1. Chapter 3 Inventory Management, Supply Contracts and Risk Pooling
Qi Xu
Professor of Donghua University
Tel:

2. Outline of the Presentation
3.1 Introduction to Inventory Management
3.2 Single Warehouse Inventory
(1) EOQ
(2) Demand Forecast
(3) Supply Contracts
(4) A multi-Period Inventory Model
(5) Periodic Review Policy
3.3 Risk Pooling
3.4 Centralized vs. Decentralized Systems
3.5 Managing Inventory in the SC
3.6 Practical Issues in Inventory Management

3. Supply
Sources:
plants
vendors
ports
Regional
Warehouses:
stocking
points
Field
Customers,
demand
centers
sinks
Production/
purchase
costs
Inventory &
warehousing
Transportation

4. Case: JAM Electronics: Service Level Crisis
JAM Electronics is a Korean manufacturer of products such as industrial relays.The company has five manufacturing facilities in different countries in the Far East with headquarters in Seoul,South Korea.
JAM produces about 2,500 different products, all of them manufactured in the Far East. Finished products are stored in a central warehouse in Korea and are shipped from there to different countries. Items sold in the US are transported by ship to the warehouse in Chicago.

5. Case: JAM Electronics
Problems: the service level is at an all-time low. Only about 70% of all orders are delivered on time.
Difficulty forecasting customer demand.
Long lead time in the supply chain.
The large number of SKUs handled by JAM USA.

6. Case: JAM Electronics

7. By the end of this chapter, you should be able to understand the following issues:
How a firm can cope with huge variability in customer demand.
What the relationship is between service and inventory levels.
What an effective inventory management policy is.

8. 4.1 Inventory Where do we hold inventory? Types of Inventory
Suppliers and manufacturers
warehouses and distribution centers
retailers
Types of Inventory
WIP
raw materials
finished goods
Why do we hold inventory?
Economies of scale
Uncertainty in supply and demand
Lead Time, Capacity limitations

9. Goals: Reduce Cost, Improve Service
By effectively managing inventory:
Xerox eliminated $700 million inventory from its supply chain
Wal-Mart became the largest retail company utilizing efficient inventory management
GM has reduced parts inventory and transportation costs by 26% annually

10. Goals: Reduce Cost, Improve Service
By not managing inventory successfully
In 1994, “IBM continues to struggle with shortages in their ThinkPad line” (WSJ, Oct 7, 1994)
In 1993, “Liz Claiborne said its unexpected earning decline is the consequence of higher than anticipated excess inventory” (WSJ, July 15, 1993)
In 1993, “Dell Computers predicts a loss; Stock plunges. Dell acknowledged that the company was sharply off in its forecast of demand, resulting in inventory write downs” (WSJ, August 1993)

11. Understanding Inventory
The inventory policy is affected by:
Demand Characteristics
Lead Time
Number of Products
Objectives
Service level
Minimize costs
Cost Structure

12. Cost Structure Order costs Holding Costs Fixed Variable Insurance
Maintenance and Handling
Taxes
Opportunity Costs
Obsolescence

13. 4.2.1 EOQ: A Simple Model* A Case : Book Store Mug Sales Question
EOQ illustrates the trade-offs between ordering and storage costs.
A Case : Book Store Mug Sales
Demand is constant, at 20 units a week (D for a year)
Fixed order cost of $12.00, no lead time (k)
Holding cost of 25% of inventory value annually (H)
Mugs cost $1.00, sell for $5.00
Question
How many(Q), when to order?

14. EOQ: A View of Inventory*
Note:
• No Stockouts
• Order when no inventory
• Order Size determines policy
Inventory
当库存量下降到平均库存时，再次订货
Order
Size
Avg. Inven
Time

15. EOQ: Calculating Total Cost*
Purchase Cost Constant
Holding Cost: (Avg. Inven) * (Holding Cost)
Ordering (Setup Cost):Number of Orders * Order Cost
Goal: Find the Order Quantity that Minimizes These Costs

16. EOQ:Total Cost*
Total Cost
Holding Cost
Order Cost

17. EOQ: Optimal Order Quantity*
Optimal Quantity = (2*Demand*Setup Cost)/holding cost
Q=Sqrt((2*D*K)/H)=Sqrt(2*20*52*12)/25%)=316
So for our problem, the optimal quantity is 316

