1

1

Chapter 5Chapter 5

Network Design Network Design in the Supply Chainin the Supply Chain

2

OutlineOutline

1. Decisions in network design2. A strategic framework for logistics network decisions3. Factors influencing network design4. Network design tools – major components5. Solution techniques for network design

1) Optimizing facility location models2) Heuristic approaches3) Simulation technique

3

1. The Decisions in Network Design:1. The Decisions in Network Design:

A Logistics Network consists of:

Facilities (- at the nodes)

Vendors, Manufacturing Centers, Warehouse/ Distribution Centers, and Customers

Flows (- along the arcs)Raw materials, parts and finished products, etc. that flow between the facilities

Decisions: Where? Decisions: Where? Who?Who? What? What?

Decisions in Network Design:Facility roleNumber of facilitiesLocation of facilities Product allocation of facilitiesCapacity allocation of

facilitiesMarket and supply allocation… 4

Network Design Network Design –– Key issuesKey issuesNetwork setting:

Decide the optimal number, location, and size of warehouses and/or plants

Network operation:Determine optimal sourcing strategy

Which plant/vendor should produce which product

Determine best distribution channels

Which warehouses should service which customers…

Supply

Sources:plantsvendorsports

RegionalWarehouses:stocking points

Field Warehouses:stockingpoints

Customers,demandcenterssinks

Production/purchase costs

Inventory &warehousing costs

Transportation costs Inventory &

warehousing costs

Transportation costs

The objectiveThe objective :– to balance service level against total cost

(production, purchasing, inventory, facilities, transportation, handling and processing, etc.)

- to find a minimal-cost configuration of the distribution network that satisfies product demands at specific customer service levels

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5

2. Factors Influencing Network Design Decisions2. Factors Influencing Network Design Decisions

Strategic TechnologicalMacroeconomicPoliticalInfrastructureCompetitionLogistics and facility costs…

Total Costs

Percent Service Level Within

Promised Time

Transportation

Cos

t of O

pera

tions

Number of Facilities

InventoryFacilities

Labor

6

3. A framework for network design3. A framework for network design

PHASE ISupply Chain

Strategy

PHASE IIRegional Facility

Configuration

PHASE IIIDesirable Sites

PHASE IVLocation Choices

Competitive STRATEGY

INTERNAL CONSTRAINTSCapital, growth strategy,existing network

PRODUCTION TECHNOLOGIESCost, Scale/Scope impact, supportrequired, flexibility

COMPETITIVEENVIRONMENT

PRODUCTION METHODSSkill needs, response time

FACTOR COSTSLabor, materials, site specific

GLOBAL COMPETITION

TARIFFS AND TAXINCENTIVES

REGIONAL DEMANDSize, growth, homogeneity,local specifications

POLITICAL, EXCHANGERATE AND DEMAND RISK

AVAILABLEINFRASTRUCTURE

LOGISTICS COSTSTransport, inventory, coordination

7

Decision Classification:Decision Classification:

Strategic Planning -- Decisions that typically involve major capital investments and have a long term effect1. Determination of the number, location and size of new plants, distribution centers and warehouses2. Acquisition of new production equipment and the design of working centers within each plant3. Design of transportation facilities, communications equipment, data processing means, etc.Tactical Planning -- Effective allocation of manufacturing and distribution resourcesover a period of several months1. Work-force size2. Inventory policies3. Definition of the distribution channels4. Selection of transportation and trans-shipment alternatives…Operational Control -- Includes day-to-day operational decisions1. The assignment of customer orders to individual machines2. Dispatching, expediting and processing orders3. Vehicle scheduling…

8

Complexity of Network Design ProblemsComplexity of Network Design Problems

Location problems are, in general, very difficult problems (-- NP hard!!!)

The complexity increases with

the number and type of customers, the number and type of products, the number of potential locations for warehouses, and the number of warehouses located….

Multi-criteria, uncertainty ..

