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Modeling Fashion Retail Supply Chain through Causal Loop Diagram
Information Control Problems in Proceedigs of the 15th IFAC Symposium on Information Control Problems in Manufacturing Manufacturing Proceedigs of theOttawa, 15th IFAC Symposium on May 11-13, Canada Information Control Problems in Manufacturing Proceedigs of theOttawa, 15th IFAC Symposium on May 11-13, 2015. 2015. Canada Information Control Problems in Manufacturing Available online at www.sciencedirect.com May 11-13, 2015. Ottawa, Canada Information Control Problems in Manufacturing May 11-13, 2015. Ottawa, Canada May 11-13, 2015. Ottawa, Canada
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IFAC-PapersOnLine 48-3 (2015) 1290–1295 Supply Chain Modeling Fashion Retail Modeling Fashion Retail Chain Modeling Fashion Supply Chain through CausalRetail Loop Supply Diagram Modeling Fashion Retail Supply Chain through Causal Loop Diagram through Causal Loop Diagram through Causal LoopSalvatore Diagram Raffaele Miranda, Raffaele Iannone, Iannone, Giada Giada Martino, Martino, Salvatore Miranda,
Stefano RiemmaSalvatore Raffaele Martino, Stefano Riemma Raffaele Iannone, Iannone, Giada Giada Martino, Salvatore Miranda, Miranda, Raffaele Iannone, Giada Martino, Salvatore Miranda, Stefano Riemma Stefano Riemma Stefano Riemma Department Engineering, University Department of of Industrial Industrial Engineering, University of of Salerno, Salerno, via via Giovanni Paolo II, 132, 84084, Fisciano (SA) Italy (e-mail: Department of Industrial Engineering, University of Salerno, via Giovanni Paolo II, 132, Engineering, 84084, Fisciano (SA) - of Italy (e-mail: Department of Industrial University Salerno, via Department of Industrial Engineering, University of Salerno, via [email protected]) Giovanni Paolo II, 132, 84084, Fisciano (SA) Italy (e-mail: [email protected]) Giovanni Paolo II, 132, 84084, Fisciano (SA) - Italy (e-mail: Giovanni Paolo II, 132, 84084, Fisciano (SA) - Italy (e-mail: [email protected]) [email protected]) [email protected]) Abstract: Abstract: The The increasing increasing request request for for speed speed and and efficiency efficiency in in today’s today’s Fashion Fashion and and Apparel Apparel Retail Supply Chains, is adding more and more complexity to the system which asks for Abstract: The increasing request for speed and efficiency in today’s Fashion and Apparel Retail Supply Chains, is adding more and more complexity to the system which asks for high high Abstract: The increasing request for speed and efficiency in today’s Fashion and Apparel Abstract: The increasing request forand speed and efficiencyto inthe today’s Fashion and Apparel product availability and quick response to always changing market demand. In this context, Retail Supply Chains, is adding more more complexity system which asks for high product availability and quick response to always changing market demand. In this context, Retail Supply Chains, is adding more and more complexity to the system which asks for high Retail Supply Chains, is adding more and more complexity to the system which asks for high using System Thinking approach, this paper aims at developing a Causal Loop Diagram for product availability and quick response to always changing market demand. In this context, using System Thinking this paper aims changing at developing a Causal Loop Diagram for product availability andapproach, quick response to always market demand. In this context, product availability and quick response to always changing market demand. In this context, the definition of the cause and effect relationships between the several variables which define using System Thinking approach, this paper aims at developing a Causal Loop Diagram the definition of the cause and effect relationships between the several variables which define using System Thinking approach, this paper aims at developing a Causal Loop Diagram for for using System Thinking approach, this paper variable aims between at in ain Loop which Diagram for the under exam. Being a this field, fact, dynamic complexity definition of the the cause andtime effect relationships the several variables define the system under exam. Being time a crucial crucial variable indeveloping this the field, inCausal fact, dynamic complexity the system definition of cause and effect relationships between several variables which define the definition of the cause and effect relationships between the several variables which define arises due to interaction of agents over time and evolving situations. In this context, our work system under exam. Being time a crucial variable in this field, in fact, dynamic complexity arises due to interaction of agents time and evolving situations. In this context,complexity our work the system under exam. Being timeover a crucial variable in this field, in fact, dynamic the system under exam. all Being time a crucial variable inthat this field, be in fact, dynamic complexity highlights analyses conflicting requirements must accurately evaluated and arises due and to interaction of the agents over time and evolving situations. In this context, our work work highlights and analyses all the conflicting requirements that must be accurately evaluated and arises due to interaction of agents over time and evolving situations. In this context, our arises duein toorder interaction of the agents over the time and evolving situations. In thisto context, our work balanced to effectively manage complex network of retailers and help the decision highlights and analyses all conflicting requirements that must be accurately evaluated and balanced in order to effectively manage the complex network of retailers and to help the decision highlights and analyses all the conflicting requirements that must be accurately evaluated and highlights and analyses all the conflicting requirements that ofmust be accurately evaluated and making process behind the purchasing, delivery and replenishment steps. balanced in order to effectively manage the complex network retailers and to help the decision making process behind the purchasing, delivery and replenishment steps. balanced in order to effectively manage the complex network of retailers and to help the decision balanced in orderbehind to effectively manage the complex of retailers and to help the decision making process process the purchasing, purchasing, delivery andnetwork replenishment steps. making behind the delivery and replenishment steps. making process behind the purchasing, delivery and replenishment steps. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rightsApparel reserved. Keywords: Keywords: System System Thinking, Thinking, System System Dynamics, Dynamics, Causal Causal Loop Loop Diagram, Diagram, Fashion Fashion and and Apparel Industry, Retail, Supply Chain Keywords:Retail, SystemSupply Thinking, System Dynamics, Dynamics, Causal Causal Loop Loop Diagram, Diagram, Fashion Fashion and and Apparel Apparel Industry, Chain Keywords: System Thinking, System Keywords: SystemSupply Thinking, System Dynamics, Causal Loop Diagram, Fashion and Apparel Industry, Retail, Retail, Chain Industry, Supply Chain Industry, Retail, Supply Chain 1. normally 1. INTRODUCTION INTRODUCTION normally do do not not change change quickly quickly over over time time and and have have a a stable stable and predictable demand, innovative products, like fash1. INTRODUCTION normally do not change quickly over time and have a stable and predictable demand, innovative products, like fash1. INTRODUCTION normally do not change quickly over time and have a stable 1. Apparel INTRODUCTION normally do not quickly over time and have avariety stable ion are characterized by newness, greater and apparel, predictable demand, innovative products, like fashToday, (F&A) ion apparel, are change characterized by newness, greater variety Today, Fashion Fashion and and Apparel (F&A) Supply Supply Chains Chains (SC) (SC) and predictable demand, innovative products, like fashand predictable demand, innovative products, like fash(Vaagen and Wallace, 2008) and customisation (De Feion apparel, are characterized by newness, greater variety are more strategically important than ever before, due Today, Fashion and Apparel (F&A) Supply Chains (SC) (Vaagen andare Wallace, 2008) and customisation Feare more strategically important than ever Chains before, (SC) due ion apparel, characterized by newness, greater(De variety Today, Fashion and Apparel (F&A) Supply ion apparel, are characterized by newness, greater variety lice et al., 2012) which needs low production volumes (Vaagen and Wallace, 2008) and customisation (De FeToday, Fashion and Apparel (F&A) Supply Chains (SC) to added pressure brought by globalization (De Felice are more strategically important than ever before, due lice et al., 2012) which needs low production volumes to added pressure brought by globalization (De Felice and Wallace, 2008) and customisation (De Feare more strategically important than ever before, due (Vaagen (Vaagen and Wallace, 2008) andlow customisation (De Fe(De Carlo et al., 2013) and flexibility (Sammarco et al., lice et et al., 2012) which needs production volumes are more strategically important than ever et before, due lice and Petrillo, 2013) and digitalization (Abtan al., 2013) to added pressure brought by globalization (De Felice (De Carlo et al., 2013) and flexibility (Sammarco et al., and Petrillo, 2013) and digitalization (Abtan et al., 2013) 2012) which needs low production volumes to added pressure brought by globalization (De Felice lice et al., al., 2012) which needs low production volumes 2014) and makes demand unpredictable (Wang et al., (De Carlo et al., 2013) and flexibility (Sammarco et to added pressure brought by globalization (De Felice and by the growth of Quick Response and Fast Fashion Petrillo, 2013) and digitalization (Abtan et al., 2013) 2014) and makes demand unpredictable (Wang et al., and by the growth of Quick Response and Fast Fashion (De Carlo et al., 2013) and flexibility (Sammarco et al., and Petrillo, 