Logistics Network Configuration

Designing & Managing the Supply Chain

Chapter 2

Byung-Hyun Ha

bhha@pusan.ac.kr

Outline Case: Bis Corporation What is logistics network configuration? Methodology

Modeling Data Aggregation Validation

Solution Techniques

Case: the Bis Corporation

Background Produce & distribute soft drinks 2 manufacturing plant 120,000 account (retailers and stores), all over the US 3 existing warehouse (Chicago, Dallas, Sacramento) 20% gross margin $1,000 for each SKU (stock-keeping unit) for all products

Current distribution strategy (designed 15 years ago) Produce and store at the manufacturing plant Pick, load, and ship to a warehouse/distribution center Unload and store at the warehouse Pick, load, and deliver to store

Case: the Bis Corporation

You, consulting company Proposal as reengineering the sales and distribution functions First phase, identifying 10,000 direct delivery account, based on

• Dock receiving capabilities• Storage capability• Receiving methodologies• Merchandising requirements• Order-generation capabilities• Delivery time window constraints• Current pricing• Promotional activity patterns

Case: the Bis Corporation

Redesign distribution network Grouped accounts into 250 zones, products into 5 families Data collected

• Demand in 1997 by SKU per product family for each zone• Annual production capacity at each manufacturing plant• Maximum capacity for each warehouse, new and existing• Transportation costs per product family per mile for distributing• Setup cost for establishing a warehouse

Customer service level requirement No more than 48 hours in delivery

Additionally, Estimated yearly growth, variable production cost, cost for

increasing production capacity, …

Case: the Bis Corporation

Issues How can the Bis Corporation validate the model? Impact of aggregating customers and products Number of established distribution centers and their locations Allocation of plant’s output between warehouses When and where should production capacity be expanded?

The Logistics Network The Logistics Network consists of:

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

Raw materials and finished products that flow between the facilities

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 Logistics Network Strategic Planning: Decisions that typically involve

major capital investments and have a long term effect Determination of the number, location and size of new plants,

distribution centers and warehouses Acquisition of new production equipment and the design of

working centers within each plant Design of transportation facilities, communications equipment,

data processing means, etc.

Network Design Key Issues

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

Determine optimal sourcing strategy• Which plant/vendor should produce which product

Determine best distribution channels Which warehouses should service which customers

The objective is to balance service level against Production/ purchasing costs Inventory carrying costs Facility costs (handling and fixed costs) Transportation costs

Network Design Tradeoffs

$-

$10

$20

$30

$40

$50

$60

$70

$80

$90

0 2 4 6 8 10

Number of Warehouses

Cos

t (m

illio

ns $

)

Total CostTransportation CostFixed CostInventory Cost

Network Design DSS: Major Components Mapping

Mapping allows you to visualize your supply chain and solutions Mapping the solutions allows you to better understand different

scenarios Color coding, sizing, and utilization indicators allow for further

analysis

Data Data specifies the costs of your supply chain The baseline cost data should match your accounting data The output data allows you to quantify changes to the supply

chain

Engine Optimization Techniques

Visualize Your Supply Chain

Compare Scenarios

Data Collection Data for Network Design

A listing of all products Location of customers, stocking points and sources Demand for each product by customer location Transportation rates Warehousing costs Shipment sizes by product Order patterns by frequency, size, season, content Order processing costs Customer service goals

Customers and Geocoding sales data in a geographic DB rather than accounting DB Geographic Information System (GIS)

Data Aggregation Optimization model for the problem?

Typical soft drink distribution system: 10,000~20,000 accounts Wal-Mart or JC Penney: hundreds of thousands! Too much

Customer Aggregation Aggregating customers located in close proximity

• Using a grid network or clustering techniques All customers within a single zone

• Replaced by a single customer located at the centroid of the zone Aggregation by classes

• Service levels/frequency of delivery/…

Data Aggregation: Customer The customer zone balances

Accuracy loss due to over aggregation needless complexity

Why aggregation? The cost of obtaining and processing data The form in which data is available The size of the resulting location model The accuracy of forecast demand

Recommended Approach Use at least 300 aggregated points Make sure each zone has an equal amount of total demand Place the aggregated point at the center of the zone In this case, the error is typically no more than 1%

Testing Customer Aggregation Experimental results: cost difference < 0.05%

Considering transportation costs only Customer data

• Original Data had 18,000 5-digit zip code ship-to locations• Aggregated Data had 800 3-digit ship-to locations• Total demand was the same in both cases

Total Cost:$5,796,000 Total Customers: 18,000 Total Cost:$5,793,000 Total Customers: 800

Data Aggregation: Product Product aggregation

Hundreds to thousands of individual items in production line• Variations in product models and style• Same products are packaged in many sizes

Collecting all data and analyzing it is impractical

Aggregation by distribution pattern Place all SKU’s into a source-group

• A source group is a group of SKU’s all sourced from the same place Aggregate the SKU’s by similar logistics characteristics

• Weight• Volume• Holding Cost

Aggregation by product type

Data Aggregation: Product Aggregation by distribution pattern

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 c

ase)

Test Case for Product Aggregation Setting

5 Plants 25 Potential Warehouse Locations Distance-based Service Constraints Inventory Holding Costs Fixed Warehouse Costs Product Aggregation

• 46 Original products• 4 Aggregated products• Aggregated products were created using weighted averages

Test Case for Product Aggregation Results: cost difference < 0.05%

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

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

Impact of Aggregation on Variability Measure of variability?

