Teaching Note: The Need for Speed at Winner Apparel
The goal of this case is to get students to evaluate the benefits of responsiveness for different product
categories. Trendy is a product line with higher unpredictability, while Basic is more predictable. While
With the low-cost supplier, the buyers at Winner have to place a single order before the start of the
sales season. The optimal service level (sl) and order quantity is linked to the margin and salvage value
as follows:
; ( , , )
pc
sl Order size NORMINV sl
ps

−
==
−
The results for the two products are shown in Table 1 (see spreadsheet Winner apparel Case, worksheet
Single order in season).
Table 1: Order Quantities and Financial Performance with Low-Cost Supplier
Given the costs and margins, it is optimal for Winner to provide a 75% service level for the Trendy line
and a 66.67% service level for the Basic line. This results in an optimal order of 568 units for Trendy and
1086 units for Basic. It seems that the buyers at Winner were very close to the optimal numbers in
The Value of the Responsive Supplier
Product
Sale
Price, p
Sourcing
cost, c
Net
salvage
value, s
Mean
Season
Demand, μ
SD of
Season
Demand, σ
Optimal
Service
Level
Optimal
Order
Size
Expected
Overstock
Expected
Profit
Trendy 100 40 20 400 250 75.00% 568 205.44 37.44 17,644.45
Basic 50 30 20 1000 200 66.67% 1086 130.05 44.05 17,818.40
Maximum gain from eliminating all over– and under-stock (over entire season) for Basic = 130.05 * (30 −
20) + 44.05 * (50 − 30) = $2,182
Observe that the potential gain from matching supply and demand is higher for Trendy compared to
Basic. This gain becomes even larger when we consider the gain per unit sold. The higher potential gain
for Trendy can be linked to the fact that Trendy has higher demand variability as measured by the
coefficient of variation (standard deviation/mean).
But there is a cost to responsiveness as well because the responsive supplier charges an extra 5 percent.
Also, in reality, it will not be possible to eliminate all over- and under-stock. Thus, the actual gains will be
Given the higher sourcing cost from the local supplier, Winner should aim for a service level of 72.5
percent for Trendy and 61.67 percent for Basic. Thus, Winner should start the first half of the season
with 305 units of Trendy and 541 units of Basic. Such a policy will result in expected over- and under-
stocking for each product as shown in Table 2. If we assume that the responsive supplier allows Winner
to avoid understocking (by bringing extra product as a second order in time) and overstocking (by
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Best case expected profit for Trendy = $6,875.16 {expected profit from first cycle} + 135.19 * (42 − 20)
{Eliminate cost of overstocking for first cycle} + 30.19 * (100 − 42) {Eliminate cost of understocking for
first cycle} + $6,875.16 {expected profit from second cycle} = $18,475.16.
Best case expected profit for Basic = $7,635.13 {expected profit from first cycle} + 79.11 * (31.50 − 20)
{Eliminate cost of overstocking for first cycle} + 38.11 * (50 − 31.5) {Eliminate cost of understocking for
first cycle} + $7,635.13 {expected profit from second cycle} = $16,885.13.
Our results indicate that sourcing Trendy from the local supplier can increase expected profits if the
local supplier is responsive enough to eliminate all over- and under-stocking during the first cycle. For
Basic T-shirts, however, the 5 percent increase in cost is too much and sourcing from the local supplier