2013) and digitalization (Abtan et al., 2013) (De Carlo et al., 2013) and flexibility (Sammarco et 2012). In their cycle 2009), 2014) and and makes demand demand unpredictable (Wang et et al., and Petrillo, 2013) and digitalization (Abtan etcontribute al., 2013) 2014) (Bhardwaj Fairhurst, 2009). These issues by the the and growth of Quick Quick Response and Fast Fashion 2012). In addition, addition, their life life unpredictable cycle is is short short (Barnes, (Barnes, 2009), (Bhardwaj and Fairhurst, 2009). These issues contribute makes (Wang al., and by growth of Response and Fast Fashion 2014) and makes demand unpredictable (Wang et al., because as imitators erode the competition advantage that 2012). In addition, their life cycle is short (Barnes, 2009), and by the growth of Quick Response and Fast Fashion to add complexity to the whole system which must respond (Bhardwaj and Fairhurst, 2009). These issues contribute because as imitators erode the competition advantage that to add complexity to the whole system which must respond 2012). In addition, their life cycle is short (Barnes, 2009), (Bhardwaj and Fairhurst, 2009). These issues contribute 2012). life cycle is short (Barnes, innovative products enjoy, companies are to introbecauseInas asaddition, imitators erode the competition advantage that (Bhardwaj Fairhurst, 2009). These issues contribute quickly and efficiently to always changing market demand to add add complexity complexity to the the whole system which must respond because innovative productstheir enjoy, companies are forced forced to 2009), introquickly and and efficiently towhole always changing market demand imitators erode the competition advantage that to to system which must respond because as imitators erode the competition advantage that duce a steady stream of newer innovations. innovative products enjoy, companies are forced to introto add complexity to the whole system which must respond (Battista and Schiraldi, 2013). quickly and efficiently to always changing market demand duce a steady stream of newer innovations. (Battista and Schiraldi, 2013). innovative products enjoy, companies are forced to introquickly and efficiently to always changing market demand innovative products enjoy, companies are forced to introWith peculiarities, F&A products duce aathese steady stream of of newer newer innovations. quickly efficiently to2013). always demand In this context, purpose of work to aa duce (Battista and Schiraldi, With these peculiarities, F&A innovations. products require require a a fundafundaIn this and context, purpose of this thischanging work is is market to construct construct steady stream (Battista and Schiraldi, 2013). duce athese steady stream ofthan newer innovations. mentally different SC do stable, functional prodWith peculiarities, F&A products require a funda(Battista andDiagram, Schiraldi, 2013). Causal Loop through the application of System In this context, purpose of this work is to construct a mentally different SC than do stable, functional prodCausal Loop Diagram, through the application of System these peculiarities, F&A products require a fundaIn this context, purpose of this work is to construct a With With these peculiarities, F&A products require aon fundaucts. While an efficient SC strategy with focus cost mentally different SC than do stable, functional prodIn this Loop context, purpose offor this work is to of construct a mentally Dynamics (SD) principles, the definition the cause Causal Diagram, through the application of System ucts. While an efficient SC strategy with focus on cost Dynamics (SD) principles, for the definition of the cause SC than do stable, functional prodCausal Loop Diagram, through the application of System mentally different different SC than do stable, functional prodminimization should be used for functional products, ucts. While an efficient SC strategy with focus on costa Causal Loop Diagram, through the application of System and effect relationships between the several factors which Dynamics (SD) principles, for the definition of the cause minimization should be used for functional products, and effect relationships between the several factors which ucts. While an efficient SC strategy with focus on cost Dynamics (SD) principles, for the definition of the cause ucts. While an efficient SC strategy with focus on costa responsive/demand driven SC strategy with focus on prodminimization should be used for functional products, Dynamics (SD) principles, for the definition of the cause define a typical F&A Retail Supply Chain. and effect relationships between the several factors which responsive/demand driven SC strategy with focus on proddefine a typical F&A Retail Supply should be used for functional products, aa and effect relationships between the Chain. several factors which minimization minimization should be used for functional products, ucts availability, matching the marketplace customer responsive/demand driven SC strategy with with focus on prodprod-a and effect relationships between the several factors which responsive/demand Motivation behind this research is to help the decision define a typical F&A Retail Supply Chain. ucts availability, matching the strategy marketplace with customer Motivation behind this research is to help the decision driven SC with focus on define a typical F&A Retail Supply Chain. responsive/demand driven SC strategy with focus on proddemands, could best fit innovative products (Lam and ucts availability, matching the marketplace with customer define a typical F&A Retail Supply Chain. making process behind purchasing, delivery and Motivation behind this the research is to to help help the decision decision demands, could matching best fit innovative products and making process behind the purchasing, delivery and rere- ucts availability, the marketplace with(Lam customer Motivation behind this research is the ucts availability, matching the marketplace with customer Postle, 2006). A demand driven SC must offers real-time demands, could best fit innovative products (Lam and Motivation behind this research is to help the decision plenishment steps of a company that manages an extended making process behind the purchasing, delivery and rePostle, 2006). A demand driven SC must offers real-time plenishment steps of a company that manages an extended demands, could best fit innovative products (Lam and making process behind the purchasing, delivery and re- demands, could best fit innovative products (Lam and information inventory levels in order Postle, 2006). 2006).on Ademand demandand driven SC must must offers real-time making process the purchasing, delivery andprore- Postle, network of operated mono-brand retailers. plenishment stepsbehind of aa company company that manages manages an This extended information onA demand and inventory levels in real-time order to to network of direct direct operated mono-brand retailers. This prodemand driven SC offers plenishment steps of that an extended Postle, 2006).onA demand driven SC must offers real-time react quickly and effectively when unexpected changes information demand and inventory levels in order to plenishment steps of adynamic company that manages an This extended cess must be highly due to constantly changing network of direct operated mono-brand retailers. proreact quickly and effectively when unexpected changes cess must be highly dynamic due to constantly changing on demand and inventory levels in order to network of direct operated mono-brand retailers. This pro- information information on demand and inventory levels in order to arises (Budd et al., 2012). react quickly quickly and effectively when unexpected unexpected changes network of be direct operated mono-brand retailers. This pro- react conditions, such as market demand, thus adding comcess must highly dynamic due to constantly changing arises (Budd et al., 2012). conditions, such as market demand, thus adding comand effectively when changes cess must be highly dynamic due to constantly changing react quickly and effectively when unexpected changes arises (Budd (Budd et et al., al., 2012). 2012). cess must besuch highly due to changing plexity to whole system the strong interactions conditions, as dynamic market given demand, thus adding adding com- arises plexity to the the whole system given theconstantly strong interactions conditions, such as market demand, thus comarises (Budd et al., 2012). conditions, such as market demand, thus adding combetween factors. plexity to the whole system given the strong interactions betweentofactors. 1.2 Principles Principles of of System System Thinking Thinking and and System System Dynamics Dynamics plexity the whole system given the strong interactions 1.2 plexity tofactors. the wholeintroduction system given interactions Then, after a of peculiarities of between Then, after a brief brief introduction of the the strong peculiarities of the the 1.2 in Chain Management 1.2Supply Principles of System Thinking and System Dynamics in Supply Chain Management between factors. Principles of System Thinking and System Dynamics between factors. Fashion Industry and a summary of the SD principles, we Then, after a brief introduction of the peculiarities of the 1.2 Principles of System Thinking and System Dynamics Fashion Industry and a summary of the SD principles, we in Supply Chain Management Then, after a brief introduction of the peculiarities of the in Supply Chain Management Then, a briefand introduction ofofthe the define the background our and describe Fashionafter Industry summary thepeculiarities SD principles, principles, we System in Supplydynamics Chain Management define the background of our research research and describeof into into (SD) Fashion Industry and aa of summary of the SD we System dynamics (SD) is is aa methodology methodology developed developed by by Fashion Industry and a summary of the SD principles, we details the proposed Causal Loop Diagram. define the background of our research and describe into details the the background proposed Causal Loop Diagram. Forrester to understand the structure and dynamics of System dynamics dynamics (SD) is a methodology developed by define of our research and describe into System Forrester to understand the structure and dynamics of (SD) is a methodology developed by define of our research and describe into complex details the the background proposed Causal Causal Loop Diagram. System dynamics (SD) isthe a1961). methodology developed by systems (Forrester, This approach has been Forrester to understand structure and dynamics of details the proposed Loop Diagram. complex systems (Forrester, 1961). This approach has been Forrester to understand the structure and dynamics of details the proposed Causal Loop Diagram. 