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Risk Pooling (continued): Oct. 26
Remaining Classes
Nov. 2: Beer game + Bullwhip Effect: E-Lab (6th Floor)
Nov. 9: Bullwhip + Supply Chain Contracts
Nov. 16: Midterm exam: 7-9:30pm, Sci. Centre L1
Nov . 23: SC Contracts + +Trade
Nov. 30: SC Transportation+ Revenue Mgmt
Dec. 7 : + Strategy + Review
Dec. 14: Final Exam
The central question which we try to address is
How to manage the great variety of demand in
supply chains?
Also a related question:
How to manage variability/uncertainty of demand
in supply chains ?
Risk pooling strategies:
Lead time pooling
14-3
More on Risk Pooling Applications
Pooling Game: (1) or (2) would do better?
Supplier
SupplierW/h
4 wks
2 wks
2 wks
Retailer1
Retailer 2
Retailer 3
Retailer1
Retailer 2
Retailer 3
(2) Ignore the cost of running the w/h
(1)
Leadtime =4
On-
hand
Ship.
due
Now
Order
D’d
Wk 1
(Now)
D’d
Wk 2
D’d
Wk3
D’d
Wk4
D’d
Wk5
R1 250 300
(wk 2)
400
(wk 5)
No
more
due
50
(200)
120
(380)
R2 300 200
(wk 2)
300
(wk 5)
No
more
due
120
(180)
150
(230)
R3 350 200
(wk 2)
300
(wk 5)
No
more
due
130
(220)
140
(280)
It would be beneficial if reallocation after wk 2 is possible
Ending inventory (Wk1)
Location pooling -- Full Service
Distribution Center – inventory carrying
at DC
warehouse
Retailers
(Resellers)
Location pooling Location pooling
• When inventory is at the Factory it is difficult to predict
which retailer will have the highest need for inventory.
• It is easier to predict the “correct” allocation when the
inventory arrives at the w/h
• The benefit of delaying the inventory allocation decision
from F to W is called “location pooling” - a special form
of risk pooling
• Such pooling effect partially brought about by “Leadtime
risk pooling”
F W
R
R
R
How about postponement?
Location pooling pros, cons and alternatives
Pros
Efficient inbound and outbound transportation:
Inbound aggregates orders from many retailers
Outbound contains products from multiple suppliers/SKUs
Inventory allocation is decided at the DC, i.e., leadtime risk
pooling is exploited
Supplier can ship single SKU
Cons:
Location pooling moves inventory away from customers:
“Big quantity” at each customer/store v.s. “smaller quantity” at each customer/store + a warehouse
Requires more handling of inventory and space for
storage14-8
GM 通用汽車 – Cadillac (凱迪拉克)
工廠Fty
中央倉庫 CDC
地區倉庫 Reg. DC
銷售商 Dealers
A
B
C
D
Cadillac
4- tie inventory system
銷售商類車/流行車 – popular: 0 （Leadtime)
地區倉庫類車 – 車室內選擇限制 (interior) -- 1
中央倉庫類車 –選擇限制少一些 (more options) --10
定制類車 –任何選擇 (personalized) -- 32 天 交貨期
Cadillac
效果 Results
庫存 平均 減少 (reduction in inventory) 25-50%
銷售商省$12億 (Dealers saving $1.2 bil in capital)
預測精度改善 (more acurrate forecasting)
更具響應性 (more responsive)
Consolidated distribution summary
Consolidated distribution reduces inventory in a supply chain via lead time risk pooling
Due to lead time risk pooling the supply chain only needs to decide the total quantity to ship from the supplier, not a total quantity and its allocation across locations. Hence, some uncertainty is avoided.
Most effective if demands are negatively correlated across locations.
Most effective if the supplier lead time is long and the DC to store lead time is short.
But consolidated distribution increases total distance traveled and total lead time from supplier to stores.
Other benefits of consolidated distribution:
Easier to obtain quantity discounts in purchasing.
Easier to obtain economies of scale in transportation:
the DC may be able to order a full truck load every day, whereas an individual store might requires much more time to order a full truckload)
14-12
Risk pooling strategies:
Capacity pooling
14-13
Risk Pooling App. – Part 3
Based on G. Cachon and C. Terwiesch: Matching Supply with
Demand , 2009; in turn, from “Jordon W., S. Graves:
Principles on the Benefits of Manufacturing Process
Flexibility,” MS, 41, pp.577-94, 1995.”
Capacity pooling with flexible manufacturing
Consider the following stylized situation faced by GM …
They have 10 production facilities
They have 10 vehicles to produce (GMC truck, Chevy Tahoe, Buick
Roadmaster, etc).
Each plant is capable of producing 100 units.
Demand for each product is Normally distributed with mean 100 and
standard deviation 40.
Each plant can be configured to produce up to 10 products
But flexibility is expensive, i.e., the cost to construct a plant is increasing
in the number of products it can produce.
GM must decide which plants can produce which products before
demand is realized.
After demand is realized, GM can allocate its capacity to satisfy
demand.
If demand exceeds capacity, sales are lost.
14-14
Four possible capacity configurations: no flexibility
to total flexibility
The more links in the configuration, the more flexibility constructed
In the 16 link configuration plant 4 is flexible enough to produce 4 products
but plant 5 has no flexibility (it produces a single product).
14-15
How is flexibility used
Flexibility allows production shifts to high selling products to avoid lost sales.
Consider a two plant, two product example and two configurations, no
flexibility and total flexibility:
If demand turns out to be 75 for product A, 115 for product B then..
Product Demand Plant 1 Plant 2 SalesA 75 75 0 75B 115 0 100 100
Total Sales 175 Plant Utilization 88%
Production With no flexibility
Product Demand Plant 1 Plant 2 SalesA 75 75 0 75B 115 15 100 115
Total Sales 190 Plant Utilization 95%
Production With total flexibility
14-16
The value of flexibility
Adding flexibility increases capacity utilization and expected sales:
Note: 20 links can provide nearly the same performance as total flexibility!
800
850
900
950
1000
80 85 90 95 100
Expected capacity utilization, %
Ex
pec
ted
sal
es,
un
its
No flexibility
Total flexibility
20 links
11 links
12 links
These data are
collected via simulation
14-17
Chaining: how to add flexibility
A chain is a group of plants and products connected via links.
Flexibility is most effective if it is added to create long chains.
A configuration with 20 links can produce nearly the results of total flexibility
as long as it constructs one large chain:
Hence, a little bit of flexibility is very useful as long as it is designed correctly
14-18
Other applications in service environments
How about cross training?
Imagine a trade company: Sourcing; Customs
clearance; Banks/credit; Shipping;
Administration; Legal issues
Risk pooling summary
Risk pooling strategies are most effective when total demand
uncertainty is lower than the uncertainty for individual
products/locations.
A little bit of risk pooling goes a long way:
With location pooling the biggest bang is from pooling a few
locations
With capacity pooling a little bit of well designed flexibility is very
effective.
Risk pooling allows a firm to “have its cake and eat it too”
It is possible to lower inventory and increase service
simultaneously.
14-20
