PhD Thesis

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PhD Thesis

  1. 1. C378etukansi.kesken.fm Page 1 Tuesday, December 21, 2010 3:43 PM OULU 2011 C 378 C 378 U N I V E R S I T Y O F O U L U P. O. B . 7 5 0 0 F I - 9 0 0 1 4 U N I V E R S I T Y O F O U L U F I N L A N D ACTA U N IIV E R S IIT AT IIS O U L U E N S IIS U N V E R S T AT S O U L U E N S S ACTA A C TA U N I V E R S I TAT I S O U L U E N S I S S E R I E S E D I T O R S Dayou Yang C TECHNICA TECHNICA ASCIENTIAE RERUM NATURALIUM OPTIMISATION OF PRODUCT Dayou Yang Professor Mikko Siponen BHUMANIORA University Lecturer Elise Kärkkäinen CHANGE PROCESS AND CTECHNICA DEMAND-SUPPLY CHAIN IN Professor Hannu Heusala HIGH TECH ENVIRONMENT DMEDICA Professor Olli Vuolteenaho ESCIENTIAE RERUM SOCIALIUM Senior Researcher Eila Estola FSCRIPTA ACADEMICA Information officer Tiina Pistokoski GOECONOMICA University Lecturer Seppo Eriksson EDITOR IN CHIEF Professor Olli Vuolteenaho PUBLICATIONS EDITOR Publications Editor Kirsti Nurkkala UNIVERSITY OF OULU, DEPARTMENT OF MECHANICAL ENGINEERING; DEPARTMENT OF INDUSTRIAL ENGINEERING AND MANAGEMENT ISBN 978-951-42-9354-2 (Paperback) ISBN 978-951-42-9355-9 (PDF) ISSN 0355-3213 (Print) ISSN 1796-2226 (Online)
  2. 2. ACTA UNIVERSITATIS OULUENSISC Te c h n i c a 3 7 8DAYOU YANGOPTIMISATION OF PRODUCTCHANGE PROCESS AND DEMAND-SUPPLY CHAIN IN HIGH TECHENVIRONMENTAcademic dissertation to be presented, with the assent ofthe Faculty of Technology of the University of Oulu, forpublic defence in Auditorium IT115, Linnanmaa, on 28January 2011, at 12 noonU N I VE R S I T Y O F O U L U , O U L U 2 0 1 1
  3. 3. Copyright © 2011Acta Univ. Oul. C 378, 2011Supervised byProfessor Kauko LappalainenProfessor Harri HaapasaloReviewed byProfessor Petri HeloDoctor Lasse PesonenISBN 978-951-42-9354-2 (Paperback)ISBN 978-951-42-9355-9 (PDF)http://herkules.oulu.fi/isbn9789514293559/ISSN 0355-3213 (Printed)ISSN 1796-2226 (Online)http://herkules.oulu.fi/issn03553213/Cover DesignRaimo AhonenJUVENES PRINTTAMPERE 2011
  4. 4. Yang, Dayou, Optimisation of product change process and demand-supply chain inhigh tech environmentUniversity of Oulu, Faculty of Technology, Department of Mechanical Engineering, P.O.Box4200, FI-90014 University of Oulu, Finland; University of Oulu, Faculty of Technology,Department of Industrial Engineering and Management, P.O.Box 4610, FI-90014 University ofOulu, FinlandActa Univ. Oul. C 378, 2011Oulu, Finland AbstractInformation and communications technology (ICT) companies face challenges in an unpredictablebusiness environment, where demand-supply forecasting is not accurate enough. How tooptimally manage product change process and demand-supply chain in this type of environment?Companies face pressures to simultaneously be efficient, responsive and innovative, i.e. tominimise costs, and shorten order delivery and product change periods. This thesis included three action research cycles within a real demand-supply chain of asignificant international actor. Each action research cycle sought answers by going into oneextreme of minimising costs, diminishing order delivery period, or shortening product changeperiods. In practice, these research cycles included the case company changing their businessaccordingly for each of these cases. Conducting required changes in the case company wereeconomically significant trials. The results of this doctoral dissertation provide tips for global high tech companies. Largeinternational companies typically have manufacturing sites in different parts of the world.According to the results, mental shift from local optimisation to a global one is required forefficient manufacturing operations. Companies have traditionally considered their strategy as a choice between minimising costs,quick delivery, and rapid product change. Also, companies have believed that one single strategyis adequate and applicable to all of their products. According to this thesis, different products mayhave a different strategy. This would allow companies to flexibly react to the needs of differentcustomer groups, business environments, and different competitors. In addition, strategy can bechanged relatively often, monthly, weekly, or even daily. Based on the results of this doctoral thesis, companies must harmonise their product portfolioglobally, including all their sites. Once the same product version is at all sites, they can help eachother from components supply viewpoint. Consequently, product changes can be taken throughquicker.Keywords: action research, agile, demand supply, innovativeness, lean, optimisation,synchronization
  5. 5. Yang, Dayou, Tuotemuutosprosessin optimointi ja kysyntä-tarjontaketju korkeanteknologian yrityksissäOulun yliopisto, Teknillinen tiedekunta, Konetekniikan osasto, PL 4200, 90014 Oulun yliopisto;Oulun yliopisto, Teknillinen tiedekunta, Tuotantotalouden osasto, PL 4610, 90014 OulunyliopistoActa Univ. Oul. C 378, 2011Oulu TiivistelmäInformaatio- ja kommunikaatioalan yritykset kohtaavat haasteita toimiessaan vaikeasti ennustet-tavassa liiketoimintaympäristössä, jossa tilaus-toimitusennusteet ovat epätarkkoja. Miten tällai-sessa ympäristössä hallitaan optimaalisesti tuotemuutosprosessi ja tilaustoimitusketju? Yrityksil-lä on paineita olla samanaikaisesti tehokkaita ja innovatiivisia: miten minimoida sekä kustan-nuksia että lyhentää toimitus- ja tuotemuutosaikoja. Tämä väitöskirja tehtiin toimintatutkimuksena merkittävän kansainvälisen yrityksen todelli-sessa tilaus-toimitusketjussa. Toimintatutkimus eteni vaiheittain kokeilemalla kolmea eri ääri-päätä minimoimalla 1) kustannuksia, 2) toimitusaikoja ja 3) tuotemuutosaikoja. Käytännössänämä ääripäät sisälsivät case-yrityksen liiketoiminnan muuttamista vastaavasti sisältäen talou-dellisesti merkittäviä kokeiluja. Tämän väitöskirjan tulokset tarjoavat käytännön esimerkkejä globaaleille korkeanteknologi-an yrityksille. Suurilla kansainvälisillä yrityksillä on tyypillisesti valmistusyksiköitä eripuolillamaailmaa. Tämän tutkimuksen tulosten mukaan yritykset tarvitsevat asennemuutoksen paikalli-sesta optimoinnista globaaliin, jotta tuotanto toimisi tehokkaasti. Perinteisesti yritykset ovat ymmärtäneet strategian tarkoittavan valinnan tekemistä kustan-nusten minimoinnin, nopeiden toimitusaikojen tai nopeiden tuotemuutosten välillä. Yrityksetovat myös uskoneet, että yksi yrityskohtainen strategia kattaa kaikki yrityksen tuotteet. Tämänväitöskirjan tulosten mukaan yrityksen eri tuotteilla voi olla erilainen strategia. Tällainen ratkai-su mahdollistaa nopean reagoinnin muutoksiin asiakasryhmien tarpeissa, liiketoimintaympäris-tössä ja kilpailutilanteissa. Strategiaa voidaan myös muuttaa usein, kuukausittain, viikoittain taijopa päivittäin. Tämän väitöskirjatutkimuksen tulosten mukaan, yritysten tulisi harmonisoida tuoteportfo-lionsa globaalisti kattaen kaikki tuotantolaitokset. Silloin kun yrityksen kaikissa valmistusyksi-köissä valmistetaan samaa tuoteversiota, yksiköt voivat auttaa toisiaan komponenttien hankin-nassa. Tuotemuutokset voidaan tällöin toteuttaa nopeammin.Asiasanat: innovatiivisuus, ketteryys, kysyntä, optimointi, synkronointi, tarjonta,toimintatutkimus
  6. 6. AcknowledgementsThis dissertation is about a research initiated in a tough situation of high-techmanufacturing back in 2002. It was economic hard time with lean strategy as amust in the company where the researcher was employed. However, the companyhad to struggle with inaccurate forecasts in their daily work making productchange management more challenging. Earlier planning, or even comprehensiveknowledge over JIT (Just-In-Time), was not enough due to big lead-time gaps indemand-supply. Thus this learning journey was initiated to develop new solutions.The research was conducted cycle-by-cycle, and the outcomes were graduallyimplemented to IT over the years. During this process, many people providedtheir valuable assistance. I am very grateful to my supervising professors - Harri Haapasalo and KaukoLappalainen for their professional guidance through the whole research process.Their strong commitment always inspired me to overcome any difficulties.Constructive advice from Dr. Janne Härkönen, Dr. Pekka Belt and Dr. MattiMöttönen of the University of Oulu were especially helpful. They helped tobroaden my way of thinking about my research and the dissertation and helpedme to see things from multiple viewpoints. Also I wish to thank Professor Juha-Matti Lehtonen being so supportive and patient when I was struggling whileaiming to a breakthrough. Deep in my heart, great thanks belong to Mr. AriKurikka who has remarkably coached me from the very beginning until all theaction research cycles were finished. The insight of focusing on the wholedemand-supply network kept the research aiming for a win-win solution to allnetwork parties. Special acknowledgement goes to Mr. Arto Tolonen for many ofhis valuable advices. Especially with his “Design for Excellence” contributionimplemented in the company, it made it easier for this research to operate withless product variants. I want to present my sincere thanks to Mr. Jukka Kukkonen,Mr. Ville Jokelainen, Mr. Kaj Sundberg and Mr. Jussi Parviainen for supportingme when conducting this research besides my daily work. I very much appreciatethe help and interest of my other colleagues for their insightful inputs. My warmthanks belong to AAC Global Oyj and other native English-speaking friends fortheir language assistance. I also need to acknowledge the financial aid fromFinnish Foundation for Economic Education. In addition, I would like to thank the pre-examiners of this study - ProfessorPetri Helo and Dr. Lasse Pesonen for their valuable comments andrecommendations. 7
  7. 7. Finally, my deepest gratitude belongs to my wife Weilin and my childrenYuchen & Tina. I value their support and care to tolerate my mental absence dueto this work. Their patience makes my learning journey possible and rewardable.Oulu, December 2010 Dayou Yang8
  8. 8. Abbreviations and key terminology3C Capacity, Commonality, Consumption (management system)3D CE Three Dimensional Concurrent EngineeringABM Agent-Based ManufacturingAR Action ResearchATO Assemble-To-OrderBAM Business Activity MonitoringBOM Bill Of MaterialBPR Business Process Re-engineeringBTO Build-To-OrderCAD Computer Aided DesignCIB Change Implementation BoardCIM Computer Integrated ManufacturingCLM Council of Logistics ManagementCLCP Closed Loop Change ProcessCM Configuration ManagementCMMI Capability Maturity Model IntegrationCPM Corporate Performance ManagementCRB Change Review BoardCRM Customer Relationship ManagementDA Delivery AccuracyDNA Deoxyribonucleic AcidECN Enterprise Change NoticeECR Enterprise Change RequestEMS Electronics Manufacturing ServicesESP Equalised and Synchronised ProductionERP Enterprise Resource PlanningEVDB Events and Venues DatabaseFAT Focus, Architecture, and TechnologyFMS Flexible Manufacturing SystemGIT Goods In Transiti2 A management application supplierICH Inventory Collaboration HubIQ Intelligence QuotientIT Information TechnologyJIT Just-In-Time 9