1.1 Forrester to understand the1961). structure and dynamics of used in several fields, from project management (Toole, complex systems (Forrester, This approach has been 1.1 Demand Demand Driven Driven Fashion Fashion Supply Supply Chain Chain used in several fields, from project management (Toole, complex systems (Forrester, 1961). This approach has been 1.1 Demand Demand Driven Driven Fashion Fashion Supply Supply Chain Chain complex systems (Forrester, 1961). This been 2005) and SC et al., 2003) product used in in several fields, from(Gnoni project management (Toole, 2005) and SC management management (Gnoni et management al.,approach 2003) to tohas product 1.1 used several fields, from project (Toole, 1.1 Demand Driven Fashion Supply Chain used several fields, (D’Amico from(Gnoni project management (Toole, life-cycle management et al., 2013) and capacity According 2005)in and SC management et al., 2003) to product life-cycle management (D’Amico et al., 2013) and capacity According to to Fisher Fisher (1997), (1997), products products can can be be divided divided into into 2005) and SC management (Gnoni et al., 2003) to product 2005) andmanagement SC management (Gnoni et 2003) toa product planning (Vlachos et 2007), describes system two categories: either primarily functional primarily life-cycle (D’Amico etand al.,al., 2013) and capacity According to Fisher Fisher (1997), products can be be or divided into life-cycle planning (Vlachos et al., al., 2007), and describes acapacity system two categories: either primarily functional or primarily management (D’Amico et al., 2013) and According to (1997), products can divided into life-cycle management (D’Amico et al., 2013) and capacity According to Fisher (1997), products can be divided into behaviour through the structure of its feedback loops. innovative. While functional products, such as grocery, planning (Vlachos et al., 2007), and describes a system two categories: either primarily functional or primarily behaviour through the structure of its feedback loops. innovative. While functional products, such as grocery, two categories: either primarily functional or primarily planning (Vlachos et al., 2007), and describes a system planning (Vlachos et al., 2007), ofand describes a system two categories: either primarily functional orasprimarily behaviour through the structure its feedback loops. innovative. While functional products, such grocery, innovative. While functional products, such as grocery, behaviour through the structure of its feedback loops. innovative. While Copyright © 2015 IFACfunctional products, such as grocery,1354behaviour through the structure of its feedback loops. Copyright © 2015 IFAC 1354 2405-8963 © IFAC (International Federation of Automatic Control) Copyright © 2015, 2015 IFAC 1354Hosting by Elsevier Ltd. All rights reserved. Copyright 2015 responsibility IFAC 1354Control. Peer review© of International Federation of Automatic Copyright ©under 2015 IFAC 1354 10.1016/j.ifacol.2015.06.263
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Basic elements of this methodology are causal loop diagrams and stock and flows diagrams. The first ones represent the feedback structure of the system while stock and flow diagrams are tools for assessing variables dynamics through a period (Gnoni and Lanzilotto, 2012). Main elements of these diagrams are (Sterman, 2000), (Georgiadis et al., 2006): • Variables which are relevant for the system description; • Oriented arches which suggest causal relationships. The + and - sign indicate that the effect is positively or negatively related to the cause; • Positive loops: they are self-reinforcing loops, identified with R. In a positive feedback loop, an initial disturbance leads to further change, suggesting the presence of an unstable equilibrium; • Negative loops: they are self-correcting or balancing loops, identified with B. In a negative feedback loop, after a disturbance, the system seeks to return to an equilibrium situation; • Delays which describe the inertia of physical system, according to which it is not possible that a quantity changes instantaneously; • Stocks which represent quantities that are accumulated or disposed over time; • Flows which indicate an entity flow from/to one or more Stocks. All these elements will be part of the Causal Loop Diagram (CLD) which graphically illustrates causal relationships and major feedback loops among variable of the system. The construction of a CLD for the description of the planning, purchasing, supply and replenishments processes of a Fashion Retail SC is the main goal of this research work and will be described into detail in next section. 2. A CAUSAL LOOP DIAGRAM FOR THE FASHION RETAIL INDUSTRY Strategic supply chain management involves a wide spectrum of issues and includes several types of decisionmaking problems, such as the determination of number, location and capacity of warehouses and the flow of material through the logistics network, inventory management policies, distribution strategies, etc. (Georgiadis et al., 2005). All these issues must be constantly faced in the F&A Industry adding complexity due to seasonality of products, fluctuating and unpredictable demand and short product life cycle. 2.1 Motivation behind research Present work aims at defining and modeling SC dynamics in the F&A retail industry and represents a preliminary study for future implementation of the model through simulating tools. Even if no experimental result is presented, this study represents the core of the simulation process since it performs a careful analysis of the problem, setting main goals and issues, and it defines the conceptual model by analysing interactions and causal relationships between variables both graphically and in mathematical terms.
Fig. 1. Planning and Operations steps of the model 2.2 Context and problem description According to Iannone et al. (2013) and Lanzilotto et al. (2014), we divided the main supply chain processes as illustrated in Fig. 1. The Pre Season stage, as the name implies, is performed before the beginning of the selling season and includes all the phases which go from the design of the clothing collection to the first deliveries to the stores. The In Season stage, instead, starts with the first sales recorded in the stores. At this point, after comparing real sales with forecasts, an adjustment process starts. In next sections, we will describe into detail each diagram block together with an economic performance evaluation, identifying variables and related causal relationships. In the diagrams, Stocks will be represented in capital letters while Flows in italic underlined letters. 2.3 Pre Season a) Collection definition and planning Many companies operating in the fashion industry highlight that the most relevant core competences to keep in house are those related to the design phase, which defines material requirements, aesthetic aspect and style of the product (Brun et al., 2008). Then, this phase, also named as New Product Development (NPD) is considered crucial and very time consuming, since it usually begins almost two years before production (Bandinelli et al., 2013). Main output data of the collection definition process which are considered relevant to our model are the Number of Items and their Price. The first variable has a positive relationship with the Number of Suppliers. Since it is likely that each clothing item requires one or more specific manufacturing skills or processes, their production will be committed to the most suitable supplier. To simplify, we can consider that each item is produced by one specific supplier. The variable Price, instead, has a clear relationship of direct proportionality with Revenues. Another significant variable is the Collection Attractiveness, which is evaluated in terms of design, quality and assortment (i.e. the number of different clothing items) but not less significant is the price factor (Mariany et al., 2012). To increase attractiveness there is also
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Marketing Investment (m), intended as the planned investment in advertising and communication campaigns, which is defined as a percentage of the Budget allocated to the entire selling season. b) Forecasting As already mentioned in previous paragraph, demand for fashion items is highly unpredictable, since isolating external effects such as season, weather conditions or mediatic phenomena can be extremely complex (Souza et al., 2014). In last years several sophisticated models have been proposed (Fumi et al., 2013), (Nenni et al., 2013) and most of them use generic algorithms based on the assumption that demand can be predicted uniformly for all companies and across all industries, product lines and geographies. This one-size-fits-all approach yields a forecast that fails to reflect the relative impact of different demand drivers and to adapt as market conditions and consumer behaviours evolve (B. and Caffrey, 2014). Nevertheless, all researchers agree in basing sales forecasting on historical data, which in our case are represented by Demand data of the Previous selling Seasons. This idea is represented in our CLD (refer to Fig. 2) by a delay. It is clear that these demand data are aggregate data coming from all the stores of the network, then the global Demand is positively related to the Number of Stores managed by the company.
