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Location Strategies

PowerPoint presentation to accompany

Heizer and Render

Operations Management, Eleventh Edition

Principles of Operations Management, Ninth Edition

PowerPoint slides by Jeff Heyl

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Outline

Global Company Profile:
FedEx

The Strategic Importance of Location
Factors That Affect Location Decisions
Methods of Evaluating Location Alternatives
Service Location Strategy
Geographic Information Systems

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Learning Objectives

When you complete this chapter you should be able to:

Identify and explain seven major factors that effect location decisions
Compute labor productivity
Apply the factor-rating method
Complete a locational break-even analysis graphically and mathematically

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When you complete this chapter you should be able to:

Learning Objectives

Use the center-of-gravity method
Understand the differences between service- and industrial-sector location analysis

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Location Provides Competitive Advantage for FedEx

Central hub concept
Enables service to more locations with fewer aircraft
Enables matching of aircraft flights with package loads
Reduces mishandling and delay in transit because there is total control of packages from pickup to delivery

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The Strategic Importance of Location

One of the most important decisions a firm makes
Increasingly global in nature
Significant impact on fixed and variable costs
Decisions made relatively infrequently

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The Strategic Importance of Location

Long-term decisions
Once committed to a location, many resource and cost issues are difficult to change

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The Strategic Importance of Location

The objective of location strategy is to maximize the benefit of location to the firm

Options include

Expanding existing facilities
Maintain existing and add sites
Closing existing and relocating

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Location and Costs

Location decisions based on low cost require careful consideration
Once in place, location-related costs are fixed in place and difficult to reduce
Determining optimal facility location is a good investment

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Factors That Affect Location Decisions

Globalization adds to complexity
Market economics
Communication
Rapid, reliable transportation
Ease of capital flow
Differing labor costs
Identify key success factors (KSFs)

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Location Decisions

Country Decision

Key Success Factors

Political risks, government rules, attitudes, incentives
Cultural and economic issues
Location of markets
Labor talent, attitudes, productivity, costs
Availability of supplies, communications, energy
Exchange rates and currency risks

Figure 8.1

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Location Decisions

Region/ Community Decision

Key Success Factors

Corporate desires
Attractiveness of region
Labor availability and costs
Costs and availability of utilities
Environmental regulations
Government incentives and fiscal policies
Proximity to raw materials and customers
Land/construction costs

Figure 8.1

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Location Decisions

Site Decision

Key Success Factors

Site size and cost
Air, rail, highway, and waterway systems
Zoning restrictions
Proximity of services/ supplies needed
Environmental impact issues

Figure 8.1

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Global Competitiveness Index of Countries

TABLE 8.1
Competitiveness of 142 Selected Countries
COUNTRY	2011-2012 RANKING
Switzerland	1
Singapore	2
Sweden	3
Finland	4
USA	5
Japan	9
UK	10
Canada	12
Israel	22
China	26
Mexico	58
Vietnam	65
Russia	66
Haiti	141
Chad	142

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Factors That Affect
Location Decisions

Labor productivity
Wage rates are not the only cost
Lower productivity may increase total cost

Labor cost per day

Productivity (units per day)

= Cost per unit

= $1.17 per unit

$70

60 units

South Carolina

= $1.25 per unit

$25

20 units

Mexico

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Factors That Affect
Location Decisions

Exchange rates and currency risks
Can have a significant impact on costs
Rates change over time
Costs
Tangible - easily measured costs such as utilities, labor, materials, taxes
Intangible - less easy to quantify and include education, public transportation, community, quality-of-life

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Factors That Affect
Location Decisions

Exchange rates and currency risks
Can have a significant impact on costs
Rates change over time
Costs
Tangible - easily measured costs such as utilities, labor, materials, taxes
Intangible - less easy to quantify and include education, public transportation, community, quality-of-life

Location decisions based on costs alone can create difficult ethical situations

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Factors That Affect
Location Decisions

Political risk, values, and culture
National, state, local governments attitudes toward private and intellectual property, zoning, pollution, employment stability may be in flux
Worker attitudes towards turnover, unions, absenteeism
Globally cultures have different attitudes towards punctuality, legal, and ethical issues

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Ranking Corruption

Rank Country 2012 CPI Score (out of 100)

1 Demark, Finland, New Zealand 90

4 Sweden 88

5 Singapore 87

6 Switzerland 86

7 Australia, Norway 85

9 Canada, Netherlands 84

13 Germany 79

14 Hong Kong 77

17 Japan, UK 74

19 USA 73

37 Taiwan 61

39 Israel 60

45 South Korea 56

80 China 39

123 Vietnam 31

133 Russia 28

Least Corrupt

Most Corrupt

CPI is the Corrupt Perceptions Index calculated by Transparency International, an organization dedicated to fighting business corruption. The Index is calculated from up to 13 different individual scores. For details and the methodology, see www.transparency.org.