  9. 9. MAS Multi-Agent SystemMICE Multimedia, information, communications, and electronicsMRP Material Requirements PlanningMTO Make-To-OrderMTS Make-To-StockNMS Network Managed SupplyNPI New Product IntroductionOEM Original Equipment ManufacturerOPP Order Penetration PointOPT Optimised Production TechnologyOSS Operation and Support SubsystemPASSI Process for Agent Societies Specification and ImplementationPC Personal ComputerPMBOK Project Management Body of KnowledgePS Physical StockPTK PASSI Tool KitPTO Pack-To-OrderPWB Printed Wiring BoardR&D Research and DevelopmentRIA Rich Internet ApplicationRDBMS Relational Database Management SystemROI Return on InvestmentSAP A management application supplierSCM Supply Chain ManagementSCOR Supply-Chain Operations ReferenceSOA Service Oriented ArchitectureSTO Ship-To-OrderTOC Theory of ConstraintsTPI Trading Partner IntegrationTQM Total Quality ManagementTTC Time to CustomerTTM Time to MarketUML Unified Modelling LanguageVMI Vender Managed InventoryVOP Value Offering PointWIP Work In Process10
  10. 10. Please note that following list describes the terminology for the purpose of thisdissertation rather than giving official definitions.Minimise costs (Lean) = Creating value with as little work and waste as possible.Quick delivery (Agility) = Responsiveness in demand fulfilmentFast product change (Innovativeness) = Making product changes as quick aspossibleZero-series = series after proto type in product development, before actualvolume productionComponent equalisation = In a large organisation there are different personsresponsible for buying different components, causing differences in the levels ofdifferent components as buyers buy in different pace and their activities are notadequately coordinated. In a situation with too many components, the componentyou have least determines the equalised level. If you have any components morethan the equalised level, those can be considered as waste. The differencebetween the equalised level and the original forecasted level can be considered astolerance margin increasing agility. However, if the company prefers lean overagility, this type of tolerance should be avoided.Time based optimisation (Synchronisation) = In modern business, when newproduct versions are introduced, there are a large number of tasks that must beconducted. As time has become increasingly important aspect for businesssuccess, time-based coordination of activities is important for total optimisation.In this dissertation this coordination is also called synchronisation. Also, thehandling of component supply change, including component equalisation on timebasis, must be included in this synchronisation.Liability = Company has contractual obligations for a certain period of a forecastbefore they can stop buying certain components from a supplier. From asupplier’s viewpoint, this gives a level of security for a certain period of time,such as two months, allowing it to cut costs and adjust to changes. This liabilityonly applies to buyer company specific components. 11
  11. 11. Dynamic cut-off window = Buyer company has a natural goal of minimising theliability of the amount of components it is obliged to buy. In order to optimise theoperations of buyer-seller cooperation, the information on critical issues must betransferred as early as possible, for instance updating forecasts on a weekly basis.This way of dynamically informing a supplier allows it to have time to reactaccordingly. This in turn makes it possible to reduce the liability of the buyer.Fixed cut-off window = Before starting a zero-series, product new versionchangeover date is selected and fixed. This type of fixed cut-off window enablessuppliers to deliver the existing order plus liability. No further orders are placedfor the old material.12
  12. 12. ContentsAbstractTiivistelmäAcknowledgements 7 Abbreviations and key terminology 9 Contents 13 Introduction 15  1.1  Research background & motivation ........................................................ 15  1.2  Objectives and scope ............................................................................... 18  1.3  Research process ..................................................................................... 19  1.3.1  Action research ............................................................................. 19  1.3.2  Research context........................................................................... 20  1.3.3  Practical realisation ...................................................................... 22  1.4  Structure of the thesis .............................................................................. 23 2  Literature review 25  2.1  Manufacturing philosophies .................................................................... 25  2.1.1  Lean manufacturing and JIT philosophy ...................................... 25  2.1.2  ESP concept beyond JIT philosophy ............................................ 26  2.1.3  Agile manufacturing and leagility concepts ................................. 27  2.1.4  Manufacturing strategies and product life cycle ........................... 28  2.1.5  The innovator’s strategy ............................................................... 29  2.1.6  Summary of manufacturing philosophies ..................................... 30  2.2  Developing demand-supply network ...................................................... 32  2.2.1  Value oriented development for demand-supply network ............ 32  2.2.2  Manufacturing strategies affect demand-supply network ............. 36  2.2.3  The role of collaboration in demand-supply ................................. 40  2.2.4  Measuring demand-supply performance ...................................... 44  2.2.5  Purchasing automation challenge in product life cycle ................ 46  2.2.6  Optimisation of demand-supply with thinking of BI automation .................................................................................... 48  2.3  Product change management................................................................... 52  2.4  Special characteristics of high-tech industries ........................................ 54  2.4.1  Challenges in forecasting ............................................................. 54  2.4.2  Telecom supply chain of case company ....................................... 55  2.4.3  Case Ericsson (analysed in 2002–2003) ....................................... 56  13
  13. 13. 2.4.4  Case Dell Corporation/Lucent Technologies (analysed in 2002–2003) ................................................................................... 58  2.4.5  Case Huawei Technologies (the new competition reality)............ 60  2.4.6  Other studies oriented by value differentiation or unique advantage ...................................................................................... 61  2.5  Theory synthesis...................................................................................... 69 3  Results of the three action research cycles 73  3.1  Research Cycle 1 – minimising costs ...................................................... 75  3.1.1  Pre-Step ........................................................................................ 76  3.1.2  Diagnosis ...................................................................................... 77  3.1.3  Planning ........................................................................................ 77  3.1.4  Taking action ................................................................................ 80  3.1.5  Evaluation ..................................................................................... 81  3.2  Research Cycle 2 - shortening order delivery time ................................. 84  3.2.1  Pre-Step ........................................................................................ 84  3.2.2  Diagnosis ...................................................................................... 85  3.2.3  Planning ........................................................................................ 86  3.2.4  Taking action ................................................................................ 88  3.2.5  Evaluation ..................................................................................... 89  3.3  Research Cycle 3 - shortening product change time ............................... 91  3.3.1  Pre-Step ........................................................................................ 93  3.3.2  Diagnosis ...................................................................................... 94  3.3.3  Planning ........................................................................................ 94  3.3.4  Taking action ................................................................................ 95  3.3.5  Evaluation ..................................................................................... 96 4  Discussion 99  4.1  Answering research questions ................................................................. 99  4.1.1  Research question 1 ...................................................................... 99  4.1.2  Research question 2 .................................................................... 100  4.1.3  Research question 3 .................................................................... 102  4.2  Managerial implications ........................................................................ 103  4.3  Scientific implications ........................................................................... 105  4.4  Reliability and validity .......................................................................... 107  4.5  Research contribution & discussion ...................................................... 110  4.6  Future research ...................................................................................... 112 5  Summary 115 References 117 14
