Advanced Spatial Analysis

October 7, 2002

Dr. Charles NoonDepartment of ManagementThe University of Tennessee

Agenda

• Beyond mapping, Geographic Information Systems (GIS) with examples

– Buffer and Overlay

– Transportation Analysis

• Advanced Descriptive Modeling example

• Advanced Prescriptive Modeling example

Competitor A Sales Dollars (000s) by State

Geographic Information Systems (GIS): A tool for spatial analysis

• GIS: a computer platform which allows chain-wide data to be easily integrated for display and analysis.

• GIS is not map making software• Data stored and handled in Layers• Data is attached to each Feature• Display can be a function of the data• Query and Analysis within or between layers

Buffer and Overlay

• Buffer around points, lines or polygons

• Overlay can, for example, merge maps together, clip one map based on another map, find the intersection of two maps, or find the union of two maps that combine both spatial and attribute data.

500-mile buffer zones around the DCs.

Clip customer sites that fall within 500-milebuffer zones around the DCs.

Select all counties that intersect with the 500-milebuffer zones around the DCs.

Transportation Analysis

• With the addition of a network layer, a number of analyses can be performed, such as

– Shortest Path

– Service areas

– Vehicle Routing

Thickness is rate

Transportation Analysis

• With the addition of a network layer, a number of analyses can be performed, such as

– Shortest Path

– Service areas

– Vehicle Routing

• Large growing industry with much of the consumption in the Southeast

• Majority of current flights are into Northeast

• Most DCs within 2 day delivery

• US Xpress and Averitt Express both currently carry pharmaceuticals

An Example of Overlay: Recommended Market Niche Pharmaceuticals

One Day Delivery

70.6%

23.7%

Two Day Delivery

Chattanooga Catchment AreaChattanooga Catchment Area

One Day Delivery

Two Day Delivery

24.8%

64.5%

Charlotte Catchment Area

Population served byChattanooga

Population served byCharlotte

Population served byChattanooga

Population served by Charlotte

Population served by both

2-Day Delivery Coverage2-Day Delivery Coverage

• Population within two-day catchment– Chattanooga – 70.6%

– Charlotte – 64.5%

• Approximately $8 billion in additional pharmaceutical potential in Chattanooga catchment

Results of Analysis:

Transportation Analysis

• With the addition of a network layer, a number of analyses can be performed, such as

– Shortest Path

– Service areas

– Vehicle Routing

An Example

• A distributor to fast-food restaurants with 12 DC’s serving 3922 restaurants with 80 vehicles.

• Currently, DC’s serve from 209 to 644 restaurants.

• TransCad was first used to determine optimal weekly delivery routes under the current restaurant-to-DC assignments.

CURRENT STORE-TO-DC ASSIGNMENTS

Total Mileage Per Week = 192,998

An Example

• A distributor to fast-food restaurants with 12 DC’s serving 3922 restaurants with 80 vehicles.

• Currently, DC’s serve from 209 to 644 restaurants.• TransCad was first used to determine optimal weekly

delivery routes under the current restaurant-to-DC assignments.

• TransCad was then used to re-assign restaurants-to-DC’s and determine approximately 400 vehicle routes that must be run each week.

OPTIMIZED STORE-TO-DC ASSIGNMENTS

Total Mileage Per Week = 173,702

STORES WITH CHANGED ASSIGNMENTS

Note: a total of 381 stores had changed DC assignments. Each dot may represent more than one store (in the same zipcode)

STORES WITH CHANGED ASSIGNMENTS

CurrentlyAssignedDC

OptimallyAssigned

DC

Cluster

Net savings of 19,296 miles per week (10% reduction)

Agenda

• Beyond mapping, Geographic Information Systems (GIS) with examples

– Buffer and Overlay

– Transportation Analysis

• Advanced Descriptive Modeling example

• Advanced Prescriptive Modeling example

Locating a proposed NICU

market analysis and visualization with “perfect” data

Study Area

20 Hospitals of Study Area

MethodistWest_TNBaptist

Unaffiliated

15 Hospitals with Maternity Service

MethodistWest_TNBaptist

Unaffiliated

Sized according to ‘97 deliveries

Labeled with number of ‘97 deliveries

MethodistWest_TNBaptist

Unaffiliated

Colored according to system

MethodistWest_TNBaptist

Unaffiliated

Population density by zipcode (est. 2000)

MethodistWest_TNBaptist

Unaffiliated

‘97 births (mother’s zip) per square mile

Baptist Market Share (of births at 15 facilities)

Methodist Market Share (of births at 15 facilities)

West_TN Market Share (of births at 15 facilities)

Meth-LB Patient Density (maternal zipcode)

Methodist System Patient Density (maternal zipcode)

West_TN System Patient Density (maternal zipcode)

Baptist System Patient Density (maternal zipcode)

County Baby Exports (only the top 7 “import” counties are color coded, the black includes all others as well as out-of-region counties)

Delivering mother imports/own-residents occurring at a county. The black number represents total births from residents of the 20 study counties that occurred in that county (note, the hospital numbers may include KY babies or other TN counties and hence the difference in some situations).

