facility capacity and location

Amity Business School

Facility Location Strategies


Introduction

• A factory or plant is the manufacturing facility of a company.

• A warehouse is the storage facility of a manufacturing or a distribution company.

• The offices of a service company, a bank, or an insurance company are its facilities.

• The facility location decision is very important for big business houses as well as new entrepreneurs.

• Wrong location of the facility may lead to a failure of the complete project.


Relocate facility to a new location

1. Only machines and equipment can be relocated. Not the human resources.

2. Capital expenditure such as land, building, etc. have to be sold, which may take a long time and investment is blocked.

3. New investment is required to purchase land, construct the building, set up machines and equipment, and hire and train new workers from scratch at the new location.

Sell off the facility to other companies (divestment)

1. Finding buyer for wrong location is difficult.

2. The price received for sell-off are very less.

3. Divestment is a time consuming process

Continue Operations at the Existing Location

1. Low profit/less market share due to inherent problems.

2. Competitors having plants at better locations always have an edge.

3. In the long run, the company will have to plan another facility at the right location in order to beat competition.

Close down the operations completely and liquidate the assets

1. Liquidation of assets is most painful for any organisation.

2. Finding buyers and negotiating with them for different assets is tedious and time-consuming.

Facility set up without proper

location planning


Strategic Importance of Location

• Companies make location decisions relatively infrequently, usually because demand has out grown the current plant’s capacity or because of changes in labour productivity, exchange rates, costs, or local attitudes.

• Companies may also relocate their manufacturing or service facilities because of shifts in demographics and customer demand.


Strategic Importance of Location

• Location Options include

– Expanding an existing facility instead of moving.

– Maintaining current sited while adding another facility elsewhere

– Closing the existing facility and moving to another location

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


Operations Strategies for Multiple Facilities

1. Separate facilities for different products/services.

2. Separate facilities to serve different geographical areas

3. Separate facilities for different processes.


Separate facilities for different products/services.

• Companies which are into diversified product/service ranges prefer to have separate facilities for each of these.

• Each facility takes care of the entire population (markets) or total geographical area for a particular product/service.

• This is done to avoid confusion and bring about economies of scale.


Separate facilities to serve different geographical areas

• This strategy reduces overall transportation cost and the lead time for supplying goods in the markets.

• Prompt action can be taken to deal with sudden changes in demand.


Separate facilities for different processes.

• This strategy helps to avoid confusion at the main manufacturing set up.

• At the same time, a lot of coordination is required between such plants as these serve as feeder units to other plants.

• In the service sector, banks and insurance companies have their central offices, where the main activity is designing various financial instruments/ policies.


Factors affecting facility location planning

1. Proximity to customers (markets) 2. Proximity to raw material 3. Good transportation facilities 4. Availability of power supply 5. Basic amenities 6. Government policies 7. Environmental and community considerations 8. Proximity to subcontractors 9. Easy availability of cheap land 10. Less construction cost 11. Availability of cheap, skillful and efficient labour 12. Residential complexes, schools hospitals, clubs, etc.


Locating Foreign Operations Facilities

• Trade barriers • International customers • International competition • Regulations • Additional resources • Lower cost • Incentives • Economies of scale • Synergy • Offensive in competitor’s home.


A Sequence of Decisions

National Decision

Regional Decision

Community Decision

Site Decision

Political, social, economic stability;

Currency exchange rates; . . . . .

Climate; Customer concentrations;

Degree of unionization; . . . . .

Transportation system availability;

Preference of management; . . . . .

Site size/cost; Environmental impact;

Zoning restrictions; . . . . .


Factors Affecting the Location Decision

• Economic

– Site acquisition, preparation and construction costs

– Labor costs, skills and availability

– Utilities costs and availability

– Transportation costs

– Taxes


Factors Affecting the Location Decision

• Non-economic

– Labor attitudes and traditions

– Training and employment services

– Community’s attitude

– Schools and churches

– Recreation and cultural attractions

– Amount and type of housing available


Facility Types and Their Dominant Locational Factors

• Mining, Quarrying, and Heavy Manufacturing – Near their raw material sources – Abundant supply of utilities – Land and construction costs are inexpensive

• Light Manufacturing – Availability and cost of labor

• Warehousing – Proximity to transportation facilities – Incoming and outgoing transportation costs

• . . . more


Facility Types and Their Dominant Locational Factors

• R&D and High-Tech Manufacturing – Ability to recruit/retain scientists, engineers, etc.

