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  • 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. (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. – 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. 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. 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. 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. 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. 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. – 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. 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. – 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. 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. 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. 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. – 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. 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. – 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. 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. 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. 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. – 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
  • 45. supply performance (Kauremaa et al. 2004). Auramo et al. (2005) found the ITsolutions to be divided into three categories, 1) transaction processing, 2) supplychain planning and collaboration, and 3) order tracking and delivery coordination.The role of information technology is shifting from a passive managementenabler through databases to a highly advanced process controller that canmonitor each activity (Gunasekaran et al. 2001). New idea or theory how tomeasure the performance should be embedded in information technology tools asIT-enabled research and development (Dong 2010). It could improve real business in global scale and also bring reliableacademic value, which is a trend focused on how to leverage knowledge fasterand better than competitors (Thite 2003). In order to discuss such a trend, Auramoet al. (2005) presented an explorative study about the benefits and theirobservations of IT involvement in performance measurement. To gain strategicbenefits, the use of IT has to be also coupled with business process re-design. It isa new normal of playground for business and a new interesting field for academicresearch, which is so called IT enabled innovation (Watad 2009).2.2.5 Purchasing automation challenge in product life cyclePurchasing is a key activity in demand-supply operation especially hard indynamic product changes. Hilmola et al. (2008) suggested why a portfolioapproach of using different purchasing policies may be central to new intelligentpurchasing systems. A portfolio approach means lot for lot policy (L4L - Theorder or run size is set equal to the demand for that period) may be useful in anearly phase of the product life-cycle, and later it may be an advantage to changeover to economic order quantity (EOQ) based ordering. Jammernegg and Reinera(2007) described about the trade-off of inventory level in purchasing operation.On the one hand, different types of inventory are necessary to buffer againstmarket and operational uncertainties but, on the other hand, inventory issometimes the result of inefficient management of the supply chain processes.Therefore, inventory management has been a focal point of managing supplychain processes. As emphasised by Hilmola et al. (2008), accuracy of demand forecasting isvital to switching point estimation. One potential method for tracking thesesignals of that switching point was mentioned as the development of the GARCHtechnique (proven useful in financial risk management and awarded the 2003Nobel Prize in Economics). GARCH stands for Generalized Auto Regressive46
  • 46. Conditional Heteroscedasticity, which is an econometric model used formodelling and forecasting time-dependent variance. Lin (2010) proposed a GARCH based collaborative planning, forecasting,and replenishment (CPFR) model. Through numerical analysis, a GARCH basedcollaborative forecasting model is much suitable than the other time seriesforecasting model. From the view of Lin (2010), ability to evaluate and qualifyrisk associated with volatility by GARCH will enable businesses tocollaboratively manage inventory risks better and benefit both parties. Meanwhile,through setting an optimal safety multiplier in exception policy, an exceptiondemand also can be efficiently and effectively controlled to maximise the netpresent value. According to the view from Rantala and Hilmola (2005), business conditionsof electronics manufacturers are demanding due to ever shortening product lifecycles, higher variety and increased outsourcing activity. Even though companiescould manage the increasing amount of purchased items with modularity,software-based customization and well designed product platforms; the case isoften so that item count in purchasing is increasing with high rates. Rantala andHilmola (2005) proposed about purchasing automation to solve it as acombination of ERP system integration as well as supply chain solutions, whichwas measured by inventory turns. Based on the case study of a middle-sized telecom electronics manufacturer,Rantala and Hilmola (2010) further reported that an entirely automated orderenables the full use of ‘economic order quantities’ and its derivatives withfollowing factors in the conditions:– Lead time for components is set to be five working days– MOQ (Minimum Order Quantities) is the manufacturer package size and its coefficients– Safety stock for parts is 20 days demand, estimated based on six months’ historical demand– Period of Supply (POS) for needs is 15 working days.As the research finding of Rantala and Hilmola (2010), the inventory turns tend tomove towards a common inventory turn level that is around ten times a year andcomponent level variance declined a great deal by purchasing automation.However, it was worried MRP nervousness and component buffering servicesrepresent caveats for future APO implementations and use. 47
  • 47. Dreyer et al. 2007 discussed the concept of Global Control Centre (GCC) formanufacturing activity. The main elements of the GCC is found to be the globalcontrol model, performance measurement system, ICT solutions and theorganization and the physical environment. The GCC should decrease the level ofcomplexity and improve control of operating environment for those main benefits:– The access to true-time monitoring facilities at a high level– A true SC (Supply Chain) perspective (different from a single actor perspective)– Speeding up recognition and decision making– Integrated decision making (for instance purchasing and production control).2.2.6 Optimisation of demand-supply with thinking of BI automationSimilar as purchasing automation, demand-supply network is mostly supportedby Business Intelligence (BI) solutions with information technology to ensure itsperformance management (Blankenship 2004). BI is a field of the investigation ofthe application of human cognitive faculties and artificial intelligencetechnologies to the management and decision support in different businessproblems (Ranjan 2009). It also needs the thinking of automation to enlargebusiness value and create higher differentiation effect (Kaipia and Laiho 2009) forthe companies to win in global competition. According to the view of Ranjan (2009, companies have understood theimportance of enforcing achievements of the goals defined by their businessstrategies through business intelligence concepts. However, it is a challenge inleading companies how to utilise huge amount of operational data for monitoringand reporting to achieve business excellence (Zicojinovic and Stanimirovic 2009).As the finding of Popovic et al. (2010), measuring the business value of businessintelligence in practice is often not or hard carried out due to the lack ofmeasurement methods and resources. Organisational or enterprise boundaries(Nightingale 2009) often cause the development of such competitive advantageextremely hard, which can be seen as lower priority if the company is alwaysstuck in business fire-fighting issues. With own end-to-end insight, business intelligence automation, is thought asa journey of innovation how to visualise, connect, simplify and optimise theintelligences. The available knowledge can be found mostly about visualisationand optimisation of demand-supply network:48
  • 48. Visibility of Demand-supply NetworkDemand-supply network needs good enough visibility as a condition foroptimising business operations. It has been one of top priorities in the most ofcompanies for high-tech industries. Otherwise, it is very hard in daily work tomatch supply and demand with least inventory (Joshi 2000; Kaipia and Hartiala2006). As observed by Falck et al. (2003), the challenge in developing aninformation management approach is to find solutions that enable informationmanagement across many different organizations. The issue of how to integrateexternal collaboration with internal processes is identified as a gap by Holmstrőmet al. (2003). As the view of Holweg et al. (2005), collaboration in the supply chain comesin a wide range of forms, but in general has a common goal: to create atransparent, visible demand pattern that paces the entire supply chain. Reducinguncertainty via transparency of information flow is a major objective in externalsupply chain collaboration. Kaipia and Hartiala (2006) have reported that there are several sources ofinformation along the supply chain, differing in data quality, information delays,and usability. There is a challenge in choosing the most beneficial data sourcesand in making the best use of the data. Information-sharing can take place acrossvarious numbers of levels in the supply chain, the most typical being sharinginformation between two levels. The information needs also varies according tothe role of each supply chain player and the location they have in the chain. Also,according to the finding from Lehtonen et al. (2005), replenishment collaboration,such as VMI, between manufacturers and distributors may be of little value inspeeding up demand synchronisation in product introductions. As the view from Kaipia (2009), specific supply chain characteristics need tobe balanced by selecting a coordination mechanism that uses informationoptimally to support the material flow. Flexible material flow needs frequentupdates of the plan based on accurate information:– If frequent information sharing and planning practices are used to support inflexible material flow, the result may be volatility in plans, and planning resources are wasted.– If a flexible material flow is supported by inadequate information, waste may be produced in the material flow, in the form of excess inventories or capacity. 49