  14. 14. Introduction1.1 Research background & motivationIndustrial globalisation has greatly changed high-tech companies while they havecreated significant operations in multiple countries. Because poor visibility andmassive uncertainty are part of the operational nature, new challenges arisecontinuously for companies who want to internationalise their demand-supplynetwork. The struggle to survive has become an integral part of each giantcompany’s way of life (Hill, 2000). As the operations become more dynamic(Wazed et al. 2009), the problems of the famous JIT (Just-In-Time) concept (Voss,1987) are increasingly reported with the facts, even in Japan: zero-inventorymanagement is just a fiction (Hann et al., 1999), and JIT is not necessarily usefulfor part suppliers (Naruse, 2003). Even Toyota Motor Corporation as a model ofoperational efficiency within the auto industry, it also got its first annual operatingloss in 2009 after 70 years of enjoying healthy profits. Not as a symbol ofoperational excellence, Toyota recall crisis of 2010 has prompted much criticismin media circles, national business forums and automotive trade publications(Piotrowski and Guyette 2010). Consequently, it is now time for new thinking.For example, it needs to go against the mainstream and take current strategy to amore extreme version of itself, before scaling back just a little bit (Schmitt 2007). The research was initiated in 2002 during last economic downtime bysolution-finding for product change management in a famous internationalcompany, the case company of this research, who operates as one the world’slargest telecommunications infrastructure suppliers, and which continuouslysuffers from inaccurate forecasting and dynamic demand in its innovativemanufacturing. As the nature of mobile infrastructure industry (Collin et al., 2005;Heikkilä 2002), the system vendors have to be able to quickly respond to short-term changes in demand. On the one hand, they are forced to have an in-builtability to constantly adapt their supply chains to rapid and unexpected changes inthe markets or technologies (Raisinghani et al. 2002; Webster 2002). On the otherhand, the vendors are also expected to be fast and flexible while deliveringcustomised products and services with a high standard of delivery accuracy(Alfnes and Strandhagen 2000; Småros et al. 2003; Knowles et al. 2005). In the case company, the old way of doing things was to make a perfectproduction plan based on a perfect forecast, at some point this did not work 15
  15. 15. anymore. In reality there was always some components missing, and productionstopped. As a consequence, scrapping costs became very high. There weredifferent product versions in different sites, with up to one year’s differenceresulting in sites being unable to help each other. In addition, more R&D peoplewere required to support the supply-chain and product changes became very slow,almost out of control. Figure 1 presents an example of the problem situation, relating to demandfulfilment, during a one-year period in the case company. It shows how theforecasts of one or two months were so different from the true demand fulfilled.The example records a hopeless situation, in which such uncertainties makeproduct innovation through engineering changes as well as normal delivery ofcustomer order fulfilment extremely problematic. In other words, and to state theproblem for academic purpose, the intangible information flow in demand-supplynetwork cannot ensure physical product flow just-in-time at each step of themanufacturing operation. Due to the bullwhip effect (Lee et al., 1997; Lee, 2002)in material forecast and product delivery, it is even more frustrating whenutilising traditional purchase orders or long distance transportation. The toughchoice of a trade-off (such as inventory increase, change slow-down, deliverydelay, lost sales) has to be made due to such lead-time gaps in global operation(Shahbazpour and Seidel 2006; Bozarth et al. 2009). It can be even worse whenproduct changes are included as extra uncertainties in this unsynchronised status(Salmi and Holmström 2004).Fig. 1. Challenge with monthly forecast and true demand.16
  16. 16. In innovative businesses, the changes occur for most of a product’s life with greatimpact to whole demand-supply network (Aitken et al. 2003; Dreyer et al. 2007).It is unique to utilise the details about cases of product change managementconstantly in the research of manufacturing operation, which was not seen inprevious attempts by others. It can include more factors than those studies onlydealing with product development (Knight, 2003; Guess, 2002) and demand-supply operation (Bengtsson, 2002; Christopher and Peck 2004) alone, or mainlyat a conceptual and simulation-oriented level (Subramoniam et al. 2008; Falascaand Zobel 2008; Koh and Gunasekaran 2006; Zhou 2006; Kemppainen andVepsäläinen 2004; Saab and Correa 2004). Under a complex businessenvironment as in Figure 2, the research was based on a simple clue from productchange implementation. It is then expected to equalise the amount of all materialin the whole supply operation at anytime and anywhere.Fig. 2. Business operational environment of the research. 17
  17. 17. In the case company, there were simultaneous pressures to minimise costs,shorten the product change period and quicken order delivery processes. Inaddition, the case company had an aim to minimise scrapping costs in allsituations.1.2 Objectives and scopeThe research problem arises from the case company’s challenges in anunpredictable business environment, where demand-supply forecasting is notaccurate enough. How to optimally manage product change process and demand-supply chain in this type of environment? Companies phase pressures tosimultaneously be efficient, responsive and innovative, i.e. to minimise costs, andshorten order delivery and product change periods. The research problem of thisdissertation is formulated: How should companies optimise the product change process strategy in a situation where there are simultaneous and variable pressures to be lean, agile and innovative.This research problem is addressed by focusing on product change process anddemand-supply chain optimisation of large global ICT companies operating inbusiness-to-business environment. First, literature was reviewed to gain understanding on lean philosophy,agility, and innovativeness and consequently to find potential solutions for theresearch problem. In order to obtain information for deeper analyses and conclusions, thefollowing research question were formulated. RQ1 What are the effects for the product change process when costs are minimised (Cycle 1)? RQ2 What are the effects for the product change process when order delivery period is minimised (Cycle 2)? RQ3 What are the effects for the product change process when product change time is minimised (Cycle 3)?Action research method was utilised in the case company to find answers to theseabove mentioned research questions. Each action research cycle, representing aseparate trial, seeks answers for one research question by going into one extreme18
  18. 18. of minimising costs, diminishing order delivery time, or shortening productchange periods.1.3 Research processThe aim of this study was to conduct practical analyses on the effects of changesin essential parameters, namely inventory level, order delivery period, andproduct change time. The effects were studied for a real demand-supply chain of asignificant international actor. Secondly, based on these analyses, this studyattempted to find new means of dealing with complex issues in the describedenvironment.1.3.1 Action researchAccording to O’Brien (1998) action research can be used in practical situationswhere the primary focus is on solving real problems. In addition, the researcherwas employed by a company to whom the studied aspects were of greatimportance. Action research was chosen as a research method as it enablescombining research and ordinary business work within the studied organisation. Action research is concerned with the resolution of organisational issues,such as the implications of change together with those who experience the issuesdirectly. In action research the practitioners are involved in the research, and thereis a collaborative partnership between practitioners and researchers. In simpleterms, the researcher is a part of the research subject. Often action research is aniterative process, often depicted as a spiral, of diagnosing, planning, takingactions and evaluating. (Saunders et al. 2007). Action Research is the process of systematically collecting research dataabout an ongoing system relative to some objective, goal, or need of that system;feeding these data back into the system; taking actions by altering selectedvariables within the system based on the data and on the hypothesis; andevaluating the results of actions by collecting more data (French et al., 1973). Action research enables simultaneous utilisation of different researchmethods and techniques (O’Brien 1998). According to Coughlan (2002) actionresearch requires that the researcher enters the culture, understands the commonvalues, and uses its language. This research method was chosen, even thoughaction research does not meet the verification criteria of positivitism, meaningobjective study as in natural sciences (Susman and Evered, 1978; Saunders 2007). 19
  19. 19. 1.3.2 Research contextSelected case company is a significant global actor in the ICT system business.The researcher was employed by the company, thus having a good access and theresearch was related to his everyday work. The global demand-supply chain ofthe case company is studied in this thesis from the perspective of product changeprocess. The research can be described to simultaneously include aspects ofworldwide business impact, rapid innovative pace, and high volume in operation.There are many engineering changes during a product’s lifetime without a periodwhen new and old versions overlap as execution principle. Component changes inproducts often happen at any time adding extra complexity for manufacturingbesides original demand uncertainty. Product versions were different more thanone year at some manufacturing sites before the research was launched. The component logistics, as in the electronics industry in general, isextremely complex due to a vast number of required components with longproduction or delivery lead-times. For example, the lead-times may differ by days,weeks (such as PWB and own specific integrated circuits), or even months due tosea transportation (such as the cabinet). This causes bottlenecks or big inventoriesin the supply network due to those time variances and real demand often notmatching with earlier forecasts. The case company had to combine push-basedsupply chain and pull-based demand chain together as a mix to synchroniseproduction and delivery of all product parts with big lead-time gaps. Pullprinciple was applied at internal steps of the production, as well as the deliveryend. Push principle had to apply for the supply end and keep the inventories toabsorb the impact of inaccurate forecast. Demand-supply network had to thushave enough tolerance to avoid undesirable conditions, such as production stopdue to lack of key components. Below list describes the challenges faced by the case company:1. Both strategies of lean or agile thinking were not good enough as there were some obvious drawbacks. For example, production lead time was at a level of counting hours or days, which was not a critical step if comparing to months or weeks for material supply. The wish of zero inventory or fast response is hard to achieve constantly in dynamic demand situation. With whole demand- supply network in consideration, not just the case company itself, lead time gaps could not be solved by lean or agile principles alone. It was the20
