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© 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

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Page 1: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Warehouse Operations: Performance

Assessment and Benchmarking

Page 2: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Leon F. McGinnisSchool of Industrial

and Systems Engineering

Georgia Tech

Page 3: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Competition

Page 4: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Collaboration

Page 5: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

It makes good economic sense to collaborate on infrastructure standards that “lift all boats”

It also makes good economic sense to collaborate on

improving warehousing and distribution infrastructure

Page 6: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Warehousing in general is 2-5% of cost of goods sold

A 20% improvement in warehouse efficiency goes straight to the

bottom line…

Page 7: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Old Way to Improve Warehousing

Page 8: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

New Way to Improve Warehousing

www.isye.gatech.edu/ideas

Page 9: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Warehouse Operations

Receiving Function

Unload

Inspect

Put Away

Shipping Function Pack

Order Pick

StorageFunction

• Consume resources:– Space– Equipment (and

software)– Labor– Inventory

• Produce services– Customer orders

filled– Replenishment

orders received– Value adding services– Returns processedLoad

Page 10: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

iDEAs Provides:

• An “SAT-like” score, evaluating overall resource efficiency, based on “fantasy league” warehouse constructed from a large peer group ONLINE

• A comparative analysis of partial productivities, relative to the best in the peer group, identifying the “true” opportunity for improvement ONLINE

• An industry-level analysis of key factors affecting resource efficiency OFFLINE

Page 11: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Htmldocuments

Solver

Database

At your siteAt your site

Georgia Tech ServerGeorgia Tech Server

Over the InternetOver the Internet

Your data is private and

secure

How Does iDEAs Work?

Page 12: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Key Points

• Process is secure: nobody ever sees individual company data, except for the research team

• Process is inexpensive:– Free version:

www.isye.gatech.edu/ideas– BISG-sponsored version: contact Jeff

Abraham at BISG to subscribe– These two versions are different!

Page 13: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Page 14: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Page 15: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Page 16: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Page 17: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Your Warehouse “SAT”

Page 18: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Now you know how you compare

What drives your performance?

•To the “best possible”•Ranking in the peer group

Page 19: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Partial Efficiency (PE) Analysis

• PE can be decomposed into 7 multiplicative factors including DEA.

• Partial Efficiency

=Technical Efficiency

Technical Change

Scale Efficiency

Input Slack Factor

Input Substitution Factor

Output Slack Factor

Output Substitution Factor

waste

can be fixed, long term

not a warehouse issue

excessive resourceswrong mix of resources

overproduce some services

wrong mix of services

Page 20: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Page 21: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

The Basic iDEAs

• One system efficiency score• Relative to the “best possible” based on a

specified peer group• Partial efficiency analysis

Page 22: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Over 600 warehouse records in our database

Over 180 qualified users

Roughly 60 “extended” warehouse records

Page 23: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Benchmarking and Best Practices

Illust

ratio

n Purp

oses O

nly!

Page 24: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Are there measurable factors that “explain” efficiency

performance?

Quality of laborNumber of customers

Response time requirementsInventory turnover

etc

Page 25: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Seasonality Data

0

0.2

0.4

0.6

0.8

1

1.2

1 1.5 2 2.5 3 3.5 4 4.5 5

Seasonality (Peak Month Demand divided by Average Month Demand)

Effic

iency

_

Page 26: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Seasonality EffectAverage Effi ci ency (Based on 52

DMUs and 4x5 model ) vs Seasonal i ty

0. 4

0. 5

0. 6

0. 7

0. 8

0. 9

1

1. 1

1. 2

0 0. 5 1 1. 5 2 2. 5 3 3. 5 4Seasonal i ty

Effici

ency

Page 27: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Labor Turnover Effect

Average (over 31 DMUs) Efficiency (Based on 54 DMUs

and 4x5 model) vs. Labor Turnover without 1s

0

0.2

0.4

0.6

0.8

1

0 20 40 60 80 100

Labor Turnover (%)

Effi

cien

cy

Page 28: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Inventory Turnover EffectAverage (over 42 DMUs) Effi ci ency (Based on 42 DMUs and 4x5 model )

vs. I nventory Turns

y = 0. 0574x + 0. 5062R2 = 0. 9993

0

0. 5

1

1. 5

2

2. 5

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

I nventory Turns

Effici

ency

Page 29: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Where do we go from here?

Page 30: © 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking

© 2005 Georgia Tech

Questions?

http://www.isye.gatech.edu/ideas

[email protected]