  • 49. Obviously, the influence of demand-supply network integration on productinnovation is greater than other variables (Baharanchi 2009). It is important thatrapidly responding demand-supply requires more integrated planning andfrequent information sharing (Kaipia 2009). As studied by Christopher and Towill (2000), lean or agile strategy needs alsoto emphasise information visibility in demand-supply network. Whereasinformation transparency is desirable in a lean regime, it is obligatory for agility.Lean forecasting is algorithmic, but agile forecasting requires shared informationon current demand captured as close to the marketplace as possible. As the observation from Auramo (2006), visibility can be thus approachedfrom both a tactical and strategic perspective. The tactical perspective focuses ontransactions as it offers visibility to the flow of materials, available capacity andresources. From a strategic perspective, visibility enables evaluation andreshaping of such operational network more in line with changing businessenvironments.Optimisation of Demand-Supply NetworkThinking of business intelligence automation is not just for traditional automationof tasks that were previously performed by humans (Stohr and Zhao 1997). Withvisibility development focusing heavily on individual results, there are manyopportunities to connect and simplify them further for new offers in businessintelligence field. They are the steps leading to optimisation of demand-supplynetwork, which can form a journey of business intelligence automation to developgreat value. But, capturing the business value of business intelligence (BI) is astrategic challenge (Williams et al. 2003). It has bee hard to find those practicalcases of optimisation reported in industrial or academic world. Especially,available information of the research is found more often as the simulation ormathematical models (Reiner et al. 2009, Sepehri et al. 2010). A focused reviewof literature is mostly to study the outcome (such as simulation result orconclusion) if applicable for its trial and implementation later in real businessenvironment. The thoughts can be useful to support action research at least beforeown thinking of business intelligence automation will be continued. Reiner (2005) described how process improvements can be dynamicallyevaluated under consideration of customer orientation and supported by anintegrated usage of discrete-event simulations models and system dynamicsmodels. It was the use of selected performance measures as well as indicators by50
  • 50. a specific process improvement (postponement), which was conducted by anelectronic manufacturer in the telecom industry. Using process simulation by Jammernegg and Reiner (2007), theydemonstrated how the coordinated application of methods from inventorymanagement and capacity management result in improved performance measuresof both intra-organizational (costs) and inter-organizational (service level)objectives. It was conducted to a quantitative model-oriented research, based onempirical data. The results had shown that a change from MTS (Make-To-Stock)to ATO (Assemble-To-Order) production leads to reduction of total costs(shipping and inventory carrying) of 11% on average. Govindu and Chinnam (2007) described a generic process-centredmethodological framework for analysis and design of multi-agent supply chainsystems with following contributions:– Development and validation of generic methodological support for analysis and design of multi-agent supply chain systems.– Creative adoption of SCOR (Supply Chain Operations Reference) to generic MAS (Multi-Agent Systems) development methodology.– Introduction of the notion “process-centred organisation metaphor” for multi- agent systems.Amer et al. (2008) provided a method optimising order fulfilment by six sigmaand fuzzy logic, which is as an effective methodology for monitoring andcontrolling supply chain variables, optimizing supply chain processes andmeeting customer’s requirements. Unlike product design where the finaldeliverable is a tangible product, the supply chain can be presented as anintangible component of service design (i.e. covering a work plan to meet supplytargets, management of information flow, decision making, etc) with the tangiblecomponent being the practical implementation of the service design (actualhardware like logistics, transportation, information infrastructure, etc). Raj and Lakshminarayanan (2008) proposed that entropy based complexityminimization method is able to improve the performance of the distributionsystem significantly compared to the initial performance of the supply chain. Thiscomplexity management strategy can be extended to the overall network and forsystems with more states of interest. The work aims to improve supply chainperformance by quantifying and minimizing the complexity associated with thedistribution system through entropy calculations in accordance with the businessgoal and demand pattern faced by the network. 51
  • 51. Reiner and Fichtinger (2009) developed a dynamic model that can be used toevaluate supply chain process improvements, e.g. different forecast methods. Inparticular they used for evaluation a bullwhip effect measure, the service level(fill-rate) and the average on hold inventory. It was found that the bullwhip effectis an important but not the only performance measure that should be used toevaluate process improvements Rabta et al. (2009) discussed about queuing networks modelling software formanufacturing. In order to improve performance of a complex manufacturingsystem, the dynamic dependencies need to be understood well (e.g., utilization,variability, lead time, throughput, WIP, operating expenses, quality, etc). In thismanner rapid modelling techniques like queuing theory, can be applied toimprove such an understanding. Queuing networks are useful to model andmeasure the performance of manufacturing systems and also complex serviceprocesses. Radhakrishnan et al. (2009) studied inventory optimisation in supply chainmanagement using genetic algorithm. It is a innovative and efficient methodologythat works with the aid of Genetic Algorithms in order to facilitate the precisedetermination of the most probable excess stock level and shortage level requiredfor inventory optimization in the supply chain so that minimal total supply chaincost is ensured. Sepehri et al. (2010) suggested a Corporate Supply Optimizer (CSO), as acentral entity taking advantage of the notion of flow networks, gathers necessaryoperational information from members of the corporate supply chain. The CSOthen guides supply chain members on ordering decisions for a minimum overallcost for the entire supply chain. The CSO seeks a solution with minimum totalcosts, unlike non-cooperative supply chains where individual members competeto optimize their local costs.2.3 Product change managementAs Christopher (1998) explained, time has become a critical issue in managementas the most visible feature in industries. Product life cycles are shorter than ever,industrial customers and distributors require just-in-time deliveries, and end usersare ever more willing to accept a substitute product if their first choice is notinstantly available. Product change management has to be applied as a key role inenterprise operation, which has been able to establish a differential advantage inhigh-tech industry. It can bring an end-to-end impact through the supply network52
  • 52. to other partners. According to Knight (2003), Product change management hadbeen standardised to a popular process - enterprise change request and notice inits version control. In detail, it was mainly based on CM II principles of ClosedLoop Change Process (CLCP), which was developed and marketed by theInstitute of Configuration Management in co-operation with Arizona StateUniversity and the University of Tennessee. All results of product version changeover were recorded as quantified data nomatter if the case was belonging to 75–85% of the fast track or 15–25% of largechanges. For high-quality of product change management, a balance is neededbetween implementation speed at each manufacturing site and scraping cost in thewhole supply network. Scraping cost was normally caused by those non-standardised components in material supply not usable anymore after productchanges. The targets of faster implementation and lower scraping cost should becontrolled carefully in all changes. Particularly, every ECN was generated with change description detail, as wellas Bill of Material (BOM) for product current and new versions. It included allaffected sites and their implementation results. The analysis to indentify changedrivers (key components) was essential for updating demand-supply status atweekly level and selecting changeover date with scraping cost known in advanceas a quantitative manner. The amount of new, existing and closed ECN wasfollowed monthly with implementation time as main focus. The scraping costtrend was also studied regularly according to product or manufacturing site.Quantified data in such a change management practice was traceable along withwhole product life. As a research, the selection of those cases was oriented by differentmanufacturing strategies in order to present the results from ECN database in acomparable way but also with meaningful diversities. Christopher (1998)suggested that successful companies should have a productivity advantage (lowercost profile) or a “value” advantage (offering a differential “plus” – such as quickdelivery), or a combination of the two. The research was aimed to develop aunique breakthrough that goes beyond either traditional lean or agile benchmarks(Krishnamurthy et al., 2007 or Mohebbi et al., 2007). As the research shown by Reiner et al., (2009), technology advances andcompetitive pressure have shortened the life cycles for many products anddrastically increased the penalty of holding inventories. A major problem is thatforecasting the volume of products with short life cycles is difficult. Therefore, 53
