1. Chapter 3: Logistics Network Planning

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 Product Groups
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. Replacing Original Detailed Data with Aggregated Data
Technology exists to solve the logistics network design problem with the original data
Data aggregation still useful because forecast demand is significantly more accurate at the aggregated level
Aggregating customers into about zones usually results in no more than a 1 percent error in the estimation of total transportation costs

11. General Rules for Aggregation
Aggregate demand points into at least 200 zones
Holds for cases where customers are classified into classes according to their service levels or frequency of delivery
Make sure each zone has approximately an equal amount of total demand
Zones may be of different geographic sizes.
Place aggregated points at the center of the zone
Aggregate products into 20 to 50 product groups

12. Customer Aggregation Based on 3-Digit Zip Codes

13. Product Aggregation

14. Transportation Rates
Rates are almost linear with distance but not with volume
Differences between internal rate and external rate

15. Internal Transportation Rate
For company-owned trucks
Data Required:
Annual costs per truck
Annual mileage per truck
Annual amount delivered
Truck’s effective capacity
Calculate cost per mile per SKU.

16. External Transportation Rate Two Modes of Transportation
Truckload, TL
Country sub-divided into zones. One zone/state except for:
Big states, such as Florida or New York (two zones)
Zone-to-zone costs provides cost per mile per truckload between any two zones.
TL cost from Chicago to Boston =
Illinois-Massachusetts cost per mile X Chicago-Boston distance
TL cost structure is not symmetric

17. External Transportation Rate Two Modes of Transportation
Less-Than-Truckload, LTL
Class rates
standard rates for almost all products or commodities shipped.
Classification tariff system that gives each shipment a rating or a class.
Factors involved in determining a product’s specific class include:
product density, ease or difficulty of handling and transporting, and liability for damage.
After establishing rating, identify rate basis number.
Approximate distance between the load’s origin and destination.
With the two, determine the specific rate per hundred pounds (hundred weight, or cwt) from a carrier tariff table (i.e., a freight rate table).
Exception rates provides less expensive rates
Commodity rates are specialized commodity-specific rates

18. SMC3’s CzarLite Engine to find rates in fragmented LTL industry
Nationwide LTL zip code-based rate system.
Offers a market-based price list derived from studies of LTL pricing on a regional, interregional, and national basis.
A fair pricing system
Often used as a base for negotiating LTL contracts between shippers, carriers, and third-party logistics providers

19. Transportation Rate for Shipping 4,000 lbs.
FIGURE 3-7: Transportation rates for shipping 4,000 lb

20. Mileage Estimation
Estimate lona and lata, the longitude and latitude of point a (and similarly for point b)
Distance between a and b
For short distances
For large distances

21. Circuity Factor, ρ Equations underestimate the actual road distance.
Multiply Dab by ρ.
Typical values:
ρ = 1.3 in metropolitan areas
ρ = 1.14 for the continental United States

22. Chicago-Boston Distance
lonChicago =
latChicago = 41.85
lonBoston =
lonBoston = 42.36
DChicago, Boston = 855 miles
Multiply by circuity factor = 1.14
Estimated road distance = 974 miles
Actual road distance = 965 miles
GIS systems provide more accuracy
Slows down systems
Above approximation good enough!

23. Warehouse Costs Handling costs Fixed costs Storage 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.

24. Determining Fixed Costs
FIGURE 3-8: Warehouse fixed costs as a function of the warehouse capacity

25. Determining Storage Costs
Multiply inventory turnover by holding cost
Inventory Turnover =
Annual Sales / Average Inventory Level

26. Warehouse Capacity Estimation of actual space required
Average inventory level =
Annual flow through warehouse/Inventory turnover ratio
Space requirement for item = 2*Average Inventory Level
Multiply by factor to account for
access and handling
aisles,
picking, sorting and processing facilities
AGVs
Typical factor value = 3

27. Warehouse Capacity Example
Annual flow = 1,000 units
Inventory turnover ratio = 10.0
Average inventory level = 100 units
Assume each unit takes 10 sqft. of space
Required space for products = 2,000 sqft.
Total space required for the warehouse is about 6,000 square feet

28. 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

29. 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

30. 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

31. Number of Warehouses
Optimal
Number
of Warehouses

32. Industry Benchmarks: Number of Distribution Centers
Pharmaceuticals
Food Companies
Chemicals
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

33. 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?