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4. Network Design Tools 4. Network Design Tools ---- Major ComponentsMajor Components

MappingMapping allows you to visualize your supply chain and solutionsMapping the solutions allows you to better understand different scenariosColor coding, sizing, and utilization indicators allow for further analysis

Data analysisData specifies the costs of your supply chainThe baseline cost data should match your accounting dataThe output data allows you to quantify changes to the supply chainAggregation is essential

EngineSolution Techniques

10

Mapping Allows You to Mapping Allows You to Visualize Your Supply ChainVisualize Your Supply Chain

Displaying the Solutions Allows you To Compare Scenarios

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Data for Network DesignData for Network Design

1. A listing of all products2. Location of customers, stocking points and sources3. Demand for each product by customer location4. Transportation rates5. Warehousing costs6. Shipment sizes by product7. Order patterns by frequency, size, season, content8. Order processing costs9. Customer service goals ..

Customers and Geocoding -- Too Much Information !!!!!!Sales data is typically collected on a by-customer basisNetwork planning is facilitated if sales data is in a geographic database rather than accounting database1. Distances2. Transportation costsNew technology exists for Geocoding the data based on Geographic Information System (GIS)

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Aggregating CustomersAggregating Customers

Customers located in close proximity are aggregated using a grid network or clustering techniques. All customers within a single cell or a single cluster are replaced by a single customer located at the centroid of the cell or cluster.We refer to a cell or a cluster as a customer zone.

Impact of Aggregation CustomersThe customer zone balances1. Loss of accuracy due to over aggregation2. Needless complexityWhat effects the efficiency of the aggregation? 1. The number of aggregated points, that is the number of different zones2. The distribution of customers in each zone.

Why Aggregation:The cost of obtaining and processing dataThe form in which data is availableThe size of the resulting location modelThe accuracy of forecast demand

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13

Testing Customer AggregationTesting Customer Aggregation

1 Plant; 1 ProductConsidering transportation costs onlyCustomer data

Original Data had 18,000 5-digit zip code ship-to locationsAggregated Data had 800 3-digit ship-to locationsTotal demand was the same in both cases

Comparing Output Comparing Output -- Cost Difference < 0.05% !!!

Total Cost:$5,796,000Total Customers: 18,000

Total Cost:$5,793,000Total Customers: 800 14

Product Aggregation:Product Aggregation:

Companies may have hundreds to thousands of individual items in their production line1. Variations in product models and style2. Same products are packaged in many sizesCollecting all data and analyzing it is impractical for so many product groups

Strategies for product aggregation:Place all SKU’s into a source-group

A source group is a group of SKU’s all sourced from the same place(s)

Within each of the source-groups, aggregate the SKU’s by similar logistics characteristics

WeightVolumeHolding Cost…

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

0.000 0.010 0.020 0.030 0.040 0.050 0.060 0.070 0.080 0.090 0.100

Volume (pallets per case)

Wei

ght (

lbs

per

case

)

Rectangles illustrate how to cluster SKU’s.

Within Each Source Group, Aggregate Within Each Source Group, Aggregate Products by Similar CharacteristicsProducts by Similar Characteristics

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Test Case for Product AggregationTest Case for Product Aggregation

5 Plants25 Potential Warehouse LocationsDistance-based Service ConstraintsInventory Holding CostsFixed Warehouse CostsProduct Aggregation

46 Original products4 Aggregated productsAggregated products were created using weighted averages

Aggregation Test:Aggregation Test:Product AggregationProduct Aggregation

-- Cost Difference < 0.03% !!!

Total Cost:$104,564,000Total Products: 46

Total Cost:$104,599,000Total Products: 4 16

5. Solution Techniques for Network Design5. Solution Techniques for Network Design

1) Mathematical optimization techniques:

Exact algorithms: find optimal solutions

2) Heuristics methods:

find “good” solutions, not necessarily optimal

3) Simulation models: provide a mechanism to evaluate specified design alternatives created by the designer

Hybrid approaches are often effective!!

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55--1) Network Optimization Models1) Network Optimization Models

Allocating demand to production facilitiesLocating facilities and allocating capacity

Which plants to establish? How to configure the network?

