Location Strategy

8 – 1

• One of the most important decisions a firm makes
• Increasingly global in nature
• Long term impact and decisions are difficult to change
• The objective is to maximize the benefit of location to the firm

Location and Innovation

8 – 2

• Cost is not always the most important aspect of a strategic decision
• Four key attributes when strategy is based on innovation
• High-quality and specialized inputs
• An environment that encourages investment and local rivalry
• A sophisticated local market
• Local presence of related and supporting industries

Location Decisions

8 – 3

• Long-term decisions
• Decisions made infrequently
• Decision greatly affects both fixed and variable costs
• Once committed to a location, many resource and cost issues are difficult to change

Location Decisions

8 – 4

Country Decision

Critical Success Factors

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

Figure 8.1

Location Decisions

8 – 5

Region/ Community Decision

Critical Success Factors

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

MN

WI

MI

IL

IN

OH

Figure 8.1

Location Decisions

8 – 6

Site Decision

Critical Success Factors

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

Figure 8.1

Factors That Affect �Location Decisions

8 – 7

• 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

Connecticut

= $1.17 per unit

$70

60 units

Juarez

= $1.25 per unit

$25

20 units

Factors That Affect �Location Decisions

8 – 8

• Exchange rates and currency risks
• Can have a significant impact on cost structure
• 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

Factors That Affect �Location Decisions

8 – 9

• Attitudes
• National, state, local governments toward private and intellectual property, zoning, pollution, employment stability
• Worker attitudes towards turnover, unions, absenteeism
• Globally cultures have different attitudes towards punctuality, legal, and ethical issues

Factors That Affect �Location Decisions

8 – 10

• 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

Factors That Affect �Location Decisions

8 – 11

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

Growth Competitiveness Index of Countries

8 – 12

Country 2004 Rank 2003 Rank

Finland 1 1

USA 2 2

Sweden 3 3

Taiwan 4 5

Japan 9 11

UK 11 15

Germany 13 13

Canada 15 16

New Zealand 18 14

France 27 26

Russia 70 70

Clustering of Companies

8 – 13

Industry

Locations

Reason for clustering

Wine makers

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

Race car builders

Huntington/North Hampton region (England)

Critical mass of talent and information

Table 8.3

Clustering of Companies

8 – 14

Industry

Locations

Reason for clustering

Theme parks

Orlando

A hot spot for entertainment, warm weather, tourists, and inexpensive labor

Electronic firms

Northern Mexico

NAFTA, duty free export to US

Computer hardware manufacturers

Singapore, Taiwan

High technological penetration rate and per capita GDP, skilled/educated workforce with large pool of engineers

Table 8.3

Clustering of Companies

8 – 15

Industry

Locations

Reason for clustering

Fast food chains

Sites within one mile of each other

Stimulate food sales, high traffic flows

General aviation aircraft

Wichita, Kansas

Mass of aviation skills

Table 8.3

Factor-Rating Method

8 – 16

• 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 critical 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
• Recommend the location with the highest point score

Factor-Rating Example

8 – 17

Critical Scores

Success (out of 100) Weighted Scores

Factor 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

Table 8.3

Locational �Break-Even Analysis

8 – 18

• Method of cost-volume analysis used for industrial locations
• 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

Locational Break-Even Analysis Example

8 – 19

Three locations:

Akron $30,000 $75 $180,000

Bowling Green $60,000 $45 $150,000

Chicago $110,000 $25 $160,000

Selling price = $120

Expected volume = 2,000 units

Fixed Variable Total

City Cost Cost Cost

Total Cost = Fixed Cost + Variable Cost x Volume

Locational Break-Even Analysis Example

8 – 20

–

$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

Akron lowest cost

Bowling Green lowest cost

Chicago lowest cost

Chicago cost curve

Akron cost curve

Bowling Green cost curve

Figure 8.2

Center-of-Gravity Method

8 – 21

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

Center-of-Gravity Method

8 – 22

• 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

Center-of-Gravity Method

8 – 23

x - coordinate =

∑d_ixQ_i

∑Q_i

i

i

∑d_iyQ_i

∑Q_i

i

i

y - coordinate =

where d_ix = x-coordinate of location i

d_iy = y-coordinate of location i

Q_i = Quantity of goods moved to or from location i

Center-of-Gravity Method

8 – 24

North-South

East-West

120 –

90 –

60 –

30 –

–

| | | | | |

30 60 90 120 150

Arbitrary origin

Chicago (30, 120)

New York (130, 130)

Pittsburgh (90, 110)

Atlanta (60, 40)

Center-of-Gravity Method

8 – 25

Number of Containers

Store Location Shipped per Month

Chicago (30, 120) 2,000

Pittsburgh (90, 110) 1,000

New York (130, 130) 1,000

Atlanta (60, 40) 2,000

x-coordinate =

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

2000 + 1000 + 1000 + 2000

= 66.7

y-coordinate =

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

2000 + 1000 + 1000 + 2000

= 93.3

Center-of-Gravity Method

8 – 26

North-South

East-West

120 –

90 –

60 –

30 –

–

| | | | | |

30 60 90 120 150

Arbitrary origin

Chicago (30, 120)

New York (130, 130)

Pittsburgh (90, 110)

Atlanta (60, 40)

Center of gravity (66.7, 93.3)

+

Transportation Model

8 – 27

• 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

Worldwide Distribution of Volkswagens and Parts

8 – 28

Figure 8.4

Service Location Strategy

1. Purchasing power of customer-drawing area

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

3. Competition in the area

4. Quality of the competition

5. Uniqueness of the firm’s and competitors’ locations

6. Physical qualities of facilities and neighboring businesses

7. Operating policies of the firm

8. Quality of management

8 – 29

Location Strategies

8 – 30

Service/Retail/Professional Location Goods-Producing Location

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

Operations 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

Table 8.4

Location Strategies

8 – 31

Service/Retail/Professional Location Goods-Producing Location

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 methods

Factor-rating method

Locational break-even analysis

Crossover charts

Table 8.4

Location Strategies

8 – 32

Service/Retail/Professional Location Goods-Producing Location

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

Table 8.4

How Hotel Chains Select Sites

8 – 33

• 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!

Telemarketing/Internet Industries

8 – 34

• Require neither face-to-face contact nor movement of materials
• Have very broad location options
• Traditional variables are no longer relevant
• Cost and availability of labor may drive location decisions

Geographic Information Systems (GIS)

8 – 35

• New 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

Geographic Information Systems (GIS)

8 – 36