Then, the CLD for these first three processes is shown in Fig. 2. d) Delivery The deliveries (or primary transport) from the suppliers to the Central Warehouse (Deliveries to Warehouse - DW ), which are an incoming flow in the Warehouse Stock (SW ), are defined by the Delivery Plan which contains information concerning delivery quantity (Purchase Quantity) and times for each supplier (Number of Suppliers). The first balancing loop (B1) identified in this system is defined between DW and SW . The positive causal relationship (from DW to SW ) is given by the material flow incoming into the warehouse with an unavoidable delay due to Delivery Lead Time increasing with Suppliers Distance. The negative feedback (from SW to DW ), instead, refers to the updating process in the delivery plans: warehouse physical limits, concerning both storage and material handling capacity, must not be overcome, then delivery quantities and times must be revised accordingly. The cost item related to this process is the Primary Transport Cost (CP T ) given by: CP T =
M j=1
(Ctf,j + Ctv,j ∗ QDj ∗ DISTj )
(3)
Where, M is the number of suppliers and, Ctf and Ctv are constant values and are respectively fixed and variable cost for primary transport for the j-th supplier, QD is the quantity delivered and DIST is the distance between suppliers plant and central warehouse. The CLD for this process is showed in Fig. 3.
Fig. 2. Causal relationships for Collection Definition and Planning, Forecasting and Purchasing processes c) Purchasing Main output of the purchasing process is the definition of the global Purchase Quantity for each item included in the collection. The Purchase Cost (CP ) will be then calculated as: CP =
N i=1
Qi ∗ cui
(1)
Where N is the Number of Items, Qi is the Purchase Quantity for the i-th item and cui is the i-th item’s unitary cost (Items cost). It is clear that this cost must fall within the Budget (B) allocated according to the following equation: m + CP ≤ B where m is the Marketing Investment.
(2)
Fig. 3. Causal relationships for Delivery process e) Replenishment In a fast changing environment, such as the fashion one, the generic problem of allocating inventory from a central warehouse to several locations satisfying separate demand streams, is considered the most crucial. This replenishment process (or secondary transport) principally aims at dynamically optimizing the assortment of the stores trying to minimize overstock or out of stock events. In this process we can identify two different balancing loops (refer to Fig. 4): B2) between Warehouse Stock (SW ) and Deliveries to Stores (DS ): • The negative causal relationship (from DS to SW ) is given by the material flow out coming from the warehouse; • The positive feedback (from SW to DS ) is given by the necessity to respect physical warehouse
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limits (refer to Delivery process). In order to avoid overloading of the warehouse, when stocks increase, deliveries to store must become bigger and more intensive. B3) between Deliveries to Stores (DS ) and Stores Stock (SS ): • The positive causal relationship (from DS to SS ) is given by the material flow incoming in the stores, with a delay due to transport lead time increasing with Stores Distance from the warehouse; • The negative feedback (from SS to DS ) is given by the necessity to respect physical internal stores warehouse limits, such as for the central warehouse. This second loop also reflects two conflicting requirements of the fashion retail environment. From one side, given customers impulsive purchasing behaviour, we need to ensure high availability of products, not only in terms of product range but also in sizes and colours. From the other side, higher stock levels may lead to the overloading of internal stores warehouses and consequent related costs, and to the increase in unsold stocks.
2.4 In Season a) Sales The In Season phase starts with the first Sales recorded in the Stores. In this process we can clearly identify a balancing loop (B4) between Demand (d), Sales (s) and Stores Stock (SS ): • The negative causal relationship (from s to SS ) is given by the real Sales which represent a material flow out going from the stores; • The positive causal relationship (from SS to d ) reflects customers impulsive and compulsive purchasing behaviour (refer to Replenishment process), then an increasing demand will be observed with a higher assortment level; • The positive feedback (from d to s) shows the direct proportionality between Demand and Sales (refer to equation 6). In addition, in order to estimate uncensored customer requests, Caro and Gallien (2007) define Demand as the sales that would have been observed had all merchandise been displayed without any stock out. Then we can define the following equation:
The two cost items related to this process are: • Warehouse Management Cost (CM W ): CM W = Cmf +
N i=1
Demand = Sales + Outof Stock (6) The cost item connected to this process is the Stores Management Cost (CM S ):
chi ∗ cui ∗
∗(
M j=1
QD,ij −
L
CM S,k = cmf + QR,ik )
L
k=1
(4)
chi ∗ cui ∗ (QR,i − si )
(7)
Where cmf is the fixed store management cost, chi is the store holding cost for the i-th item expressed as percentage of its value. This value is higher than the same chi for the central warehouse since products stored in the stores can not be used any more for the replenishment of other stores and other possible transfers will generate higher costs. Another variable that must be considered in this process is Revenues (R), expressed as:
k=1
ctf,k + ctv, k ∗ QR,k ∗ distk
N i=1
Where Cmf is the fixed warehouse management cost, chi is the holding cost for the i-th item expressed as percentage of its value and QR is the quantity delivered to the k-th store. • Secondary Transport Cost (CST ): CST =
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(5)
Where, for the k-th store, ctf and ctv are constant values and are respectively fixed and variable cost for secondary transport, QR is the quantity delivered and dist (Stores Distance) is the distance between central warehouse and the k-th store.
R=
N M i=1 j=1
sij ∗ P ri
(8)
The CLD for this process is showed in Fig. 5.
The CLD for this process is showed in Fig. 4.
Fig. 5. Causal relationships for Sales process Fig. 4. Causal relationships for Replenishment process
b) Adjusting Supply and demand are easily matched if demand is steady over time with no change in volume or mix. 1357
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As soon as demand changes, however, a company must adjust the supply levels accordingly at each step of the supply chain (Budd et al., 2012). According to these considerations, the best designed fashion supply chains must be (Abtan et al., 2013): • Fast, demonstrating particular speed in fulfilling customer orders and adapting to changes; • Flexible, creating efficient processes that enable flexibility in the end-to-end supply chain; • Lean, emphasizing effective, low-cost operations. This adjusting process is based on the comparison between real Demand and Forecasts, which allows us to perform two different deviation analysis: • Supply Chain Deviation: it evaluates aggregate data from Warehouse Stock and Stores Stock and, if this deviation is higher than a fixed threshold, the system will update Purchasing Quantity possibly cancelling some orders or issuing new ones; • Replenishment Deviation: through the analysis of current Stores Stock, it evaluates in real time how much Demand was under or over estimated and, if it overcomes a fixed threshold, we will have to adjust the replenishment plans (Deliveries to Stores). The CLD for this process is showed in Fig. 6.
3. CONCLUSION AND PERSPECTIVES Effective management to achieve competitive advantages includes the ability to manage a complex network as a whole. In the fashion industry, the operational strategy consists of ordering, well in advance, a large number of different references, each having a relatively short life cycle of only a few weeks. However, on the contrary, a fashion supply chain must respond quickly to market changes in order to meet customers requests and increase profitability. In this context, this paper proposes a Causal Loop Diagram which describes into detail the conflicting typical needs of the Fashion and Apparel Industry. These opposing requirements, force the management to face several decision making problems in order to find the best definition and mix of all the variables, such as the definition of the Seasonal Budget, the selection of the items composing the collection, the choice of the quantities to be purchased etc., with the aim of maximising profits. The present work only represents a preliminary study since it does not offer any experimental result even if it represents the core of the simulation process. Then, next steps will be the implementation of the model through simulating tools and design of an experimental campaign for the analysis of supply chain performances under different conditions. REFERENCES
Fig. 6. Causal relationships for Adjusting process 2.5 Economic Performance For each Retail SC and, generically, for each Supply Chain, main purpose is the maximization of the Profit (P) expressed as:
P = R − CP − CP T − CM W − CST −
L
k=1
CM S,k − M (9)
The causal relationships representing this economic evaluation are showed in Fig. 7.
Fig. 7. Economic relationship 2.6 The Final Causal Loop Diagram Integrating all the variables and interactions previously described, the final CLD of the system under exam is shown in Fig. 8.