  • 53. many supply chains rely on large inventory holding to reduce the risk of productunavailability, which is a costly way very slow for implementing product changes. The research of Reiner et al. (2009) has been targeted to mobile phoneindustry with simultaneous inventory and pricing decision in the consideration,which utilise the software tool Ithink to generate and analyse the mathematicalformulation. However, it is a different challenge to study mobile infrastructurecompanies due to no product version overlapping there. For example, it is hardlyto see any research about reducing material supply liability and obsolete cost insuch product changes. With product innovation as a creative force proposed byUtterback (1996), new search can be thus as the first study in this field, includingadequate details, covering new thinking to utilise product change cases tounderstand the nature of global manufacturing.2.4 Special characteristics of high-tech industries2.4.1 Challenges in forecastingSimilar analyses of typical disturbances in industrial environments can be easilyfound from others researching the uncertainties of supply networks. According toMascada (1998), they can be grouped to two main types: internal and externaldisturbances. The internal disturbances can include equipment failures, qualitymiss, lack of co-ordination, and workforce unavailability. The rest of the othersare external disturbances caused by customers or suppliers. All of those factorsaffect the forecast, which is thus difficult to make it accurately. Another sample is from the research on different planning deviations anddisruptions in the risk management of supply chains (Roshan et al., 2004) shownas Table 2:Table 2. Types of deviationsPlanning Level Type of Event ExampleStrategic Deviation Logistics/Manufacturing Capacity Reduction Disruption Supplier bankruptcyTactical Deviation Order forecast Disruption Port strikeOperational Deviation Lead-time variation Disruption Machine/Truck breakdown54
  • 54. The events at each level of corporate planning can bring challenges with differentscales. As Roshan et al. (2004) states, both factors of regular deviations and majordisruptions should be considered. Especially, the impact from the higher level cancreate a disaster with a system-wide effect. From all of the above analysis, it is reasonable to consider that the businessforecast is unlikely to be right most of time in light of these uncertainties. Peoplehave to live with and survive business uncertainty by seeking other ways if notjust to improve forecasting accuracy alone. As global markets are becoming moreturbulent and volatile, it reveals such a common challenge in the industryaffecting truly to everyone. Thus, it can be also as a great opportunity for researchpurpose.2.4.2 Telecom supply chain of case companyManufacturing operation in telecommunications infrastructure industry is closelyrelated to product life cycles. Such a feature of innovative business model hasbeen studied by Bengtsson and Berggren (2002), which can be briefly as a basicintroduction of the industry. As the operational type of case company, both product development andmanufacturing functions are well combined in a project business way to fulfilcustomer demand (Collin 2003). For example, it includes prototype fabricationand pilot capability (zero-series production), departments for productindustrialisation and high volume production (Bengtsson and Berggren 2002).Volume production can be also called flow production, repetitive flow production,or other names. Indicated by Terwiesch et al. (1999) for achieving a fast pay-backof investments in new product designs and production facilities, companies inhigh-tech industry must reduce their development time (time-to-market) as wellas the time it takes them to achieve acceptable manufacturing volume, cost, andquality (time-to-volume). The reason for keeping volume production in-house,apart from cost and revenue considerations, is the importance of maintaining ahigh skill level in manufacturing from the view of Bengtsson and Berggren(2002). As Flynn (1994) emphasised, fast product innovation can be considered tobe an element of world class manufacturing. Such a way can thus provide a rapidfeedback from mass production to product design and engineering directly. As “product focused”, the manufacturing and sourcing operation is a“component oriented” manner, which means the company maintained strategiccomponents and processes in-house, together with the majority of final assembly 55
  • 55. and testing of ready modular products (Bengtsson and Berggren 2002). Of course,non-strategic components are sourced from selected suppliers or sub-contractedmanufacturers. However, a reliable forecasting for telecom industry is difficult insuch an increasingly deregulated and competitive market place (Fildes and Kumar2002). It can be very hard to analyse future trends and adapt the capacity levelsaccordingly for all parties in demand-supply network. Heikkilä (2002) discussed about three demand chain processes as variationsof generic demand chain architecture with following features:1. Supporting the customer’s network building process by sufficiently fast deliveries.2. Building a product structure to enable decisions on the order-penetration point for a base station according to the customer need.3. Flexibility in the assembly capacity to meet the market uncertainty.4. Inventory optimisation within the constraints resulting from the above criteria.Heikkilä (2002) proposed that supply chain improvement should start from thecustomer end, and the concept of SCM should be changed into demand chainmanagement. Demand chain management understands the need for goodcustomer–supplier relationships and reliable information flows as contributors tohigh efficiency. Berggren and Bengtsson (2004) have described this horizontal model assuperior option, which includes the advantages of speed to market, and revenue.The used horizontal model can facilitate intensive interaction and reduces inter-organisational interfaces. It is seen as more responsive and conducive to rapidindustrialisation of new products than a vertically sliced model, where volumeproduction is externalised.2.4.3 Case Ericsson (analysed in 2002–2003)From the study to one of leading players in this industry, Gustafsson and Norrman(2001) reported a detail description about TTC (Time to Customer) flow andTTM (Time to Market) flow in Ericsson’s demand-supply network. An obviousfeature of the demand-supply network is to use a common forecast to all partiesand call-off as the feedback to form a close loop. Due to its manufacturing mainlyoutsourced, the information flow interacting with the customers and suppliers isvery essential to Ericsson. With such a set-up, it could help the speed ofintroducing new products and also normal time of its global operation.56
  • 56. Ericsson Radio System’s demand-supply chain was proud of its followingfeatures (Gustafsson et al., 2001):– Able to track and manage customer orders from receipt to fourth-tier supplier authorization.– A response to a customer inquiry about a delivery promise can be determined within 10 seconds based on a current view of value-chain capabilities.– The order information is then sent throughout the enterprise, which includes the currently connected 25 first-tier suppliers, 10 second-tier suppliers, one third-tier supplier, and one fourth-tier supplier.– The resulting improvements include order lead-time reductions from 15 to 1– 2 days, inventory-turn increases from five to 80, and on-time delivery improvement from 20% to 99.9%. But, Ericsson’s bad situation (at the end of 2003) came back later again. Itwas mainly because the difficulty was not just to measure one company itself butto synchronize all parties in demand-supply network. Here was the informationfrom internet (Contact no.20) found at that time:– Purchasing amount is near 2/3 of Ericsson’s total costs.– Market is unpredictable in challenging to require better forecasts.– Product volumes are smaller but the level of complexity is greater.– Fire-fighting to get components.– Delivery problems in Ericsson and its suppliers.– Existing lead-time too long and uncertain forecasts are causing production plan out of synch with actual demand for last-minute changes.– Sales organization will add a safety margin and order more than needs resulting greater variations in volumes with long or increasing lead times.– Material shortage causes the plant and subcontractors with more stress, money, quality inspection … All putting Ericsson back where it started – long lead times.– Customer satisfaction is only about 70 percent.– “Santa Claus always delivers on time, but only once a year.” 57
  • 57. 2.4.4 Case Dell Corporation/Lucent Technologies (analysed in 2002– 2003)As one of the most commonly cited success stories of business operationalexcellence, Dell Corporation represents the out-box-thinking model in computerindustry with remarkable achievements (Bilbrey 2000). Karemer et al. (2000)described the exceptional performance was achieved by innovative response to afundamental competitive factor in the personal computer industry—the value oftime. It included Dell’s strategies of direct sales and build-to-order productionhave proven successful in minimizing inventory and bringing new products tomarket quickly, enabling it to increase market share and achieve high returns oninvestment. The detailed features of Dell’s model are stated as follows (DellCorporation 2003):– Dell computers are made with the latest available technology.– Materials costs account for about 74% of the revenues.– The suppliers are actually located all over the world (such as its Ireland plant with the suppliers 65% in Asia, 25% in Europe and 10 % in USA). Many of the suppliers have plants within 20 minutes of Dells manufacturing plants. Dell replenishes inventory levels as often as hourly with some vendors; it turns over 52 inventory cycles each year, or once a week.– Share information by real time communication with suppliers for rapid order fulfilment (such as 10,000-plus customers every day in USA to change demands unpredictably).– Five day average Dell’s inventory in 2001 with target of 2.5 days (the competitors carry 30, 45, or even 90 days worth) & the third-party logistics providers storing supplier-owned products with ten extra days or one week in HUB near Dell’s factory.– Dell Company gets billed after the components leaving supplier’s HUB. The inventory-carrying costs are transferred to its suppliers to decreases the level of inventory on Dell’s balance sheet.– Demand-pull rather than supply-push. It never builds a computer without a customer order. Most Dell systems are built in five hours or less.– Excess and obsolete inventory (about $21 million / year) between 0.05% and 0.1% of total material costs (the competitors probably 2% to 3% worth of excess and obsolete inventory).– 84% of orders are built, customized, and shipped within 8 hours.58