  20. 20. playground reality when product changes were to be also added into the complexity.2. Production can be described as a multiproduct / multistage stochastic pull system (Askin and Krishnan 2009). Pull principle was applied from product delivery till production start, in order to balance the pace and the flow of manufacturing operations. When the gap of material supply occurred, such a balance would be destroyed in a fire-fighting manner to take time for its recovery. As an example, principles of popular theories were all checked but with the product flow in FIFO (First-In-First-Out) mode at each step of manufacturing, meant that not a same product was initiated, moved and delivered in the operation to fulfil the demand at customer end. Observing in various ways, the effects of different theories could be seen “virtually”, e.g. MTO (Make-To-Order), ATO (Assemble-To-Order), DTO (Deliver-To-Order), and even MTS (Make-To-Stock).3. The main difficulty related to material supply and its liability for key components due to long lead times. It could not be avoided and was a reality for the case company if lead times were not possible to be shortened. For example, new and old material in product change should be controlled well in such a synchronisation. Especially, old components with lead time as weeks could cause the liability as the amount for months to consume. Otherwise, it could result in enormous scraping costs. It was the limitation to product change and normal operations lean effect in mind. The liability was invisible in MRP systems because of inaccurate forecast in the past, which was seldom to be studied to reduce its effect.The bottom-line was to deliver products to customers’ requirements (especiallyhaving the changes of delivery amount or product configuration) at a high speed,without means to develop efficient forecasting processes to manage demanduncertainty. Whenever the volume of pull at delivery side was larger than theamount of push at supply side, production had to be stopped due to missingcomponents. The case company had to find an alternative way to survive better inthe competition as everyone in the industry suffered by those same challenges. In addition, multiple tiers of many companies were involved in the demand-supply chain with international manufacturing operation. Faster transfer ofdemand information or a more reactive planning was not enough to savemanufacturing companies as a physical process is inflexible in responding tofrequent plan changes in normal operation. When product changes added on this, 21
  21. 21. demand-supply planning practices became even more fragmented and frustrated.There were no existing solutions available, academic or industrial, at the time.1.3.3 Practical realisationThe research was mainly realised during the period of 2003–2006. The researchincluded three action research cycles. Each action research cycle sought answersby going into one extreme of minimising costs, diminishing order delivery period,or shortening product change periods. In practice, these research cycles includedthe case company changing their business accordingly for each of these cases.Conducting required changes in the case company were economically significanttrials. Figure 3 describes the research process.Fig. 3. The research process.Research Cycle 1 included the case company aiming all of its actions tominimising costs. The case company executed a strategy of cost effectiveness.Minimising inventory and scrapping costs required swift component control in thewhole demand-supply chain. In research Cycle 2 the case company aimed at diminishing order deliveryperiod. In this trial, the case company aimed at strong concurrency in engineeringto get order delivery period as short as possible. Research Cycle 3 concentrated on shortening product change period. Thecase company executed a strategy of innovativeness making product changes asfast as possible. The trial clarified whether a ready-product inventory could beused to speed up product change. During research cycles, every change case was recorded using change notes(CN). Change notes compare the old and the new product versions, indicating allchanges in used components. CN also indicated the expectation when the changes22
  22. 22. will be conducted. CN was common for all sites enabling to tell which site isinfluenced. Site specific implementation reports were utilised to record changes, theimplementation time and scrapping costs. Implementation report described all theresults from different sites. Both, implementation reports and change notes werestored into a database. There were over one hundred product change cases available within thecompany at the time of research. The researcher selected three cases out of allproduct changes, one for each cycle. The cases were important for business andthere was a significant change in the product. Process improvements were made based on the three selected product changecases individually. After the process improvements, it was checked whether thetargets set for that particular cycle was reached or not. The researcher worked as the project manager for all the studied productchange cases. He was responsible for product change implementations, includingplanning & informing all the sites, and cooperation between these sites, collectingresults, analysing and making conclusions.1.4 Structure of the thesisChapter 1 describes the background information of this research straightforwardlyby using a true problem from industrial practices. The goal is to survive betterthan others in the industry under inaccurate forecast. Because modernmanufacturing in global scale is more sophisticated than ever, it is essential todefine the scope and the limitation of this research precisely. It is aiming to bebeyond lean or agile manufacturing, as well as any improved versions currently inuse. The research approach is selected briefly from reviewing differentmethodologies in order to obtain the advantages of the action research method.This method enables developing modular solutions piece by piece in aninnovative way. In Chapter 2, the literature review is conducted to collect applicable elementsfrom existing management science for further development. They are mainlyfrom the fields of manufacturing philosophies, operational performance ofdemand-supply, product change management, and industrial case study. The empirical research is stated in Chapter 3, and the results accomplished in3 cycles of action research are presented. The key thoughts of each research cycleare verified in order to ensure the research questions studied by sufficient details. 23
  23. 23. In Chapter 4, research questions are answered to summarise the thoughts onflexible optimisation rather than choosing only one option and being stuck in themiddle. The key is applying multi-strategies in business environment as amultidimensional playground. The validation and reliability of the research arechecked. The implications of research with its constructive contributions arediscussed for practical and academic evaluation. After summarising newcontributions of the research, the recommendations for future development arealso presented in order to continue the learning journey further for great success.24
  24. 24. 2 Literature review2.1 Manufacturing philosophiesDifferent manufacturing philosophies include, lean thinking, JIT (Just-In-Time),agile manufacturing, and their derivates.2.1.1 Lean manufacturing and JIT philosophyLean manufacturing, as practiced in the Toyota production system, was arevolutionary change of just-in-time (JIT) philosophy to mass productionpractices in the automotive industry (Haan et al., 1999). The conceptual modelcan be like a continuously moving conveyor belt from the beginning ofproduction to the delivery of finished products. It aimed to provide cost-effectiveproduction as its delivery of only the necessary quantity of parts at the rightquality, at the right time and place, while using a minimum amount of facilities,equipment, materials and human resources. A time line from 1930 to 2006 aboutits development within Toyota to form an overview of JIT can be found inHolweg (2006). However, the problems have been widely reported more and more as thedisadvantages of JIT in the dynamic business of global manufacturing nowadays:– Limited to repetitive manufacturing– Requires stable production level– Does not allow much flexibility in the products producedSeeking for the improvements, one example is the most efficient type of JIToperation – Synchronous Manufacturing (Umble et al., 1996; Srikanth et al., 1997;Doran, 2002), which can be a direction towards new JIT to solve the abovedrawbacks. Synchronous manufacturing embodies many concepts related tofocusing and synchronising production control around bottleneck resources(Frazier et al., 2000). Other common names for these concepts are the theory ofconstraints (or simply TOC) and Drum-Buffer-Rope, which was introduced in1984 by Eliyahu Goldratt in The Goal (Walker, 2002). The Theory of Constraints (TOC) is an overall management philosophy thataims to continually achieve more of the goal of a system. The key is to improveschedule attainment performance and reduce inventories, as well as lead times 25