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Fig. 8. The Final Causal Loop Diagram for a Fashion Retail Supply Chain De Felice, F., Gnoni, M.G., and Petrillo, A. (2012). A multi-criteria approach for sustainable mass customisation in the fashion supply chain. International Journal of Mass Customisation, 4. De Felice, F. and Petrillo, A. (2013). Key success factors for organizational innovation in the fashion industry. IJEBM. Fisher, M.L. (1997). What is the right supply chain for your product? Harvard Business Review. Forrester, J.W. (1961). Industrial Dynamics. Pegasus Communications. Fumi, A., Pepe, A., Scarabotti, L., and Schiraldi, M.M. (2013). Fourier analysis for demand forecasting in a fashion company. IJEBM. Georgiadis, P., D., V., and Tagaras, G. (2006). The impact of product lifecycle on capacity planning of closed-loop supply chains with remanufacturing. Production and Operations Management, 15. Georgiadis, P., Vlachos, D., and Iakovou, E. (2005). A system dynamics modeling framework for the strategic supply chain management of food chains. Journal of Food Engineering, 351–364. Gnoni, M., Iavagnilio, R., Mossa, G., and Mummolo, G. (2003). Modelling dynamics of a supply chain under uncertainty: a case from the automotive industry. International Journal of Automotive Technology and Management, 3. Gnoni, M. and Lanzilotto, A. (2012). System dynamics for sustainability analysis of mobile phone reverse logistics. Istanbul - Turkey. Iannone, R., Ingenito, A., Martino, G., Miranda, S., Pepe, C., and Riemma, S. (2013). Merchandise and replenishment planning optimisation for fashion retail. IJEBM, 5.
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IFAC-PapersOnLine 48-3 (2015) 1290–1295 Supply Chain Modeling Fashion Retail Modeling Fashion Retail Chain Modeling Fashion Supply Chain through CausalRetail Loop Supply Diagram Modeling Fashion Retail Supply Chain through Causal Loop Diagram through Causal Loop Diagram through Causal LoopSalvatore Diagram Raffaele Miranda, Raffaele Iannone, Iannone, Giada Giada Martino, Martino, Salvatore Miranda,
Stefano RiemmaSalvatore Raffaele Martino, Stefano Riemma Raffaele Iannone, Iannone, Giada Giada Martino, Salvatore Miranda, Miranda, Raffaele Iannone, Giada Martino, Salvatore Miranda, Stefano Riemma Stefano Riemma Stefano Riemma Department Engineering, University Department of of Industrial Industrial Engineering, University of of Salerno, Salerno, via via Giovanni Paolo II, 132, 84084, Fisciano (SA) Italy (e-mail: Department of Industrial Engineering, University of Salerno, via Giovanni Paolo II, 132, Engineering, 84084, Fisciano (SA) - of Italy (e-mail: Department of Industrial University Salerno, via Department of Industrial Engineering, University of Salerno, via [email protected]) Giovanni Paolo II, 132, 84084, Fisciano (SA) Italy (e-mail: [email protected]) Giovanni Paolo II, 132, 84084, Fisciano (SA) - Italy (e-mail: Giovanni Paolo II, 132, 84084, Fisciano (SA) - Italy (e-mail: [email protected]) [email protected]) [email protected]) Abstract: Abstract: The The increasing increasing request request for for speed speed and and efficiency efficiency in in today’s today’s Fashion Fashion and and Apparel Apparel Retail Supply Chains, is adding more and more complexity to the system which asks for Abstract: The increasing request for speed and efficiency in today’s Fashion and Apparel Retail Supply Chains, is adding more and more complexity to the system which asks for high high Abstract: The increasing request for speed and efficiency in today’s Fashion and Apparel Abstract: The increasing request forand speed and efficiencyto inthe today’s Fashion and Apparel product availability and quick response to always changing market demand. In this context, Retail Supply Chains, is adding more more complexity system which asks for high product availability and quick response to always changing market demand. In this context, Retail Supply Chains, is adding more and more complexity to the system which asks for high Retail Supply Chains, is adding more and more complexity to the system which asks for high using System Thinking approach, this paper aims at developing a Causal Loop Diagram for product availability and quick response to always changing market demand. In this context, using System Thinking this paper aims changing at developing a Causal Loop Diagram for product availability andapproach, quick response to always market demand. In this context, product availability and quick response to always changing market demand. In this context, the definition of the cause and effect relationships between the several variables which define using System Thinking approach, this paper aims at developing a Causal Loop Diagram the definition of the cause and effect relationships between the several variables which define using System Thinking approach, this paper aims at developing a Causal Loop Diagram for for using System Thinking approach, this paper variable aims between at in ain Loop which Diagram for the under exam. Being a this field, fact, dynamic complexity definition of the the cause andtime effect relationships the several variables define the system under exam. Being time a crucial crucial variable indeveloping this the field, inCausal fact, dynamic complexity the system definition of cause and effect relationships between several variables which define the definition of the cause and effect relationships between the several variables which define arises due to interaction of agents over time and evolving situations. In this context, our work system under exam. Being time a crucial variable in this field, in fact, dynamic complexity arises due to interaction of agents time and evolving situations. In this context,complexity our work the system under exam. Being timeover a crucial variable in this field, in fact, dynamic the system under exam. all Being time a crucial variable inthat this field, be in fact, dynamic complexity highlights analyses conflicting requirements must accurately evaluated and arises due and to interaction of the agents over time and evolving situations. In this context, our work work highlights and analyses all the conflicting requirements that must be accurately evaluated and arises due to interaction of agents over time and evolving situations. In this context, our arises duein toorder interaction of the agents over the time and evolving situations. In thisto context, our work balanced to effectively manage complex network of retailers and help the decision highlights and analyses all conflicting requirements that must be accurately evaluated and balanced in order to effectively manage the complex network of retailers and to help the decision highlights and analyses all the conflicting requirements that must be accurately evaluated and highlights and analyses all the conflicting requirements that ofmust be accurately evaluated and making process behind the purchasing, delivery and replenishment steps. balanced in order to effectively manage the complex network retailers and to help the decision making process behind the purchasing, delivery and replenishment steps. balanced in order to effectively manage the complex network of retailers and to help the decision balanced in orderbehind to effectively manage the complex of retailers and to help the decision making process process the purchasing, purchasing, delivery andnetwork replenishment steps. making behind the delivery and replenishment steps. making process behind the purchasing, delivery and replenishment steps. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rightsApparel reserved. Keywords: Keywords: System System Thinking, Thinking, System System Dynamics, Dynamics, Causal Causal Loop Loop Diagram, Diagram, Fashion Fashion and and Apparel Industry, Retail, Supply Chain Keywords:Retail, SystemSupply Thinking, System Dynamics, Dynamics, Causal Causal Loop Loop Diagram, Diagram, Fashion Fashion and and Apparel Apparel Industry, Chain Keywords: System Thinking, System Keywords: SystemSupply Thinking, System Dynamics, Causal Loop Diagram, Fashion and Apparel Industry, Retail, Retail, Chain Industry, Supply Chain Industry, Retail, Supply Chain 1. normally 1. INTRODUCTION INTRODUCTION normally do do not not change change quickly quickly over over time time and and have have a a stable stable and predictable demand, innovative products, like fash1. INTRODUCTION normally do not change quickly over time and have a stable and predictable demand, innovative products, like fash1. INTRODUCTION normally do not change quickly over time and have a stable 1. Apparel INTRODUCTION normally do not quickly over time and have avariety stable ion are characterized by newness, greater and apparel, predictable demand, innovative products, like fashToday, (F&A) ion apparel, are change characterized by newness, greater variety Today, Fashion Fashion and and Apparel (F&A) Supply Supply Chains Chains (SC) (SC) and predictable demand, innovative products, like fashand predictable demand, innovative products, like fash(Vaagen and Wallace, 2008) and customisation (De Feion apparel, are characterized by newness, greater variety are more strategically important than ever before, due Today, Fashion and Apparel (F&A) Supply Chains (SC) (Vaagen andare Wallace, 2008) and customisation Feare more strategically important than ever Chains before, (SC) due ion apparel, characterized by newness, greater(De variety Today, Fashion and Apparel (F&A) Supply ion apparel, are characterized by newness, greater variety lice et al., 2012) which needs low production volumes (Vaagen and Wallace, 2008) and customisation (De FeToday, Fashion and Apparel (F&A) Supply Chains (SC) to added pressure brought by globalization (De Felice are more strategically important than ever before, due lice et al., 2012) which needs low production volumes to added pressure brought by globalization (De Felice and Wallace, 2008) and customisation (De Feare more strategically important than ever before, due (Vaagen (Vaagen and Wallace, 2008) andlow customisation (De Fe(De Carlo et al., 2013) and flexibility (Sammarco et al., lice et et al., 2012) which needs production volumes are more strategically important than ever et before, due lice and Petrillo, 2013) and digitalization (Abtan al., 2013) to added pressure brought by globalization (De Felice (De Carlo et al., 2013) and flexibility (Sammarco et al., and