  • 58. – Dell sells 90% product directly to the customer.– Market share +170% in 5 years (1997–2002) with profitable growth even in a global economic hard time.As indicated by Karemer et al. (2000), the key to Dell’s success has been itsdirect sales and build-to-order business model. This model is simple in conceptbut highly complex in its execution, especially under conditions of rapid growthand change. Dell has continually renewed and extended its business model whilestriking a balance between control and flexibility. However, the customerfeedbacks show the results of its delivery still with big challenges (from web ofHardwareCentral accessed in 2003):– Good feedback: “The delivery was 12 business days after ordering”, “PC delivery was within 6 business days”.– Bad feedback: “Computer was not received more than 3 weeks after ordering”, “Delaying the delivery by 3 weeks”, “Delayed shipment up to 30 days”– Customer satisfaction indicator = 2.9/5 (58% - quite low).The challenge aiming for delivery properly on time seems hard in real life to DellCorporation due to its demand-supply chain sometime not matching with the idealrequirement of responsiveness if bottlenecks does exist in suppliers! As explained by Hoover et al. (2001), a new approach was developed inLucent Technologies as 3C (capacity, commonality, consumption) materialsmanagement system with the following principles:– Plan the business (sales) based on capacity.– Leverage commonality to reduce inventory.– Produce according to consumption (actual demand).Its success key factor is because the 3C approach links sales planning seamlesslyto component suppliers using a collaboration process based on ranking maximumusage rates of individual components (Holmström et al. 2002). Hoover et al.(2001) stated the details about the 3C approach: The first step is to define amaximum sales rate of each end product that the factory will support. Second, thefactory capacity to produce the end product (units of output per day) isdetermined. And finally, the component level maximum daily usage rate isdefined. 59
  • 59. Kumar and Meade (2002) described the system allows a manufacturer to beprepared to produce anything they manufacture up to the maximum productioncapacity for that item at any time. Instead of being driven by a finished goodsforecast that is turned into a daily or weekly production schedule, the 3C systemis driven by component-level maximum daily usage rates, which are set quarterlyor annually. According to further explanation by Hoover et al. (2001), the only thing thatis needed daily is to check the on-hand inventory, what is on the way fromsuppliers, and make sure that the sum is better than the maximum usage rage forthe number of days it takes the supplier to replenish. The supplier replenishes toconsumption. As a result at the Lucent Technologies Tres Cantos, Spain, plant, theapplication of 3C led to an increase in fill rate from 75% to 95% (Kopczak et al.,1998), nearly double the industry average.2.4.5 Case Huawei Technologies (the new competition reality)As indicated by Pisano and Shih (2009), outsourcing manufacturing has left U.S.industry without the means to invent the next generation of high-tech products.Nearly every U.S. brand of laptop and cell phone is not only manufactured butdesigned in Asia. A new original equipment manufacturer (OEM) should bestudied from those rapid growth companies or countries, in which HuaweiTechnologies can be such a leading Chinese player with remarkable impact ininternational telecommunications markets. Its aggressive strategy has resulted inthe acquisition and merger of several international telecommunication devicesuppliers (Dickson and Fang, 2008). In 1988, Huawei was establishes in Shenzhen China as sales agent for HongKong company producing Private Branch Exchange (PBX) switches. It wasranked as No. 3 in terms of worldwide market share in mobile network equipmentin 2008. Then, it became No.2 in global market share of radio access equipmentin 2009 (Huawei 2010). According to the view of Nishimura (2008), Huaweishould be able to attain its full growth potential as one of the strongestmultinational companies. With its strong capabilities in development and design,it can combine with the most advanced technology and parts, meanwhile utilisingcheap domestic labour and other resources. As reported by Wu and Zhao (2007), Huawei applied different market entrymode in different markets (different geographical markets and different productsmarkets). It had to enter the developing countries’ market first before it enters60
  • 60. developed countries’ market. Similar as its business model in domestic market,the method was to set up the R&D department or register subsidiary companies indeveloped countries to develop an international market share. Zhang (2009) studied also following reasons why Huawei has beenrecognized by Business Week as the 3rd World’s Most Influential Company(following after Apply and Google):– In order to develop management skills and structure, Huawei invested in collaboration with IBM Consultant.– Besides catching up in management, Huawei invested heavily in Research and Development. Averagely each year, at least 10 % of annual sales were put into R&D for developing absorptive capacity. For example, Huawei so far has established 14 R&D centres around the world.– Its alliance-based network is characterized by multidiscipline, multi-level, and multi-regions, being embedded in the collaboration with suppliers, customers, universities, and leading players.To support motivating Huawei people, it adopted a bonus and stock-option systemto reward good technology (Lau et al. 2002). As the observation of Liu (2005),Huawei can thus grow faster based on a market-oriented innovation strategy. In contrast with current No. 1 leader in same industry, the battlefield ofleagility in demand-supply operation can be no longer to protect its leadingposition or even ensure its better survival. The key is because Huawei has morerelative advantages as the compensation to win the battle: lower break-even andlower revenue expectation in cost-profit analysis. Same competitive effect couldbe achieved easily if product value is as good as other competitors. It will becomean unstoppable journey for Huawei to re-write the history if other leadingcompanies would ignore the radical innovation as a new must nowadays. Similarin many circumstances, the No. 1 leader should bring its value differentiation tothe customers or keep its unique advantage in the industry.2.4.6 Other studies oriented by value differentiation or unique advantageKim and Mauborgne (2005) indicated that head-to-head competition results innothing but a bloody red ocean as rivals fight over shrinking profits. Similar astheir proposal of blue ocean strategy focused on creating unknown market space,value differentiation can have a same effect in any period of the lifecycle for 61
  • 61. industrial innovation by making the competition irrelevant, as well as leading thetrend in Information and Communication Technologies (ICTs).Industrial lifecycle analysis as a toolAccording to the research of Gottfredson et al. (2008), experience curves can beused to show how much industry prices and company costs have fallen each timethe industry’s cumulative experience (total units produced or services delivered)has doubled. It is possible to allow the companies to predict how much inflationadjusted prices and costs are likely to decline in the future. Tan and Mathews (2010) made a similar research how to utilise the view ofbusiness cycle, industry / technology lifecycle, and industry cycle for thecompanies to win in the competition. They also indicated that cyclical behaviourin the economic system is one of the great themes in economic forecasting andinnovation study. Firms such as Intel have made a major discovery in their abilityto profit from industry cyclical downturns. Intel has consistently acted as a‘counter-cyclical investor’ over the past two industry cycle downturns. Thesebusiness successes now call for complementary innovations in the fields ofbusiness policy and strategy to generalize the findings and account for theirsuccess in terms of the fields theoretical frameworks. Tan and Mathews (2010) executed the time series analysis in the time domainand in the frequency domain. It was not only to understand more precisely thecyclical movement of the industry, but also new insights about potential sourcesof the cyclicality and the implications of industry cycles to innovation strategiesand behaviour in the industry.Business growth by blue ocean strategy thinkingThe Blue Ocean Strategy was introduced by W. C. Kim and R Mauborgne withfollowing six principles (Kim and Mauborgne 2005):1. Reconstruct Market Boundaries2. Focus on the Big Picture, not the Numbers3. Reach beyond existing demand4. Get the Strategic Sequence Right5. Overcome Key Organizational Hurdles6. Build Execution in the Strategy.62
  • 62. Kim and Mauborgne (2005) emphasise the strategic move is the right unit ofanalysis for explaining the root of profitable growth, and not the company or theindustry. As explained by Kim and Mauborgne (2005), the strategic move is theset of managerial actions and decisions involved in making a major market-creating business offering. The definition of the red or blue ocean can be seen asfollows:– In the red oceans, industry boundaries are defined and accepted, and the competitive rules of the game are known. As the market space gets more crowded, prospects for profits and growth are reduced. Products become commodities, and cut-throat competition turns the red ocean bloody.– Blue oceans, in contrast, are defined by untapped market space, demand creation, and the opportunity for highly profitable growth. Although some blue oceans are created well beyond existing industry boundaries, most are created from within red oceans by expanding existing industry boundaries. In blue oceans, competition is irrelevant because the rules of the game are waiting to be set.From the view of Kim and Mauborgne (2005), the market universe has neverbeen constant; rather, blue oceans have continuously been created over time. Tofocus on the red ocean is therefore to accept the key constraining factors ofcompetition— limited market space and the need to beat the enemy in order tosucceed. However, companies need to go beyond competing in establishedindustries. To seize new profit and growth opportunities, they also need to createblue oceans.Leading industrial innovation as AppleIn order to create value differentiation via platform leadership similar as Intel,Ghazawneh (2010) emphasised the Apple’s iPhone as another one of the projectsadopting the open innovation paradigm since it does not only depend on internalbut external and distributed sources for the developments of its applications andservices. The adoption of this open innovation model is mainly fulfilled by theimplementation of a product platform that enables almost anyone to innovateupon its evolving system in an interdependent way. From the view of Braithwaite (2007), the benefit of using the iTunes platformis that Apple can maintain a direct and ongoing relationship with customers notfeasible for other handset manufacturers. Apple uses the iTunes ecosystem as the 63
