The Value of Information
Chap 05 王仁宏 助理教授 國立中正大學企業管理學系 ©Copyright 2001 製商整合科技中心
Lecture Outline 1) Barilla SpA Part A, B, and C 2) The Bullwhip Effect 4) Effect Forecasts 5) Information for Coordination of Systems 6) Locating Desired Products 7) Lead Time Reduction 8) Integrating the Supply Chain Reading: 1. Barilla SpA, Harvard Business School, 9-694-046
Barilla SpA Part A • Barilla SpA is the world’s largest pasta manufacturer • The company sells to a wide range of Italian retailers, primarily through third party distributors • During the late 1980s, Barilla suffered increasing operational inefficiencies and cost penalties that resulted from large week-toweek variations in its distributors’ order patterns
Figure 4.2
Figure 4.3 Weekly Demand for Barilla Dry Products from Cortese’s Northeast Distribution Center to the Pedrignano CDC, 1989.
• What exactly is causing the distributor’s order pattern to look this way? • What are the underlying drivers of the fluctuations?
Causes for Demand Fluctuations • Transportation discounts • Volume discount • Promotional activity • No minimum or maximum order quantities • Product proliferation • Long order lead times • Poor customer service rates • Poor communication
Barilla SpA Part A (continued) • To address this problem, the director of logistics suggests the implementation of Just-in-Time Distribution (JITD), with Barilla’s distributors. • Under the proposed JITD system, decisionmaking authority for determining shipments from Barilla to a distributor would transfer from the distributor to Barilla. • Specifically, rather than simply filling orders specified by the distributor, Barilla would monitor the flow of its product through the distributor’s warehouse, and then decide what to ship to the distributor and when to ship it.
Evaluation of the JITD Proposal • Clearly the variation in demand is imposing additional costs on the channel. What do you think of the JITD proposal as a mechanism for reducing these costs? • Why should this work? • How does it work? • What makes Barilla think that it can do a better job of determining a good product/delivery sequence than its distributors?
Implementation Issues Resistance from the Distributors • “Managing stock is my job; I don’t need you to see my warehouse or my figures.” • “I could improve my inventory and service level myself if you would deliver my orders more quickly; I would place my order and you would deliver within 36 hours.” • “We would be giving Barilla the power to push products into our warehouse just so that Barilla can reduce its costs.” • ?
Implementation Issues Resistance from Sales and Marketing (1/2) • “Our sales levels would flatten if we put this program in place.” • “How can we get the trade to push Barilla product to retailers if we don’t offer some sort of incentive?” • “If space is freed up in our distributors’ warehouses, the distributors would then push our competitors’ product more than ours.” • “It seems that the distribution organization is not yet ready to handle such a sophisticated relationship.”
Implementation Issues Resistance from Sales and Marketing (2/2) • “We run the risk of not being able to adjust our shipments sufficiently quickly to changes in selling patterns or increased promotions.” • “We increase the risk of having our customers’ stock out of our product if we have disruption in our supply process.” • “We wouldn’t be able to run trade promotions with JITD.” • “It is not clear that costs would even be reduced.”
How Can Maggiali Solve the Implementation Problems? • Demonstrate that JITD benefits the distributors (lowering inventory, improving their service levels and increasing their returns on assets); Run experiment at one or more of Barilla’s 18 depots • Maggiali needs to look at JITD not as a logistics program, but as a company-wide effort; Get top management closely involved • Trust
Barilla SpA Part B • What did Barilla learn from the experiments in Florence and Milan? (Fig 4.9 & 4.10) • How should Barilla change the way it attempts to sell the JITD concept to its distributors? • If you were a Barilla distributor, would you sign onto the program after seeing these results?
Figure 4.9
Figure 4.10
Figure 4.11
Figure 4.12
Barilla SpA Part C • How do you evaluate the implementation process Barilla used with Cortese? – Figure 4.11 – Figure 4.12
The Bullwhip Effect and its Impact on the Supply Chain • Consider the order pattern of a single color television model sold by a large electronics manufacturer to one of its accounts, a national retailer.
Figure 1. Order Stream
Huang at el. (1996), Working paper, Philips Lab
The Bullwhip Effect and its Impact on the Supply Chain
Figure 2. Point-of-sales Data-Original
Figure 3. POS Data After Removing Promotions
The Bullwhip Effect and its Impact on the Supply Chain
Figure 4. POS Data After Removing Promotion & Trend
Higher Variability in Orders Placed by Computer Retailer to Manufacturer Than Actual Sales
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
Increasing Variability of Orders Up the Supply Chain
Lee, H, P. Padmanabhan and S. Wang (1997), Sloan Management Review
We Conclude ….