Key Costs:

• Fixed facility cost• Transportation cost• Production cost• Inventory cost• Coordination cost• …

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Model (a): Model (a): Demand Allocation ModelDemand Allocation Model

Which market is served by which plant?Which supply sources are used by a plant?

xij = Quantity shipped from plant site i to customer j 0

..

1

1

1 1

≥

≤∑

=∑

∑ ∑

=

=

= =

x

Kx

Dx

ts

xcMin

ij

im

jij

jn

iij

n

i

m

jijij

Supply

Ki

Demand

Dj

xij

cij

A typical network design problem:• Several products are produced at

several plants.• Each plant has a known production

capacity.• There is a known demand for each

product at each customer zone.• The demand is satisfied by shipping the

products via regional distribution centers.• There may be an upper bound on total

throughput at each distribution center.

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Case 1: Demand Allocation at Case 1: Demand Allocation at ApplichemApplichem

ToFrom

Mexico Canada Venezuela Frankfurt Gary Sunchem Capacity

Mexico $ 81 $ 92 $ 136 $ 101 $ 96 $ 101 220 Canada $ 147 $ 78 $ 135 $ 98 $ 88 $ 97 37

Venezuela $ 172 $ 106 $ 96 $ 120 $ 111 $ 117 45 Frankfurt $ 115 $ 71 $ 110 $ 59 $ 74 $ 77 470

Gary $ 143 $ 77 $ 134 $ 91 $ 71 $ 90 185 Sunchem $ 222 $ 129 $ 205 $ 145 $ 136 $ 116 50 Demand 30 26 160 200 264 119

Applichem

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1981 Network (Optimal)1981 Network (Optimal)

Annual Cost = $79,598,500

MexicoCanada

VenezuelaFrankfurt

Gary

Sunchem

MexicoCanada

Latin America

EuropeU.S.A

Japan

Mexico

Canada

Venezuela

Frankfurt

Gary

SunchemCLOSED

Mexico

Canada

Latin America

Europe

U.S.A

Japan

Annual Cost = $82,246,800

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Cash Flows From Cash Flows From SunchemSunchem PlantPlant

Year 1977 1978 1979 1980 1981 1982

Optimal ($ Million)

60.562 68.889 75.999 79.887 79.598 72.916

Sunchem Closed

60.721 68.889 77.503 80.999 82.247 72.916

Difference 0.159 0.000 1.504 1.112 2.649 0.000

M e x i c o $ 0

C a n a d a $ 8 ,3 0 0

V e n e z u e l a $ 3 6 ,9 0 0

F r a n k f u r t $ 2 2 ,3 0 0

G a r y $ 2 5 ,2 0 0

S u n c h e m $ 0

Value of Adding 0.1 Million Pounds Capacity (1982)Value of Adding 0.1 Million Pounds Capacity (1982)

Should be evaluated as an option and priced accordingly.

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Model (b) Model (b) -- Plant Location & demand allocation Plant Location & demand allocation

with Multiple Sourcingwith Multiple Sourcing

yi = 1, if plant is located at site i, 0, otherwise

xij = Quantity shipped from plant site i to customer jfi – fixed cost for locating plant at site Ik – # of plants to be built/used }1,0{0

;

..

,1

1

1

1 11

∈≥

≤

≤

=

+

∑

∑

∑

∑ ∑∑

=

=

=

= ==

yx

y

yKx

Dx

xcyf

ij

k

ts

Min

i

m

ii

ii

n

jij

j

n

iij

n

i

m

jijiji

n

ii

PotentialSupplylocation

Ki

fi

Demand

Dj

xij

cijyi

A typical location problem:• There may be an upper bound on the

distance between a distribution center and a market area served by it

• A set of potential location sites for the new facilities was identified

• Costs:• Set-up costs• Transportation cost is proportional to the distance• Storage and handling costs• Production/supply costs

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Model (c) Model (c) -- Plant Location and demand allocation with single SourcingPlant Location and demand allocation with single Sourcing

yi = 1 if plant is located at site i, 0 otherwisexij = 1 if market j is supplied

from plant site i, 0 otherwiseFi – fixed cost of locating plant at

site i

}1,0{,

;

1

..