– Near companies with similar technology interests

• Retailing and For-Profit Services

– Near concentrations of target customers

• Government and Health/Emergency Services

– Near concentrations of constituents


Analyzing Service Location Decisions Consumer Behavior

Research

Market Research

Data Gathering for

Each Location Alternative

Revenue Projections for


Why do customers buy our

products and services?

Who are our customers?

What are their characteristics?

What are the economic projections?

What is the time-phased revenue?

Profit Projections for


What are the projected revenues

less time-phased operating costs?

Where are our customers concentrated?

What are their traffic/spending patterns?


Steps in Facility Location Planning Generate a list of alternative

location options for the facility

Find out factors relevant to the facility being planned

Factor Rating Method Break Even Analysis

Simple Median Method

Centre of Gravity Model

Transportation Model

Load-Distance Method


Factor-Rating Method

There are many factors, both qualitative and quantitative, considered in choosing a location.

The factors affecting the facility location decision are all important for any type of industry.

At the same time, the importance of each of these factor may vary for different types of plants.

Managers can use weightings to make the decision process more objective.


Factor-Rating Method

This method is popular because a wide variety of factors can be included in the analysis

Six steps in the method 1. Develop a list of relevant factors called critical success factors

2. Assign a weight to each factor

3. Develop a scale for each factor

4. Score each location for each factor

5. Multiply score by weights for each factor for each location

6. Recommend the location with the highest point score


Factor-Rating Example

Five flags over Florida, a US chain of 10 family-oriented theme parks, has decided to expand overseas by opening its first park in Europe. It whishes to select between France and Denmark.

The ratings sheet lists critical success factors that management has decided are important; their weightings and their rating for two possible sites – France and Denmark are shown


Factor-Rating Example

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


Solution

• Weights and scores are used to evaluate alternative site locations. Given the option of 100 points assigned to each factor, the French location is preferable.

• Insight: By changing the points or weights slightly for those factors about which there is some doubt, we can analyze the sensitivity of the decision.

• For instance, we can see that changing the scores for “Labour availability and attitude” by 10 points can change the decision.

• The number used in factor weighting can be subjective and the model’s results are not exact even though this is a quantitative approach.

Solution


• Triveni steels Pvt. Ltd is planning to start a new factory for manufacturing steel utensils. It is considering three location options, namely, Bokaro, Jamshedpur, and Bhilai. The fixed costs at the three locations have been estimated at Rs 8.15 million, Rs 7.377 million, and Rs 7.903 million, respectively. The variable costs at the three locations are estimated at Rs 500 per unit, Rs 580 per unit, and Rs 490 per unit, respectively. The factory will have annual production capacity of 10,000 steel utensils and in the initial years it will operate at 75% efficiency. Find the best location option, which has the lowest total cost of production.

Locational Break-Even Analysis Example


Solution • At 75% efficiency, the factory will annually produce 75% of 10,000 units = 7,500 units • Total production cost TC = FC + VC * no. of units

– For Bokaro TC = 8,150,000 + (500 x 7,500) = Rs 11,900,000 – For Jamsedpur TC = 7,377,000 + (580 x 7,500) = Rs 11,727,000 – For Bhilai TC = 7,903,000 + (490 x 7,500) = Rs 11,578,000

• Hence, Bhilai is the best location from the economic point of view, as the total cost is minimum there.

Solution


• John Kros, owner of Carolina Ignitions Manufacturing, needs to expand his capacity. He is considering three locations – Akron, Bowling Green, and Chicago – for the new plant. The compnay wishes to find the most economical location for an expected volume of 2,000 units per year.

• Kros conducts locational break even analysis. To do so, he determines that fixed costs per year at he sites are $30,000, $60,000 and $110,000, respectively; and variable costs are $75 per unit, $45 per unit and $25 per unit, respectively. The expected selling price of each ignition system produced is $120.




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



– $180,000 –

– $160,000 – $150,000 –

– $130,000 –

– $110,000 –

– –

$80,000 – –

$60,000 – – –

$30,000 – –

$10,000 – –

An

nu

al co

st

| | | | | | |

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

Volume

Akron lowest cost

Bowling Green lowest cost

Chicago lowest cost

Locational break-even

results can be sensitive

to input data.

For a volume of less

than 1,000, Akron would

be preferred.

For a volume greater

than 2,500, Chicago

would yield the greatest

profit.


Simple Median Model

This model is used for the final selection of the best location option.

Transportation cost is a major consideration in facility location planning.

This model helps to locate a new facility such that the total transportation cost between the new facility and the existing facilities of the organization is minimum.

The term median refers to the statistical median of the loads to be transported between the existing facilities and the new facility.


