Operations Mang CASE 2

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location_strategy.ppt

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Location Strategy

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

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Location and Innovation

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

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Location Decisions

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

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Location Decisions

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

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Location Decisions

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

Figure 8.1

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Location Decisions

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

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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

Connecticut

= $1.25 per unit

$25

20 units

Juarez

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Factors That Affect
Location Decisions

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

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Factors That Affect
Location Decisions

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

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

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Growth Competitiveness Index of Countries

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

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Clustering of Companies

Table 8.3

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

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Clustering of Companies

Table 8.3

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

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Clustering of Companies

Table 8.3

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

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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 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

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Factor-Rating Example

Table 8.3

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

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Locational
Break-Even Analysis

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

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Locational Break-Even Analysis Example

Three locations:

Total Cost = Fixed Cost + Variable Cost x Volume

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

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Locational Break-Even 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

Akron lowest cost

Bowling Green lowest cost

Chicago lowest cost

Chicago cost curve

Akron cost curve

Bowling Green 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

∑dixQi

∑Qi

x - coordinate =

∑diyQi

∑Qi

y - coordinate =

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Center-of-Gravity Method

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

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

(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

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

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

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Location Strategies

Table 8.4

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

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Location Strategies

Table 8.4

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

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Location Strategies

Table 8.4

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

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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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Telemarketing/Internet Industries

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

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Geographic Information Systems (GIS)

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

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Geographic Information Systems (GIS)