1

1

1

1 11

∈

≤

≤

=

+

∑

∑

∑

∑∑∑

=

=

=

= ==

yixij

ky

yiKiD

ts

xcDyifMin

n

ii

j

n

jij

n

iij

ijij

n

i

m

jj

n

ii

x

xPotentialSupplylocation

Ki

fi

Demand

Dj

xij

cijyi24

Model (d) Model (d) –– Simultaneous plant and warehouse locationSimultaneous plant and warehouse location

Which plants to establish? Which warehouses to establish?How to configure the network?

Potential Plants location Warehouses

12

Markets

n m

1

t

1

l

Ki

Shwe

Dj

chicie cej

Fi feXhi Xie Xejyi ye

Suppliers

7

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Multiple levels facility location Multiple levels facility location –– Transshipment modelTransshipment model

{ }1,0,

)(

)(

)(0

)(

)(0

)(

.

min

1

1

11

1

11

1

1 11 11 111

∈

=

≤

≥−

≤

≥−

≤

++++

∑

∑

∑∑

∑

∑∑

∑

∑ ∑∑ ∑∑ ∑∑∑

=

=

==

=

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=

= == == ===

ei

j

t

eie

ee

m

jej

m

jej

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iie

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hhi

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eei

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yy

jallforDx

eallforywx

eallforxx

iallforyKx

iallforxx

hallforsx

st

xcxcxcyfyf

-- Node balancing

-- Node balancing

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Model (e) Model (e) -- Gravity Methods for LocationGravity Methods for Location

Mile-Center Solutionx,y: Warehouse Coordinatesxn, yn : Coordinates of delivery location ndn : Distance to delivery location n

n n n

iii

n

ii

n

iii

n

ii

n

d x x y y

x

xd

d

y

yd

d

= − + −

=∑

∑

=∑

∑

=

=

=

=

2 2

1

1

1

1

1

1

( ) ( )

Min ∑ −+− )()( 22 yyxx ii

Focus on distance!!

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Gravity Location ModelGravity Location Model

Ton-Center Solutionx,y: Warehouse Coordinatesxn, yn : Coordinates of delivery location nDn : Annual tonnage to delivery location n

∑

∑

∑

∑

=

=

=

=

=

=

n

ii

n

iii

n

ii

n

iii

D

Dy

D

Dx

y

x

1

1

1

1

Min ∑ −− + )()(22 yyxxD iii

-- Focus on tonnage!!

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Gravity Location ModelGravity Location Model

Ton Mile-Center Solutionx,y: Warehouse Coordinatesxn, yn : Coordinates of

delivery location ndn : Distance to delivery

location nDn : Annual tonnage to

delivery location nFn : Cost of shipping one unit to

location n

∑

∑

=

∑

∑

=

−+−=

=

=

=

=

n

i ii

n

i

i

i

ii

n

i ii

n

i

i

iii

n

dF

dF

Fy

y

dF

dF

Fx

x

yyxxd nn

1

1

1

1

22 )()(

Min ∑ −+− )()( 22 yyxxDF iiiiExcel File

-- Look at both distance and tonnage!!

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55--2) Heuristics Methods2) Heuristics Methods

Example:Single productTwo plants p1 and p2Plant p2 has an annual capacity of 60,000 units.The two plants have the same production costs.There are two warehouses w1 and w2 with identical warehouse handling costs.There are three markets areas c1,c2 and c3 with demands of 50,000, 100,000 and 50,000, respectively.

Table 1 Distribution costs per unit

Facility Warehouse

P1

P2

C1

C2

C3

W1

W2

0

5

4

2

3

2

4 1

5 2

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The IP model: min 0X(p1,w1) + 5X(p1,w2) + 4X(p2,w1) + 2X(p2,w2) + 3X(w1,c1) + 4X(w1,c2)

+ 5X(w1,c3) + 2X(w2,c1) + 2X(w2,c3)subject to the following constraints:

X(p2,w1) + X(p2,w2) ≤ 60000X(p1,w1) + X(p2,w1) = X(w1,c1) + X(w1,c2) + X(w1,c3)X(p1,w2) + X(p2,w2) = X(w2,c1) +X(w2,c2) + X(w2,c3)X(w1,c1) +X(w2,c1) = 50000X(w1,c2) + X(w2,c2) = 100000X(w1,c3) +X(w2,c3) = 50000all flows greater than or equal to zero.