  25. 25. (Frazier et al., 2000). Drum-Buffer-Rope is a manufacturing executionmethodology, named for its three components.– The drum is the physical constraint of the plant: the work centre or machine or operation that limits the ability of the entire system to produce more.– The buffer protects the drum, so that it always has work flowing to it. Buffers in DBR have time as their unit of measure, rather than quantity of material.– The rope is the work release mechanism for the plant. Pulling work into the system earlier than a buffer time guarantees high work-in-process and slows down the entire system.It was also reported Drum-Buffer-Rope as the synchronisation for agility purpose(Walker, 2002). This can support optimisation, possibly for both lean and agilemanufacturing as two different balancing points for the synchronisation. However, few companies can keep the focus on bottlenecks (as they are hardto identify or too often keep changing) to plan and control production. It cannotbecome a popular way due to such a limitation from the Theory of Constraints(TOC) as the base of synchronous manufacturing. In fact, the synchronisationshould not be related only to the constraints – it is more reasonable to act abovethe business bottom-line if the tolerance is needed as a must from the view ofsynchronisation.2.1.2 ESP concept beyond JIT philosophy In high-mix manufacturing, a new concept of Equalised and SynchronisedProduction (ESP) has been researched by Toshiki Naruse for a revolution beyondthe Japanese Just-In-Time (JIT) system (Naruse, 2003). According to Naruse (2003), the new system of ESP has the followingfeatures in the development:– ESP original concept one: Production guard strictly to customer needs is inefficient. – Hint: Need product inventory to separate production schedule from direct link to the buyer’s orders.– ESP original concept two: To fulfil the production division’s mission, daily production output and production sequences must be stabilised, with production output equalised among the various item numbers.26
  26. 26. – The production Division’s mission: – To maximise production efficiency by making and maintaining improvements toward that end. – To minimise inventory by working toward the goal of zero inventory.For the JIT concept, the supplier or its warehouse must physically locate its plantseither within the manufacturer’s site or nearby. If located far away, it is hard forthem to make synchronisation well enough to meet the requirements of demand-supply (specific volumes and delivery deadlines for specific product items).However, Naruse (2003) claimed the ESP approach is the best way for suppliersin various industries. As a feature or a limitation from view of Naruse (2003), the system of ESP ismore for a parts supplier to deliver products made on its production lines tomultiple buyers / locations. JIT is more for a company to purchase material froma parts supplier and assemble them to finished products, or a parts supplier tobuilt dedicated production lines synchronised with the production ofcorresponding buyers. The ESP production system basically uses the periodicreordering of variable amounts method. Both production and purchasing can usethe multiples of these equalised units. It also needs to ensure the supplierimplements synchronisation with the buyer’s delivery deadline. Shortening leadtime, using smaller lots and raising in-house production efficiency are all keyactivities under ESP. Comparing with JIT of 100 percent response to orders fromcustomers, ESP emphasises maximising in-house production efficiency andminimising inventory as its focus.2.1.3 Agile manufacturing and leagility conceptsBecause of the complexity of today’s supply chains, another direction ofoperational improvements leading to agile manufacturing has been discussedwidely (more radical than the above lean-alternatives of synchronousmanufacturing or ESP). Other names include responsive manufacturing andsupply chain flexibility. The 1990s is associated with two importantconsiderations of agility and supply chain in a history review by Sharifi et al.(2006). A summary of the literature on supply chain flexibility can be found fromStevenson et al. (2007). There is also a list of the contributors relating toflexibility / responsiveness / agility in Reichart et al. (2007). 27
  27. 27. Agile manufacturing is a vision of manufacturing that is a naturaldevelopment from the original concept of lean manufacturing (Gunasekaran,1999). Yusuf et al. (1999) indicates the main driving force behind agility ischange. It is recognised as a necessary condition for competitiveness. Thecomparison of lean supply with agile supply can be seen in the following Table 1(Mason-Jones et al., 2000):Table 1. The comparison of lean supply with agile supply.Distinguishing attributes Lean supply Agile supplyTypical products Commodities Fashion goodsMarketplace demand Predictable VolatileProduct variety Low HighProduct life cycle Long ShortCustomer drivers Cost AvailabilityProfit margin Low HighDominant costs Physical costs Marketability costsStockout penalties Long-term contractual Immediate and volatilePurchasing policy Buy goods Assign capacityInformation enrichment Highly desirable ObligatoryForecasting mechanism Algorithmic ConsultativeHowever, it is very rare to see benchmark cases from famous companies for agilesupply operation as well as IT applications (Helo et al., 2006). More and more,researchers are adjusting the concept backwards and forwards, using with a newword, “leagility” – better to keep efficiency and flexibility always together. It is amore balanced thinking to compare or combine both factors properly in business. According to Mason-Jones et al. (2000) leagility is the combination of thelean and agile paradigm within a total supply chain strategy by positioning thedecoupling point so as to best suit the need to respond to volatile demand.2.1.4 Manufacturing strategies and product life cycleScholarly research in the manufacturing strategy field has moved its focus moreand more to the total impact on product life cycle, as well as to the trend to wholesupply chain in a global scale (Aitken et al., 2003). Aitken (2003) identified theoperational differences of demand-supply network needed in each phase ofproduct life cycle (PLC) as an interesting example of those multiple choices at28
  28. 28. strategy level. The strategic effect from a higher level can provide a largertolerance to supply operation. Holmström et al. (2006) reported external collaboration initiatives such asVendor Managed Inventory (VMI) and Collaborative Planning Forecasting andReplenishment (CPFR) not being sufficient on their own to produce improvedefficiency and responsiveness. Firms need to actively co-ordinate internalcollaborative practices between functions to benefit from their developmentprojects with customers and suppliers. As the view of Hilletofth et al. (2010), it has been always a big challengehow to bring new product to the market faster as a competitive advantage, whichremains to be an essential need in high-tech industries discussed. In marketswhere short product life cycles are the norm, delays in bringing products to themarket can have detrimental consequences to sales and profit. To remaincompetitive in these environments, companies need to produce innovative, highquality, highly value-added products and services and bring them quickly andeffectively to the market. Hilletofth et al. (2010) emphasise two major issues need to be addressed:– The need to develop innovative, value-adding products– The necessity of bringing them quickly to the market.2.1.5 The innovator’s strategyWith the additional interest of radical innovation in industries, a further reviewwas conducted of the innovator’s strategy (Christensen, 2003) about anextraordinary way of competing by disruption in business, as well as its greatimpact especially on the manufacturing operation. There are two kinds ofindustrial innovation: Sustaining or disruptive innovation. A sustaining innovation targets satisfying highly demanding customers byincremental improvements in products with better performance, rather than whatwas previously available. A disruptive innovation model shapes the strategies forthose new growth builders to win the fights. To create a new value network on the third axis is called new-marketdisruptions. According to Christensen (2003), it brings an opportunity for thecompany to satisfy the customer well enough by squeezing the bubble out ofdisruptive innovation. The innovation is thus leveraged by the value as businessdriver focused clearly on the customers. 29
  29. 29. With its big impact, disruptive innovation can act as a force also inmanufacturing, for example, going to market as soon as possible to take morerisks than in normal time. This is the reason to use the innovation inmanufacturing strategies along with product life cycle changes as a new thinking,which actually also happened in one of the cases in the action research.2.1.6 Summary of manufacturing philosophiesThis thesis utilises the following concepts from earlier research as theoreticalfoundation:1. New JIT to adopt postponement for a leaner efficiency as synchronous manufacturing Originally JIT was oriented for a repetitive manufacturing environment. Synchronous manufacturing was developed for low-volume/high-mix production. Concepts related to JIT operational strategy include lean and postponement principles together with flexibility in the manufacturing process. (Cusumano, 1992; Gunasekaran, 1999; Haan et al., 1999; Frazier et al., 2000; Vokurka et al., 2000; Amasaka, 2002; Coronado M. et al., 2002; Doran, 2002; Papadopoulou et al., 2005; Bhasin et al., 2006; Graman et al., 2006; Holweg, 2006; Ruffa, 2008).2. Agile manufacturing to achieve flexible and responsive operation The concepts related to agile manufacturing are claimed to be the next steps after the lean philosophy in production management evolution. Their focus is to respond to customer needs and market changes faster while still controlling costs and quality. These agile concepts are suitable for product-based industries with unstable markets and volatile demand, as well as products with short life cycles. (Brennan et al., 1999; Gunasekaran, 1999; Yusuf et al., 1999; Rigby et al., 2000; Hoek et al., 2001; Little et al., 2001; Prater et al., 2001; Welker et al., 2005; Sharifi et al., 2006; Swafford et al., 2006; Reichhart et al., 2007; Stevenson et al., 2007).3. The leagility to combine lean and agile characteristics The definition of leagility, i.e. combining leanness and agility, was originally developed to describe manufacturing supply chains. The basic idea behind leagility is the existence of a decoupling point, which separates the lean30
