Risk Pooling
Chap. 14
• Risk Pooling – “Theory”
• Applications
– Differentiation Postponement/Delay
– Location, …
HP Case - handed out – preparation questions
1. On page 1, it said “We can’t run our business with this level of unproductive
assets.” What are these assets?
2. What is “the I-word” referred to?
3. Is the ink-jet printer a commodity or fashionable product?
4. At the European DC, did HP have too much stock or too little stock?
5. What were the symptoms of the problem in the European DC?
6. When customers buy ink-jet printers, is brand/product loyalty playing an
important factor in their choosing which products to buy?
7. How did the Vancouver Division impress visitors? Was the line suitable for high
volume or low volume production? Why?
8. Were Ink-Jet Printers completely built in the Vancouver factory? Can a printer
that was built for the Germany market be directly sold in Italy market? Why? Be
precise.
9. What were the performance evaluation criteria for European DC? Should the DC
manager be concerned about the inventory level?
10. What were the alternatives for resolving the inventory and service crisis?
Coefficient of Variation
CV = Standard Dev / Average demand
Demand series 1: CV1 = 0.5
Demand series 2: CV2 = 2.0
Which is more volatile?
Risk Pooling
• Which sales are more volatile: the regional
sales or sales at the store level?
• Which demand is more volatile : a family
of products or individual members of the
family?
• Do people wait longer in a multiplewaiting-lines system than a single-waitingline system?
• Implication for forecasting ?
Family vs. Individual Products
Sales
N
A
B
C
Time
Family vs. Individual Products
Model
X
XX
XY
XH
XC
XY
Mean
42
420
15,830
2,301
4,208
309
Stdv
32
203
5,624
1,168
2,204
103
CV
0.78
0.46
0.36
0.51
0.52
0.34
Total
23,109
6,244
0.27
Pooling, Profit & Service Level
(An Example)
• Two products (paints) differ only in colour
• It is fast to mix to the required colour upon
receiving orders
• Assume that the demand for each follows a
distribution given by tossing a dice
An Example
• Alternative I: Make to Stock
• Alternative II: Make to Order (for colouring
only)
• Order-up-to inventory replenishment policy
• One season, c=$2.5, p=$12.5, s=0
For Alternative I: 5 units for each
• For Alternative II: ?
Preliminary Calculations
1
2
3
4
5
6
1
1,1
2
3
4
5
5,4
x
4,5
5,5
x
4,3
x
Chance of stockout?
x
x
6
x
x
x
x
x
x
Preliminary Calculations
1
2
3
4
5
6
1
1,1
2
3
4
5
5,4
x
4,5
5,5
x
4,3
x
x
If D1=4, D2 =5, profit = ?;
If D1=6, D2=4, profit = ?.
x
6
x
x
x
x
x
x
• Holding 10 units of “generic” colour pigment, the chance of stocking out in a
period is only
3/36 = 1/12 = 0.083
The “risk” of disservice is lowered.
• Even holding 9 units, a higher level of
“service” will be achieved (as compared with
Alternative 1)
Preliminary Calculations
1
2
3
4
5
6
1
2
3
4
5
6
7
2
3
4
5
6
7
8
3
4
5
6
7
8
9
4
5
6
7
8
9
10
5
6
7
8
9
10
11
6
7
8
9
10
11
12
If D1=4, D2 =5, profit = ; If D1=6, D2=4, profit = 0. If
D1=2, D2=6, profit= . Additional cost?
“Theory”
T wo products : x1 , x2
Mean
Stdv
1 ,  2
 1, 2
Let x  x1  x2 , mean( x )  1   2
2
Var ( x )   12  2  1 2   2
(a)
If   0,
(b )
If   1,
(c )
If   1,
(d )
In general, |  | 1,
Why？
Implications?
• Variety is the “culprit” of high forecasting
errors, and higher forecasting accuracy can be
achieved if only a few varieties are offered
• Since we can not reduce them, we must find a
way to get around
– By postponing mass customisation
– By redesigning the product
• Universal products and common parts
(modules)
Product Variety Proliferation
• Product proliferation exists in various
forms
– global mkt: “protocols”, languages, phases,
elec.
– local mkt: multiple models differ in features &
capacities
– mkting strategies
• Marketing strategy is the major reason
The world of The Long Tail
Pitfalls of increasing product variety
Risk pooling strategies
• The objective of a risk pooling strategy is to redesign the supply chain,
the production process or the product to either reduce the uncertainty
the firm faces or to hedge uncertainty so that the firm is in a better
position to mitigate the consequence of uncertainty.
• Four versions of risking pooling:
– product pooling -- delayed differentiation/postponement
– location pooling
– lead time pooling
• delayed differentiation (HP case)
• consolidated distribution
– capacity pooling
14-18
Postponement
• Key idea - postpone the commitment of
WIP into a particular finished product –
SKU
• Delay of product differentiation closer
to time of sale.
