Quo vadis? Estimating shipping distances to products’ point-of-use

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Quo vadis? Estimating shipping distances to products’ point-of-use Katrina Smith-Mannschott Christoph Koffler, PhD


Quo vadis? Estimating shipping distances Evenly distributed consumer goods

Pulp & paper

Processed foods

Personal care

Consumer electronics Home improvement

Apparel

Beverages

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Automobiles

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Quo vadis? Estimating shipping distances The distribution problem warehousing

mostly unknown

retailers

distribution centers

producer

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Quo vadis? Estimating shipping distances Modeling the unknown • Primary data collection not feasible for the entire distribution network • One-point assumptions and sensitivity analysis most common

?

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Quo vadis? Estimating shipping distances Research question

How to establish a reasonable estimate of transportation distance from any given point of origin in the continental United States?

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Quo vadis? Estimating shipping distances 12 chosen points of origin

source: www.batchgeo.com

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Quo vadis? Estimating shipping distances 6,683 most populous places (≼ 1,000) as destinations

source: www.census.gov

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Quo vadis? Estimating shipping distances Automated data mining using the cloud

fx = WEBSERVICE

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Quo vadis? Estimating shipping distances

12 points of origin x 6,683 destinations = 80,196 data points

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Quo vadis? Estimating shipping distances Average distances Average transportation distance to the 6,683 most populous places in the continental U.S. Portland, OR

1,951

Portland, ME

1,730

New York, NY

1,447

Minneapolis, MN

1,208

Miami, FL

1,683

Los Angeles, CA

1,630

Denver, CO

1,198

Dallas, TX

1,106

Chicago, IL

1,079

Charlotte, NC

1,255

Billings, MT

1,489

Albuquerque, NM

1,223

Weighted averages Unweighted averages

0

500

1,000

1,500

2,000

2,500

3,000

[miles]

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Quo vadis? Estimating shipping distances How many are enough? Deviation from baseline for smaller sample sizes (unweighted) -80%

-60%

-40%

-20%

0%

20%

40%

60%

80% Albuquerque, NM Billings, MT

to the 10 most populous

Charlotte, NC Chicago, IL Dallas, TX Denver, CO

to the 100 most populous

Los Angeles, CA Miami, FL Minneapolis, MN New York, NY

to the 1,000 most populous Portland, ME Portland, OR

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Quo vadis? Estimating shipping distances How many are enough? Deviation from baseline for smaller sample sizes (weighted) -80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

Albuquerque, NM Billings, MT

to the 10 most populous

Charlotte, NC Chicago, IL Dallas, TX Denver, CO

to the 100 most populous

Los Angeles, CA Miami, FL Minneapolis, MN New York, NY

to the 1,000 most populous

Portland, ME Portland, OR

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Quo vadis? Estimating shipping distances Limitations & assumptions • Single point of origin limited to products from one US facility OR products manufactured abroad arriving at US port for distribution

• Results a rather optimistic estimate  real distribution networks will not use the shortest path between origin and destination  distances likely underestimated

• Alaska & Hawaii excluded in current analysis

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Quo vadis? Estimating shipping distances Conclusions • For single-origin products distributed in the entire continental US, average transportations distances range from 1,000 to 2,000 miles depending on the point of origin (±50%).

• Combining census data with automated web queries can help to establish better estimates of distribution distances.

• Using population-weighted averages, it seems sufficient to include the 100 most populous places in the US in the analysis (1.5%).

• Approach can be applied to any point of origin and to subsets of distribution areas.

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Thank you! k.smith-mannschott@pe-international.com c.koffler@pe-international.com

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