time.
The more complicated the demand models and the
forecasting techniques, the greater the increase.
Centralized demand information can significantly
reduce the bullwhip effect, but will not eliminate it.
Steps in Cycle Time Reduction
Establish a cycle-time reduction team
Develop an understanding of given SC
processes and current cycle time
performance
Identify opportunities for cycle time reduction
Develop and implement recommendations for
cycle time reduction
Measure process cycle time reduction
Conduct CI efforts for process cycle time
reduction
CSF of Cycle Time Reduction
Top management support
Commitment to significant cycle time
reduction
Use of cross function teams
Application of TQM tools
Training in cycle time reduction approaches
Establish, monitor, and report cycle time
performance measures
Collaboration with supply chain member
Locating Desired Products
How can demand be met if products are not
in inventory?
Locating products at other stores
What about at other dealers?
What level of customer service will be
perceived?