Average and standard deviation• Enough?

Which one has bigger SD than the other?

nXX

SDnX

X ii

22 )(

0

15

30

0

200

400

Impact of Aggregation on Variability Measure of variability

Coefficient of variation

CVA CVB

XSDCV

0

15

30

0

200

400

A B

Impact of Aggregation on Variability Historical data for the two customers

Summary of historical data

Year 1992 1993 1994 1995 1996 1997 1998Customer 1 22,346 28,549 19,567 25,457 31,986 21,897 19,854

Customer 2 17,835 21,765 19,875 24,346 22,876 14,653 24,987

Total 40,181 50,314 39,442 49,803 54,862 36,550 44,841

Average Standard deviation CoefficientStatistics annual demand annual demand of variation

Customer 1 24,237 4,658 0.192

Customer 2 20,905 3,427 0.173

Total 45,142 6,757 0.150

Transport Rates Internal/external fleet Truckload (TL)/less than truckload (LTL)

Cost structure is not symmetric

LTL industry (3PL?) Class, exception, commodity

Additionally, Mileage estimation, …

$-

$10

$20

$30

$40

$50

$60

$70

$80

$90

0 2 4 6 8 10

Number of Warehouses

Cos

t (m

illio

ns $

)

Total CostTransportation CostFixed CostInventory Cost

Warehouse Costs Three main components

Handling costs: labor costs, utility costs Fixed costs: not proportional to the amount of material the flows

through the warehouse Storage costs: proportional to the inventory level

• Inventory turnover ratio = annual sales / average inventory level

Industry Benchmarks:# of Distribution Centers

Sources: CLM 1999, Herbert W. Davis & Co; LogicTools

Avg.# ofWH 3 14 25

Pharmaceuticals Food Companies Chemicals

- High margin product- Service not important (or easy to ship express)- Inventory expensiverelative to transportation

- Low margin product- Service very important- Outbound transportationexpensive relative to inbound

Other Issues Potential Warehouse Locations

Geographical and infrastructure conditions Natural resources and labor availability Local industry and tax regulations Public interest

Service level requirements Future demand

Model and Data Validation Model? Data validation

Ensuring data and model accurately reflect the network design problem

Done by reconstructing the existing network configuration using the model and collected data comparing the output of the model to existing data

Can identify errors in the data, problematic assumptions, modeling flaws, …

• Does the model make sense?• Are the data consistent?• Can the model results be fully explained?• Did you perform sensitivity analysis?

Solution Techniques Mathematical optimization techniques

Exact algorithms: find optimal solutions Heuristics: find “good” solutions, not necessarily optimal

Simulation models provide a mechanism to evaluate specified design alternatives

created by the designer

Heuristics and Exact Algorithms A distribution system

Single product Two plants p1 and p2 Plant 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 Distribution cost per unit

Facilitywarehouse p1 p2 c1 c2 c3

w1 0 4 3 4 5

w2 5 2 2 1 2

Heuristics and Exact Algorithms A distribution system

D = 50,000

D = 100,000

D = 50,000Cap = 60,000

$4

$5

$2

$3

$4

$5

$2

$1

$2

Production costs are the same, warehousing costs are the same

$0

Heuristics and Exact Algorithms Heuristic 1

For each market, choose the cheapest warehouse to source demand. Then, for every warehouse, choose the cheapest plant.

D = 50,000

D = 100,000

D = 50,000Cap = 60,000

$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

Heuristics and Exact Algorithms Heuristic 2

For each market area, choose the warehouse such that the total delivery costs to the warehouse and from the warehouse to the market is the smallest. (i.e. consider inbound and outbound costs)

D = 50,000

D = 100,000

D = 50,000Cap = 60,000

$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

Heuristics and Exact Algorithms Heuristic 2

For each market area, choose the warehouse such that the total delivery costs to the warehouse and from the warehouse to the market is the smallest. (i.e. consider inbound and outbound costs)

D = 50,000

D = 100,000

D = 50,000Cap = 60,000

$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

Heuristics and Exact Algorithms xij: the flow from i to j

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22543

2450.min

3231

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Total Cost = $740,000

Heuristics and Exact Algorithms Network configuration problem is generally

formulated as integer programming Hard to obtain the optimal solution

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Source: Camm et al. 1997