H_M Business Analysis & Decision Making

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Supplier selection and order allocation for H&M Andrea Bendandi 774610 Carol Bortolotto 774431 Marco Cersosimo 773626 Alberto Giannone 774434

Transcript of H_M Business Analysis & Decision Making

Page 1: H_M Business Analysis & Decision Making

Supplier selection and order

allocation for H&M

Andrea Bendandi 774610Carol Bortolotto 774431Marco Cersosimo 773626Alberto Giannone 774434Marta Pozzar 774609

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□Swedish multinational fashion retailer

□Second biggest retailer□Two main collections

per year plus some sub-collections to meet fashion trends

Introduction

H&M does NOT own any factories, but it outsources manufacturing to more than 800 independent suppliers in Europe and Asia

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Problem Identification Supplier selection and order allocation

□ obtain the number of products j ordered from supplier i and delivered with k transportation channels

Train = 1 Ship = 2□ minimizing the total costs and respecting the budget

□ respect H&M’s demand□ respect the production capacity □ not go below the minimum inventory of each supplier,

otherwise penalty costs would be applied□ consider custom fees □ and costs deriving from suppliers’ lead times□ total deliveries by train should not exceed 10%□ at least 20% of products for each category should be ordered

from European suppliers□ suppliers should not exceed the maximum limit of CO2

emissions

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Variables number of products j ordered from supplier i delivered with k transportation channel

𝑢𝑖={1 ,0 ,if the order from supplier is less than otherwise

if supplier is selectedotherwise

if both and are 1otherwise

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Objective function

Product cost

Security cost

Transportation cost

Custom fees Penalty cost

Minimize z =

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Origin Constraint□At least 20% of each product 𝑗 must be

ordered from European suppliers

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Transportation constraint□We decided to consider two types of

transportation means: train and ship. Indeed they are most environmentally friendly and efficient means of transportation

□Transportation by ship is more secure than the train

□Therefore we assumed that no more than 10% of deliveries can be completed via train, while the remaining 90% will occur via sea

∑𝑖=1

𝑛

∑𝑗=1

𝑚

𝑥 𝑖𝑗2−0,1×∑𝑖=1

𝑛

∑𝑗=1

𝑚

∑𝑘=1

𝑝

𝑥 𝑖𝑗𝑘≤0 (𝑡𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡𝑎𝑡𝑖𝑜𝑛𝑐𝑜𝑛𝑠𝑡𝑟𝑎𝑖𝑛𝑡 )

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Transportation costs□ Since the transportation cost is based on the

volume in m3, we have estimated the total volume for each product.

□ After that we assigned the costs of delivery involved from European and Asian countries

□ Finally, we multiplied each volume of product with the cost of transportation

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Security cost□First component: risk of each supplier multiplied

by the value of the products□Second component: risk of each mean of

transportation multiplied by the cost of transportation

□Finally we added the first with the second component

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Custom fees□Custom fees are applied whenever the firm

imports goods from extra European countries

□Custom fees have been calculated as 12% of the value of goods

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Max n° of Supplier Constraint□ Maximum number of suppliers 𝑖

that can be selected, according to H&M’s corporate policy

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Final Constraints

 

, ,

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Sensitivity analysis

1. Increasing the limit of trains to 50% increases the amount of products delivered by train.

□ Aim: understand how our variables impact on the order allocation and objective function

Total costs decrease by 1.47%

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Sensitivity analysis2. We ignored the 20% limit of firms in europe - Most of the production would be then allocated

to Asian suppliers- Problem: clashes with the need to have close

production facilities for urgent orders

Total costs decrease by 10.72%

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Sensitivity analysis3. No cap of maximum 8 suppliers and each supplier respects the maximum emissions of CO2- Inefficient order allocations- Penalty costs applied because of orders not

reaching suppliers’ minimum inventory levels

Total costs increase by 6.31%

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Limitations

□ Suppliers produce all the products indifferently and the product offering has been simplified compared to H&M’s actual collection

□ Only 12 suppliers were considered in the model due to technical limitations of Excel

□ Adopting pollution per capita in suppliers’ evaluation, due to the lack of relevant data linked to unitary production emissions

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Strengths of the model□ We tailored our model to H&M’s needs

□ Fast fashion industry companies mainly localize the production of basic items in Asia, whereas seasonal collections come from Europe

□ Sustainability issues that relate to H&M’s environmental standards.

□ The reliability of each supplier in terms of the rate of non delivery toincorporate the qualitative factor of supplier risks

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Thank you!