T a b le 2D istr ib u tio n s tr a teg y

F a c ili tyW a reh o u s e

P 1 P 2 C 1 C 2 C 3

W 1W 2

1 4 0 0 0 00

06 0 0 0 0

5 0 0 0 00

4 0 0 0 06 0 0 0 0

5 0 0 0 00

T he to ta l co st fo r th e o p tim a l stra te gy is 7 4 0 ,0 0 0 .

The Optimal StrategyThe Optimal Strategy

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Heuristic 1: For each market we choose the cheapest warehouse to source demand. Thus, c1, c2 and c3 would be supplied by w2.Now for every warehouse choose the cheapest plant, i.e., get 60,000 units from p2 and the remaining 140,000 from p1. The total cost is:

2×50000 + 1×100000 + 2*50000+ 2×60000 + 5×140000 = 1,120,000.

The Heuristics Approach

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Heuristic 2:For each market area, choose the warehouse such that the total costs to get delivery from the warehouse is the cheapest, that is, consider the source and the distribution.Thus, for market area c1, consider the paths p1→w1→c1, p1→w2→c1, p2→ w1→c1, p2→w2→c1. Of these the cheapest is p1→w1→c1 and so choose w1 for c1.Similarly, choose w2 for c2 and w2 for c3.

The total cost for this strategy is 920,000.

The Heuristics Approach

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Why Optimization Matters?Why Optimization Matters?

D = 50,000

D = 100,000

D = 50,000Cap = 60,000

Cap = 200,000

$4

$5

$2

$3

$4

$5

$2

$1

$2

Production costs are the same, warehousing costs are the same

$0

Example:

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Traditional Approach #1:Traditional Approach #1:Assign each market to closet WH. Then assign each plant based oAssign each market to closet WH. Then assign each plant based on cost.n cost.

D = 50,000

D = 100,000

D = 50,000Cap = 60,000

Cap = 200,000

$5 x 140,000

$2 x 60,000

$2 x 50,000

$1 x 100,000

$2 x 50,000

Total Costs = $1,120,000

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Traditional Approach #2:Traditional Approach #2:Assign each market based on total landed costAssign each market based on total landed cost

D = 50,000

D = 100,000

D = 50,000Cap = 60,000

Cap = 200,000

$4

$5

$2

$3

$4

$5

$2

$1

$2

$0

P1 to WH1 $3P1 to WH2 $7P2 to WH1 $7P2 to WH 2 $4

P1 to WH1 $4P1 to WH2 $6P2 to WH1 $8P2 to WH 2 $3

P1 to WH1 $5P1 to WH2 $7P2 to WH1 $9P2 to WH 2 $4

Market #1 is served by WH1, Markets 2 and 3are served by WH2

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Traditional Approach #2:Traditional Approach #2:Assign each market based on total landed costAssign each market based on total landed cost

D = 50,000

D = 100,000

D = 50,000Cap = 60,000

Cap = 200,000

$5 x 90,000

$2 x 60,000

$3 x 50,000

$1 x 100,000

$2 x 50,000

$0 x 50,000

P1 to WH1 $3P1 to WH2 $7P2 to WH1 $7P2 to WH 2 $4

P1 to WH1 $4P1 to WH2 $6P2 to WH1 $8P2 to WH 2 $3

P1 to WH1 $5P1 to WH2 $7P2 to WH1 $9P2 to WH 2 $4

Total Cost = $920,000

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55--3) Simulation Models3) Simulation Models

Optimization techniques deal with static models:

1. Deal with averages.

2. Does not take into account changes over time

Simulation takes into account the dynamics of the system

Simulation models allow for a micro-level analysis:1. Individual ordering pattern analysis

2. Transportation rates structure

3. Specific inventory policies

4. Inter-warehouse movement of inventory

5. Unlimited number of products, plants, warehouses and customers

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Optimization Techniques vs. SimulationOptimization Techniques vs. Simulation

The main disadvantage of a simulation model is that it fails to support warehouse location decisions; only a limited number of alternatives are considered

The nature of location decisions is that they are taken when only limited information is available on customers, demands, inventory policies, etc, thus preventing the use of micro level analysis.