• Prior to point of postponement, only
certain degree of aggregate forecast
needed
• Individual forecasts more accurate
close to time of sale
Postponement Concepts
• Mainly two forms
– Logistics Postponement: moving customisation point
closer to customers - out of mgr functions
– Form Postponement: delaying differentiation point by
standardisation or process re-sequencing
Logistics Postponement
Manufacturing
Integra- Customi- Locali- Packtion
sition
tion
ing
Supply Chain Process
Factory
Distribution Centers
Logistic Postponement by Process
Resequencing: Paint Retail
Colour pigments,
paint mixing,
packaging
Colour pigments,
white paint
Retail sales
Retail sales,
paint mixing
packaging
Nippon: combined
Dishwasher
Black
Integration+ship
Fib
DC
White
Before module design of the
metal frame
Black
DC+ pannel assembly
Fab.
Integration+ship
Operations
Buffer
White
Log PP: More Examples
• Rheem Manufacturing Co., kept 120 SKUs (heaters)
at its factory. Some were overstocked while other
fall short - only different in several elements
– Using a 3rd party to hold around 10 basic models
and parts
– Filling orders in hours and saving 15% of
inventory cost
• Even Coffee Rosters use it
• Of course, PC mfgrs apply it
• Some done by customers. More real life examples?
PC: indirect model (traditional)
PC
Company
Orders
Suppliers
Mfr factory
Distribution
Centers
Distributor
Configuration:
Disk, memory...
Product
VARs
Customers
Hybrid Model
PC
Company
Orders
Suppliers
Factory: core
Distribution
Centers
Distributor
Assembly
+Configuration
Product
VARs
Customers
Other examples of delayed
differentiation
• Private label soup manufacturer:
– Problem: many different private labels (Giant, Kroger, A&P, etc)
– Solution: Hold inventory in cans without labels, add label only
when demand is realized.
• Black and Decker:
– Sell the same drill to different retailers that want different
packaging.
– Store drills and package only when demand is realized.
• Nokia:
– Customers want different color phones.
– Design the product so that color plates can be added quickly and
locally.
14-27
Form Postponement
by Common Part
Before
After
Sometimes called
standardization
Mono/Color Printers
Mono
PCA
FA&T
Customizatio
Color
PCA
FA&T
Mono
Customization
Color
Operations
No correlation
Buffer
Form Postponement
by Process Reengineering
Series of tests and burn-in
PCB Insertion
Common
tests
Coupon PCB
Customisation
tests
Benetton: Process Reengineering
Old Sequence
New Sequence
Purchase Yarn
Purchase Yarn
Dye Yarn
Knit Garment Parts
Finish Yarn
Join Parts
Knit Garment Parts
Dye Garment
Join Parts
Finish Garment
This process
is postponed
Process Redesign for Supply Chain:
Postponement at Benetton
Dye yarn only after the season’s fashion preferences become more
established (knit lead-time much longer than dyeing lead-time).
Example: single product; four colors
knit
dye
Dyeing
operations
postponed
dye
knit
Outcome: Reduces demand uncertainty & inventory
Demand correlation
• Correlation refers
to how one random
variable’s outcome
tends to be related
to another random
variable’s
outcome.
20
20
18
18
16
16
14
14
12
12
10
10
8
8
6
6
4
4
2
2
0
0
0
5
10
15
20
0
5
10
15
20
20
Random demand for two products (x-axis
is product 1, y-axis is product 2). In
scenario 1 (upper left graph) the
correlation is 0, in scenario 2 (upper right
graph) the correlation is -0.9 and in
scenario 3 (the lower graph) the
correlation is 0.90. In all scenarios
demand is Normally distributed for each
product with mean 10 and standard
deviation 3.
18
16
14
12
10
8
6
4
2
0
0
5
10
15
20
14-33
Limitations of product
pooling/universal design
•
A universal design may not provide key functionality to consumers with
special needs:
– High end road bikes need to be light, high end mountain bikes need to be
durable. It is hard to make a single bike that performs equally well in both
settings.
•
A universal design may be more expensive to produce because additional
functionality may require additional components.
•
But a universal design may be less expensive to produce/procure because each
component is needed in a larger volume.
•
A universal design may eliminate brand/price segmentation opportunities:
– There may be a need to have different brands (e.g., Lexus vs Toyota) and
different prices to cater to different segments.
14-34
Summary: When is PP
Valuable?
• A lot of varieties
• Demand uncertainties over the variety are high
– Negatively correlated, ?
– Positively correlated, ?
• Differentiation is not too costly to perform locally, or
not time consuming
• The “core components” have high value, but
differentiating parts are of low value
Common Obstacles
• Though often design changes do not cost much, people
resist their implementation
• As production cost may increase, prod. people may oppose
to changes
• They also pose challenges to designers
• Indirect cost savings and intangible benefits