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© 2005 Georgia Tech Warehouse Operations: Performance Assessment and Benchmarking
© 2005 Georgia Tech Leon F. McGinnis School of Industrial and Systems Engineering Georgia Tech
© 2005 Georgia Tech Competition
© 2005 Georgia Tech Collaboration
© 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
© 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…
© 2005 Georgia Tech Old Way to Improve Warehousing
© 2005 Georgia Tech New Way to Improve Warehousing
© 2005 Georgia Tech Warehouse Operations Receiving Function Unload Inspect Put Away Shipping Function Pack Order Pick Storage Function Consume resources: –Space –Equipment (and software) –Labor –Inventory Produce services –Customer orders filled –Replenishment orders received –Value adding services –Returns processed Load
© 2005 Georgia Tech iDEAs Provides: An SAT-like score, evaluating overall resource efficiency, based on fantasy league warehouse constructed from a large peer groupONLINE 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
© 2005 Georgia Tech Html documents Solver Database At your site Georgia Tech Server Over the Internet Your data is private and secure How Does iDEAs Work?
© 2005 Georgia Tech Key Points Process is secure: nobody ever sees individual company data, except for the research team Process is inexpensive: –Free version: –BISG-sponsored version: contact Jeff Abraham at BISG to subscribe –These two versions are different!
© 2005 Georgia Tech
Your Warehouse SAT
© 2005 Georgia Tech Now you know how you compare What drives your performance? To the best possible Ranking in the peer group
© 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 resources wrong mix of resources overproduce some services wrong mix of services
© 2005 Georgia Tech
The Basic iDEAs One system efficiency score Relative to the best possible based on a specified peer group Partial efficiency analysis
© 2005 Georgia Tech Over 600 warehouse records in our database Over 180 qualified users Roughly 60 extended warehouse records
© 2005 Georgia Tech Benchmarking and Best Practices Illustration Purposes Only!
© 2005 Georgia Tech Are there measurable factors that explain efficiency performance? Quality of labor Number of customers Response time requirements Inventory turnover etc
© 2005 Georgia Tech Seasonality Data
© 2005 Georgia Tech Seasonality Effect
© 2005 Georgia Tech Labor Turnover Effect
© 2005 Georgia Tech Inventory Turnover Effect
© 2005 Georgia Tech Where do we go from here?
© 2005 Georgia Tech Questions?
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