18. EOQ
总成本用如下公式表示：
等式右边的第一项表示的是库存持有成本。右边的第二项表示的是订货成本或者生产准备成本，R/Q表示每年向供货点发出订货定单的次数。由此可见，如果Q增加，而每年的需求固定，那么每年的订货的次数就相应减少。第三项是货物自身的成本，它不影响最优订货批量和最优订购周期的确定。
为获得使总成本最低的最优订货批量Q*，总成本TC看作以Q为自变量的函数，将TC函数对Q微分：

19. EOQ
令　　　 为0，可求出最优的Q*为
两次订货之间最佳的时间间隔为
每年的订货次数为　

20. EOQ: Important Observations*
Tradeoff between set-up costs and holding costs when determining order quantity.
Total Cost is not particularly sensitive to the optimal order quantity

21. The Effect of Demand Uncertainty
Most companies treat the world as if it were predictable:
Production and inventory planning are based on forecasts of demand made far in advance of the selling season
Companies are aware of demand uncertainty when they create a forecast, but they design their planning process as if the forecast truly represents reality
Recent technological advances have increased the level of demand uncertainty:
Short product life cycles
Increasing product variety
前面的模型说明了准备成本和库存持有成本之间的权衡，但是它忽略了需求不确定和需求预测的问题。

22. Outline 4.1 Introduction to Inventory Management
4.2 Single Warehouse Inventory
(1) EOQ
(2) Demand Forecast
(3) Supply Contracts
(4) A multi-Period Inventory Model
(5) Periodic Review Policy
4.3 Risk Pooling
4.4 Centralized vs. Decentralized Systems
4.5 Managing Inventory in the SC
4.6 Practical Issues in Inventory Management

23. 4.2.2 Demand Forecast
The three principles of all forecasting techniques:
Forecasting is always wrong
The longer the forecast horizon the worst is the forecast
Aggregate forecasts are more accurate

24. Case: SnowTime Sporting Goods
Fashion items have short life cycles, high variety of competitors
SnowTime Sporting Goods
New designs are completed
One production opportunity
Based on past sales, knowledge of the industry, and economic conditions, the marketing department has a probabilistic forecast
The forecast averages about 13,000, but there is a chance that demand will be greater or less than this.

25. Supply Chain Time Lines
Jan 01
Jan 02
Jan 00
Design
Production
Retailing
Feb 00
Sep 00
Feb 01
Sep 01
Production

26. SnowTime Demand Scenarios

27. SnowTime Costs The variable Production cost per unit (C): $80
Selling price per unit (S): $125
Salvage value per unit (V): $20
Fixed production cost (F): $100,000
To start production ,the manufacturer has to invest $100,000 independent of the amount produced.
Q is production quantity, D demand
Profit = Revenue - Variable Cost - Fixed Cost + Salvage

28. SnowTime Scenarios
Profit = Revenue - Variable Cost - Fixed Cost + Salvage
Scenario One:
Suppose you make 12,000 jackets and demand ends up being 13,000 jackets.
Profit = 125(12,000) - 80(12,000) - 100,000 = $440,000
Scenario Two:
Suppose you make 12,000 jackets and demand ends up being 11,000 jackets.
Profit = 125(11,000) - 80(12,000) - 100, (1000) = $ 335,000

29. SnowTime Best Solution
Find order quantity that maximizes weighted average profit.
Question: Will this quantity be less than, equal to, or greater than average demand?
加权平均利润

30. What to Make? Average demand is 13,100
Question: Will this quantity be less than, equal to, or greater than average demand?
Average demand is 13,100
Look at marginal cost Vs. marginal profit
if extra jacket sold, profit is = 45
if not sold, cost is = 60
So we will make less than average

31. SnowTime Expected Profit
The quantity that maximizes average profit, is about 12,000.

32. SnowTime Expected Profit
It indicates that producing 9,000 units or producing 16,000 units will lead to about the same average profit of $294,000.

33. SnowTime: Important Observations
Tradeoff between ordering enough to meet demand and ordering too much
Several quantities have the same average profit
Average profit does not tell the whole story
Question: 9000 and units lead to about the same average profit, so which do we prefer?