• Order Variability is amplified up the supply chain; upstream echelons face higher variability. • What you see is not what they face.
The Causes of Bullwhip Effect • • • • •
Demand Forecast Long lead times Order Batching Price fluctuation (Promotional sales) Inflated orders - IBM Aptiva orders increased by 2-3 times
when retailers thought that IBM would be out of stock over Christmas - Same with Motorola’s Cellular phones
What are the Causes…. • Single retailer, single manufacturer. – Retailer observes customer demand, Dt. – Retailer orders qt from manufacturer. – Lead time = L.
Dt
Retailer
qt L
Manufacturer
The Bullwhip Effect
2
Var (Q) 2L 2L ≼ 1+ + 2 Var ( D) P P
Var(q)/Var(D): For Various Lead Times 14
L=5
12 10
L=3
8 6
L=1 L=1
4 2 0 0
5
10
15
20
25
30
Multi-Stage Supply Chains Consider a multi-stage supply chain: – Stage i places order qi to stage i+1. – Li is lead time between stage i and i+1.
qo=D
Retailer Stage 1
q1 L1
Manufacturer Stage 2
q2 L2
Supplier Stage 3
Formula k −1
K
Var (Q ) ≥ 1+ Var ( D )
2( ∑ Li ) i =1
p
k −1
+
2( ∑ Li ) i =1
p
2
2 Li 2 Li Var (Q ) ≥ ∏ 1 + + 2 Var ( D ) p p i =1 K
k −1
2
2
Multi-Stage Systems:Var(qk)/Var(D) 30 25
Dec, k=5
20 15
Cen, k=5
10
Dec, k=3 Cen, k=3
5
k=1
0 0
5
10
15
20
25
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 reduce the bullwhip effect, but will not eliminate it.
Coping with the Bullwhip Effect • Reduce Uncertainty - POS - Sharing Information - Centralizing demand information
• Reduce Variability – Year round or Everyday low pricing
• Reduce Lead Times - Information lead times: EDI - Order lead times: Cross Docking
• Alliance Arrangements – Vendor managed inventory
Supply Chain Management: Pitfalls and Opportunities Conflicting Objectives in the Supply Chain 1. Purchasing • Stable volume requirements • Flexible delivery time • little variation in mix • large quantities 2. Manufacturing • Long run production • High quality • High productivity • Low production cost
Supply Chain Management: Pitfalls and Opportunities 3. Warehousing • Low inventory • Reduced transportation costs • Quick replenishment capability 4. Customers • Short order lead time • High in stock • Enormous variety of products • Low prices
Supply Chain Integration Dealing with Conflicting Goals • • • • •
Lot Size vs. Inventory Inventory vs. Transportation Lead Time vs. Transportation Cost Product Variety vs. Inventory Cost vs. Customer Service
Symptoms of Supply Chain Problems • • • • •
Stock-outs and High Inventory Long Cycle Times High Returns High Costs Poor Service Level
Common Pitfalls 1. Information and Management
• No Supply Chain Metrics • Inadequate Definition of Customer Service • Inaccurate Delivery Status Data • Inefficient Information Systems
2. Operational Control
• Ignoring the Impact of Uncertainties • Simplistic Inventory Stocking Policies • Discrimination against Internal Customers • Poor Coordination
Common Pitfalls 3. Design and Strategy • Incomplete Shipment Methods Analysis • Incorrect Assessment of Inventory Costs • Product and Process Design without SC Consideration • Focus on Incomplete Supply Chain
Example: Quick Response at Benetton • Benetton, the Italian sportswear manufacturer, was founded in 1964. In 1975 Benetton had 200 stores across Italy. • Ten years later, the company expanded to the U.S., Japan and Eastern Europe. Sales in 1991 reached 2 trillion. • Many attribute Benetton’s success to successful use of communication and information technologies.
Example: Quick Response at Benetton • Benetton uses an effective strategy, referred to as Quick Response, in which manufacturing, warehousing, sales and retailers are linked together. In this strategy a Benetton retailer reorders a product through a direct link with Benetton’s mainframe computer in Italy. • Using this strategy, Benetton is capable of shipping a new order in only four weeks, several week earlier than most of its competitors.
How Does Benetton Cope with the Bullwhip Effect?
1. Integrated Information Systems
• Global EDI network that links agents with production and inventory information • EDI order transmission to HQ • EDI linkage with air carriers • Data linked to manufacturing
2. Coordinated Planning • Frequent review allows fast reaction • Integrated distribution strategy