  30. 30. processes from the agile processes in the supply chain. Lean processes are seen to be on the upstream side of the decoupling point, and agile processes on downstream. A similar concept is applicable also within a company. Lean and agile concepts can be applied at different stages of the same manufacturing process, for different machines and parts, etc. In this case, a level of buffer stock is maintained between lean and agile manufacturing strategies. (Bonney et al., 1999; Naylor et al., 1999; Robertson et al., 1999; Bolander et al., 2000; Hoek, 2000; Mason-Jones et al., 2000; Pagell et al., 2000; Sahin, 2000; Takahashi et al., 2000; McCullen et al., 2001; Prince et al., 2003; Christopher et al., 2002; Stratton et al., 2003; Corti et al., 2006; Hoque et al., 2006; Stratton et al., 2006; Krishnamurthy et al., 2007; Mohebbi et al., 2007).4. Manufacturing strategy management focused for superior demand-supply performance Demand-supply performance is further studied for optimising, not only a company, but also its ecosystem. Competitive advantages of global manufacturing can be achieved if the supply chain has less organisational boundaries. The key is to simultaneously aim for operational efficiency and market responsiveness, including all parties. (Lummus et al., 1998; Banerjee, 2000; Golder, 2000; Sahin, 2000; Brassler et al., 2001; Olhager et al., 2001; Christopher et al., 2002; Hinterhuber et al., 2002; Loch et al., 2002; Brown et al., 2003; Stratton et al., 2003; Hui, 2004; Hallgren et al., 2006; Brown et al., 2007).5. Others: product innovation, agent-based modelling, IT implementation proposal, research methodology This group of concepts ensures the research supporting a wider knowledge base. For example, the innovation through product changes is in the focus of this research. The development of IT tools for optimising manufacturing execution can be also important, as well as right methodology. (Papandreou et al., 1998; Bajgoric, 2000; Davidrajuh et al., 2000; Thomke et al., 2000; Corbett et al., 2001; Coronado M. et al. 2002; Coughlan et al., 2002; Forza, 2002; Mandal et al., 2002; Walker, 2002; Dooley et al., 2003; Jalote et al., 2004; Ottosson, 2004; Ashayeri et al., 2005; Buxey, 2006; Helo et al., 2006; Nilsson et al., 2006). 31
  31. 31. In order to ensure the literature review focusing on manufacturing optimisation,the discussion includes synchronous manufacturing, Equalised and SynchronisedProduction (ESP), the Leagility, Manufacturing Strategies in Product Life Cycle,and the Innovator’s Strategy.2.2 Developing demand-supply networkIt has been many years as a popular thought that DCM (Demand ChainManagement) and SCM (Supply Chain Management) are not separate butinextricably intertwined (Min and Mentzer 2000) The demand-supply networkmanagement concept of Holmström et al. (1999) proved to be a useful tool inanalysing the demand and supply balancing mechanisms (Auramo and Ala-Risku2005). Combining push-based supply chain and pull-based demand chain together,the study is better focused directly on demand-supply network theory moreapplicable to case company in the research. The reason is no major differencebetween the demand and supply chain with respect to the network oforganizations involved, which are all to create, produce, and deliver customervalue. (Hilletofth 2010).2.2.1 Value oriented development for demand-supply networkThe target of developing demand-supply network is to maximise the overall valuegenerated.Value as a key of winning in competitionAccording to the analysis by Chopra & Meindl (2001), the value is the differencebetween what the final product is worth to the customer and effort the supplychain expends in filling the customer’s request. The success key is the appropriatemanagement of all flows of information, and product, generating costs within thesupply chain. Monczka and Morgan (2000) identified those “critical six” asfollows to be the trend of developing demand-supply network:– Increasing efficiency requirements– Making use of information technology– Integration and consolidation– Insourcing and outsourcing32
  32. 32. – Strategic cost management– “Network” management.For example, PC (Personal Computer) industry has many ways to organize thevalue chain in a network manner. Curry and Kenney (1999) illustrated that thetraditional production-distribution channel (such as IBM and Compaq) co-existedwith new emerging structures represented by “local assemblers” and “directmarketers” such as Dell. Such a complexity as global operation scale has beenalso seen nowadays widely in other high-tech industries. Ketchen et al. (2008) presented a tool as the best value supply chainsdesigned to deliver superior total value to the customer in terms of speed, cost,quality, and flexibility. It is not just simply to create low costs, but also tomaximise the total value added to the customer. Relative to traditional supplychains, best value supply chains also take much different approaches to keyfunctions such as strategic sourcing, logistics, information systems, andrelationship management.Thinking as a networked wayWu and Zhang (2009) introduced the value network perspective into the field ofbusiness model study and discussed basic issues about business model such asdefinition, elements and classification through the lens of value network. Fromthe perspective of value network, the definition of its business module is thesystem connecting internal and external actors by value flows to create, deliverand capture value:– Value actors as the network nodes– Value flows as the network relation– Part of or the whole value network as the network structure.In comparison with real business cases, Wu and Zhang (2009) summarisedbusiness model innovations of value network as follows:– Business model innovation based on actor change– Business model innovation based on relation change– Business model innovation based on network subdivision– Business model innovation based on network extension– Business model innovation based on network integration. 33
  33. 33. Gadde and Håkansson (2001) studied activity co-operation of JIT (Just-In-Time)deliveries with numerous activities conducted by a large number of actors as anetwork view. The complexity of strategising in networks is related to theirmultidimensionality. Any change has some direct effects but also a number ofindirect effects, on other firms, impact on the actor’s performance. The focus isemphasised on the interdependence among the activities conducted by customerand supplier and call for more co-ordination than is needed when inventoriesserve as buffers. The main issue in all network thinking is that “others” need to beincluded. The second key aspect is related to time. The importance of others andthe crucial time dimension indicate that boundaries are key issues in all networkthinking.Focus on demand or supply?Esper et al. (2010) emphasised two primary sets of processes through which thefirm creates value for its customers by moving goods and information throughmarketing channels: demand-focused and supply-focused processes. Historically,firms have invested resources to develop a core differential advantage in one orother of these areas—but rarely in both—often resulting in mismatches betweendemand (what customers want) and supply (what is available in the marketplace).Yusuf et al. (2004) also found supply chains (or demand-supply network) wereunderstood mainly in terms of long-term upstream collaboration with suppliers.However, an equal amount of emphasis is then paid to downstream collaborationwith customers and even collaboration with competitors as a means of integratingthe total value creation process. Hilletofth and Hilmola (2010) indicated management of the demand side(DCM – Demand Chain Management) being revenue driven and focused oneffectiveness whilst the management of the supply side (SCM – Supply ChainManagement) having a tendency to be cost oriented and focus on efficiency.Together these management directions determine a company’s profitability andthus need to be coordinated, requiring a demand supply oriented managementapproach. As the finding of Hilletofth (2010), it is important to promote thecoordination of DCM and SCM, which can occur within a particular companyand across the demand supply chain at different planning levels (strategic,tactical, and operational). From a survey result by Boonyathan and Power (2007), following outcomeswere found:34
  34. 34. – Supply uncertainty is a more significant determinant of performance than demand uncertainty.– Closer relationships with trading partners are associated with higher levels of performance.– Uncertainty can be reduced by being more closely aligned with both suppliers and customers.Mason-Jones et al. (2000) emphasised that the success and failure of supplychains are ultimately determined in the marketplace by the end consumer. Gettingthe right product, at the right price, at the right time to the consumer is not onlythe lynchpin to competitive success but also the key to survival. According to thereport from Ervolina et al. (2006), availability management process calledAvailable-to-Sell (ATS) is an example that incorporates demand shaping andprofitable demand response to drive better operational efficiency throughimproved synchronisation of supply and demand. IBM has implemented an ATSprocess in its complex-configured server supply chain in 2002. The realizedsavings include $100M of inventory reduction in the first year of implementationand over $20M reduction annually in the subsequent years.New trend of operations managementAs a strong trend, demand management should be more integrated in supplyoperation to increase customer satisfaction and life cycle profit (Reiner et al.2009). As the view of Frohlich and Westbrook (2002), the DCM strategyappeared to be the best overall approach for manufacturers to follow and therelatively few manufacturers that are already following this approach. As Ettl et al.(2006) described, a demand-driven supply network (DDSN) is a system oftechnologies and business processes that senses and responds to real time demandacross a network of customers, suppliers, and employees. DDSN principlesrequire that companies shift from a traditional push-based supply chain to a pull-based, customer-centric approach. Waters and Rainbird (2008) even claimed the demand chain and responsemanagement is new direction for operations management. Supply chainmanagement would appear to be at the end of its lifecycle. Customers of all typesare expressing preferences based upon some degree of product-servicedifferentiation and not simply on cost. They suggested the supply chain isobsolescent and should be replaced by a more proactive response system. 35