34. SnowTime Expected Profit

35. Probability of Outcomes
When the production quantity is 16,000 units, the distribution of profit is not symmetrical. Losses of $220,000 happen about 11%, while profits of at least $410,000 happen 50%.
When the production quantity is 9,000 units ,the distribution has only two possible outcomes. Profit is either $200,000 with probability of about 11%,or $305,000 with probability of about 89%.

36. Key Insights from this Model
The optimal order quantity is not necessarily equal to average forecast demand
The optimal quantity depends on the relationship between marginal profit and marginal cost
As order quantity increases, average profit first increases and then decreases
As production quantity increases, risk increases. In other words, the probability of large gains and of large losses increases

37. SnowTime Costs: The Effect of Initial Inventory
Production cost per unit (C): $80
Selling price per unit (S): $125
Salvage value per unit (V): $20
Fixed production cost (F): $100,000
Q is production quantity, D demand
Profit = Revenue - Variable Cost - Fixed Cost + Salvage

38. SnowTime Expected Profit

39. Initial Inventory
Suppose that one of the jacket designs is a model produced last year.
Some inventory is left from last year
Assume the same demand pattern as before
If only old inventory is sold, no setup cost
Question: If there are 5000 units remaining, what should SnowTime do? What should they do if there are 10,000 remaining?

40. Initial Inventory and Profit

41. Initial Inventory and Profit

42. Initial Inventory and Profit
If the manufacturer does not produce any additional suits, no more than 5,000 units can be sold and no additional fixed cost will be incurred. However, it the manufacturer decides to produce, a fixed production cost is charged independent of the amount produced.

43. Initial Inventory and Profit
Average profit excluding fixed production cost
Average profit including fixed production cost

44. Analysis (1) there are 5000 units remaining
If nothing is produced, average profit is equal to
Production should increase inventory from 5,000 units to 12,000 units. Thus, average profit is equal to (from the figure).
(2) there are 10,000 units remaining
It is easy to see that there is no need to produce anything because the average profit associated with an initial inventory of 10,000 is larger than what we would achieve if we produce to increase inventory to 12,000 units.
If we produce, the most we can make on average is a profit of$375,000. This is the same average profit that we will have if our initial inventory is about 8,500 units.
Hence, if our initial inventory is below 8,5000 units, we produce to raise the inventory level to 12,000 units. If initial inventory is at least 8,5000 units,we should not produce anything.

45. (s, S) Policies
For some starting inventory levels, it is better to not start production
If we start, we always produce to the same level
Thus, we use an (s,S) policy. If the inventory level is below s, we produce up to S.
s is the reorder point, and S is the order-up-to level
The difference between the two levels is driven by the fixed costs associated with ordering, transportation, or manufacturing

46. Who takes the risk? What would the manufacturer like?
4.2.3 Supply Contracts
Manufacturer
Manufacturer DC
Retail DC
Stores
Fixed Production Cost =$100,000
Variable Production Cost=$35
Wholesale Price =$80
Selling Price=$125
Salvage Value=$20
Who takes the risk? What would the manufacturer like?
前面假设制造商有足够的原材料供应，也总能按照制造商订购的数量及时交货。为了这个目标， 买方和供应商一般签订供应合同。
根据前面讨论，最优订货量依赖于边际利润和边际损失，而不依赖于固定成本。因此零售商的最优策略是订购12000件，并获得470700美元的平均利润。如果零售商发出这个订单，制造商的利润就是1200(80)-100,000=440,000美元
Who takes the risk? What would the manufacturer like?

47. Demand Scenarios

48. Distributor Expected Profit

49. Distributor Expected Profit
470,000

50. Supply Contracts (cont.)
Distributor optimal order quantity is 12,000 units
Distributor expected profit is $470,000
Manufacturer profit is $440,000
Supply Chain Profit is $910,000
根据前面讨论，最优订货量依赖于边际利润和边际损失，而不依赖于固定成本。因此零售商的最优策略是订购12000件，并获得470700美元的平均利润。如果零售商发出这个订单，制造商的利润就是1200(80)-100,000=440,000美元
Is there anything that the distributor and manufacturer can do to increase the profit of both?