In 2012 they changed their scoring system from “out of 10” to “out of 100”.

In case students are interested, three countries tied for the lowest score in the 2012 survey with a score of 8 out of 100 – Afghanistan, North Korea, and Somalia.

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Factors That Affect
Location Decisions

Proximity to markets
Very important to services
JIT systems or high transportation costs may make it important to manufacturers
Proximity to suppliers
Perishable goods, high transportation costs, bulky products

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Factors That Affect
Location Decisions

Proximity to competitors (clustering)
Often driven by resources such as natural, information, capital, talent
Found in both manufacturing and service industries

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Clustering of Companies

TABLE 8.3	Clustering of Companies
INDUSTRY	LOCATIONS	REASON FOR CLUSTERING
Wine making	Napa Valley (US) Bordeaux region (France)	Natural resources of land and climate
Software firms	Silicon Valley, Boston, Bangalore (India)	Talent resources of bright graduates in scientific/technical areas, venture capitalists nearby
Clean energy	Colorado	Critical mass of talent and information, with 1,000 companies

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Clustering of Companies

TABLE 8.3	Clustering of Companies
INDUSTRY	LOCATIONS	REASON FOR CLUSTERING
Theme parks (Disney World, Universal Studios, and Sea World)	Orlando, Florida	A hot spot for entertainment, warm weather, tourists, and inexpensive labor
Electronics firms	Northern Mexico	NAFTA, duty free export to U.S.
Computer hardware manufacturers	Singapore, Taiwan	High technological penetration rate and per capita GDP, skilled/educated workforce with large pool of engineers

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Clustering of Companies

TABLE 8.3	Clustering of Companies
INDUSTRY	LOCATIONS	REASON FOR CLUSTERING
Fast food chains (Wendy’s, McDonald’s, Burger King, and Pizza Hut)	Sites within 1 mile of each other	Stimulate food sales, high traffic flows
General aviation aircraft (Cessna, Learjet, Boeing, Raytheon)	Wichita, Kansas	Mass of aviation skills
Athletic footwear, outdoor wear	Portland, Oregon	300 companies, many owned by Nike, deep talent pool and outdoor culture

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Factor-Rating Method

Popular because a wide variety of factors can be included in the analysis
Six steps in the method
Develop a list of relevant factors called key success factors
Assign a weight to each factor
Develop a scale for each factor
Score each location for each factor
Multiply score by weights for each factor for each location
Make a recommendation based on the highest point score

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Factor-Rating Example

TABLE 8.4	Weights, Scores, and Solution
SCORES (OUT OF 100)	WEIGHTED SCORES
KSF	WEIGHT	FRANCE	DENMARK	FRANCE	DENMARK
Labor availability and attitude	.25	70	60	(.25)(70) = 17.5	(.25)(60) = 15.0
People-to-car ratio	.05	50	60	(.05)(50) = 2.5	(.05)(60) = 3.0
Per capita income	.10	85	80	(.10)(85) = 8.5	(.10)(80) = 8.0
Tax structure	.39	75	70	(.39)(75) = 29.3	(.39)(70) = 27.3
Education and health	.21	60	70	(.21)(60) = 12.6	(.21)(70) = 14.7
Totals	1.00	70.4	68.0

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Locational
Cost-Volume Analysis

An economic comparison of location alternatives
Three steps in the method
Determine fixed and variable costs for each location
Plot the cost for each location
Select location with lowest total cost for expected production volume

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Locational Cost-Volume Analysis Example

Three locations:

Total Cost = Fixed Cost + (Variable Cost x Volume)

Selling price = $120

Expected volume = 2,000 units

Athens $30,000 $75 $180,000

Brussels $60,000 $45 $150,000

Lisbon $110,000 $25 $160,000

Fixed Variable Total

City Cost Cost Cost

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Locational Cost-Volume Analysis Example

Crossover point – Athens/Brussels

30,000 + 75(x) = 60,000 + 45(x)

30(x) = 30,000

(x) = 1,000

60,000 + 45(x) = 110,000 + 25(x)

20(x) = 50,000

(x) = 2,500

Crossover point – Brussels/Lisbon

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Locational Cost-Volume Analysis Example

Figure 8.2

–

$180,000 –

–

$160,000 –

$150,000 –

–

$130,000 –

–

$110,000 –

–

$80,000 –

–

$60,000 –

–

$30,000 –

–

$10,000 –

–

Annual cost

| | | | | | |

0 500 1,000 1,500 2,000 2,500 3,000

Volume

Athens lowest cost

Brussels

lowest cost

Lisbon lowest

cost

Lisbon cost curve

Athens

cost curve

Brussels

cost curve

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Center-of-Gravity Method

Finds location of distribution center that minimizes distribution costs
Considers
Location of markets
Volume of goods shipped to those markets
Shipping cost (or distance)

