supply chain management lecture 9. outline today –chapter 6 –skipping 3e: section 6.5 p....
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Supply Chain Management
Lecture 9
Outline
• Today– Chapter 6– Skipping
• 3e: Section 6.5 p. 164-175, 4e: Section 6.6 p. 160-171• AM Tires: Evaluation of Supply Chain Design Decisions
Under Uncertainty
• Thursday– Finish Chapter 6 start with Chapter 7
• Homework 2 – Due Friday February 12 before 5:00pm
• If you email “save as” .doc and .xls format
Example: Dell Facility Location
? ??
What are the decisions?
What are the constraints?
Example: SC Consulting Facility Location
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?
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Making Network Design Decisions in Practice
• Computer models versus sound judgment– Most facility location decisions are based on tariffs and
tax incentives
Example: Dell Facility Location
Romenia Poland Ireland DemandFrance 23 19 31 15,000Germany 9 15 11 20,000Italy 23 21 40 13,000Spain 29 26 40 12,000United Kingdom 33 36 20 19,000Capacity 40,000 40,000 40,000Fixed operating cost 18,000,000.00$ 17,500,000.00$ 24,500,000.00$
Example: SC Consulting Facility Location
State L.A. Tulsa Denver Seattle Trip demandWashington $150 $250 $200 $25 40Oregon $150 $250 $200 $75 35California $75 $200 $150 $125 100Idaho $150 $200 $125 $125 25Nevada $100 $200 $125 $150 40Montana $175 $175 $125 $125 25Wyoming $150 $175 $100 $150 50Utah $150 $150 $100 $200 30Arizona $75 $200 $100 $250 50Colorado $150 $125 $25 $250 65New Mexico $125 $125 $75 $300 40North Dakota $300 $200 $150 $200 30South Dakota $300 $175 $125 $200 20Nebraska $250 $100 $125 $250 30Kansas $250 $75 $75 $300 40Oklahoma $250 $25 $125 $300 55Fixed Cost $165,428 $131,230 $140,000 $145,000Office Capacity 675 675 675 675
Travel Cost
Impact of Uncertainty in Network Design
• Supply chain network design decisions include– Facility location (number of facilities)– Capacity allocation (size of each facility)– Market and supply allocation (distribution)
These decisions, once made, cannot be changed easily in the short-term, they remain in place for several years
A decision that looks very good under the current environment may be quite poor if the situation changes
Demand, prices, exchange rates, and the competitive market change constantly
Supply Chain Risk
Supply failure
Commodity price volatility
Internal product failures
Lower consumer spending
Natural disaster
Supply Chain Risks to be Considered During Network Design
Category Risk DriversDisruptions Natural disaster, war, terrorism
Labor disputes, supplier bankruptcyDelays High capacity utilization at supply source
Inflexibility of supply sourcePoor quality or yield at supply source
Systems risk Information infrastructure breakdownSystem integration or extent of systems being networked
Forecast risk Inaccurate forecasts due to long lead times, seasonality,product variety, short life cycles, small cusomter baseBullwhip effect or information distortion
Intellectual property risk Vertical integration of supply chainGlobal outsourcing and markets
Procurement risk Exchange-rate riskFraction purchased from a single sourceIndustry-wide capacity utilization
Receivables risk Number of customersFinancial strength of customers
Inventory risk Rate of product obsolescenceInventory holding costProduct valueDemand and supply uncertainty
Capacity risk Cost of capacityCapacity flexiblityDoes offshoring increase or decrease these risks?