51. Supply Contracts (between manufacturer and retailer)
In the previous strategy, the retailer takes all the risk and the manufacturer takes zero risk. This is why the retailer has to be very conservative with the amount he orders.
If the retailer can transfer some of the risk to the manufacturer, the retailer may be willing to increase his order quantity and thus increase both his profit and the manufacturer profit.
Fixed Production Cost =$100,000
Variable Production Cost=$35
Manufacturer
Manufacturer DC
Retail DC
Stores
Wholesale Price =$80
Selling Price=$125
Salvage Value=$20
Notice that in the previous strategy, the retailer takes all the risk and the manufacturer takes zero risk. This is way the retailer has to be very conservative with the amount he orders.
If the retailer can transfer some of the risk to the manufacturer, the retailer may be willing to increase his order quantity and thus increase both his profit and the manufacturer profit

52. Retailer Profit (Buy Back=$55)回购

53. Retailer Profit (Buy Back=$55)
$513,800
假定制造商同意以55美元的价格从零售商处购买销售不了的衣服，则零售商愿意增加订货量到14000件，并获得513800美元的利润，而制造商的平均利润增加到471900
* 假定制造商同意以55美元的价格从零售商处购买销售不了的衣服，则零售商愿意增加订货量到14000件，并获得513800美元的利润，而制造商的平均利润增加到471900

54. Manufacturer Profit (Buy Back=$55)

55. Manufacturer Profit (Buy Back=$55)
$471,900

56. Supply Contracts (between manufacturer’s wholesale price and retailer)
What does wholesale price drive?
How can manufacturer benefit from lower price?
Manufacturer
Manufacturer DC
Retail DC
Stores
Fixed Production Cost =$100,000
Variable Production Cost=$35
Wholesale Price =$??
Selling Price=$125
Salvage Value=$20
What does wholesale price drive?
How can manufacturer benefit from lower price?

57. Retailer Profit (Wholesale Price $70, Retailers back 15% to manufacturer )

58. Retailer Profit (Wholesale Price $70, RS 15%)
$504,325
没有回购前，订购14000件获利513800美元，

59. Manufacturer Profit (Wholesale Price $70, RS 15%)

60. Manufacturer Profit (Wholesale Price $70, RS 15%)
$481,375
没有回购前，制造商的利润为471900美元

61. Supply Contracts
Wholesale Price $70, RS 15%

62. Supply Contracts
What is the maximum profit that the supply chain can achieve? To answer this question, one needs to forget about the transfer of money from the retailer to the manufacturer.
Manufacturer
Manufacturer DC
Retail DC
Stores
Fixed Production Cost =$100,000
Variable Production Cost=$35
Wholesale Price =$80
Selling Price=$125
Salvage Value=$20
What is the maximum profit that the supply chain can achieve? To answer this question, one needs to forget about the transfer of money from the retailer to the manufacturer.

63. Supply Chain Profit

64. Supply Chain Profit (Global optimization)
$1,014,500

65. Supply Contracts

66. Supply Contracts: Key Insights
Effective supply contracts allow supply chain partners to replace sequential optimization by global optimization
Buy Back and Revenue Sharing contracts achieve this objective through risk sharing

67. Supply Contracts: Case Study
Example: Demand for a movie newly released video cassette typically starts high and decreases rapidly
Peak demand last about 10 weeks
Blockbuster purchases a copy from a studio for $65 and rent for $3
Hence, retailer must rent the tape at least 22 times before earning profit
Retailers cannot justify purchasing enough to cover the peak demand
In 1998, 20% of surveyed customers reported that they could not rent the movie they wanted
峰值需求大约持续10周, 百事达(Blockbuster)

68. Supply Contracts: Case Study
Starting in 1998 Blockbuster entered a revenue sharing agreement with the major studios
Studio charges $8 per copy
Blockbuster pays 30-45% of its rental income
Even if Blockbuster keeps only half of the rental income, the breakeven point is 6 rental per copy
The impact of revenue sharing on Blockbuster was dramatic
Rentals increased by 75% in test markets
Market share increased from 25% to 31% (The 2nd largest retailer, Hollywood Entertainment Corp has 5% market share)
the breakeven point is 6 rental per copy,盈亏平衡点也只是每个拷贝出租6次

69. Other Contracts Quantity Flexibility Contracts Sales Rebate Contracts
Supplier provides full refund for returned items as long as the number of returns is no larger than a certain quantity
Sales Rebate Contracts
Supplier provides direct incentive for the retailer to increase sales by means of a rebate paid by the supplier for any item sold above a certain quantity
Rebate回扣