  • 63. means for upgrading the phone’s capabilities through software upgrades as wellas an e-commerce web site for the sale of music and video content. Braithwaite(2007) argued the revolutionary “user interface” and enhanced “user experience”as the function of new technology as well as software designed to simplify theoperations of the phone. The iPhone proves to be as revolutionary as widelypredicted other cell phone manufacturers would need to respond. As reported by Mohr et al. (2010), Apple does product design of all itsproducts in-house in California with its own designers and engineers. Design is acore, proprietary skill set for Apple which gives it competitive advantage in themarketplace. For example, Rixner (2007) indicated the Apple’s iPod wildlysuccessful relative to MP3 offerings is a business design that provides a completedigital music experience. While its competitors pursued either a device approachfocused on MP3 players or a music-store approach focused on downloadablesongs, Apple provided an integrated offer of hardware (iPod), software (iTunesmusic library), and content (iTunes music store). For Apple’s iPod, its manufacturing and even core software are outsourced(Lo 2008). The subcontracting manufacturer likes to work with Apple more thanwith other firms because “the iPod’s popularity ensures that orders keep comingin” largely due to customers’ loyalty to Apple’s notable R&D capabilities. Asmentioned by Spink and Krudewagen (2009), Apple sells a $299 iPod (designedin California, assembled in China), for instance, it makes an $80 profit, while theChinese assembly plant makes $4. Known from the analysis of Mulrennan (2010),Apple’s share price rise from $9.43 to $203.00 per share in the following eightyears after the iPod was launched in 2001. By late 2009, the unique position thatthe iPod held within the market was validated by the announcement that 225million units had been sold worldwide. The iPod currently holds a market share of78% among digital media players. By contrast, Copeland and Shapiro (2010) mentioned that Apple is slower attechnological adoption than the other PC (Personal Computer) manufacturers. PCmanufacturers are introducing significantly more products with shorter life spansrelative to Apple. Apple keeps its computers on the market about twice as long asthe other PC manufacturers. Apples prices fall relatively slowly and lessextensively than do the prices of the PC manufacturers. Prater et al. (2001) alsomentioned Apples supply chain was not complex, the uncertainty involved in seatransportation made Apples supply chain vulnerable. At the same time, Applessupply chain agility was low because of the low speed and flexibility with whichproduct could be brought to market.64
  • 64. Obviously, Apple has learned the tricks from its practices in PC industry andbrought open innovation into smart-phone industry better than other competitors(such as Nokia or RIM’s Blackberry acting still so similar as Apple’s verticalplatform in PC industry), as well as keeping some advantages on product lifecyclecontrol. Sako (2009) claimed Apple Computer was not successful as an integratedPC firm, but emerged successful as Apple Inc. with its iPod and iPhone, when itbundled entertainment and mobile telephony.Competing by new product or business design (case RIM’s Smartphone)?In comparison with unique advantage of Apple in a same market, it is interestingto check other competitors such as RIM (Research In Motion) with its BlackBerryproduct as an example. As Hahn and Singer (2009) described, it was Research inMotion (RIM) and not Nokia that developed the smart-phone segment. AlthoughRIM’s BlackBerry was not the first wireless device with reliable e-mail access, itpopularized mobile e-mail among business professionals because of itsintegration with Microsoft Exchange servers and strong encryption. Through theintroduction of the iconic BlackBerry, RIM has proven itself to be a leader in thehandset industry. Expectations were high in November 2008 when RIMintroduced a touch-screen smart-phone, the BlackBerry Storm, to compete withthe iPhone. But the Storm has proven to be somewhat of a disappointment.However, innovation is a continuous process. Hahn and Singer (2009) believed that BlackBerry will likely learn from itssuccesses and failures. Given the pace of technology development in the mobilehandset market, the iPhone’s position is hardly guaranteed. A new device couldrender the iPhone obsolete quickly. As indicated by Rixner (2007), the key toeach of these successes (such as Intel, Apple, or RIM) goes far beyond thecompany’s products and lies in the business designs surrounding theirtechnologies. If the Apple’s iPhone can be seen as a strategic move to the blueocean of Smartphone market, what is the next big thing to beat it or re-create anew successful story by another unique way?“Shanzhai” to be a bad copycat manner or as an open innovationAs Lee et al. (2010) explained, “Shanzhai” is a Chinese term referring tocompanies that operate outside traditional rules and practices. One product thathas been particularly impacted by Shanzhai manufacturers is the mobile phone. 65
  • 65. According to the study of Li (2010), the first Shanzhai mobile phone appeared in2004. They were fake goods of famous brands such as Nokia or Samsung. Withvery cheap chips in bad quality, they were not accepted by consumers. Since 2006,the MTK mobile phone chip was developed by MediaTek (headquartered inTaiwan). Due to more integration of multimedia features and lower prices, theMTK chip was utilized by mobile phone companies and mobile phone designcompanies in a wide range. Lee et al. (2010) reported an impressive growth statusof Shanzhai phones. In 2008, more than 750 million cell phones were produced inChina. A significant portion (20 percent, or about 150 million units) of thesephones were produced by Shanzhai companies. These companies had rapidlytaken a significant share (about 10 percent) of the worldwide market. As thecomparison from International Data Corporation (IDC) about market share ofmain business players in the fourth quarter of 2008, Nokia is 39.1%, Samsung is18.3%, LG is 8.9%, Sony Ericsson is 8.4% and Motorola is 6.6%. Li (2010) stated Shanzhai mobile phones can attract many customers whofocused on the cost performance of products. There are many advantages toShanzhai products: no 17 percent added-value tax, no network license fee, nosales tax, and no 3–4 Euros checking fee to the government. Shanzhai runningcosts are further minimized by the absence of marketing and after-sales service.However, sales were not only high in the domestic mobile phone market; itsexport volume was considerable as well, including India, Brazil, Russia, and eventhe European market. Wu and Zhang (2009) indicated “Shanzhai” is actually not simply to be acopycat, which was thought as a bad manner in the competition with its threatoften ignored by mainstream companies. In fact, "Shanzhai mobile phone" canalso offer numerous innovative functions such as emergency light, telephoto lensand even counterfeit currency detector. "Shanzhai mobile phone " represents notonly product innovations, but also business model innovations. Lee et al. (2010)emphasised this phenomenal growth of “Shanzhai” was primarily due tononconventional approaches to the global market in market positioning, rapidproduct development, and tightly coupled, responsive and efficient supply chainmanagement. Known from the explanation of Wu and Zhang (2009), "Shanzhaimobile phone" companies needn’t to invest on R&D because of using chips fromTaiwanese company MTK as “turn-key” solution also with SDK (softwaredevelopment toolkit) and application software ready. Besides, there are thousandsof design houses in Shenzhen, the capital of "Shanzhai mobile phone" providingtotal solution of mobile phone design and thousands of dealers providing all kinds66
  • 66. of components like supermarkets. Such an open innovation way applied inmanufacturing industry is so well combined with the innovator’s strategy when itsdisruptive effect in market competition is often noticed too late by those leadingcompanies. As the view of Li (2010), in the low-end consumption market in China, theforeign products tend to be over-designed. Thus, a large number of domesticsupplier and demands emerge which results in a heated competition on prices.Shanzhai manufacturers start to produce recreation products through imitation,and then undergo the rapid change from imitation to innovation. The Shanzhaiindustrial development began with imitation, which can be traced back to theexamples in Korea (such as Samsung) and Japan (such as Toyota). They are all asleading companies nowadays in the industry - not anymore just based on offeringcheaper cost or lower-end product. As Quad-Band-Phones.com (‘QBP’) to beanother example (accessed in December 2010), it can offer some really cool nonbrand mobile phones that are for sale at ridiculously low prices, which is ownedby US citizen even the company is located in China. Obviously, “Shanzhai” hasbeen becoming more neutral with many complex effects as a business model fornew comers in the industries. Lee et al. (2010) argued it would be unfair and inaccurate to classify allShanzhai mobile phones as “pirated” or “illegal” products. Whether legal orillegal, whether they imitate or innovate, they have demonstrated amazingflexibility and tenacity. With the determination, a company can be successfullytransitioned from a Shanzhai culture to become a major mainstream force in theindustry. “Shanzhai” just indicates that it has been gradually organized andenlarged in an unauthorized fashion during company’s earlier life. The innovationcan be as one of the driving forces of Shanzhai manufacturer’s competitivestrategy. Understanding the product development process and supply chains usedby Shanzhai mobile phone makers may stimulate new ideas for design andmanufacturing by mainstream companies.The complexity of high-tech innovation studied by case Nokia Naturally, the review of mobile phone industry should be continued with caseNokia as the next step after a wider study was mostly concentrated on those withbusiness model impacts (such as Apple and Shanzhai). Although many of newchallenges have turned the competition as a red bloody ocean, how Nokia canremain its No. 1 leading position better than other competitions? As analysed by 67
