Chapter 3: Network Planning

CMB 8050

Matthew J. Liberatore 3-1

3.1 Why Network Planning?

 Find the right balance between inventory, transportation and manufacturing costs,  Match supply and demand under uncertainty by positioning and managing inventory effectively,  Utilize resources effectively by sourcing products from the most appropriate manufacturing facility 3-2

Three Hierarchical Steps

  

Network design

    Number, locations and size of manufacturing plants and warehouses Assignment of retail outlets to warehouses Major sourcing decisions Typical planning horizon is a few years.

Inventory positioning:

    Identifying stocking points Selecting facilities that will produce to stock and thus keep inventory Facilities that will produce to order and hence keep no inventory Related to the inventory management strategies

Resource allocation:

   Determine whether production and packaging of different products is done at the right facility What should be the plants sourcing strategies? How much capacity each plant should have to meet seasonal demand?

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3.2 Network Design

 Physical configuration and infrastructure of the supply chain.  A strategic decision with long-lasting effects on the firm.  Decisions relating to plant and warehouse location as well as distribution and sourcing 3-4

Reevaluation of Infrastructure

 Changes in:  demand patterns  product mix  production processes  sourcing strategies  cost of running facilities.  Mergers and acquisitions may mandate the integration of different logistics networks 3-5

Key Strategic Decisions

 Determining the appropriate number of facilities such as plants and warehouses.

 Determining the location of each facility.

 Determining the size of each facility.

 Allocating space for products in each facility.

 Determining sourcing requirements.

 Determining distribution strategies, i.e., the allocation of customers to warehouse 3-6

Objective and Trade-Offs

 Objective: Design or reconfigure the logistics network in order to minimize annual system-wide cost subject to a variety of

service level

requirements  Increasing the number of warehouses typically yields:      An improvement in service level due to the reduction in average travel time to the customers An increase in inventory costs due to increased safety stocks required to protect each warehouse against uncertainties in customer demands.

An increase in overhead and setup costs A reduction in outbound transportation costs: transportation costs from the warehouses to the customers An increase in inbound transportation costs: transportation costs from the suppliers and/or manufacturers to the warehouses.

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Data Collection

         Locations of customers, retailers, existing warehouses and distribution centers, manufacturing facilities, and suppliers.

All products, including volumes, and special transport modes (e.g., refrigerated).

Annual demand for each product by customer location.

Transportation rates by mode.

Warehousing costs, including labor, inventory carrying charges, and fixed operating costs.

Shipment sizes and frequencies for customer delivery.

Order processing costs.

Customer service requirements and goals.

Production and sourcing costs and capacities 3-8

Data Aggregation



Customer Zone

   Aggregate using a grid network or other clustering technique for those in close proximity. Replace all customers within a single cluster by a single customer located at the center of the cluster Five-digit or three-digit zip code based clustering. 

Product Groups

 

Distribution pattern

  Products picked up at the same source and destined to the same customers Logistics characteristics like weight and volume.

Product type

 product models or style differing only in the type of packaging. 3-9

Warehouse Costs



Handling costs

 Labor and utility costs  Proportional to annual flow through the warehouse.



Fixed costs

 All cost components not proportional to the amount of flow  Typically proportional to warehouse size (capacity) but in a nonlinear way. 

Storage costs

 Inventory holding costs  Proportional to

average

positive inventory levels.

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Potential Locations

 Geographical and infrastructure conditions.

 Natural resources and labor availability.

 Local industry and tax regulations.

 Public interest.

 Not many will qualify based on all the above conditions 3-11

Service Level Requirements

 Specify a maximum distance between each customer and the warehouse serving it  Proportion of customers whose distance to their assigned warehouse is no more than a given distance  95% of customers be situated within 200 miles of the warehouses serving them  Appropriate for rural or isolated areas 3-12

Future Demand

 Strategic decisions have to be valid for 3-5 years  Consider scenario approach and net present values to factor in expected future demand over planning horizon 3-13

$90 $80 $70 $60 $50 $40 $30 $20 $10 $ 0

Number of Warehouses

Optimal Number of Warehouses 2 4 6

Number of Warehouses

8 10 Total Cost Transportation Cost Fixed Cost Inventory Cost 3-14

Industry Benchmarks: Number of Distribution Centers

Food Companies Chemicals Pharmaceuticals Avg.

# of WH 3 - High margin product - Service not important (or easy to ship express) - Inventory expensive relative to transportation 14 25 - Low margin product - Service very important - Outbound transportation expensive relative to inbound 3-15

Model Validation

     Reconstruct the existing network configuration using the model and collected data Compare the output of the model to existing data Compare to the company’s accounting information  Often the best way to identify errors in the data, problematic assumptions, modeling flaws. Make local or small changes in the network configuration to see how the system estimates impact on costs and service levels.

 Positing a variety of what-if questions. Answer the following questions:     Does the model make sense?

Are the data consistent?

Can the model results be fully explained?