70. 4.2.4 A Multi-Period Inventory Model
Often, there are multiple reorder opportunities
Consider a central distribution facility which orders from a manufacturer and delivers to retailers. The distributor periodically places orders to replenish its inventory

71. The DC holds inventory to:
Satisfy demand during lead time
Protect against demand uncertainty
Balance fixed costs and holding costs

72. Reminder: The Normal Distribution
Standard Deviation = 5
Standard Deviation = 10
This is expressed as the the likelihood that the distributor will not stock out during lead time
Average = 30

73. The Multi-Period Continuous Review Inventory Model
Normally distributed random demand
Fixed order cost plus a cost proportional to amount ordered.
Inventory cost is charged per item per unit time
If an order arrives and there is no inventory, the order is lost
The distributor has a required service level. This is expressed as the the likelihood that the distributor will not stock out during lead time.
Intuitively, how will this effect our policy?
Normally distributed,正态分布, This is expressed as the the likelihood that the distributor will not stock out during lead time.这可以由在订货提前期内分销商不会断货的概率表示

74. A View of (s, S) Policy S Inventory Level s Time Inventory Position
Lead
Time
Lead
Time
Inventory Level s
Time

75. The (s,S) Policy
(s, S) Policy: Whenever the inventory position drops below a certain level, s, we order to raise the inventory position to level S.
The reorder point is a function of:
The Lead Time
Average demand
Demand variability
Service level

76. Notation AVG = average daily demand
STD = standard deviation of daily demand
LT = replenishment lead time in days
h = holding cost of one unit for one day
K = fixed cost
SL = service level (for example, 95%). This implies that the probability of stocking out is 100%-SL (for example, 5%)
Also, the Inventory Position at any time is the actual inventory plus items already ordered, but not yet delivered.

77. Analysis The reorder point (s) has two components:
To account for average demand during lead time: LTAVG
To account for deviations from average (we call this safety stock) z  STD  LT where z is chosen from statistical tables to ensure that the probability of stockouts during leadtime is 100%-SL.
Since there is a fixed cost, we order more than up to the reorder point: Q=(2 K AVG)/h
The total order-up-to level is: S=Q+s
Z: 安全系统

78. Example
What is Reorder point? what is the order-up-to-level?
The distributor has historically observed weekly demand of: AVG = 44.6 STD = 32.1 Replenishment lead time is 2 weeks, and desired service level SL = 97%
Average demand during lead time is:  2 = 89.2
Safety Stock is:  32.1  2 = 85.3
Reorder point is thus 175, or about 3.9 weeks of supply at warehouse and in the pipeline
Suppose the distributor of the TV sets is trying to set inventory policies at the warehouse for one of the TV models. The data have been provided on the number of TV sets sold . Every time the warehouse places an order to the manufacturer, replenishment time(I.e.,lead time) is about two weeks. The distributor would like to ensure that service level is about 97%. Assuming there is no fixed ordering cost, what is the order-up-to-level that the distributor should use?
The average monthly demand is and the standard deviation of monthly demand is
Since lead time is two weeks, we transform the average and the standard deviation to weekly values as follows: Average weekly demand=(Average monthly demand)/4.3
While
Standard deviation of weekly demand=Monthly standard deviation/sqrt(4.3)
We calculate average demand during lead time and safety stock using a constant Z=1.9. The reorder point is simply the sum of the average demand during lead time plus the safety stock. The order-up-to-level is equal to 855. The distributor needs to keep about four weeks’ worth of inventory at the warehouse and in the pipeline.

79. Example, Cont. Weekly inventory holding cost: .87
Therefore, Q=679
Order-up-to level thus equals:
Reorder Point + Q = = 855
Suppose the distributor of the TV sets is trying to set inventory policies at the warehouse for one of the TV models. The data have been provided on the number of TV sets sold . Every time the warehouse places an order to the manufacturer, replenishment time(I.e.,lead time) is about two weeks. The distributor would like to ensure that service level is about 97%. Assuming there is no fixed ordering cost, what is the order-up-to-level that the distributor should use?
The average monthly demand is and the standard deviation of monthly demand is
Since lead time is two weeks, we transform the average and the standard deviation to weekly values as follows: Average weekly demand=(Average monthly demand)/4.3
While
Standard deviation of weekly demand=Monthly standard deviation/sqrt(4.3)
We calculate average demand during lead time and safety stock using a constant Z=1.9. The reorder point is simply the sum of the average demand during lead time plus the safety stock. The order-up-to-level is equal to 855. The distributor needs to keep about four weeks’ worth of inventory at the warehouse and in the pipeline.