  • 67. Chang and Horng (2010), Nokia operates successfully not only on high-endmarket but also on low-end mobile phones. For example, Nokia ranked numberone in China’s branding market in 2008. Its high-quality low-price businessstrategies include many creative changes actually as a new business model in thepast if comparing to other competitors:– Manufacturing strategy on integrating supply chain– Technology strategy on establishing R&D centres in China– Channelling strategy of consumers in small towns and villages– Pricing strategy in response to low-end market.The capability to bring radical changes in the innovation based on people spirit ofmotivation to win business growth is the key of Nokia success in the past or in thefuture, no matter facing which traditional competitors as Motorola or Samsunglack of such impacts. However, Nielsen and Hanseth (2010) compared Nokia withthe iPhone approach from a free and open innovation perspective. Apple has atthe same time shown as a fairly successful model in serving users and innovators.For example, buying an iPhone is also buying into a value network where newservices can easily be bought and installed from an application store (App Store).Even if the application store has been criticized for challenging some of the corevalues of the Internet since all applications have to be signed by Apple, this hasreally made a difference for the users, and other mobile phone manufacturers arefollowing (like Nokia’s Ovi). As reported by Halonen et al. (2010), Nokia hasn’tbeen as successful as Apple in building its application store. Nokia launched OviStore in May 2009, almost one year behind Apple. During the first three months,Ovi Store had only 10 million downloads; whereas Apple App Store had 100million downloads during the first two months only. The weakness of openinnovation comparing with Apple makes Nokia to introduce radical changes soslowly, which used to be Nokia strength but now as a sign of dangerous losses inhigh-end market. Similar as Nokia Siemens Networks in mobile infrastructure industrystruggling with Ericsson and Huawei, another threat to Nokia can come from low-end competition, in which the advantages of Shanzhai can be mostly utilised by amuch more powerful competitor. As an example reported by Foster (2010),Huawei Technologies shot past Alcatel-Lucent and Nokia Siemens in 2009 tobecome the worlds No. 2 telecom-equipment provider, powered by quality andproduct upgrades on top of its long-standing low prices. For leading companies(as Nokia or Ericsson), the winner at the end of battle in red ocean will be not68
  • 68. determined by lean or agile improvement efforts, but the No. 1 position in theindustry by the capability to create radical innovation and bring blue oceanopportunities. If the urgency is misplaced somewhere else, same wrong focus can affectNokia’s success in mobile phone industry again even Apple is just a new comer athigh-end market now. From the view of Braithwaite (2007), the iPhone has thecapacity to impact all players in the cell phone network: consumers, rival wirelesscarriers, Apple’s wireless partner, and rival handset manufacturers. Issues ofusability and enhanced ‘user’ experience are also likely to influence rivals’ phoneoperating systems software. From the perspective of the ‘user experience’, themulti-touch screen and enhanced functionality, the iPhone introduces a radicallyinnovative and simplified user interface. Due to the complexity of high-techbusiness, Nokia should be alerted and focused how to regain the competitiveadvantage beyond Apple and lead new radical innovation in the industry. Nokia isstill as the No. 1 leader for market share even now also in smart-phone field.Great opportunity to win the competition exists if Nokia will not repeat the pathof Nokia Siemens Networks and keep top priority to its right battlefield.Outcome of value differentiation studiesAll in all, the innovation for value differentiation should be emphasised not onlyas the element in lean or agile improvements, but also more importantly as itsown portion in the research. The difficulty of radical innovation must be notunderestimated in business with the risk ahead. Besides, same thought can be alsoapplied to optimise company’s manufacturing operation, as well as new productindustrialisation in change implementation research. It should not be forgottenabout great opportunities in leading companies how to synchronise with industrylifecycles – always aiming for value differentiation or unique advantage by theinnovation!2.5 Theory synthesisThere is a growing concern to emphasise global manufacturing in a strategy-driven way. The above review of existing theories indicates that there is a gaprequiring further research. For example, there have been a number of valuablestudies emphasising lean and agile in global manufacturing, separately as well astheir combination. However, business reality is much more complex similar as a 69
  • 69. dynamic world with three-dimensions, which can not be looked sufficiently as astatic picture of two-dimensions. Lean and agile strategies have not been studiedwell in an environment of global manufacturing where the third dimension isinnovativeness: interacting dramatically with each other influencing productchange. Such an environment can be shown as following Figure 4:Fig. 4. Thinking three dimensions for product change.Theory findings that act as a basis for this research:1. Strategy is not static but needs adapt swiftly In modern high tech business, the competitive situation is turbulent, resulting in pressures for changing manufacturing strategy even separately for different products or product groups. Previously it was thought the strategy can be generated and maintained for years, even the shortest update period could be as long as a half year.2. Lean and agile aspects are both needed in manufacturing strategy Traditionally, literature indicates that a company must make a choice between lean or agile. This can be misleading and result in an unbalanced situation in modern high tech business. On the contrary, lean and agile ingredients should be embedded. The literature uses the term leagility to describe the simultaneous combination of these two. Only in few extreme cases, extreme choice along lean-agile axis is sensible.3. Rapid product change as a driver for manufacturing strategy70
  • 70. Rapid product change is not an element of lean or agile, but an element of its own influencing the choice of strategy. It is not enough to work on the two dimensions of lean and agile, but rather to introduce a third dimension of rapid product change. Rapid product change can be seen as a part or an example of the innovation. Same principle can be applied to any of other similar innovative changes (such as new breakthrough technologies, disruptive business model, or even revolutionary “user interface” and enhanced “user experience” as iPhone).4. Demand-supply chain as a competitive factor Industrial competition in this current period of globalisation is becoming a battle between demand-supply networks, not just single companies. However, it is a great challenge to find ways to tackle operational bottlenecks, and to overcome organisational boundaries, both within the company and between its suppliers.5. Accept inaccurate forecasts As seen from Ericsson’s model, it is challenging to ensure the reliability of a company’s operational performance. A company has to make a choice in an environment with uncertainties on whether to accept inaccurate forecasts or seek for other ways to overcome this problem.6. Emphasise radical innovation always in new high-tech business reality With many high-tech companies analysed in the literature review, it shows the innovation should be emphasised as an independent strategy, not just as a component in the legality thinking. For leading companies or new comers aimed for the No. 1 position in industry, radical innovation needs to be as a must to achieve or keep winning in the competition. Although it increases the complexity to describe, business reality should be thought as a 3D world no matter how easier from lean or agile view only. 71
  • 71. 72
  • 72. 3 Results of the three action research cyclesSelected case company is a significant global actor in the mobile infrastructureindustry. The research environment can be described in line with product changeimplementation, which is mostly focused how to optimise manufacturingoperation and global demand-supply chain. There are many engineering changes during a product’s lifetime without aperiod when new and old versions overlap as execution principle. Componentchanges in products often happen at any time adding extra complexity formanufacturing besides original demand uncertainty. Product change managementscope includes planning & informing all the sites (own primary and substitutefactories, as well as its subcontract manufacturing partners), and cooperationbetween these sites, collecting results, analysing and making conclusions. Theresearch can be characterised to simultaneously include aspects of worldwidebusiness impact, rapid innovative pace, and high volume in operation. The case company combines push-based supply chain and pull-based demandchain together as a mix to synchronise production and delivery of all productparts with big lead-time gaps (mostly unavoidable from material supply). Pullprinciple is applied at internal steps of the production, as well as the delivery end.The product flow is in FIFO (First-In-First-Out) mode at each step ofmanufacturing, meant that not a same product is initiated, moved and delivered inthe operation to fulfil the demand at customer end. With it, short lead time can beachieved in production to balance the pace and the flow of manufacturingoperations. Push principle has to apply for the supply end and keep theinventories to absorb the impact of inaccurate forecast. Demand-supply networkhas to thus have enough tolerance to avoid undesirable conditions, such asproduction stop due to lack of key components. Observing in such 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). Obviously, the challenge is caused from component logistics in theelectronics industry, which is extremely complex due to a vast number of requiredcomponents with long production or delivery lead-times. For example, the lead-times may differ by days (such as VMI – Vendor Managed Inventory or two-binsystem), weeks (such as PWB and own specific integrated circuits), or evenmonths due to sea transportation (such as the cabinet). This creates bottlenecks orbig inventories in the supply network due to those time variances and real demand 73