Locating New Plant The table below gives information about the existing facilities of a

beverage company

The existing facilities may be the factories, warehouses, or markets of the company. The company wants to know where it should locate its new plant.

Facility (F) Coordinate location (x,y)

Cost (C) of moving one unit by unit distance (Rs)

Annual Load (L) Units

Bareilly (10,80) 10 452

Shahjahanpur (30,60) 10 678

Gonda (80,50) 10 483

Kanpur (50,10) 10 711

Sultanpur (80,10) 10 539

2,863


Plot of the Existing Facilities (F)

North-South

East-West

120 –

90 –

60 –

30 –

– | | | | | |

30 60 90 120 150 Arbitrary origin

Bareilly

(10,80)

Shahjanpur

(30,60)

Gonda

(80,50)

Sultanpur

(80,10)

Kanpur

(50,10)


Step 1 : Find the Median Load

Assume the loads are marked with identification numbers starting from 1 to 2,863. Hence, we may say that the loads are arranged in the ascending order of numbering ( a requirement for finding the median).

The median is the [(n+1)/2]th item.

Therefore, (2,863 +1)/2, i.e., 1,432 is the median load.


Step 2 : Find the x coordinate of the New Plant (NP)

Move from the extreme left towards the right along the positive x-axis. In doing so we come across Bareilly first.

Assume that loads 1 to 452 has to be moved between Bareilly and the NP as the Bareilly’s annual load is 452. This range does not include the median load 1,432.

Further we come across Shahjanhanpur next, Assume that loads 453 to 1,130 (678 is the annual load of Shahjahanpur) are moved. This range does not include the median load 1,432.

We come across Kanpur now. Assume that loads 1,131 to 1,842 (712 is the annual load of Kanpur) are moved between Kanpur and the NP. This rang includes the median load 1,432.

Therefore the x – coordinate of the new plant is same as the x-coordinate of Kanpur i.e., 50

There fore

= 50


Step 3 : Find the y coordinate of the New Plant (NP)

Move from the bottom towards along the positive y-axis. In doing so we come across Kanpur and Sultanpur simultaneously.

Assume that loads 1 to 1,250 have to be moved between Kanpur and the NP as the Kanpur and Sultanpur have annual loads of 711 and 539 repectively. This range does not include the median load 1,432.

Further we come across Gonda next, Assume that loads 1251 to 1,733 (483 is the annual load of Gonda) are moved. This range includes the median load 1,432.

Therefore the y – coordinate of the new plant is same as the y-coordinate of Gondai.e., 50

There fore

= 50


Plot of the Existing Facilities (F)

North-South

East-West

120 –

90 –

60 –

30 –

– | | | | | |


Bareilly

(10,80)

Shahjanpur

(30,60)

Gonda

(80,50)

Sultanpur

(80,10)

Kanpur

(50,10)

New Plant

(50,50)


Solution

As shown the route to be followed between, say, NP and Bareilly is represented by a dotted line.

The total distance here is

l50-xl + ly-50l = l50-10l +l80-50l

= 40+30 = 70


Locating New Plant

Facility (F) Coordinate location (x,y)

Distance (D)

Cost (C) of moving one unit by unit distance (Rs)

Annual Load (L) Units

Transportation Cost (Rs) T= DCL

Bareilly (10,80) 70 10 452 316,400

Shahjahanpur

(30,60) 30 10 678 203,400

Gonda (80,50) 30 10 483 144,900

Kanpur (50,10) 40 10 711 284,400

Sultanpur (80,10) 70 10 539 377,300

1,326,400


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)



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



x - coordinate =

∑dixQi

∑Qi i

i

∑diyQi

∑Qi i

i

y - coordinate =

where dix = x-coordinate of location i

diy = y-coordinate of location i

Qi = Quantity of goods moved to or from location i


•

= 49.66

•

= 39.64



Quain’s Discount Department Stores, a chain of four large Target –type outlets, has store locations in Chicago, Pittsburg, New York, and Atlanta; they are currently being supplied out of an old and inadequate warehouse in Pittsburg, the sit of the chain’s first store. The firm wants to find some “central” location in which to build a new warehouse.

It gaters data on demand rates at each outlet as , Chicago = 2,000, Pittusburg = 1,000, New york = 1,000 and Atlanta = 2,000



North-South

East-West

120 –

90 –

60 –

30 –

– | | | | | |


Chicago (30, 120) New York (130, 130)

Pittsburgh (90, 110)

Atlanta (60, 40)



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



North-South

East-West

120 –

90 –

60 –

30 –

– | | | | | |


Chicago (30, 120) New York (130, 130)

Pittsburgh (90, 110)

Atlanta (60, 40)

Center of gravity (66.7, 93.3) +


Insight

By overlaying a US map on this exhibit, we find this location is near central Ohio. The firm may well wish to consider Columbus, Ohio, or a nearby city as an appropriate location.

