1. Determining Optimal Level of Product Availability

2. Importance of the Level of Product Availability
Product availability affects supply chain responsiveness
Trade-off:
High levels of product availability  increased responsiveness and higher revenues
High levels of product availability  increased inventory levels and higher costs
What is the cycle service level that will result in maximum supply chain profits?

3. Single product is to be ordered at the beginning of a period
Newsvendor Model:
Single product is to be ordered at the beginning of a period
and can only be used to satisfy demand during that period.
A newsboy has to make decision on buying how many copies (Q) of newspapers in the early
morning each day.
p = sale price (to the customer); c = purchase price (from the newspaper company),
s =salvage price;
Profit from selling one copy of newspaper = p-c (Cost of understocking, Cu)
Cost of not selling one copy of newspaper = c-s (Cost of overstocking, Co)
There are two scenarios
Demand (X) >order quantity (Q)
Profit =Q(p-c) with probability of P(X>Q)
Demand (X) <order quantity (Q)
Profit =pX-cO+s(Q-X) with probability of P(X<Q)
Therefore, expected profit=
F(Q*) = Cu / (Cu + Co) (1)
Q* =F-1 [Cu / (Cu + Co)] (2)

4. F(Q*) (also called CSL) = Probability that demand will
Newsvendor Model:
Single product is to be ordered at the beginning of a period
and can only be used to satisfy demand during that period.
F(Q*) (also called CSL) = Probability that demand will
be at or below a certain quantity.
CSL* = Cu / (Cu + Co) (12.1)

5. Example 1
The manager at Sportmart store, has to decide on the number of skis to purchase
for the winter season. Considering past demand data and weather forecasts for the
year, management has forecast demand to be normally distributed with mean of µ=350 and
a standard deviation of σ=100. Each pair of skis costs c=$100 and retails for p=$250. Any
unsold skis at the end of the season are disposed of for $85. Assume that it costs $5 to hold
a pair of skis in inventory for the season. Evaluate the number of skis that the manager
should order to maximize expected profits.
Unit cost c = $100
Sale price p = $250
Inventory holding cost h= $5
Salvage value s = $85-$5=$80
Cost of understocking=Cu = p-c = = $150
Cost of overstocking =CO= c-s = = $20
Using (1) CSL*=probability (demand<=O*)=Cu/(Cu+ CO )=150/(150+20)
Using (2)
Using (3)
Notes: What information is required to make the ordering decision? Stress cost of understocking and overstocking. How to evaluate these costs for this example?

6. Managerial Levers to Improve Supply Chain Profitability
“Obvious” actions
Increase salvage value of each unit
Improved forecasting
Quick response
Postponement
Tailored sourcing

7. Improved Forecasts Improved forecasts result in reduced uncertainty
Less uncertainty (lower sR) results in either:
Lower levels of safety inventory (and costs) for the same level of product availability, (11.9) or
Higher product availability for the same level of safety inventory, or
Both lower levels of safety inventory and higher levels of product availability contribute to supply chain profitability.

8. Impact of Improving Forecasts (Example 2)
Consider a buyer at Bloomingdales responsible for purchasing dinnerware with Christmas
patterns. The dinnerware only sells over the Christmas season and the buyer places an order for
delivery in early Nov.. Each dinnerware set costs c=$100 and sells for a retail price of p=$250.
Any sets unsold by Christmas are heavily discounted in the post-Christmas sales and sold for a
salvage value of s=$80. The buyer has estimated that demands normally distributed with a mean
of µ=350 and a standard deviation of σ=150. The buyer has decided to conduct additional market
research to get a better forecast. Evaluate the impact of improved forecast accuracy on
profitability and inventories as the buyer reduces σ from 150 to 0 in increments of 30.
Demand: Normally distributed with a mean of µ = 350 and standard deviation of = 150
Salvage value s = $80
Unit cost c = $100
Sale price p = $250
Cost of understocking=Cu = p-c = = $150
Cost of overstocking =CO= c-s = = $20
Using (1) CSL*=probability (demand<=O*)=Cu/(Cu+ CO )=150/(150+20)=0.88
Using (2) and (3), the optimal order size and the maximal expected profit are obtained.
Note:
Cost of understocking = = $150
Cost of overstocking = = $20
p = 150/(150+20) = 0.88
Order size = 426