  • 73. often not matching with earlier forecasts. When the gap of material supplyoccurred by the changes of product customisation or delivery requirements,demand-supply network balance would be easily destroyed in a fire-fightingmanner to take time for its recovery. It affects also the speed of productdevelopment in its change implementation phase. For example in case company,the product versions were different more than one year at some manufacturingsites before the research was launched. The case company had to find an alternative way to survive better in thecompetition as everyone in the industry suffered by those same challenges. Thebottom-line was to deliver products to customers’ requirements (especially havingthe changes of delivery amount or product configuration) at a high speed, withoutmeans to develop efficient forecasting processes to manage demand uncertainty.Whenever the volume of pull at delivery side was larger than the amount of pushat supply side, production had to be stopped due to missing components. Such ademand-supply network problematic area could not be simply solved by theoutsourcing of manufacturing operation or VMI (Vendor Managed Inventory) likesupply, which would just mean to move the headaches to other business partners.Faster transfer of demand information or a more reactive planning was also notenough to save manufacturing companies as a physical process is inflexible inresponding to frequent plan changes in normal operation. When product changesadded on this, demand-supply planning practices became even more fragmentedand frustrated. There were no existing solutions available, academic or industrial,at the time. As a competitive advantage of case company, both product development andmanufacturing functions are well combined. For example, it includes prototypefabrication and pilot capability (zero-series production), departments for productindustrialisation (where the research existed) and high volume production. Thepilot of zero-series production uses same BOM (Bill-Of-Material) as the lastprototype-run but now with a bigger volume similar as normal production lot size.If the result is failed, product development should be returned to prototype phaseto solve the problems found in the pilot and then back to zero-series production inthe future. If the result is successful, it is the approval for product developmententering new phase of change implementation. There are no other more-series ofthe pilot (or normal production) needed as the way of one single gate to approveproduct development before volume production phase. Volume production can bealso called flow production as manufacturing the products in a repetitive manner.74
  • 74. Research Cycle 1 included the case company aiming all of its actions tominimising costs, which was as a strategy of cost effectiveness. Minimisinginventory and scrapping costs required its effect into the whole demand-supplychain. In research Cycle 2 the case company aimed at diminishing order deliveryperiod. Research Cycle 3 concentrated on shortening product change period. Thecase company executed a strategy of innovativeness making product changes asfast as possible. During research cycles, every change case was recorded usingchange notes (CN). Change notes compare the old and the new product versions,indicating all changes in used components. CN also indicated the expectationwhen the changes will be conducted. Site specific implementation reports wereutilised to record changes, the implementation time and scrapping costs.Implementation report described all the results from different sites. Both,implementation reports and change notes were stored into a database. There wereover one hundred product change cases available within the company at the timeof research. The researcher selected three cases out of all product changes, one foreach cycle. The cases were important for business and there was a significantchange 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.3.1 Research Cycle 1 – minimising costsThe action research was initiated by problem-solving in a tough situation: Theforecast was so inaccurate. The lead time of material supply varied from a fewhours to several months. When demand is this dynamic, it is not possible to reactquickly, often delaying of the implementation of product changes or causing aproduction stop at some manufacturing sites. The old way of planning based onthe forecast cannot work well anymore when faced with such business uncertainty.Although the learning journey actually started in a fire-fighting way, a systematicapproach was planned. In the research, the focus was on the challenges of seeking a new solution forsurviving product changes. Even with the urgency of problem solving, it wasexpected to be a part of the long-term development (as the above pre-step) ofglobal manufacturing’s adaptation to a dynamic business environment. Withproduct change implementation and action research combined together, it can 75
  • 75. ensure the quality in a systematic way with all strategic and operational factorstaken into account.3.1.1 Pre-StepBefore the first cycle of action research was started, several cases of large productchanges were actually already done. The implementation of product change canbe seen as a black-box in context analysis. Its interactions with external factorswere very similar in all cases. It was already introduced in an earlier chapter when explaining why productchanges can be used for operational improvement – both with the same variantsaffecting inputs or outputs. There were many ideas from previous lessons forfurther development. Such a procedure was repeatedly utilised also in laterresearch cycles because it can act in a target-driven manner to make the outcomewith a better quality. Here was the review of research conditions in the company as a contextanalysis:– A worldwide economic hardship to most of the global companies at that time naturally with cost-effectiveness as the strategy.– Dynamic business environment with forecast accuracy extremely poor.– The product or material variation has been controlled and reduced continuously well by company-wide process of “Design for Excellence”.– Lead time of own production has been shortened to a good level (not as a main factor).– Inventory should be kept as small as possible to be an operational condition.– To avoid scraping cost in material supply as a big issue to product change management.– Earlier planning to reduce inventory for implementation of product changes not working good enough.– The production stop caused by actual demand and supply do not match each other due to inaccurate forecast and material lead time gaps.– It had to seek new solutions in the survival for product delivery and engineering changes.As expecting synchronisation for survival, it was aimed to accept inaccurateforecast / dynamic demand, introduce a timely manner in balancing supplyoperation, and even synchronise invisible liability. From a Change Notice76
  • 76. database of product change results, the implementation time and scraping costwere used as two measuring indicators comparable with all research cycles. Thethoughts from this round can be brought to the next cycle as its input, i.e., as thepre-step of that cycle. It can thus make the cycle-by-cycle progress a continuouslearning journey.3.1.2 DiagnosisThe diagnosis was done in a more practical sense to detail new improvementideas, which can be used further for action planning in the next step. Such a wayof analysis (at pre-step in general and at this step in practice) will be used forevery cycle of action research. It can thus ensure the quality of action research, aswell as product change implementation itself. The outcome of diagnosing in thisCycle 1 can be shown as follows:– Acceptance of inaccurate forecasts– Clock-speed to be weekly as the material in-flow for demand-supply network– Invisible liability in material supply – controllable or not?All of the above elements acted as the targets or baselines for planning the actionsin this cycle and to prepare for the next step.3.1.3 PlanningThe breakthrough was intended in action research Cycle 1 to achieve thefollowing two solutions of weekly clock-speed and dynamic cut-off window.Weekly Clock-speedWith PWB (Printed Wiring Board) purchasing as an example, a new attempt wasmade to change the material order for small and frequent deliveries (such as on aweekly basis) as the improvement in demand-supply operation. It will replace theway originally with a big order just according to the message from MRP systemby inventory level control. The idea was to consider the time added to the amountas both factors for forming a material supply flow. The actions were planned in a procedure shown as following Figure 5: 77
  • 77. Fig. 5. A series of actions planned for the trial of weekly purchasing.Even with the difficulties at the beginning, it was gradually becoming more andmore understandable by the buyers in practice. It was found that it was better toconsider not only the amount but also the time for all components in the supply. Itwas needed to repeatedly equalise the available amount of each componentaccording to the product’s BOM (Bill Of Material) at every moment in line withthe weekly updating of the forecast or demand. Such a dynamic balance with thepostponement of manufacturing can be the key of true synchronisation. No matterhow the forecast would be right or wrong, it actually just changed the usage timedue to dynamic demand. The adaptive focus was clearly moved to the deliveryand the usage – even the supply operation was still in a business uncertainsituation. Although material sourcing department had difficulties understanding theidea at first, the attempt was finally succeed in moving the focus tosynchronisation for demand-supply as a weekly pace!Dynamic Cut-off WindowThe material liability to the company was caused by its responsible forecast toother parties in the supply chain on a pre-agreed scale (such as weeks or months).It is the duty of the platform company to take the liability amount for its78
  • 78. consumption or pay for it as scraping cost. It can thus impact the implementationof product change or the scraping cost dramatically as an unbalanced componentamount. Normally, the material liability amount cannot be seen directly in MRPsystems of any company when approaching the version changeover date. It wasbecause the forecast can already be changed so greatly month by month. It shouldbe negotiated case by case between the companies at each tier of the demand-supply chain. The design of a creative solution for this challenge can be stated as a four-step process called dynamic cut-off window in Figure 6:Fig. 6. Action plan for a dynamic cut-off window.It was needed to set a product version change date in that MRP system that waslonger than the longest lead-time of any component in the current and new BOM.This date can be changed in a weekly management meeting. The idea was to keepa status just not to stop the ordering of old material but also not to start thepurchasing of new material during the trial period of a new product version. The moving of version changeover date was done weekly to ensure such atime-window (one week more than the longest lead-time of key component – thechange driver) just working at the “risky-edge” to cut off the forecast of currentversion material. The attempt was meant to avoid the liability and not harm thecurrent supply operation. If the product trial period might take one month, theforecast of that amount globally could be eliminated without harmful side-effects. 79