80. Suppose the distributor places orders every month
4.2.5 Periodic Review
Suppose the distributor places orders every month
What policy should the distributor use?
What about the fixed cost?
Fixed costs are sunk, and so don’t matter…

81. Base-Stock Policy Inventory Level Time r Base-stock Level Inventory
Inventory
Position r L

82. Periodic Review Policy
Each review echelon, inventory position is raised to the base-stock level.
The base-stock level includes two components:
Average demand during r+L days (the time until the next order arrives): (r+L)*AVG
Safety stock during that time: z*STD* r+L
基本存储水平
We continue with the previous example and assume that whenever our distributor places an order for TV sets, there is a fixed ordering cost of $4,500, which is independent of the order size. The cost of a TV set to the distributor is $250 and annual inventory holding cost is about 18% of the product cost. Thus, weekly inventory holding cost per TV set is:
0.18*250/52=0.87
This implies that the order quantity, Q, should be calculated as: Q=SQRT(2*4,500*44.58/0.87=679
And hence the order-up-to-level is :Safety stock+Q=86+679=765
That is, the distributor should place an order to raise the inventory position to 765 TV sets whenever the inventory level is below or at 176 units.

83. 4.3 Risk Pooling Example Consider these two systems:
Some problems faced by ACME, a company that produces and distributes electronic equipment in the Northeast of the United States.
(1)The current distribution system partitions the Northeast into two markets, each of which has a single warehouse. Retailers receive items directly from the warehouses; each retailer is assigned to a single market and receives deliveries from the corresponding warehouse.
Supplier
Warehouse One
Warehouse Two
Market One
Market Two

84. Risk Pooling Example (cont’)
(2)Replace the two warehouses with a single warehouse. The same service level,97%, be maintained regardless of the logistics strategy employed.
This system allows ACME to achieve either the same service level of 97% with much lower inventory or a higher service level with the same amount of total inventory.
Market Two
Supplier
Warehouse
Market One

85. Risk Pooling Example (cont’)
For the same service level, which system will require more inventory? Why?
For the same total inventory level, which system will have better service? Why?
What are the factors that affect these answers?

86. Risk Pooling Example (cont’)
Compare the two systems:
two products(A,B)
maintain 97% service level
$60 order cost
$.27 weekly holding cost
$1.05 transportation cost per unit in decentralized system, $1.10 in centralized system
1 week lead time

87. Risk Pooling Example Table 1 Historical Data for Product A and B
The tables include weekly demand information for each product for the last eight weeks in each market area. Observe that Product B is a slow-moving product –the demand for Product B is fairly small relative to the demand for Product A.

88. Risk Pooling Example Table 2 Summary of Historical Data A 39.3 13.2
Product
Average Demand
Standard Deviation Demand
Coefficient of Variation
Market1 A
39.3
13.2
0.34 B
1.125
1.36
1.21
Market2
38.6
12.0
0.31
1.25
1.58
1.26
Total
77.9
20.71
0.27
2.375
1.9
0.81
CV = STD/AVG

89. Risk Pooling Example A Table 3 Inventory Levels B Market1 39.3 25.8 65
Product
AVG D
Safety Stock
Reorder point Q
Order-up to level
Market1 A
39.3
25.8 65
132
197 B
1.125
2.58 4 25 29
Market2
38.6
22.8 62
131
193
1.25 3 5 24
Total
77.9
39.35
118
186
304
2.375
3.61 6 33 39
Average Inventory ~ ss + Q/2

90. Risk Pooling: Important Observations
Centralizing inventory control reduces both safety stock and average inventory level for the same service level.
This works best for
High coefficient of variation, which increases required safety stock.
Negatively correlated demand. Why?
What other kinds of risk pooling will we see?