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Recommended approachRecommended approach

Use an optimization model first to solve the problem at the macro level, taking into account the most important cost components

1. Aggregate customers located in close proximity2. Estimate total distance traveled by radial distance to the

market area3. Estimate inventory costs using the EOQ model

Use a simulation model to evaluate optimal solutions generated in the first phase.

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Case 2: Case 2: Evaluating Facility InvestmentsEvaluating Facility Investments under Uncertainty under Uncertainty ---- AM TiresAM Tires

Dedicated Plant Flexible Plant Plant Fixed Cost Variable Cost Fixed Cost Variable Cost

US 100,000 $1 million/yr. $15 / tire $1.1 million / year

$15 / tire

Mexico 50,000 4 million pesos / year

110 pesos / tire

4.4 million pesos / year

110 pesos / tire

U.S. Demand = 100,000; Mexico demand = 50,0001US$ = 9 pesos

Demand goes up or down by 20 percent with probability 0.5 andexchange rate goes up or down by 25 per cent with probability 0.5.

11

41

RU=100RM=50

E=9

Period 0 Period 1 Period 2

RU=120RM = 60E=11.25

RU=120RM = 60E=6.75

RU=120RM = 40E=11.25

RU=120RM = 40E=6.75

RU=80RM = 60E=11.25

RU=80RM = 60E=6.75

RU=80RM = 40E=11.25

RU=80RM = 40E=6.75

RU=144RM = 72E=14.06

RU=144RM = 72E=8.44

RU=144RM = 48E=14.06

RU=144RM = 48E=8.44

RU=96RM = 72E=14.06

RU=96RM = 72E=8.44

RU=96RM = 48E=14.06

RU=96RM = 48E=8.44

AM TiresAM Tires

-- scenarios with uncertain demand and exchange rate

42

AM TiresAM Tires

Four possible capacity scenarios:• Both dedicated• Both flexible• U.S. flexible, Mexico dedicated• U.S. dedicated, Mexico flexible

For each scenario solve the demand allocation model.

Plants Markets

U.S.

Mexico

U.S.

Mexico

43

AM Tires: AM Tires: Demand Allocation for RU = 144; RM = 72, E = 14.06Demand Allocation for RU = 144; RM = 72, E = 14.06

Source Destination Variable cost

Shipping cost

E Sale price Margin ($)

U.S. U.S. $15 0 14.06 $30 $15 U.S. Mexico $15 $1 14.06 240 pesos $1.1

Mexico U.S. 110 pesos $1 14.06 $30 $21.2 Mexico Mexico 110 pesos 0 14.06 240 pesos $9.2

Plants Markets

U.S.

Mexico

U.S.

Mexico

100,000

44,000

6,000

Profit =$649,360

P la n t C o nfigu ra t io n U n ited S ta tes M ex ico

N P V

D ed ic a ted D ed ic a ted $ 1 ,6 2 9 ,3 1 9 F lex ib le D ed ic a ted $ 1 ,5 1 4 ,3 2 2

D ed ic a ted F lex ib le $ 1 ,7 2 2 ,4 4 7 F lex ib le F lex ib le $ 1 ,5 2 9 ,7 5 8

FacilityDecision:

44

Case 3: Case 3: BuyPC.comBuyPC.comDeveloped by

Jim Morton; UPS Professional ServicesDavid Simchi-Levi; MIT

Michael Watson; LogicTools, Inc.