34. 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.

35. 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.

36. Unit Distribution Costs
Facility warehouse p1 p2 c1 c2 c3 w1 4 3 5 w2 2 1

37. Heuristic #1: Choose the Cheapest Warehouse to Source Demand
$2 x 50,000
$5 x 140,000
D = 100,000
$1 x 100,000
$2 x 60,000
Cap = 60,000
D = 50,000
$2 x 50,000
Total Costs = $1,120,000

38. Market #1 is served by WH1, Markets 2 and 3
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
D = 50,000 $3
P1 to WH1 $3
P1 to WH2 $7
P2 to WH1 $7
P2 to WH 2 $4 $4 $2 $5 $5
D = 100,000
P1 to WH1 $4
P1 to WH2 $6
P2 to WH1 $8
P2 to WH 2 $3 $4 $1 $2
Cap = 60,000 $2
D = 50,000
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

39. 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 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
$5 x 90,000
D = 100,000
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
$2 x 50,000
D = 50,000
P1 to WH1 $5
P1 to WH2 $7
P2 to WH1 $9
P2 to WH 2 $4
Total Cost = $920,000

40. 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

41. 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) =
x(w1,c3) + x(w2,c3) = 50000
all flows greater than or equal to zero.

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

43. 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

44. 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.

45. DSS for Network Design
Flexibility to incorporate a large set of preexisting network characteristics
Other Factors:
Customer-specific service level requirements.
Existing warehouses kept open
Expansion of existing warehouses.
Specific flow patterns maintained
Warehouse-to-warehouse flow possible
Production and Bill of materials details may be important
Robustness
Relative quality of the solution independent of specific environment, data variability or specific settings

46. 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?

47. Single Product, Single Facility Periodic Review Inventory Model
Assume -
SI: amount of time between when an order is placed until the facility receives a shipment (Incoming Service Time)
S: Committed Service Time made by the facility to its own customers.
T: Processing Time at the facility.
Net Lead Time = SI + T - S
Safety stock at the facility:

48. 2-Stage System Overall objective is to choose:
Reducing committed service time from facility 2 to facility 1 impacts required inventory at both facilities
Inventory at facility 1 is reduced
Inventory at facility 2 is increased
Overall objective is to choose:
the committed service time at each facility
the location and amount of inventory
minimize total or system wide safety stock cost.

49. ElecComp Case
Large contract manufacturer of circuit boards and other high tech parts.
About 27,000 high value products with short life cycles
Fierce competition => Low customer promise times < Manufacturing Lead Times
High inventory of SKUs based on long-term forecasts => Classic PUSH STRATEGY
High shortages
Huge risk
PULL STRATEGY not feasible because of long lead times

50. New Supply Chain Strategy
OBJECTIVES:
Reduce inventory and financial risks
Provide customers with competitive response times.
ACHIEVE THE FOLLOWING:
Determining the optimal location of inventory across the various stages
Calculating the optimal quantity of safety stock for each component at each stage
Hybrid strategy of Push and Pull
Push Stages produce to stock where the company keeps safety stock
Pull stages keep no stock at all.
Challenge:
Identify the location where the strategy switched from Push-based to Pull-based
Identify the Push-Pull boundary
Benefits:
For same lead times, safety stock reduced by 40 to 60%
Company could cut lead times to customers by 50% and still reduce safety stocks by 30%

51. Notations Used
FIGURE 3-11: How to read the diagrams

52. Trade-Offs
If Montgomery facility reduces committed lead time to 13 days
assembly facility does not need any inventory of finished goods
Any customer order will trigger an order for parts 2 and 3.
Part 2 will be available immediately, since it is held in inventory
Part 3 will be available in 15 days
13 days committed response time by the manufacturing facility
2 days transportation lead time.
Another 15 days to process the order at the assembly facility
Order is delivered within the committed service time.
Assembly facility produces to order, i.e., a Pull based strategy
Montgomery facility keeps inventory and hence is managed with a Push or Make-to-Stock strategy.