  35. 35. 2.2.2 Manufacturing strategies affect demand-supply networkMason-Jones et al. (2000) presented that classifying supply chain design andoperations according to the Lean, Agile and Leagile paradigms enables thecompanies to match the demand-supply type according to marketplace need. Forexample, they could be mechanical precision products (lean); carpet manufacture(agile); and electronics products (leagile).Multiple strategy choicesChristopher and Towill (2000) summarised the differences on how to apply leanor agile thinking for demand-supply network affected by manufacturing strategies.The lean paradigm requires that ``fat is eliminated. However, the agile paradigmmust be ``nimble since sales lost are missed forever. An important difference isthat lean supply is associated with level scheduling, whereas agile supply meansreserving capacity to cope with volatile demand. Lack of agile benchmark cases brings the difficulty to understand such aconcept clearly. As the view of Yusuf et al. (2004), the agility of a supply chain isa measure of how well the relationships involved in the processes of design,manufacturing and delivery of products and services. Monroe and Martin (2009)described that agility in the supply chain is described as being able to “respond tosudden and unexpected changes in markets. Agility is critical, because in mostindustries, both demand and supply fluctuate more rapidly and widely than theyused to. According to the explanation of Mason-Jones et al. (2000), leagile supplychains already exist in the real world. Just as case company due to big differencesof material supply lead-time, there is decoupling point in demand fulfilmentprocess where order-driven way changed to forecast-driven way.Design of demand-supply network to support strategiesVonderembse et al. (2006) defined the characteristics for standard, innovative,and hybrid products, and provided a framework for understanding lean and agilesupply chains. Lean supply chains (LSCs) employ continuous improvementefforts and focus on the elimination of nonvalue added steps across the supplychain. Agile supply chains (ASCs) respond to rapidly changing, continuallyfragmenting global markets by being dynamic, context-specific, growth-oriented,36
  36. 36. and customer focused. Hybrid supply chains (HSCs) combine the capabilities oflean and agile supply chains to create a supply network that meets the needs ofcomplex products. As the view of Vonderembse et al. (2006), early in their product life cycle,innovative products, which may employ new and complex technology, requireASC. As the product enters the maturity and decline phases of the product lifecycle, a LSC could be more appropriate. Hybrid products, which are complex,have many components and participating companies in the supply chain. Somecomponents may be commodities while others may be new and innovative. Hilletofth (2009) suggested that companies need to use several SC (SupplyChain) solutions concurrently (i.e. develop a differentiated SC strategy) to staycompetitive in today’s fragmented and complex markets. The arguments in favouris that there are no SC strategies that are applicable to all types of products andmarkets and since companies usually offer a wide range of products and servicesin various types of non-coherent business environments. In particular, Hilletofthand Hilmola (2010) also emphasised a need for real life based industrial casestudies addressing how the various demand and supply processes influence eachother and how they can be coordinated across intra- and inter-organizationalboundaries. Thus, benefits to all parties should be aimed for developing win-winsolution in demand-supply network co-operation. The differences in supplier selection were further studied by Chopra andSodhi (2004) how to plan the manufacturing in demand-supply network smarter:When planning capacity, companies should select an efficient, low-cost supplierfor fast-moving (low-risk) items. In contrast a more responsive supplier bettersuits slow-moving (high-risk and high-value) items. For example, Cisco tailors itsresponse by manufacturing fast-moving products in specialised, inexpensive butnot-so-responsive Chinese plants. High-value, slow-moving items are assembledin responsive, flexible (and more expensive) U.S. plants. Santoso et al. (2005) reported a stochastic programming model and solutionalgorithm for solving supply chain network design problems of a realistic scale.Existing approaches for these problems are either restricted to deterministicenvironments or can only address a modest number of scenarios for the uncertainproblem parameters. Santoso et al. (2005) proposed a methodology to quicklycompute high quality solutions to large-scale stochastic supply chain designproblems with a huge (potentially infinite) number of scenarios. 37
  37. 37. Lead time reduction as strategic effectAmoako-Gyampah (2003) indicated that manufacturing strategy represents theway a company plans to deploy its manufacturing resources and to use itsmanufacturing capability to achieve its goals. Lead time has been recognised as avery important issue in almost all strategy theories. It is one of the root-causes todetermine the choice of manufacturing strategies in many cases. From the view ofSapkauskiene and Leitoniene (2010), speed as a competitive factor is gainingmore and more importance for companies involved in global market competition.The company tends to compete for rapid response to consumer demand and newproducts and technologies introduced to the market. This type of competition interms of reaction time is described as time based competition (TBC). Comparing to lead time reduction in production, such an effort in demand-supply network is often limited so as to bring big operational uncertainty and thebullwhip effect significantly. The time gains so greater importance, as speed,which is required by business and consumer expectations, continues to increaseeven more (Sapkauskiene and Leitoniene 2010). Lyu and Su (2009) described thechallenges in demand-supply including uncertainty of customers’ demands, highinventory levels and cost, inaccurate due date estimation, and slow response tocustomer inquires. Lead time reduction is a critical issue which enablesmanufactures to solve problems. They proposed extended master productionscheduling (MPS) system, developed using Internet technology, can be deployedin a supply chain environment. As similar philosophy focused for reducing lead time, Quick ResponseManufacturing (QRM) developed by Rajan Suri is a strategy that enablescompanies to significantly improve their productivity and their competitive edge.Suri (1998) presented the way how QRM has refined time based competition by:– Focusing only on manufacturing.– Taking advantage of basic principles of system dynamics to provide insight into how to best reorganise an enterprise to achieve quick response.– Clarifying the misunderstandings and misconceptions managers have about how to apply time-based strategies.– Providing specific QRM principles on how to rethink manufacturing process and equipment decisions.– Developing a whole new material planning and control approach.– Developing a novel performance measure.38
  38. 38. – Understanding what it takes to implement QRM to ensure lasting success.Suri (2002) claimed that JIT (Just-In-Time) was perfected by Toyota over 30years ago. For certain markets, lean manufacturing has several drawbacks. QuickResponse Manufacturing (QRM) can be a more effective competitive strategy forcompanies targeting such markets. Specifically, QRM is more effective forcompanies making a large variety of products with variable demand, as well asfor companies making highly engineered products. Suri (2003) explained why QRM has greater competitive potential anddescribed POLCA (Paired-cell Overlapping Loops of Cards with Authorization), amaterial control system to be used as part of QRM. The combination of QRM andPOLCA will provide companies with significant competitive advantage throughtheir ability to deliver customised products with short lead times. Suri and Krishnamurthy (2003) explained that POLCA is a hybrid push-pullsystem that combines the best features of push/MRP systems and Kanban/pullcontrol, while at the same time avoiding their disadvantages. The flow of ordersthrough the different production cells is controlled through a combination ofrelease authorizations (High Level Materials Requirements Planning system orHL/MRP) and production control cards known as POLCA cards (not part-specificlike a Kanban card). The release authorization times only authorize the beginningof the work, but the cell cannot start unless the corresponding POLCA card is alsoavailable. A POLCA card is a capacity signal, while a pull/Kanban signal is aninventory signal. If there is no authorized job, then no job is started, even thougha POLCA card is available. It should be designed available capacities are notsignificantly below the required levels. From the description by Suri and Krishnamurthy (2003), there are SafetyCards, which are only used to release POLCA cards that get stuck in the loop dueto occasional component part shortages. After a period of time, statistics fromthese incidents will provide concrete insight into root causes of the shortages. As their suggestions, the key metrics are measured as follows:– The lead times for the products– The throughputs of the cells– The reliability of delivery between cells– WIP inventories at various points in the system– The on-time delivery performance of upstream and downstream cells in the POLCA loops. 39
  39. 39. Vandaele et al. (2005) also reported the implementation of an E-POLCA systemin a paperless – cardless – environment. It is a load based version for a multi-product, multi-machine queuing network to determine release authorisations andallowed workloads.2.2.3 The role of collaboration in demand-supplyAccording to the explanation of Kaipia and Hartiala H (2006), manufacturingcompanies need the collaboration with customers and suppliers to improve theperformance of demand-supply network. Better information-sharing can reduceboth the bullwhip effect and the operational risk (such as the level of safetystocks).Networked collaboration for better performanceHolweg et al. (2005) discussed that collaboration in the demand-supply networkcomes in a wide range of forms, but in general have a common goal: to create atransparent, visible demand pattern that paces the entire supply chain. Suchcollaboration is for jointly creating the common pace of information sharing,replenishment, and supply synchronisation in the system to reduce both excessinventory and the costly bullwhip effect. For example, Ryu et al. (2009) can identify types of demand informationaccording to their timestamp. There are three types of demand informationclassified according to where they are located along the time-axis. These arerealised demand information, planned demand information, and forecasteddemand information. Two different information-sharing methods are definedaccording to types of shared information and sharing procedures. One is the‘planned demand transferring method (PDTM)’ and the other is the ‘forecasteddemand distributing method (FDDM)’. Udin et al. (2006) proposed a collaborative supply chain managementframework. Normally, supply chain management (SCM) is a system that containsmultiple entities, processes and activities from suppliers to customers.– The basic concept behind SCM is how the raw materials and information flow from the supplier to the manufacturer, before final distributions to customers as finished products or services.40