Petrillo, 2013) and digitalization (Abtan et al., 2013) 2012) which needs low production volumes to added pressure brought by globalization (De Felice lice et al., al., 2012) which needs low production volumes 2014) and makes demand unpredictable (Wang et al., (De Carlo et al., 2013) and flexibility (Sammarco et to added pressure brought by globalization (De Felice and by the growth of Quick Response and Fast Fashion Petrillo, 2013) and digitalization (Abtan et al., 2013) 2014) and makes demand unpredictable (Wang et al., and by the growth of Quick Response and Fast Fashion (De Carlo et al., 2013) and flexibility (Sammarco et al., and Petrillo, 2013) and digitalization (Abtan et al., 2013) (De Carlo et al., 2013) and flexibility (Sammarco et 2012). In their cycle 2009), 2014) and and makes demand demand unpredictable (Wang et et al., and Petrillo, 2013) and digitalization (Abtan etcontribute al., 2013) 2014) (Bhardwaj Fairhurst, 2009). These issues by the the and growth of Quick Quick Response and Fast Fashion 2012). In addition, addition, their life life unpredictable cycle is is short short (Barnes, (Barnes, 2009), (Bhardwaj and Fairhurst, 2009). These issues contribute makes (Wang al., and by growth of Response and Fast Fashion 2014) and makes demand unpredictable (Wang et al., because as imitators erode the competition advantage that 2012). In addition, their life cycle is short (Barnes, 2009), and by the growth of Quick Response and Fast Fashion to add complexity to the whole system which must respond (Bhardwaj and Fairhurst, 2009). These issues contribute because as imitators erode the competition advantage that to add complexity to the whole system which must respond 2012). In addition, their life cycle is short (Barnes, 2009), (Bhardwaj and Fairhurst, 2009). These issues contribute 2012). life cycle is short (Barnes, innovative products enjoy, companies are to introbecauseInas asaddition, imitators erode the competition advantage that (Bhardwaj Fairhurst, 2009). These issues contribute quickly and efficiently to always changing market demand to add add complexity complexity to the the whole system which must respond because innovative productstheir enjoy, companies are forced forced to 2009), introquickly and and efficiently towhole always changing market demand imitators erode the competition advantage that to to system which must respond because as imitators erode the competition advantage that duce a steady stream of newer innovations. innovative products enjoy, companies are forced to introto add complexity to the whole system which must respond (Battista and Schiraldi, 2013). quickly and efficiently to always changing market demand duce a steady stream of newer innovations. (Battista and Schiraldi, 2013). innovative products enjoy, companies are forced to introquickly and efficiently to always changing market demand innovative products enjoy, companies are forced to introWith peculiarities, F&A products duce aathese steady stream of of newer newer innovations. quickly efficiently to2013). always demand In this context, purpose of work to aa duce (Battista and Schiraldi, With these peculiarities, F&A innovations. products require require a a fundafundaIn this and context, purpose of this thischanging work is is market to construct construct steady stream (Battista and Schiraldi, 2013). duce athese steady stream ofthan newer innovations. mentally different SC do stable, functional prodWith peculiarities, F&A products require a funda(Battista andDiagram, Schiraldi, 2013). Causal Loop through the application of System In this context, purpose of this work is to construct a mentally different SC than do stable, functional prodCausal Loop Diagram, through the application of System these peculiarities, F&A products require a fundaIn this context, purpose of this work is to construct a With With these peculiarities, F&A products require aon fundaucts. While an efficient SC strategy with focus cost mentally different SC than do stable, functional prodIn this Loop context, purpose offor this work is to of construct a mentally Dynamics (SD) principles, the definition the cause Causal Diagram, through the application of System ucts. While an efficient SC strategy with focus on cost Dynamics (SD) principles, for the definition of the cause SC than do stable, functional prodCausal Loop Diagram, through the application of System mentally different different SC than do stable, functional prodminimization should be used for functional products, ucts. While an efficient SC strategy with focus on costa Causal Loop Diagram, through the application of System and effect relationships between the several factors which Dynamics (SD) principles, for the definition of the cause minimization should be used for functional products, and effect relationships between the several factors which ucts. While an efficient SC strategy with focus on cost Dynamics (SD) principles, for the definition of the cause ucts. While an efficient SC strategy with focus on costa responsive/demand driven SC strategy with focus on prodminimization should be used for functional products, Dynamics (SD) principles, for the definition of the cause define a typical F&A Retail Supply Chain. and effect relationships between the several factors which responsive/demand driven SC strategy with focus on proddefine a typical F&A Retail Supply should be used for functional products, aa and effect relationships between the Chain. several factors which minimization minimization should be used for functional products, ucts availability, matching the marketplace customer responsive/demand driven SC strategy with with focus on prodprod-a and effect relationships between the several factors which responsive/demand Motivation behind this research is to help the decision define a typical F&A Retail Supply Chain. ucts availability, matching the strategy marketplace with customer Motivation behind this research is to help the decision driven SC with focus on define a typical F&A Retail Supply Chain. responsive/demand driven SC strategy with focus on proddemands, could best fit innovative products (Lam and ucts availability, matching the marketplace with customer define a typical F&A Retail Supply Chain. making process behind purchasing, delivery and Motivation behind this the research is to to help help the decision decision demands, could matching best fit innovative products and making process behind the purchasing, delivery and rere- ucts availability, the marketplace with(Lam customer Motivation behind this research is the ucts availability, matching the marketplace with customer Postle, 2006). A demand driven SC must offers real-time demands, could best fit innovative products (Lam and Motivation behind this research is to help the decision plenishment steps of a company that manages an extended making process behind the purchasing, delivery and rePostle, 2006). A demand driven SC must offers real-time plenishment steps of a company that manages an extended demands, could best fit innovative products (Lam and making process behind the purchasing, delivery and re- demands, could best fit innovative products (Lam and information inventory levels in order Postle, 2006). 2006).on Ademand demandand driven SC must must offers real-time making process the purchasing, delivery andprore- Postle, network of operated mono-brand retailers. plenishment stepsbehind of aa company company that manages manages an This extended information onA demand and inventory levels in real-time order to to network of direct direct operated mono-brand retailers. This prodemand driven SC offers plenishment steps of that an extended Postle, 2006).onA demand driven SC must offers real-time react quickly and effectively when unexpected changes information demand and inventory levels in order to plenishment steps of adynamic company that manages an This extended cess must be highly due to constantly changing network of direct operated mono-brand retailers. proreact quickly and effectively when unexpected changes cess must be highly dynamic due to constantly changing on demand and inventory levels in order to network of direct operated mono-brand retailers. This pro- information information on demand and inventory levels in order to arises (Budd et al., 2012). react quickly quickly and effectively when unexpected unexpected changes network of be direct operated mono-brand retailers. This pro- react conditions, such as market demand, thus adding comcess must highly dynamic due to constantly changing arises (Budd et al., 2012). conditions, such as market demand, thus adding comand effectively when changes cess must be highly dynamic due to constantly changing react quickly and effectively when unexpected changes arises (Budd (Budd et et al., al., 2012). 2012). cess must besuch highly due to changing plexity to whole system the strong interactions conditions, as dynamic market given demand, thus adding adding com- arises plexity to the the whole system given theconstantly strong interactions conditions, such as market demand, thus comarises (Budd et al., 2012). conditions, such as market demand, thus adding combetween factors. plexity to the whole system given the strong interactions betweentofactors. 1.2 Principles Principles of of System System Thinking Thinking and and System System Dynamics Dynamics plexity the whole system given the strong interactions 1.2 plexity tofactors. the wholeintroduction system given interactions Then, after a of peculiarities of between Then, after a brief brief introduction of the the strong peculiarities of the the 1.2 in Chain Management 1.2Supply Principles of System Thinking and System Dynamics in Supply Chain Management between factors. Principles of System Thinking and System Dynamics between factors. Fashion Industry and a summary of the SD principles, we Then, after a brief introduction of the peculiarities of the 1.2 Principles of System Thinking and System Dynamics Fashion Industry and a summary of the SD principles, we in Supply Chain Management Then, after a brief introduction of the peculiarities of the in Supply Chain Management Then, a briefand introduction ofofthe the define the background our and describe Fashionafter Industry summary thepeculiarities SD principles, principles, we System in Supplydynamics Chain Management define the background of our research research and describeof into into (SD) Fashion Industry and aa of summary of the SD we System dynamics (SD) is is aa methodology methodology developed developed by by Fashion Industry and a summary of the SD principles, we details the proposed Causal Loop Diagram. define the background of our research and describe into details the the background proposed Causal Loop Diagram. Forrester to understand the structure and dynamics of System dynamics dynamics (SD) is a methodology developed by define of our research and describe into System Forrester to understand the structure and dynamics of (SD) is a methodology developed by define of our research and describe into complex details the the background proposed Causal Causal Loop Diagram. System dynamics (SD) isthe a1961). methodology developed by systems (Forrester, This approach has been Forrester to understand structure and dynamics of details the proposed Loop Diagram. complex systems (Forrester, 1961). This approach has been Forrester to understand the structure and dynamics of details the proposed Causal Loop Diagram. 