BuyPC.com is a fictitious company that sells computers via the InternetBuyPC.com stresses next day delivery of its computers

BuyPC.com has opted to provide this service with many distribution points, and this results in a significant inventoryinvestment

BuyPC.com ships via UPS, so customers outside the 1-day ground zone must be shipped via air.The warehouses are replenished from factories in Asia

The product arrives to the U.S. via Los Angeles

12

45

Chicago WHChicago WH

AtlantaAtlanta

MilwaukeeMilwaukee1- Day

2-Days

(Use UPS Ground Service)

(Use UPS Next Day Air Service)

Integrating TimeIntegrating Time--inin--Transit DataTransit Data

Decide the service level required for each laneSet outbound rates in model accordingly

46

BuyPC.comBuyPC.com Case Study:Case Study:Current NetworkCurrent Network

Inbound: $ 851,000Outbound: $ 2,930,000Inv Cost: $13,291,000WH Fixed: $ 1,875,000

Total: $18,947,000

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BuyPC.comBuyPC.com Case Study:Case Study:Cost TradeCost Trade--OffOff

Cost Trade-Off for BuyPC.com

$0$2$4$6$8

$10$12$14$16$18$20

0 5 10 15

Number of DC's

Cos

t ($

mill

ion)

Total CostInventoryTransportationFixed Cost

48

Inventory Reduction and WarehousesInventory Reduction and Warehouses

BuyPC.com faced heavy variability in consumer demandEach DC had to carry sufficient safety stockWarehouse to warehouse transfers were discouraged because of the extra liability in shipping computers

Studies within BuyPC.com indicated that reducing the warehouses would reduce the inventory

The Risk Pooling Effect

13

49

BuyPC.comBuyPC.com Case Study:Case Study:Optimal NetworkOptimal Network

Inbound: $ 83,000Outbound: $ 5,900,000Inv Cost: $ 7,679,000WH Fixed: $ 625,000

Total: $14,987,000

$4 Million Savings

Solution result:Warehouses picked and sizes

Harrisburg 26,000 sq. feetAtlanta 15,000Chicago 18,000Dallas 13,000LA 23,000 50

BuyPC.comBuyPC.com Case StudyCase StudyNetwork Design Conclusion and Next StepsNetwork Design Conclusion and Next Steps

By reducing the number of warehouses, BuyPC.com could reduce their overall logistics network costs

The reduction in inventory costs more than outweighed the increase in next-day air shipments

But, the strategic network did not consider the impact of seasonality

Would they have enough space?When would they have to start building inventory to meet demand?Where would the product be stored?Would the territories change during peak season?

51

Demand and Production Capacity

010000

20000300004000050000

6000070000

Jan

Feb

Mar Apr

May Ju

n

Jul

Aug

Sep Oct

Nov

Dec

Month

Uni

ts DemandProduction Capacity

BuyPC.comBuyPC.com Demand and Demand and Production CapacityProduction Capacity

BuyPC.com needed to start building inventory in advance of the Christmas season

52

What is Tactical Planning?What is Tactical Planning?

A tactical plan allows you to develop optimal plan across the supply chainthat minimizes transportation costs, inventory costs, and production costs.

CapacityLimits

Plants DC’s Customers and Demand

Prod: A23

Prod: A55Prod: A1

LT = 4 wks

14

53

Coordinating Limited ResourcesCoordinating Limited Resources

Low CostLimited Capacity

High Cost

How do I best usemy low cost producers?

Which productionline do I use for

a product?

Sea, LT = 5 weeks

Air, LT = 4 days

When do we ship air or sea, to minimize in-transit inventory and avoid capacity

problems?

How do I buildfor the seasonal

spike and stillmeet shelf liferestrictions?

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Benefits of Tactical Planning SoftwareBenefits of Tactical Planning Software

Apply forecasts to the supply chainTake your company’s forecast and relate it directly to the supply chain

Create better supply chain plansCreate plans that are optimal across the entire supply chainAnalyze different inventory and production strategies

Avoid supply chain bottlenecksAnticipate problems months in advance and take action now to alleviate the issue

Improved coordination within your supply chainShare the output and collaborate with all your supply chain partners to ensure a successful execution of the plan

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WhatWhat--Ifs with Tactical Planning SoftwareIfs with Tactical Planning Software

When and where will we run out of capacityWhich plant or warehouse? In which month?

What do we do if we run out of capacity?Should we add capacity? Should we re-align territories?

What are the benefits of smoothing out the quarterly demand spikes?How do we meet seasonal demand?

