Modeling Warehouse Capacity to Support Monthly S&OP Global retailer uses detailed DC models to predict capacity bottlenecks and support monthly S&OP process and long-term investment and tactical planning Challenge Solution A large global retailer of athletic shoes and apparel wanted to have a more detailed view into capacity within its four primary European DCs in order to improve resource utilization, support monthly S&OP planning and reduce penalty costs. The company had monthly volume/productivity data but no real connection to corresponding capac- ity. High intra-month variations in processing capacity as well as machine bottlenecks were constraining DC productivity. Product is sourced globally, stored and processed in four European DCs and then shipped to customers via 3PLs. Each of the four DCs is dedicated to a specific product category. Processing at DCs includes: • Full case • Repack and picking • Value-added services (VAS) including customer labeling/tagging and hanging • E-commerce The company worked with the LLamasoft solutions team to build a detailed short-term model of processing activity within the four DCs, using LLama- soft ® Supply Chain Guru ® . The model included a weekly view of volume requirements and a detailed view of product flow in each DC as well as 3PL capacity in order to: • Predict capacity requirements for expected customer deliveries • Identify the best split to improve resource utilization and level processing • Support the monthly S&OP process—supporting decisions on the amount of product to be pulled forward (i.e. sold earlier), or hold off inbound (i.e. process it later) Model inputs included staff productivity, staff to infrastructure ratio, infrastructure efficiency and number of “effective” available work hours per period. CASE STUDY: REtAIl InduStRy © 2014 llamasoft, Inc. All rights reserved. v.031114 High-level model flow
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Modeling Warehouse Capacity to Support Monthly S&OPGlobal retailer uses detailed DC models to predict capacity bottlenecks and support monthly S&OP process and long-term investment and tactical planning
Challenge
Solution
A large global retailer of athletic shoes and apparel wanted to have a more detailed view into capacity within its four primary European DCs in order to improve resource utilization, support monthly S&OP planning and reduce penalty costs. The company had monthly volume/productivity data but no real connection to corresponding capac-ity. High intra-month variations in processing capacity as well as machine bottlenecks were constraining DC productivity.
Product is sourced globally, stored and processed in four European DCs and then shipped to customers via 3PLs. Each of the four DCs is dedicated to a specific product category. Processing at DCs includes:
•Fullcase
•Repackandpicking
•Value-addedservices(VAS)includingcustomerlabeling/taggingandhanging
•E-commerce
The company worked with the LLamasoft solutions team to build a detailed short-term model of processing activity within the four DCs, using LLama-soft® Supply Chain Guru®. The model included a weekly view of volume requirements and a detailed view of product flow in each DC as well as 3PL capacity in order to:
•Predictcapacityrequirementsforexpected
customer deliveries
•Identifythebestsplittoimproveresource
utilization and level processing
•SupportthemonthlyS&OPprocess—supportingdecisionsontheamountof
producttobepulledforward(i.e.soldearlier),orholdoffinbound(i.e.processitlater)
Model inputs included staff productivity, staff to infrastructure ratio, infrastructure efficiency and number of “effective” available work hours per period.
CASE STUDY: REtAIlInduStRy
©2014llamasoft,Inc.Allrightsreserved.v.031114
High-level model flow
ResultsBy separating capacity data by DC, the model allowed the company to balance inbound and outbound volumes, thus creating a positive or negative net effect on inventories. This model is used on an ongoing basis to support monthly decision making. Benefits include:
•Improvedaccuracyinpredictingcapacitybottlenecks
•Fasteranalysisturnaround
•Betterlevellingofprocessingrequirementsthroughoutthemonthand
throughout DCs
•Reducedfrequencyandvolumeofpenaltycostsforovertime,offsite
storage and trailer rentals
CASE STUDY: REtAIlInduStRy
LLamasoft, Inc.
201 South Main Street, Suite 400
Ann Arbor, Michigan 48104, USA
Phone: +1 866.598.9831
LLamasoft.com
©2014llamasoft,Inc.Allrightsreserved.v.031114
•Modelingframeworkformakinglong-termwarehouseinfrastructureimprovements
Examplemodeloutputgraphic
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