9. Impact of Improving Forecasts

10. Quick Response Set of actions taken by managers to reduce lead time
Reduced lead time results in improved forecasts
Typical example of quick response is multiple orders in one season for retail items (such as fashion clothing)
For example, a buyer can usually make very accurate forecasts after the first week or two in a season
Multiple orders are only possible if the lead time is reduced – otherwise there wouldn’t be enough time to get the later orders before the season ends
Benefits:
Lower order quantities  less inventory, same product availability
Less overstock
Higher profits

11. Quick Response: Multiple Orders Per Season
Order point
Season starts
Season ends 15 14
First order 6
Second order
Second order received
Selling season: 14 weeks, Original order lead time:15 weeks, Reduced lead time=6 weeks

12. Ordering Twice as Opposed to Once
The second order can be used to correct the demand supply mismatch in the first order, based on the realized demand.
At the time of placing the second order, take out the on-hand inventory from the demand the second order is supposed to satisfy. This is a simple correction idea.
Between the time first and second orders are placed, more information becomes available to demand forecasters. The second order is typically made, based on the more accurate forecast than the first one.
Impact of Quick Response

13. Forecast Improves for Second Order

14. Postponement
Delay of product differentiation until closer to the time of the sale of the product
All activities prior to product differentiation require aggregate forecasts more accurate than individual product forecasts
Results in a better match of supply and demand
Beginning of the season

15. Benetton Old Manufacturing Process
Spin or Purchase Yarn
Dye Yarn
Finish Yarn
Manufacture Garment Parts
Join Parts

16. Benetton New Manufacturing Process
Spin or Purchase Yarn
Manufacture Garment Parts
Join Parts
This step is postponed
Dye Garment
Finish Garment

17. Value of Postponement: Benetton
For each color
Mean demand = 1,000; SD = 500
For each garment
Sale price = $50
Salvage value = $10
Production cost using Option 1 = $20
Production cost using Option 2 (uncolored thread) = $22
Option 1: Dying is done before demand is known
Option 2: Dying is postponed until demand is known
What is the value of postponement?
Expected profit increases from $94,576 to $98,092

18. Value of Postponement: Benetton
For each color
Mean demand = 1,000; SD = 500
For each garment
Sale price = $50
Salvage value = $10
Production cost using Option 1 (long lead time) = $20
Production cost using Option 2 (uncolored thread) = $22
Option 1: Benetton must decide on the quantity of colored thread to purchase for each color. For each color we have the following:
Using Equation 2,
Expected profit for each color (using Equation 3)=$23,644. Thus, total profit=$94,576

19. Value of Postponement: Benetton
For each color
Mean demand = 1,000; SD = 500
For each garment
Sale price = $50
Salvage value = $10
Production cost using Option 1 (long lead time) = $20
Production cost using Option 2 (uncolored thread) = $22
Option 2: Benetton must decide on the total number of sweaters across all four colors to be produced because they can be dyed to the appropriate color once demand is known.
Using Equation 1,
Given that demand in independent, total demand for all four colors is
Using Equation 2,
It is optimal to produce 4524 undyed (generic) sweaters to be dyed as demand by color is available.
Expected profit (using Equation 3)=$

20. Postponement Downside
By postponing all three garment types, production cost of each product goes up
When this increase is substantial or a single product’s demand dominates all other’s (causing limited uncertainty reduction via aggregation), a partial postponement scheme is preferable to full postponement.