Twenty minute drive bands around Dyersburg overlaid on the methodist babies per square mile

Twenty minute drive bands around Jackson overlaid on the methodist babies per square mile

Agenda

• Beyond mapping, Geographic Information Systems (GIS) with examples

– Buffer and Overlay

– Transportation Analysis

• Advanced Descriptive Modeling example

• Advanced Prescriptive Modeling example

Facility Location Example

• A global consumer electronics manufacturer.

• GIS and CAPS Logistics Supply Chain Designer were used in conjunction to perform a network optimization in order to recommend DC locations and shipping zone assignments.

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Growth in offshore production.

Ever changing business environment.

Pro-active approach to network design.

Why the need for a distribution network analysis?

The System as Focused...

The System as Focused...

PLANTS DCs Customers

GV

JZ

FE

Lower 48Markets

(3-digit Zips)

EP

GV

AN

HA

Direct TransfersDirect Transfers

PLANTS DCs Customers

GV

JZ

FE

Lower 48Markets

(3-digit Zips)

EP

GV

AN

HA

$60/FTL

$0

Full Container LoadsFull Container Loads

PLANTS DCs Customers

GV

JZ

FE

Lower 48Markets

(3-digit Zips)

EP

GV

AN

HA

Full Truck LoadsFull Truck Loads

PLANTS DCs Customers

GV

JZ

FE

Lower 48Markets

(3-digit Zips)

EP

GV

AN

HA

+ $60/FTL

FTL, LTL, UPSFTL, LTL, UPS

PLANTS DCs Customers

GV

JZ

FE

Lower 48Markets

(3-digit Zips)

EP

GV

AN

HA

All Movements

PLANTS DCs Customers

GV

JZ

FE

Lower 48Markets

(3-digit Zips)

EP

GV

AN

HA

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DC CostsDC Costs

DCs

EP

GV

AN

HA

There is one base cost of location

assigned to each DC. It reflects the cost of the facility being open with

no through movements.

There is a variable cost assigned for each DC/product

combination, which is based on per unit handling cost (handling + cubic capacity

cost)

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DC CostsDC Costs

There is one fixed cost of location assigned to each DC. It reflects the cost of the facility being open with no through

movements.

MinimumSize

Cube Volume

FacilityCost

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DC CostsDC Costs

We determined a variable fixed cost for each DC. It represents the the change in fixed cost as a function of volume through

the facility.

MinimumSize

Cube Volume

FacilityCost

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DC CostsDC Costs

There is a variable cost assigned for each DC/product combination, which is based on per unit handling

cost

MinimumSize

Cube Volume

FacilityCost

Fixed & per product

variable DC costs

Candidate DC Data Requirements

Candidate DC Data Requirements

PLANTS DCs Customers

GV

JZ

FE

Lower 48Markets

(3-digit Zips)

EP

GV

AN

HA

?

Inbound FTL

rates

Inbound container

rates

Outbound FTL rates

92

Inbound Container Rates

93

Example Outbound FTL Rates

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Shipped by:EL PASOANAHEIMHANAHANGREENVILLE

Current Supply by Origin DC

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Levels of Model Decision MakingLevels of Model Decision Making

Open/Close DC Facilities

Determining facility sizes

Flowing product from Plants to DCs to Markets

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Levels of Model Decision MakingLevels of Model Decision Making

Open/Close DC Facilities

Determining facility sizes

Flowing product from Plants to DCs to Markets

OptimallyFlowing

FullyOptimizing

Projection TV’s

13 - 20 inch CTV’s

Shelf Systems

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Shipped by:EL PASOANAHEIMHANAHANGREENVILLE

Optimized Supply by Origin DC

Shipped by:GreenevilleHanahanEl Paso Anaheim

Current Shipping Pattern

Optimal Shipping Pattern

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Observations

An understanding of the drivers towards an optimal network solution is often of more organizational value than the actual “solution”.

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Observations

Executives at the very highest level of the organization often have good insight on model correctness (or lack thereof) and intuitively understand the value of sensitivity analysis …

… if such information is presented in an efficient and effective manner.