1.1 Forrester to understand the1961). structure and dynamics of used in several fields, from project management (Toole, complex systems (Forrester, This approach has been 1.1 Demand Demand Driven Driven Fashion Fashion Supply Supply Chain Chain used in several fields, from project management (Toole, complex systems (Forrester, 1961). This approach has been 1.1 Demand Demand Driven Driven Fashion Fashion Supply Supply Chain Chain complex systems (Forrester, 1961). This been 2005) and SC et al., 2003) product used in in several fields, from(Gnoni project management (Toole, 2005) and SC management management (Gnoni et management al.,approach 2003) to tohas product 1.1 used several fields, from project (Toole, 1.1 Demand Driven Fashion Supply Chain used several fields, (D’Amico from(Gnoni project management (Toole, life-cycle management et al., 2013) and capacity According 2005)in and SC management et al., 2003) to product life-cycle management (D’Amico et al., 2013) and capacity According to to Fisher Fisher (1997), (1997), products products can can be be divided divided into into 2005) and SC management (Gnoni et al., 2003) to product 2005) andmanagement SC management (Gnoni et 2003) toa product planning (Vlachos et 2007), describes system two categories: either primarily functional primarily life-cycle (D’Amico etand al.,al., 2013) and capacity According to Fisher Fisher (1997), products can be be or divided into life-cycle planning (Vlachos et al., al., 2007), and describes acapacity system two categories: either primarily functional or primarily management (D’Amico et al., 2013) and According to (1997), products can divided into life-cycle management (D’Amico et al., 2013) and capacity According to Fisher (1997), products can be divided into behaviour through the structure of its feedback loops. innovative. While functional products, such as grocery, planning (Vlachos et al., 2007), and describes a system two categories: either primarily functional or primarily behaviour through the structure of its feedback loops. innovative. While functional products, such as grocery, two categories: either primarily functional or primarily planning (Vlachos et al., 2007), and describes a system planning (Vlachos et al., 2007), ofand describes a system two categories: either primarily functional orasprimarily behaviour through the structure its feedback loops. innovative. While functional products, such grocery, innovative. While functional products, such as grocery, behaviour through the structure of its feedback loops. innovative. While Copyright © 2015 IFACfunctional products, such as grocery,1354behaviour through the structure of its feedback loops. Copyright © 2015 IFAC 1354 2405-8963 © IFAC (International Federation of Automatic Control) Copyright © 2015, 2015 IFAC 1354Hosting by Elsevier Ltd. All rights reserved. Copyright 2015 responsibility IFAC 1354Control. Peer review© of International Federation of Automatic Copyright ©under 2015 IFAC 1354 10.1016/j.ifacol.2015.06.263
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Basic elements of this methodology are causal loop diagrams and stock and flows diagrams. The first ones represent the feedback structure of the system while stock and flow diagrams are tools for assessing variables dynamics through a period (Gnoni and Lanzilotto, 2012). Main elements of these diagrams are (Sterman, 2000), (Georgiadis et al., 2006): • Variables which are relevant for the system description; • Oriented arches which suggest causal relationships. The + and - sign indicate that the effect is positively or negatively related to the cause; • Positive loops: they are self-reinforcing loops, identified with R. In a positive feedback loop, an initial disturbance leads to further change, suggesting the presence of an unstable equilibrium; • Negative loops: they are self-correcting or balancing loops, identified with B. In a negative feedback loop, after a disturbance, the system seeks to return to an equilibrium situation; • Delays which describe the inertia of physical system, according to which it is not possible that a quantity changes instantaneously; • Stocks which represent quantities that are accumulated or disposed over time; • Flows which indicate an entity flow from/to one or more Stocks. All these elements will be part of the Causal Loop Diagram (CLD) which graphically illustrates causal relationships and major feedback loops among variable of the system. The construction of a CLD for the description of the planning, purchasing, supply and replenishments processes of a Fashion Retail SC is the main goal of this research work and will be described into detail in next section. 2. A CAUSAL LOOP DIAGRAM FOR THE FASHION RETAIL INDUSTRY Strategic supply chain management involves a wide spectrum of issues and includes several types of decisionmaking problems, such as the determination of number, location and capacity of warehouses and the flow of material through the logistics network, inventory management policies, distribution strategies, etc. (Georgiadis et al., 2005). All these issues must be constantly faced in the F&A Industry adding complexity due to seasonality of products, fluctuating and unpredictable demand and short product life cycle. 2.1 Motivation behind research Present work aims at defining and modeling SC dynamics in the F&A retail industry and represents a preliminary study for future implementation of the model through simulating tools. Even if no experimental result is presented, this study represents the core of the simulation process since it performs a careful analysis of the problem, setting main goals and issues, and it defines the conceptual model by analysing interactions and causal relationships between variables both graphically and in mathematical terms.
Fig. 1. Planning and Operations steps of the model 2.2 Context and problem description According to Iannone et al. (2013) and Lanzilotto et al. (2014), we divided the main supply chain processes as illustrated in Fig. 1. The Pre Season stage, as the name implies, is performed before the beginning of the selling season and includes all the phases which go from the design of the clothing collection to the first deliveries to the stores. The In Season stage, instead, starts with the first sales recorded in the stores. At this point, after comparing real sales with forecasts, an adjustment process starts. In next sections, we will describe into detail each diagram block together with an economic performance evaluation, identifying variables and related causal relationships. In the diagrams, Stocks will be represented in capital letters while Flows in italic underlined letters. 2.3 Pre Season a) Collection definition and planning Many companies operating in the fashion industry highlight that the most relevant core competences to keep in house are those related to the design phase, which defines material requirements, aesthetic aspect and style of the product (Brun et al., 2008). Then, this phase, also named as New Product Development (NPD) is considered crucial and very time consuming, since it usually begins almost two years before production (Bandinelli et al., 2013). Main output data of the collection definition process which are considered relevant to our model are the Number of Items and their Price. The first variable has a positive relationship with the Number of Suppliers. Since it is likely that each clothing item requires one or more specific manufacturing skills or processes, their production will be committed to the most suitable supplier. To simplify, we can consider that each item is produced by one specific supplier. The variable Price, instead, has a clear relationship of direct proportionality with Revenues. Another significant variable is the Collection Attractiveness, which is evaluated in terms of design, quality and assortment (i.e. the number of different clothing items) but not less significant is the price factor (Mariany et al., 2012). To increase attractiveness there is also
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Marketing Investment (m), intended as the planned investment in advertising and communication campaigns, which is defined as a percentage of the Budget allocated to the entire selling season. b) Forecasting As already mentioned in previous paragraph, demand for fashion items is highly unpredictable, since isolating external effects such as season, weather conditions or mediatic phenomena can be extremely complex (Souza et al., 2014). In last years several sophisticated models have been proposed (Fumi et al., 2013), (Nenni et al., 2013) and most of them use generic algorithms based on the assumption that demand can be predicted uniformly for all companies and across all industries, product lines and geographies. This one-size-fits-all approach yields a forecast that fails to reflect the relative impact of different demand drivers and to adapt as market conditions and consumer behaviours evolve (B. and Caffrey, 2014). Nevertheless, all researchers agree in basing sales forecasting on historical data, which in our case are represented by Demand data of the Previous selling Seasons. This idea is represented in our CLD (refer to Fig. 2) by a delay. It is clear that these demand data are aggregate data coming from all the stores of the network, then the global Demand is positively related to the Number of Stores managed by the company.