21. Tailored Postponement: Benetton case
For each product a part of the demand is aggregated, the rest is not
Produce Q1 units for each color using Option 1 and QA units (aggregate) using Option 2, results from simulation:
It is quite likely that demand for each color will be 800 or higher (recall that mean demand = 1,000; SD = 500 for each color). The tailored postponement policy exploits this fact and produces these units using option1, which has a low cost. The remaining units are produced using Option 2 so that demand uncertainty can be reduced by aggregation.
Q1 for each QA
Profit
1337
$94,576
4524
$98,092
1100
550
$99,180
1000
850
$100,312
800
1550
$104,603

22. Tailored (Dual) Sourcing
A firm uses a combination of two supply sources, and the two sources must focus on different capabilities.
One focusing on cost but unable to handle uncertainty well.
The other focusing on flexibility to handle uncertainty, but at a higher cost.
Benetton uses its “efficiency” source to serve 65% of orders, and use its “flexibility” source to serve the other 35% of orders.
Tailored sourcing contributes to increasing profits and better matching supply and demand.

23. Supply Chain Contracts and Their Impact on Profitability
Returns policy: Buyback contracts
Revenue sharing contract.
Vendor-managed inventories

24. Returns Policy: Buyback Contracts
A manufacturer specifies a wholesale price and a buyback price at which the retailer can return any unsold items at the end of the season
Results in an increase in the salvage value for the retailer, which induces the retailer to order a larger quantity
The manufacturer is willing to take on some of the cost of overstocking because the supply chain will end up selling more on average
Manufacturer profits and supply chain profits can increase

25. Impact of SC Contracts on Profitability: Buyback Contracts
Tech Fiber(TF) produces jacket and sells to Ski Adventure(SA) which sells them in the market. Unsold jackets have no salvage value. Should TF be willing to buy back unsold jackets? Why?
Market
Price=$200
Wholesale
Price=$100
Cost=$10 TF SA
~N(1000,3002)

26. Buyback Contracts

27. Revenue Sharing Contracts
The manufacturer charges the retailer a low (or even zero) wholesale price and shares a fraction of the revenue generated by the retailer
The lower wholesale price decreases the cost to the retailer in case of an overstock
The retailer therefore increases the level of product availability, which results in higher profits for both the manufacturer and the retailer
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)

28. Traditional Situation
Selling Price=$200
Salvage Value=$0
Demand ~N (1000, 3002)
Wholesale Price =$100
Who takes the risk? What would the manufacturer like?
Manufacturer
Production cost=$10
Manufacturer DC
Retail DC
Stores

29. Revenue Sharing Contract
Selling Price=$200
Salvage Value=$0
Demand ~N (1000, 3002)
Wholesale Price =$100
Who takes the risk? What would the manufacturer like?
Manufacturer
Production cost=$10
Manufacturer DC
Retail DC
Stores

30. Traditional Situation
For the retailer:
=$100
100-0=$100
Optimal order quantity for the retailer=1,000 (Equation 12.2)
Retailer=[8000*45-( )*60]*0.11+[10,000*45-( ,000)*60]*0.11+[12,000*45-( ,000)*60]*0.28
+( )*12,000*45=470,700
Manufacturer=12000* =440000
Retailer’s expected profit is $76,063
Manufacturer profit is $90,000
Supply Chain Profit is $166,063

31. Revenue Sharing Contract
For the retailer:
200-10=$190
10-0=$10
Optimal order quantity for the retailer=1,493 (Equation 12.2)
Retailer=[8000*45-( )*60]*0.11+[10,000*45-( ,000)*60]*0.11+[12,000*45-( ,000)*60]*0.28
+( )*12,000*45=470,700
Manufacturer=12000* =440000
Supply Chain Profit is $183,812

32. Vendor-Managed Inventories (VMI)
Manufacturer or supplier is responsible for all decisions regarding inventory at the retailer
Control of replenishment decisions moves to the manufacturer
Requires that the retailer share demand information with the manufacturer
Having final customer demand data also helps manufacturer plan production more effectively, at the same time it enables the manufacturer to respond to the retailer more quickly appropriately scheduling production and replenishing the retailer inventory.

33. VMI New Initiative:VMI Manufacturer DC or store Customer demand data
Product
replenishment