Supply Chain Risk
Supply Chain Risk
“Significant supply chain disruptions can reduce your company’s revenue, cut into your market share, inflate
your costs, send you over budget, and threaten production and distribution. You can’t sell goods you can’t manufacture or deliver. Such disruptions also
can damage your credibility with investors and other stakeholders, thereby driving up your cost of capital”
Source: FM Global – The New Supply Chain Challenge: Risk Management in a Global Economy
Managing a Supply Chain is Not Easy
• Uncertainty and risk factors– 1997 Raw material shortages
• Boeing inventory write down of $2.6 billion– 2000 Nike glitch in demand planning software
• Shortage of popular Air Jordan footwear• Nike announced a $100 million sales loss
– 2001 9/11• Trucks full of parts queued up for miles at the US-Canadian
border– 2002 West Coast port strike
• Losses of $1B/day• Store stock-outs, factory shutdowns
– 2007 Mattel recall• A sub-sub-contractor used lead-based paint from a non-
authorized third-party supplier
Impact of Uncertainty in Network Design
Manufacturer Distributor Retailer CustomerSupplier
Building flexibility into supply chain operations allows the supply chain to deal with uncertainty more
effectively
Risk Mitigation Strategies
Discounted Cash Flow Analysis
• Supply chain network design decisions should be evaluated as a sequence of cash flows over the duration that they will be in place
Year Option 1 Option 20 -1,000,000 -1,400,0001 300,000 400,0002 300,000 400,0003 300,000 400,0004 300,000 400,0005 300,000 400,000
500,000$ 600,000$
Discounted Cash Flow Analysis
• Supply chain network design decisions should be evaluated as a sequence of cash flows over the duration that they will be in place– Discounted cash flow (DCF) analysis
• Evaluates the net present value (NPV) of any stream of future cash flows
• Allows for comparing two or more cash flow streams in terms of their present financial value
Discounted Cash Flow Analysis
• The present value of future cash is found by using a rate of return k– A dollar today is worth more than a dollar tomorrow– A dollar today can be invested and earn a rate of return
k over the next period
Today… Tomorrow…$1 $1*(1 + k)
$1/(1 + k) $1
Today… Tomorrow…$1 $1*(1 + k)
Net Present Value
• Given a stream of cash flows C0, C1, …, CT over the next T periods and a rate of return k
Year Option 1 Option 20 -1,000,000 -1,400,0001 300,000 400,0002 300,000 400,0003 300,000 400,0004 300,000 400,0005 300,000 400,000
500,000$ 600,000$
Year Option 1 Option 20 -1000000/(1+0.1) 0̂ -1400000/(1+0.1) 0̂1 300000/(1+0.1) 1̂ 400000/(1+0.1) 1̂2 300000/(1+0.1) 2̂ 400000/(1+0.1) 2̂3 300000/(1+0.1) 3̂ 400000/(1+0.1) 3̂4 300000/(1+0.1) 4̂ 400000/(1+0.1) 4̂5 300000/(1+0.1) 5̂ 400000/(1+0.1) 5̂
Year Option 1 Option 20 -1000000 -14000001 272727 3636362 247934 3305793 225394 3005264 204904 2732055 186276 248369
137,236$ 116,315$
Net Present Value
• Given a stream of cash flows C0, C1, …, CT over the next T periods and a rate of return k
• The net present value (NPV) of this cash flow stream is given by
Year Option 10 -1000000/(1+0.1) 0̂1 300000/(1+0.1) 1̂2 300000/(1+0.1) 2̂3 300000/(1+0.1) 3̂4 300000/(1+0.1) 4̂5 300000/(1+0.1) 5̂
11 + k( )
t
t=1
T
NPV = C0 + ∑ Ct
Ct
(1 + k)t
t=0
T
NPV = ∑
If… Then… So…NPV > 0 Investment adds valueNPV < 0 Investment substracts valueNPV = 0 Investment would neither add
or substract value
Net Present Value
If… Then… So…NPV > 0 Investment adds value The project may be acceptedNPV < 0 Investment substracts value The project should be rejectedNPV = 0 Investment would neither add
or substract valueDecision should be based on other criteria
Example: Net Present Value
• Fulfillment by Amazon– Warehousing and other
logistics services– Amazon will pick, pack, and
ship your product to your customer
• Target.com – Estimated demand 100,000
units for online orders– Required space 1,000 sq. ft.
for every 1,000 units– Revenue $1.22 for each unit
of demand
Example: Net Present Value
• Target.com can choose between two options– Spot market rate expected at $1.20 per sq.ft. per year
for each of the next 3 years– 3 year lease contract at $1 per sq.ft.