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Center-of-Gravity Method

Place existing locations on a coordinate grid
Grid origin and scale is arbitrary
Maintain relative distances
Calculate x and y coordinates for ‘center of gravity’
Assumes cost is directly proportional to distance and volume shipped

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Center-of-Gravity Method

where dix = x-coordinate of location i

diy = y-coordinate of location i

Qi = Quantity of goods moved to or from location i

x-coordinate of the center of gravity

y-coordinate of the center of gravity

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Center-of-Gravity Method

TABLE 8.5	Demand for Quain’s Discount Department Stores
STORE LOCATION	NUMBER OF CONTAINERS SHIPPED PER MONTH
Chicago	2,000
Pittsburgh	1,000
New York	1,000
Atlanta	2,000

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Center-of-Gravity Method

Figure 8.3

d1x = 30

d1y = 120

Q1 = 2,000

North-South

East-West

120 –

90 –

60 –

30 –

–

| | | | | |

30 60 90 120 150

Arbitrary origin

New York (130, 130)

Pittsburgh (90, 110)

Chicago (30, 120)

Atlanta (60, 40)

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Center-of-Gravity Method

(30)(2000) + (90)(1000) + (130)(1000) + (60)(2000)

2000 + 1000 + 1000 + 2000

x-coordinate =

= 66.7

y-coordinate =

(120)(2000) + (110)(1000) + (130)(1000) + (40)(2000)

2000 + 1000 + 1000 + 2000

= 93.3

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Center-of-Gravity Method

Figure 8.3

North-South

East-West

120 –

90 –

60 –

30 –

–

| | | | | |

30 60 90 120 150

Arbitrary origin

New York (130, 130)

Pittsburgh (90, 110)

Chicago (30, 120)

Atlanta (60, 40)

Center of gravity (66.7, 93.3)

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Transportation Model

Finds amount to be shipped from several points of supply to several points of demand
Solution will minimize total production and shipping costs
A special class of linear programming problems

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Worldwide Distribution of Volkswagens and Parts

Figure 8.4

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Service Location Strategy

Purchasing power of customer-drawing area

Service and image compatibility with demographics of the customer-drawing area

Competition in the area

Quality of the competition

Uniqueness of the firm’s and competitors’ locations

Physical qualities of facilities and neighboring businesses

Operating policies of the firm

Quality of management

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Location Strategies

TABLE 8.6	Location Strategies – Service vs. Goods-Producing Organizations
SERVICE/RETAIL/PROFESSIONAL	GOODS-PRODUCING
REVENUE FOCUS	COST FOCUS
Volume/revenue Drawing area; purchasing power Competition; advertising/pricing Physical quality Parking/access; security/lighting; appearance/ image Cost determinants Rent Management caliber Operation policies (hours, wage rates)	Tangible costs Transportation cost of raw material Shipment cost of finished goods Energy and utility cost; labor; raw material; taxes, and so on Intangible and future costs Attitude toward union Quality of life Education expenditures by state Quality of state and local government

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Location Strategies

TABLE 8.6	Location Strategies – Service vs. Goods-Producing Organizations
SERVICE/RETAIL/PROFESSIONAL	GOODS-PRODUCING
TECHNIQUES	TECHNIQUES
Regression models to determine importance of various factors Factor-rating method Traffic counts Demographic analysis of drawing area Purchasing power analysis of area Center-of-gravity method Geographic information systems	Transportation method Factor-rating method Locational cost–volume analysis Crossover charts
ASSUMPTIONS	ASSUMPTIONS
Location is a major determinant of revenue High customer-contact issues are critical Costs are relatively constant for a given area; therefore, the revenue function is critical	Location is a major determinant of cost Most major costs can be identified explicitly for each site Low customer contact allows focus on the identifiable costs Intangible costs can be evaluated

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How Hotel Chains Select Sites

Location is a strategically important decision in the hospitality industry
La Quinta started with 35 independent variables and worked to refine a regression model to predict profitability
The final model had only four variables
Price of the inn
Median income levels
State population per inn
Location of nearby colleges

r2 = .51

51% of the

profitability is

predicted by

just these

four variables!

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Geographic Information Systems (GIS)

Important tool to help in location analysis
Enables more complex demographic analysis
Available data bases include
Detailed census data
Detailed maps
Utilities
Geographic features
Locations of major services

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Geographic Information Systems (GIS)

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Printed in the United States of America.

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