Did you perform sensitivity analysis?

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Solution Techniques

 Mathematical optimization techniques: 1. Exact algorithms: find optimal solutions 2. Heuristics: find “good” solutions, not necessarily optimal  Simulation models: provide a mechanism to evaluate specified design alternatives created by the designer.

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Example

 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.

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Unit Distribution Costs

Facility warehouse

w

1

w

2

p1

0 5

p2

4 2

c1

3 2

c2

4 1

c3

5 2 3-19

Heuristic #1:

Choose the Cheapest Warehouse to Source Demand Cap = 60,000 D = 50,000 $2 x 50,000 $5 x 140,000 $2 x 60,000 D = 100,000 $1 x 100,000 $2 x 50,000 D = 50,000 Total Costs = $1,120,000 3-20

Heuristic #2:

Choose the warehouse where the total delivery costs to and from the warehouse are the lowest [Consider inbound and outbound distribution costs] $0 $3 $4 $2 D = 50,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $3 $7 $7 $4 $5 $4 $5 $2 $1 D = 100,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $4 $6 $8 $3 Cap = 60,000 $2 Market #1 is served by WH1, Markets 2 and 3 are served by WH2 D = 50,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $5 $7 $9 $4 3-21

Heuristic #2: Choose the warehouse where the total delivery costs to and from the warehouse are the lowest [Consider inbound and outbound distribution costs] Cap = 200,000 Cap = 60,000 $0 x 50,000 $5 x 90,000 $2 x 60,000 $3 x 50,000 D = 50,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $3 $7 $7 $4 $1 x 100,000 D = 100,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $4 $6 $8 $3 $2 x 50,000 D = 50,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $5 $7 $9 $4 Total Cost = $920,000 3-22

The Optimization Model

   The problem described earlier can be framed as the following linear programming problem.

Let x(p1,w1), x(p1,w2), x(p2,w1) and x(p2,w2) be the flows from the plants to the warehouses.

x(w1,c1), x(w1,c2), x(w1,c3) be the flows from the warehouse w1 to customer zones c1, c2 and c3.

x(w2,c1), x(w2,c2), x(w2,c3) be the flows from warehouse w2 to customer zones c1, c2 and c3 3-23

The Optimization Model

The problem we want to solve is: 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)  60000 x(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) = 50000 x(w1,c2) + x(w2,c2) = 100000 x(w1,c3) + x(w2,c3) = 50000 all flows greater than or equal to zero.

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p

1

Optimal Solution

p

2

c

1

c

2 Facility warehouse

w

1

w

2 140,000 0 0 60,000 50,000 0 40,000 60,000

Total cost for the optimal strategy is $740,000

c

3

50,000 0 3-25

Simulation Models

 Useful for a given design and a micro-level analysis. Examine:  Individual ordering pattern.

 Specific inventory policies.

 Inventory movements inside the warehouse.

 Not an optimization model  Can only consider very few alternate models 3-26

Which One to Use?

 Use mathematical optimization for static analysis  Use a 2-step approach when dynamics in system has to be analyzed:  Use an optimization model to generate a number of least-cost solutions at the macro level, taking into account the most important cost components.

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

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3.3 Inventory Positioning and Logistics Coordination

    Multi-facility supply chain that belongs to a single firm Manage inventory so as to reduce system wide cost Consider the interaction of the various facilities and the impact of this interaction on the inventory policy of each facility Ways to manage:    Wait for specific orders to arrive before starting to manufacture them [make-to-order facility] Otherwise, decide on

where to keep safety stock?

Which facilities should produce to stock and which should produce to order? 3-28

Integrating Inventory Positioning and Network Design

 Consider a two-tier supply chain  Items shipped from manufacturing facilities to primary warehouses  From there, they are shipped to secondary warehouses and finally to retail outlets  How to optimally position inventory in the supply chain?  Should every SKU be positioned both at the primary and secondary warehouses?, OR  Some SKU be positioned only at the primary while others only at the secondary?

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Integrating Inventory Positioning and Network Design

FIGURE 3-18:

Sample plot of each SKU by volume and demand

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Three Different Product Categories

 High variability - low volume products  Low variability - high volume products, and  Low variability - low volume products.

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Supply Chain Strategy Different for the Different Categories

   High variability low volume products   Inventory risk the main challenge for Position them mainly at the primary warehouses  demand from many retail outlets can be aggregated reducing inventory costs.

Low variability high volume products   Position close to the retail outlets at the secondary warehouses Ship fully loaded tracks as close as possible to the customers reducing transportation costs.

Low variability low volume products  Require more analysis since other characteristics are important, such as profit margins, etc. 3-32

SUMMARY

  Optimizing supply chain performance is difficult   conflicting objectives demand and supply uncertainties  supply chain dynamics. Through network planning, firms can globally optimize supply chain performance   Combines network design, inventory positioning and resource allocation Consider the entire network     account production Warehousing transportation inventory costs service level requirements. 3-33