Example: Net Present Value
• Expected annual profit if space is obtained from spot market using discount factor k = 0.1
Ct = (100,000 x $1.22) – (100,000 x $1.20) = $2,000
C1
(1 + k)1
C2
(1 + k)2
C1
(1 + k)0NPV = + +
= $ 5,471
2,000(1.1)1
2,0001.12
2,000(1.1)0= + +
Example: Net Present Value
• Expected annual profit if space is obtained by a 3 year lease using discount factor k = 0.1
Ct = (100,000 x $1.22) – (100,000 x $1.00) = $22,000
C1
(1 + k)1
C2
(1 + k)2
C1
(1 + k)0NPV = + +
= $ 60,182
22,000(1.1)1
22,0001.12
22,000(1.1)0= + +
Example: Net Present Value
• NPV(Spot) = $5,471 and NPV(Lease) = $60,182 – The NPV of signing the lease is $54,711 higher
But we ignored uncertainty. Uncertainty in demand and costs may change the outcome
Binomial Representation of Uncertainty
Pu3d2
Pu2d3
Pu4d
Pu5
Pud4
Pd5
Pu3d
Pu2d2
Pu4
Pud3
Pd4
Pu3
Pu2d
Pud2
Pd3
Pu2
Pud
Pd2
Pu
Pd
P
• Multiplicative binomial
p
1-p
p
1-p
p
1-p
p
1-p
p
1-p
Binomial Representation of Uncertainty
P+3u-2d
P+2u-3d
P+4u-d
P+5u
P+u-4d
P-5d
P+3u-d
P+2u-2d
P+4u
P+u-3d
P-4d
P+3u
P+2u–d
P+u-2d
P-3d
P+2u
P+u-d
P-2d
P+u
P-d
P
• Additive binomial
p
1-p
p
1-p
p
1-p
p
1-p
p
1-p
Decision Trees
P
Decision Trees
• A decision tree is a graphic device used to evaluate decisions under uncertainty
1. Identify the duration of each period and the number of time periods T to be evaluated
2. Identify the factors associated with the uncertainty
3. Identify the representation of uncertainty
4. Identify the periodic discount rate k
5. Represent the tree, identifying all states and transition probabilities
6. Starting at period T, work back to period 0 identify the expected cash flows at each step
Example: Decision Tree Analysis
• What product to make for the next three years using a discount factor k = 0.1?– Old product with certain demand ($90 profit/unit)– New product with uncertain demand ($85 profit/unit)
Example: Decision Tree Analysis
• Old product with certain demand ($90 profit/unit)– Annual demand is expected to be 100 units this year,
90 units next year, and 80 units in the following year– Cash flows for the three periods
• C0 = 100*90 = $9,000
• C1 = 90*90 = $8,100
• C2 = 80*90 = $7,200
– NPV(Old) • = 9,000/1.10 + 8,100 /1.11 + 7,200 /1.12
• = 9,000 + 7,364 + 5,950• = $ 22,314
Example: Decision Tree Analysis
• New product with uncertain demand ($85 profit/unit)– Annual demand expected to go up by 20% with
probability 0.6– Annual demand expected to go down by 20% with
probability 0.4
Example: Decision Tree Analysis
1. Identify the duration of each period and the number of time periods T to be evaluated• Duration of each period is 1 year, T = 3
2. Identify the factors associated with the uncertainty• Demand D
3. Identify the representation of uncertainty• D may go up by 20% with probability 0.6• D may go down by 20% with probability 0.4
4. Identify the periodic discount rate k• k = 0.1
Example
5. Represent the tree, identifying all states as well as all transition probabilities
D=144
D=96
D=64
D=120
D=80
D=100
0.6
0.4
Period 0
Period 2
0.6
0.4
0.6
0.4
Period 1 P = 12240
P = 8160
P = 5440P = 80*85+(0.6*8160+0.4*5440)/1.1 = 13229
P = 120*85+(0.6*12240+0.4*8160)/1.1 = 19844
P = 100*85+(0.6*19844+0.4*13229)/1.1 = 24135
Example: Decision Tree Analysis
• Three options for Trips Logistics1. Get all warehousing space from the spot market as
needed
2. Sign a three-year lease for a fixed amount of warehouse space and get additional requirements from the spot market
3. Sign a flexible lease with a minimum change that allows variable usage of warehouse space up to a limit with additional requirement from the spot market