53. Current Safety Stock Location
FIGURE 3-12: Current safety stock location

54. Optimized Safety Stock Location
FIGURE 3-13: Optimized safety stock

55. Current Safety Stock with Lesser Lead Time
FIGURE 3-14: Optimized safety stock with reduced lead time

56. Supply Chain with More Complex Product Structure
FIGURE 3-15: Current supply chain

57. Optimized Supply Chain with More Complex Product Structure
FIGURE 3-16: Optimized supply chain

58. Key Points Identifying the Push-Pull boundary
Taking advantage of the risk pooling concept
Demand for components used by a number of finished products has smaller variability and uncertainty than that of the finished goods.
Replacing traditional supply chain strategies that are typically referred to as sequential, or local, optimization by a globally optimized supply chain strategy.

59. Local vs. Global Optimization
FIGURE 3-17: Trade-off between quoted lead time and safety stock

60. Global Optimization
For the same lead time, cost is reduced significantly
For the same cost, lead time is reduced significantly
Trade-off curve has jumps in various places
Represents situations in which the location of the Push-Pull boundary changes
Significant cost savings are achieved.

61. Problems with Local Optimization
Prevalent strategy for many companies:
try to keep as much inventory close to the customers
hold some inventory at every location
hold as much raw material as possible.
This typically yields leads to:
Low inventory turns
Inconsistent service levels across locations and products, and
The need to expedite shipments, with resulting increased transportation costs

62. 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?

63. Integrating Inventory Positioning and Network Design
FIGURE 3-18: Sample plot of each SKU by volume and demand

64. Three Different Product Categories
High variability - low volume products
Low variability - high volume products, and
Low variability - low volume products.

65. 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.

66. 3.4 Resource Allocation Supply chain master planning
The process of coordinating and allocating production, and distribution strategies and resources to maximize profit or minimize system-wide cost
Process takes into account:
interaction between the various levels of the supply chain
identifies a strategy that maximizes supply chain performance

67. Global Optimization and DSS FACTORS TO CONSIDER
Facility locations: plants, distribution centers and demand points
Transportation resources including internal fleet and common carriers
Products and product information
Production line information such as min lot size, capacity, costs, etc.
Warehouse capacities and other information such as certain technology (refrigerators) that a specific warehouse has and hence can store certain products
Demand forecast by location, product and time.

68. Focus of the Output Sourcing Strategies: Supply Chain Master Plan:
where should each product be produced during the planning horizon, OR
Supply Chain Master Plan:
production quantities, shipment size and storage requirements by product, location and time period.

69. The Extended Supply Chain: From Manufacturing to Order Fulfillment
FIGURE 3-19: The extended supply chain: from manufacturing to order fulfillment

70. Questions to Ask During the Planning Process
Will leased warehouse space alleviate capacity problems?
When and where should the inventory for seasonal or promotional demand be built and stored?
Can capacity problems be alleviated by re-arranging warehouse territories?
What impact do changes in the forecast have on the supply chain?
What will be the impact of running overtime at the plants or out-sourcing production?
What plant should replenish each warehouse?
Should the firm ship by sea or by air. Shipping by sea implies long lead times and therefore requires high inventory levels. On the other hand, using air carriers reduces lead times and hence inventory levels but significantly increases transportation cost.
Should we rebalance inventory between warehouses or replenish from the plants to meet unexpected regional changes in demand?

71. SUMMARY Network Planning Characteristics
Network Design
Inventory Positioning and Management
Resource Allocation
Decision focus
Infrastructure
Safety stock
Production Distribution
Planning Horizon
Years
Months
Aggregation Level
Family
Item
Classes
Frequency
Yearly
Monthly/Weekly
ROI
High
Medium
Implementation
Very Short
Short
Users
Very Few
Few

72. 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.

73. SUMMARY
Demonstrate applicability of risk pooling and postponement, EOQ modeling, and inventory sizing to improve customer service in make-to-order job shop setting
Demonstrates value from getting and looking at data
Implemented in stages, slowed down by SAP problems and installation
Proposed stocking 8 intermediates and cutting cycle on rolling mill to 1 week. 80% of products could be made with one rolling cycle; so a product could wait for 2 rolling cycles and still make 3 week lead time.
Need initially 1 month of inventory, but this will allow excess stocks to be drawn down – eventually get 2 mm inventory reduction.
Set in place max and min inventories for 30/1000 for alloy 1 and 15/1000 for alloy 2
Difficult to get sales to quote shorter lead times, due to lack of confidence -- w/o this production could not demonstrate their ability to meet shorter lead times, vicious cycle