But it is important to have both North-South and East-West interstate highways near the city selected to make delivery times quicker.


• The load distance method enables a location planner to evaluate two or more potential candidates for locating a proposed facility vis-à-vis the demand (or supply)points.

• This method provides an objective measure of the total load distance for each of the potential candidates.

The Load-Distance Method


• Let us use the following notation for the load-distance method: – Number of existing demand (or supply) points in the grid map = n – Index used for existing demand (or supply) points = i – Coordinates of existing demand (or supply) points i and proposed facility =

– Number of candidates for the proposed facility =

– Index used for the candidates =

– Coordinates of the candidate j in the grip map =

– The distance measure for the Cartesian coordinates between an existing demand (or supply) point i and a candidate j for the proposed facility

is

given by

– The load-distance for a candidate j for the proposed facility

is nothing but the product of the distance between the candidate and all existing demand (or supply) points. It is given by:



Manufacturer of Industrial Component

• A manufacturer of certain industrial component is interested in locating a new facility in a target market and would like to know the most appropriate place in the target market to locate the proposed facility.

• The manufacturer feels that there are no location constraints in the target market (that is, any point in the target market is good enough).

• There are four supply points in the locality that will provide key inputs to the new facility – A, B, C, and D.


Manufacturer of Industrial Component

• A two-dimensional grid map of the target market in which we would like to locate a new facility, along with the distance coordinates of the four supply points is on the next slide.

• The annual supply from these four points to the proposed facility is 200, 450, 175 and 150 tonnes respectively.

• The coordinates with in parentheses show the distance from the origin of the target map to each of the supply points, the number that follows is the annual shipment (in tonnes) form these points to the proposed facility. Identify the most appropriate point in the grid map to locate the new facility.


Grid Map

500 –

400 –

300 –

200 –

100 –

| | | | | | | |

120 200 300 400 500 600 700

Arbitrary origin

A (125, 550), 200

D (700, 300, 150)

B (350, 400), 450

C (450, 125), 175

Center of gravity

(366, 376), 175


• Consider the previous example.

• Assume that the manufacturer came to know that there are constraints in locating the new facility. Based on an initial survey of possible sites for the proposed facility, the manufacturer identified four candidates.

• The figure in the next slide has the location coordinates of the four candidates (numbered 1 to 4). What is the best location for the proposed new facility.



Grid Map

500 –

400 –

300 –

200 –

100 –

| | | | | | | |

120 200 300 400 500 600 700

Arbitrary origin

A (125, 550), 200

D (700, 300)

B (350, 400), 450

C (450, 125), 175

3 (500, 350)

2 (200, 500)

1 (300, 500)

4 (400, 200)


Solution

Let us first summarize the coordinates of the existing supply points and the candidates for the proposed facility by tabulating them from the grid map for the target market.

Let us also tabulate the quantum of shipment from these supply points to the proposed facility.

The table on the next slide presents this information


Solution

Coordinates of supply points and proposed locations.

Existing Supply points Candidates for proposed facility

A 125 550 200 1 300 500

B 350 400 450 2 200 500

C 450 125 175 3 500 350

D 700 300 150 4 400 200


Solution Using the formula for distance measure we can

compute

values between every pair of supply point and candidate for locating new facility.

The computation for A-1 is as follows

= 182.00


Solution Computing for all the pairs in this manner, one can

obtain a matrix of

, as shown in the table.

Also, using the formula for Load-Distance we can obtain the

values and select the candidate with

the least value of LD.

1 2 3 4

A 182.00 90.14 425.00 445.11

B 111.80 180.28 158.11 206.16

C 403.89 450.69 230.49 90.14

D 447.21 538.52 206.16 316.23

1 2 3 4

2,24,474.41 2,58,801.57 2,27,410.05 2,45,000.8


Insight

AS we see from the table, Candidate 1 has the least LD value and therefore, is the most appropriate place to locate the proposed new facility.

It is interesting to note the Candidates 1 and 3 are very close to the center of gravity that we computed earlier and therefore they have the minimum LD compared to the other two sites.


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


Worldwide Distribution of Volkswagens and Parts

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


Location Strategies

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


Location Strategies


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


Location Strategies


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


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!


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

facility capacity and location

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