Chapter 3: Network Planning

1

• Chapter 3 Network Planning
• CMB 8050
• Matthew J. Liberatore

2
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
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?

4
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

5
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

6
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

7
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.

8
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

9
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.

10
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.

11
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

12
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

13
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

14
Number of Warehouses
Optimal Number of Warehouses
15
Industry BenchmarksNumber of Distribution
Centers
Food Companies
Chemicals
Pharmaceuticals
Avg. of WH
3
14
25
- High margin product - Service not important (or
easy to ship express) - Inventory
expensive relative to transportation
- Low margin product - Service very important -
Outbound transportation expensive relative to
inbound
16
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 companys 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?

17
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.

18
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.

19
Unit Distribution Costs
Facility warehouse p1 p2 c1 c2 c3
w1 0 4 3 4 5
w2 5 2 2 1 2
20
Heuristic 1Choose the Cheapest Warehouse to
Source Demand
D 50,000
2 x 50,000
D 100,000
5 x 140,000
1 x 100,000
2 x 60,000
Cap 60,000
D 50,000
2 x 50,000
Total Costs 1,120,000
21
Heuristic 2Choose the warehouse where the
total delivery costs to and from the warehouse
are the lowestConsider inbound and outbound
distribution costs
0
D 50,000
3
P1 to WH1 3 P1 to WH2 7 P2 to WH1 7 P2 to WH
2 4
4
2
5
D 100,000
5
P1 to WH1 4 P1 to WH2 6 P2 to WH1 8 P2 to WH
2 3
4
1
2
Cap 60,000
D 50,000
2
P1 to WH1 5 P1 to WH2 7 P2 to WH1 9 P2 to WH
2 4
Market 1 is served by WH1, Markets 2 and 3 are
served by WH2
22
Heuristic 2Choose the warehouse where the
total delivery costs to and from the warehouse
are the lowestConsider inbound and outbound
distribution costs
0 x 50,000
D 50,000
3 x 50,000
Cap 200,000
P1 to WH1 3 P1 to WH2 7 P2 to WH1 7 P2 to WH
2 4
D 100,000
5 x 90,000
P1 to WH1 4 P1 to WH2 6 P2 to WH1 8 P2 to WH
2 3
1 x 100,000
2 x 60,000
Cap 60,000
D 50,000
2 x 50,000
P1 to WH1 5 P1 to WH2 7 P2 to WH1 9 P2 to WH
2 4
Total Cost 920,000
23
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

24
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.

25
Optimal Solution
Facility warehouse p1 p2 c1 c2 c3
w1 140,000 0 50,000 40,000 50,000
w2 0 60,000 0 60,000 0
Total cost for the optimal strategy is 740,000
26
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

27
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.

28
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?

29
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?

30
Integrating Inventory Positioning and Network
Design
FIGURE 3-18 Sample plot of each SKU by volume
and demand
31
Three Different Product Categories

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

32
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.

33
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.