91. Risk Pooling: Types of Risk Pooling*
Risk Pooling Across Markets
Risk Pooling Across Products
Risk Pooling Across Time
Daily order up to quantity is:
LTAVG + z  AVG  LT
Orders 10 11 12 13 14 15
Demands

92. 4.4 To Centralize or not to Centralize
What are the trade-offs that we need to consider in comparing centralized distribution systems with decentralized distribution systems?
What is the effect on:
Safety stock?
Service level?
Overhead?
Lead time?
Transportation Costs?

93. Centralized vs Decentralized system
Safety stock. Clearly, safety stock decreases as a firm moves from a decentralized to a centralized system.
Service level. When the centralized and decentralized systems have the same total safety stock, the service level provided by the centralized system is higher.
Lead time. Since the warehouses are much closer to the customers in a decentralized system,response time is much lower.

94. 4.5 Managing Inventory in the SC (Centralized Systems*)
The warehouse echelon inventory
Supplier
Warehouse
Retailers
The warehouse policy controls its echelon inventory position, that is, whenever the echelon inventory position for the W is below s, an order is placed to raise its echelon inventory position to S.

95. Centralized Distribution Systems*
Question: How much inventory should management keep at each location?
A good strategy:
The retailer raises inventory to level Sr each period
The supplier raises the sum of inventory in the retailer and supplier warehouses and in transit to Ss
If there is not enough inventory in the warehouse to meet all demands from retailers, it is allocated so that the service level at each of the retailers will be equal.

96. 4.6 Inventory Management: Best Practice
Periodic inventory reviews
Tight management of usage rates, lead times and safety stock
ABC approach
Reduced safety stock levels
Shift more inventory, or inventory ownership, to suppliers
Quantitative approaches

97. Changes In Inventory Turnover
Inventory turnover ratio = annual sales/avg. inventory level
Inventory turns increased by 30% from 1995 to 1998
Inventory turns increased by 27% from 1998 to 2000
Overall the increase is from 8.0 turns per year to over 13 per year over a five year period ending in year 2000.

98. Inventory Turnover Ratio

99. Factors that Drive Reduction in Inventory
Top management emphasis on inventory reduction (19%)
Reduce the Number of SKUs in the warehouse (10%)
Improved forecasting (7%)
Use of sophisticated inventory management software (6%)
Coordination among supply chain members (6%)
Others
Recent survey of inventory managers

100. Factors that Drive Inventory Turns Increase
Better software for inventory management (16.2%)
Reduced lead time (15%)
Improved forecasting (10.7%)
Application of SCM principals (9.6%)
More attention to inventory management (6.6%)
Reduction in SKU (5.1%)
Others

101. Forecasting Recall the three rules Nevertheless, forecast is critical
General Overview:
Judgment methods
Market research methods
Time Series methods
Causal methods

102. Judgment Methods Assemble the opinion of experts
Sales-force composite combines salespeople’s estimates
Panels of experts – internal, external, both
Delphi method
Each member surveyed
Opinions are compiled
Each member is given the opportunity to change his opinion

103. Market Research Methods
Particularly valuable for developing forecasts of newly introduced products
Market testing
Focus groups assembled.
Responses tested.
Extrapolations to rest of market made.
Market surveys
Data gathered from potential customers
Interviews, phone-surveys, written surveys, etc.

104. Time Series Methods
Past data is used to estimate future data
Examples include
Moving averages – average of some previous demand points.
Exponential Smoothing – more recent points receive more weight
Methods for data with trends:
Regression analysis – fits line to data
Holt’s method – combines exponential smoothing concepts with the ability to follow a trend
Methods for data with seasonality
Seasonal decomposition methods (seasonal patterns removed)
Winter’s method: advanced approach based on exponential smoothing
Complex methods (not clear that these work better)

105. Causal Methods
Forecasts are generated based on data other than the data being predicted
Examples include:
Inflation rates
GNP
Unemployment rates
Weather
Sales of other products

106. Selecting the Appropriate Approach:
What is the purpose of the forecast?
Gross or detailed estimates?
What are the dynamics of the system being forecast?
Is it sensitive to economic data?
Is it seasonal? Trending?
How important is the past in estimating the future?
Different approaches may be appropriate for different stages of the product lifecycle:
Testing and intro: market research methods, judgment methods
Rapid growth: time series methods
Mature: time series, causal methods (particularly for long-range planning)
It is typically effective to combine approaches.