  40. 40. – In addition, functional areas within the organisation also need information that flows through the SCM in order for them to make a decision to produce products.– The capability of sharing and exchanging information is essential to improve the effectiveness of the SCM.Udin et al. (2006) provided a collaborative framework how to analyse the gapbetween the current and the desirable position (benchmark) for its effectiveimplementation in organisation. Heikkilä (2002) described about the collaboration oriented more by changingfrom SCM (Supply China Management) to DCM (Demand Supply Management)with following propositions:1. Good relationship characteristics contribute to reliable information flows.2. Reliable information flows contribute to high efficiency.3. Understanding the customer situation and need and good relationship characteristics contribute to co-operation between the customer and supplier.4. Good co-operation in implementing demand chain improvement contributes to high efficiency and high customer satisfaction.5. High customer satisfaction contributes to good relationship characteristics.Collaboration to reduce bullwhip effectAs explained by Ismail (2009), bullwhip effect is a major problem in supplychains. It means the amplification of orders as you go up along the supply chain.The bullwhip effect is a phenomenon that was discovered by Forrester (1958)who realized that variations of demand increase up the supply chain fromcustomer to supplier, what was called the Bullwhip Effect or known as theForrester Effect. Holweg et al. (2005) also described that unpredictable or non-transparent demand patterns have been found to cause artificial demandamplification in a range of settings, which is also referred to as the ‘bullwhip’effect’ (Lee et al., 1997; Lee, 2002). This leads to poor service levels, highinventories and frequent stock-outs. After studying three proposed scenarios, Bolarin et al. (2008) concluded thatcollaborative structures improve the Bullwhip effect and reduce the total costs ofthe supply chain in which these structures applied. Those are 3 scenarios in thesimulation: Traditional Supply Chain, VMI (Vendor Management Inventory)(based on collaborative structures among the members that make up the Supply 41
  41. 41. Chain), and EPOS (Electronic Point of Sales). In the collaborative EPOS scenario,the end consumer sales are sent to all members of the supply chain. Specifically,in this strategy the end consumer sales may be used by each echelon for their ownplanning purposes, but each echelon still has to deliver (if possible) what wasordered by their customer (Disney et al 2004). The EPOS chain has proved to bemore efficient than the VMI and the traditional ones in reducing the Bullwhipeffect and in holding costs. Susarla et al. (2004) argued that advances in information technology (IT) thatimprove coordinated information exchange between firms result in a significantimpact on measures of operational efficiency such as time to market, inventoryturnover, and order delivery cycle time. To reduce bullwhip effect, IT can alsomake it possible by exchanging information on a variety of parameters such asdemand and inventory related information, process quality information, feedbackfrom customers etc.Collaborative risk managementChristopher and Lee (2004) noticed that many companies have experienced achange in their supply chain risk profile as a result of changes in their businessmodels, for example the adoption of ‘lean’ practices, the move to outsourcing anda general tendency to reduce the size of the supplier base. As their view, theimprovements in confidence can have a significant effect on mitigating supplychain risk. Snyder et al. (2006) researched about supply chain disruptions. It needs toconsider the risk of disruptions when designing supply chain networks. Supplychain disruptions have a number of causes and may take a number of forms. Theypresented a broad range of models for designing supply chains resilient todisruptions. For example, these models can be categorised by the status of theexisting network: A network may be designed from scratch, or an existingnetwork may be modified to prevent disruptions at some facilities. Snyder et al.(2006) emphasised that the companies may face costs associated with destroyedinventory, reconstruction of disrupted facilities, and customer attrition (if thedisruption does not affect the firm’s competitors). In addition, the competitiveenvironment in which a firm operates may significantly affect the decisions forrisk mitigation. The key objective may be to ensure that their post-disruptionsituation is no worse than that of their competitors.42
  42. 42. Goh et al. (2007) presented a stochastic model of the multi-stage globalsupply chain network problem, incorporating a set of related risks: supply,demand, exchange, and disruption. With the increasing emphasis on supply chainvulnerabilities, effective mathematical tools for analysing and understandingappropriate supply chain risk management are now attracting much attention.They provided an optimal solution with profit maximisation and riskminimisation objectives. Thomas and Tyworth (2006) discussed about pooling lead-time risk by ordersplitting. The policy of pooling lead-time risk by simultaneously splittingreplenishment orders among several suppliers continues to attract the attention ofresearchers even after more than 20 years of extensive study. The research hasfollowing major tracks:– Modelling effective lead-time demand under a variety of stochastic assumptions and enabling an assessment of the impact of pooling on reorder points, stockout risk, safety stock, and shortages.– Modelling cost tradeoffs on a comparison of the long run average total costs for single-source versus dual- or multiple-source models under identical conditions.Thomas and Tyworth (2006) revealed two important and persistent limitations:– The models do not give appropriate attention to transportation economies of scale. Specifically, there are important gaps with respect to the true magnitude of transportation cost, as well as the impact of order quantity (weight), supply lines (distance), and mode (especially air versus ocean shipments in a global setting) on transportation and incremental ordering costs.– The current theory that a reduction in average cycle stock is the key benefit of splitting orders simultaneously considers only the buyer’s on-hand inventory in the supply chain. The absence of in-transit inventory is an important limitation, because simultaneously splitting an order among suppliers does not reduce the combined amount of in-transit stock and cycle stock in the system. Consequently, the only meaningful benefit of pooling lead times is to safety stock from a total system-cost perspective.Thomas and Tyworth (2006) also introduced other options such as a singlesupplier to receive an order and then split it into smaller shipments released 43
  43. 43. sequentially. The long-term transportation commitments can also absorb some ofthe demand variability at the consumer-facing point in the supply chain.2.2.4 Measuring demand-supply performanceAs the view of Jammernegg and Reiner (2007), supply chain performanceimprovement should be measured by reduced total costs (transport, inventorycarrying and resources), as well as improved customer service (deliveryperformance). For MTO (Make-To-Order) and ATO (Assemble-To-Order)production, delivery performance (percentage of orders fulfilled within thepromised delivery time (or due date)) is used as measure of delivery reliability.However, the trade-off between inventory cost and capacity cost has to beconsidered. Reiner (2005) also discussed how performance measures derivedfrom total quality management (TQM) models could help to overcome thelimitations of financial measures. In such a context, process management andcustomer orientation occupy a central position. The performance of demand-supply network should be measured so as toensure its improvement accountable or at least visible. As one of other morecomparable options, it is also better to use existing key performance indicators fora SCOR (Supply Chain Operations Reference) model, which can compare othercases in this field. Here is an overview of SCOR model (Supply Chain Council,2005):SCOR-model key performance indicators1. Customer focus – Delivery performance – Fill rate – Order fulfilment lead time – Perfect order fulfilment – Supply chain response time – Production flexibility2. Internal cost focus – Total supply chain management cost – Cost of goods sold – Value-added productivity44
  44. 44. – Warranty cost or returns – Processing cost – Cash-to-cash cycle time – Inventory days of supply – Asset turns.Ho et al. (2005) emphasised the SCOR model is to help companies in managingtheir supply chain. Process reference models integrate the mechanisms ofbusiness process reengineering, benchmarking, and process measurement in across-functional framework to helping companies to capture the “as-is” state of aprocess and derive the desired “to-be” future status. However, Ho et al. (2005)also indicated that SCOR does not provide a mechanism for measuringuncertainty to enable a company to understand clearly the problems related touncertainty before the setting strategy. Besides, Drzymalski and Odrey (2006) summarise a list of performancemetrics options from literature review, as well as ISO9001 and FEA (FederalEnterprise Architecture) Consolidated Reference Model Document v2.0. Chan(2003) presents following performance measurements as the suggestion. Apartfrom the common criteria such as cost and quality, five other performancemeasurements can be defined: resource utilisation; flexibility; visibility; trust; andinnovativeness. Kaipia et al. (2007) introduced another option as the time benefit method,which compares two potential collaboration modes as the following steps:1. Describe the existing mode of replenishment process – the base case – and one alternative mode.2. Collect demand data for both alternatives to be examined.3. Calculate the following for each item in the product range, and for both the base case and the alternative solution.4. Calculate for each item in the product range.5. Graph for each product item in the product range the time benefit and reordering amplification of demand.For applying the thought from Kaipia et al. (2007) to product changeimplementation, the most of key components (such as material supply normally)belong to the base case and others belong to attentive case (such as VMI). Furthermore, the trend of leading companies in high-tech industry has beenchanged to using IT (Information Technology) solutions as a must in demand- 45

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