Should we build inventory? When to start and where to store?Should we run overtime during the peak months to meet demand?

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Tactical Planning InterfaceTactical Planning Interface

Scenario Manager

DisplayMenu

Map showingshowing yoursolution lanesand capacityindicators forSeptember

15

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Input DataInput Data

Time PeriodsCustomers Information

Where you are shipping to and demand by time period

Plant / Vendor InformationCapacity by time period

Distribution CentersCosts and capacities by time period

ProductsTransportation Costs

The cost to move product from origin to destination

Minimum overall total costManufacturing costsWarehouse costs (fixed, processing, and inventory)Transportation costs

Optimal plan for inventorywhen to produce, where to store, and when to ship

Appropriate allocation of products to different warehouses

By time periodOptimal production quantity at each manufacturing plant

By time periodEfficient supply channels in the logistics network

Output DataOutput Data

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BuyPC.comBuyPC.com Tactical AnalysisTactical Analysis

BuyPC.com wanted to minimize the amount of floor space to keep overhead low, yet have enough to handle peak demand

BuyPC.com wanted to know if their order fulfillment system would have to allow dynamic changing of territories

The factories in Asia were capacity constrained, so product would have to be brought in early for the peak season

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BuyPC.comBuyPC.com Tactical Results:Tactical Results:Using the size of warehouses calculated by the strategic model, Using the size of warehouses calculated by the strategic model, BuyPCBuyPC can only meet 78% of can only meet 78% of

DecemberDecember’’s demands demand

Warehouse Average Inventory Utilization (Volume)

0

20

40

60

80

100

120

Jan

Feb Mar AprMay Ju

n Jul

Aug Sep OctNov Dec

Time Period

% U

tiliz

atio

n Atlanta, GAChicago, ILDallas, TXHarrisburg, PALos Angeles, CA

In Nov and Dec all warehouses are at capacity and cannot process any more product

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BuyPC.comBuyPC.com Tactical Results:Tactical Results:Determining warehouse sizes needed to meet seasonal demandDetermining warehouse sizes needed to meet seasonal demand

PA 26,000 --> 46,000GA 15,000 --> 28,000IL 18,000 --> 24,000TX 13,000 --> 17,000CA 23,000 --> 31,000

Increased system sq. feet by over 50%.

But, all demand is satisfied.

16

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BuyPC.comBuyPC.com Tactical Results:Tactical Results:Warehouse capacity utilization using larger facilitiesWarehouse capacity utilization using larger facilities

Warehouse Average Inventory Utilization (Volume)

0

20

40

60

80

100

120

Jan

Feb Mar AprMay Ju

n Jul

Aug Sep OctNov Dec

Time Period

% U

tiliz

atio

n Atlanta, GAChicago, ILDallas, TXHarrisburg, PALos Angeles, CA

With more warehouse space, there is less of a constraint on overall capacity, although several facilities are quite close to the limit.

However, space utilization is very poor for the first half of the year.

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BuyPC.comBuyPC.com Tactical Results:Tactical Results:Using temporary leased spaceUsing temporary leased space

Alternatively, BuyPC.com could lease space from Oct - Dec in LA (23,000 additional) and PA (26,000).

During December, LA would have to ship outside its optimal territory. The order fulfillment system would have to dynamically assign orders to DC’s

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BuyPC.comBuyPC.com Tactical Results:Tactical Results:Using temporary leased space and additional capacityUsing temporary leased space and additional capacity

Or, BuyPC.com could lease less space from Oct - Dec in LA (15,000 additional) and PA (20,000) and add an addition 25% of production capacity for Sep to Dec.

This would also result in less of a seasonal inventory build-up.

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BuyPC.comBuyPC.com ConclusionsConclusions

With the average warehouse sizes suggested by the strategic model, BuyPC.com could only meet 78% of December demandTo alleviate this, BuyPC.com had several options

Build larger warehouses at all locationsLease temporary space in LA and PA for the peak seasonLease temporary space in LA and PA and increase production

BuyPC.com determined that the most economical choice was to lease temporary space, but not increase production