Then, the CLD for these first three processes is shown in Fig. 2. d) Delivery The deliveries (or primary transport) from the suppliers to the Central Warehouse (Deliveries to Warehouse - DW ), which are an incoming flow in the Warehouse Stock (SW ), are defined by the Delivery Plan which contains information concerning delivery quantity (Purchase Quantity) and times for each supplier (Number of Suppliers). The first balancing loop (B1) identified in this system is defined between DW and SW . The positive causal relationship (from DW to SW ) is given by the material flow incoming into the warehouse with an unavoidable delay due to Delivery Lead Time increasing with Suppliers Distance. The negative feedback (from SW to DW ), instead, refers to the updating process in the delivery plans: warehouse physical limits, concerning both storage and material handling capacity, must not be overcome, then delivery quantities and times must be revised accordingly. The cost item related to this process is the Primary Transport Cost (CP T ) given by: CP T =
M j=1
(Ctf,j + Ctv,j ∗ QDj ∗ DISTj )
(3)
Where, M is the number of suppliers and, Ctf and Ctv are constant values and are respectively fixed and variable cost for primary transport for the j-th supplier, QD is the quantity delivered and DIST is the distance between suppliers plant and central warehouse. The CLD for this process is showed in Fig. 3.
Fig. 2. Causal relationships for Collection Definition and Planning, Forecasting and Purchasing processes c) Purchasing Main output of the purchasing process is the definition of the global Purchase Quantity for each item included in the collection. The Purchase Cost (CP ) will be then calculated as: CP =
N i=1
Qi ∗ cui
(1)
Where N is the Number of Items, Qi is the Purchase Quantity for the i-th item and cui is the i-th item’s unitary cost (Items cost). It is clear that this cost must fall within the Budget (B) allocated according to the following equation: m + CP ≤ B where m is the Marketing Investment.
(2)
Fig. 3. Causal relationships for Delivery process e) Replenishment In a fast changing environment, such as the fashion one, the generic problem of allocating inventory from a central warehouse to several locations satisfying separate demand streams, is considered the most crucial. This replenishment process (or secondary transport) principally aims at dynamically optimizing the assortment of the stores trying to minimize overstock or out of stock events. In this process we can identify two different balancing loops (refer to Fig. 4): B2) between Warehouse Stock (SW ) and Deliveries to Stores (DS ): • The negative causal relationship (from DS to SW ) is given by the material flow out coming from the warehouse; • The positive feedback (from SW to DS ) is given by the necessity to respect physical warehouse
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limits (refer to Delivery process). In order to avoid overloading of the warehouse, when stocks increase, deliveries to store must become bigger and more intensive. B3) between Deliveries to Stores (DS ) and Stores Stock (SS ): • The positive causal relationship (from DS to SS ) is given by the material flow incoming in the stores, with a delay due to transport lead time increasing with Stores Distance from the warehouse; • The negative feedback (from SS to DS ) is given by the necessity to respect physical internal stores warehouse limits, such as for the central warehouse. This second loop also reflects two conflicting requirements of the fashion retail environment. From one side, given customers impulsive purchasing behaviour, we need to ensure high availability of products, not only in terms of product range but also in sizes and colours. From the other side, higher stock levels may lead to the overloading of internal stores warehouses and consequent related costs, and to the increase in unsold stocks.
2.4 In Season a) Sales The In Season phase starts with the first Sales recorded in the Stores. In this process we can clearly identify a balancing loop (B4) between Demand (d), Sales (s) and Stores Stock (SS ): • The negative causal relationship (from s to SS ) is given by the real Sales which represent a material flow out going from the stores; • The positive causal relationship (from SS to d ) reflects customers impulsive and compulsive purchasing behaviour (refer to Replenishment process), then an increasing demand will be observed with a higher assortment level; • The positive feedback (from d to s) shows the direct proportionality between Demand and Sales (refer to equation 6). In addition, in order to estimate uncensored customer requests, Caro and Gallien (2007) define Demand as the sales that would have been observed had all merchandise been displayed without any stock out. Then we can define the following equation:
The two cost items related to this process are: • Warehouse Management Cost (CM W ): CM W = Cmf +
N i=1
Demand = Sales + Outof Stock (6) The cost item connected to this process is the Stores Management Cost (CM S ):
chi ∗ cui ∗
∗(
M j=1
QD,ij −
L
CM S,k = cmf + QR,ik )
L
k=1
(4)
chi ∗ cui ∗ (QR,i − si )
(7)
Where cmf is the fixed store management cost, chi is the store holding cost for the i-th item expressed as percentage of its value. This value is higher than the same chi for the central warehouse since products stored in the stores can not be used any more for the replenishment of other stores and other possible transfers will generate higher costs. Another variable that must be considered in this process is Revenues (R), expressed as:
k=1
ctf,k + ctv, k ∗ QR,k ∗ distk
N i=1
Where Cmf is the fixed warehouse management cost, chi is the holding cost for the i-th item expressed as percentage of its value and QR is the quantity delivered to the k-th store. • Secondary Transport Cost (CST ): CST =
1293
(5)
Where, for the k-th store, ctf and ctv are constant values and are respectively fixed and variable cost for secondary transport, QR is the quantity delivered and dist (Stores Distance) is the distance between central warehouse and the k-th store.
R=
N M i=1 j=1
sij ∗ P ri
(8)
The CLD for this process is showed in Fig. 5.
The CLD for this process is showed in Fig. 4.
Fig. 5. Causal relationships for Sales process Fig. 4. Causal relationships for Replenishment process
b) Adjusting Supply and demand are easily matched if demand is steady over time with no change in volume or mix. 1357
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As soon as demand changes, however, a company must adjust the supply levels accordingly at each step of the supply chain (Budd et al., 2012). According to these considerations, the best designed fashion supply chains must be (Abtan et al., 2013): • Fast, demonstrating particular speed in fulfilling customer orders and adapting to changes; • Flexible, creating efficient processes that enable flexibility in the end-to-end supply chain; • Lean, emphasizing effective, low-cost operations. This adjusting process is based on the comparison between real Demand and Forecasts, which allows us to perform two different deviation analysis: • Supply Chain Deviation: it evaluates aggregate data from Warehouse Stock and Stores Stock and, if this deviation is higher than a fixed threshold, the system will update Purchasing Quantity possibly cancelling some orders or issuing new ones; • Replenishment Deviation: through the analysis of current Stores Stock, it evaluates in real time how much Demand was under or over estimated and, if it overcomes a fixed threshold, we will have to adjust the replenishment plans (Deliveries to Stores). The CLD for this process is showed in Fig. 6.
3. CONCLUSION AND PERSPECTIVES Effective management to achieve competitive advantages includes the ability to manage a complex network as a whole. In the fashion industry, the operational strategy consists of ordering, well in advance, a large number of different references, each having a relatively short life cycle of only a few weeks. However, on the contrary, a fashion supply chain must respond quickly to market changes in order to meet customers requests and increase profitability. In this context, this paper proposes a Causal Loop Diagram which describes into detail the conflicting typical needs of the Fashion and Apparel Industry. These opposing requirements, force the management to face several decision making problems in order to find the best definition and mix of all the variables, such as the definition of the Seasonal Budget, the selection of the items composing the collection, the choice of the quantities to be purchased etc., with the aim of maximising profits. The present work only represents a preliminary study since it does not offer any experimental result even if it represents the core of the simulation process. Then, next steps will be the implementation of the model through simulating tools and design of an experimental campaign for the analysis of supply chain performances under different conditions. REFERENCES
Fig. 6. Causal relationships for Adjusting process 2.5 Economic Performance For each Retail SC and, generically, for each Supply Chain, main purpose is the maximization of the Profit (P) expressed as:
P = R − CP − CP T − CM W − CST −
L
k=1
CM S,k − M (9)
The causal relationships representing this economic evaluation are showed in Fig. 7.
Fig. 7. Economic relationship 2.6 The Final Causal Loop Diagram Integrating all the variables and interactions previously described, the final CLD of the system under exam is shown in Fig. 8.
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