  • 79. It can thus reduce the maximum amount of material liability. Besides, it wasalways planned to keep a difference of implementation time (such as one month)between the platform site and the lean sites of the company. It can help thesituation further to consume the exceeding amount of the material by those leansites. However, there were the disadvantages of confusing the whole demand-supply network because of the trouble in moving the version change date weeklyin MRP. It was a type of manual planning – also a lack of effectivecommunication in advance. (Can it be improved in a process well-defined wayalso with better IT supports if possible?) The forecast proved its power bypenetrating everywhere in the enterprise eco-system in a forced manner.Obviously, as its benefit at the end, a good result was to cut all liabilities by thatone-month period before the change approval to a new product version.3.1.4 Taking actionThe actions were taken using the process shown in the following Figure 7.Fig. 7. Actions in action research Cycle 1.The figure describes the approval process how to promote product developmentphase ready for entering volume production, as well as some improvement80
  • 80. happened in that research cycle. The BOM (Bill-Of-Material) in the last prototyperun had to be tested by a bigger amount of volume manufacturing called “0 series”run. It was mainly to prove the last proto BOM suitable as a product changewithout a quality problem in volume production. The BOM of this version can beutilised as “Planning BOM” for some earlier activities in product changemanagement, such as comparing with current BOM to identify “Product ChangeDriver” (the component with the longest lead time or as the most expensive one). If the result of the “0 series” run was OK, it can mean product changeapproval ready for buying new material and stopping the purchase of old material– a version change to the product. If the result of the “0 series” run is not OK, itcould mean another prototype run for big modification change and another 0series after it (or to run it directly again for small modifications). Theimplementation time of product change and scraping cost (caused by extramaterial left in the company not possible for its consumption or transfer to othersites) were the targets to control a change properly implemented.3.1.5 EvaluationThe result of change implementation time with very low scrapping cost can beseen in the following Figure 8 for platform site (Site 1 as primary site of casecompany) and another main lean site (Site 2 as one of substitutive sites).Fig. 8. Implementation result of action research Cycle 1 from change notice database. 81
  • 81. The analysis and explanation of the implementation resultThe implementation result can be analysed also with some of more explanations.A platform site (site 1) and another main lean site (site 2) of global manufacturingare included in the figure of the implementation result. The target ofimplementation time for site 1 was determined because the lead time for PWB(Printed Wiring Board) was six weeks, so using seven weeks as a reasonableshortest time due to the spare amount of safety inventory at a very limited levelstill required at any time. It was planned to the change implementation betteralways with one month difference between both sites to reduce the risk. The targetof the second site for implementation of product change can thus be 11 weeks (theshortest possible and allowable time). It is also aiming to the implementation atthe first site as soon as possible with reasonable amount of exceeding materialtransferable to the second site to be consumed there. All sites are independent ofthe implementation (such as getting cost saving from product change due tocheaper material in new BOM) and scraping cost. Due to material transfer fromthe first site to the second site, the consumption at the second site can generallytake about 1–1.5 months depending on their capacity ratio. In this case, both sites had done the implementation with a “normal” speedbut without the liability amount of old material for further consumption. Product1 & 2 are main products with a larger volume normally also with commoncomponents that product 3 & 4. For old material consumption, it can take a longertime if only using product 3 & 4 in the manufacturing.New findings in this action research cycleMost of the new improvements had been achieved as expectation. They can beutilised repeatedly in other cases of product changes or next cycle of actionresearch.1. Effectiveness strategy as one extreme of the choices – The strategy of cost- effectiveness means material supply is synchronised at a balance point of minimum inventory. (This also affects implementation time, producing a shorter one but with less tolerance – production stop occurred a few times).2. Acceptance of inaccurate forecasts – It can be possible if the equalisation of old material was focused.82
  • 82. 3. Clock-speed to be weekly base – It helped the material supply in a dynamic situation with the focus on the factors of amount as well as time.4. Dynamic cut-off window showing IT importance – It was done via MRP system to the whole supply chain, but manual changes were weekly adjustments.5. Possible to control invisible liability of old material – The result demonstrated a large improvement with the dynamic cut-off window, but when done manually problems appeared.Practical contributionsThe contributions can be stated as follows so as to show practical business value:1. Keeping a big picture view of the strategy in order to ensure that activities at the operational level match the target of cost-effectiveness and that the benefits are spread to all in the supply chain.2. Moving the focus away from inaccurate forecasts to the equalisation of material supply in a timely way as the core of synchronisation in global manufacturing.3. Implementing the supply balance on a weekly basis with factors of amount as well as time clearly as a synchronisation trial.4. Doing dynamic cut-off window as an example of synchronisation – as manual changes in IT systems to achieve operational adjustment interactively with global manufacturing.5. Showing synchronisation in demand-supply operation is capable of controlling old material liability.Comparing to the targets of product change management, Table 3 summarises thefindings of the research Cycle 1:Table 3. Targets & findings of the Cycle 1.Strategic Targets in Product Change Management The Implications of New Findings from the ResultsExecuting corporate strategy: cost effectiveness. Acceptance of inaccurate forecastsTrial for operating from inventory level to clock- Effectiveness strategy as one extreme of the choicesspeed control Clock-speed to be weekly baseBalancing between fast implementation & lower Dynamic cut-off window showing IT importancescraping cost in whole demand-supply chain Possible for controlling invisible liability 83
  • 83. 3.2 Research Cycle 2 - shortening order delivery timeThe action research continued in another cycle using a new product change casein Figure 9. The economic hard time was almost over and ready for agile thinkingas a new improvement focus. It was the period with a different strategy so called“responsiveness” to the company and its demand-supply network. In this cycle,the effort was targeted to a new operational model of faster responsiveness inproduct delivery. It was a great opportunity to see how this strategy in an oppositeway to affect business operation. Besides, the argument of what as good or badhappened in this case provided a valuable lesson that served to enhance theunderstanding of synchronisation.Fig. 9. The action research for new operational model.With thinking for a new operational model, some small modifications were madealso to the action research process, though most of the steps were still similar. Itcould be a great opportunity during a better economic period to make moreradical changes.3.2.1 Pre-StepBecause the research framework was generally explained in earlier parts, theinformation in this cycle can be stated immediately with the topics. As a target-driven way, it was determined to verify existing knowledge such as ESP and84
  • 84. Three Dimensional Concurrent Engineering (3D CE) – Product, Process, andSupply Chain.The Review of Research Conditions in Context Analysis:– Worldwide economy was recovering with a different situation to the most of global companies possible for using a new strategy.– It was acceptable to deal with inaccurate forecast in business operation as a given condition.– Responsiveness as the strategy even to its extreme – keep the material inventory level according to maximum production capacity.– Weekly pace to demand-supply operation as a default.– Planning BOM with dynamic cut-off window done in a manual way was applied again at the beginning but cancelled later. It was mainly due to its trouble and the confusion it caused others in the co-operation.3.2.2 DiagnosisIt was noticed that the forecast function did not matter so much in the situation ifaiming to reserve spare capacity fully. It was a case after diagnosing and planningfor a trial of new strategy to its extreme – to keep inventory required bymaximum production capacity without the forecast needed in MRP system. The outcome of diagnosing in this Cycle 1 can be shown as follows: Key Points of New Improvement Thoughts – The extreme responsiveness as the strategy (jut according to maximum production capacity in operation without forecast) – Concurrent engineering with R&D by 2 phase approval for product change started earlier in demand-supply operationIt was a radical change to the forecast by a new thinking: without it at all in theoperation because it was wrong anyway the most of time. Synchronisationbetween both processes of product creation and demand fulfilment was anotherkey issue in the trial with two-phase approval for product change. If the firstapproval can pick an earlier status in product change process, it was expected tosee the benefit from applying 3D CE (Three Dimensional – Product, Process, and 85
  • 85. Supply Chain – Concurrent Engineering). Such extra time in the supply chain willmake product change implementation faster.3.2.3 PlanningPlanning work was done for the following two issues:New Trial for an Extreme of Responsiveness StrategyThe responsiveness as the strategy means the balance point of synchronisation formaterial supply was moved to a reasonably high level in the inventory. This wasbased on a new operational model consisting of the following principles:– Systematic Concept 1: Real-Demand-Pull for whole demand-supply chain– Systematic Concept 2: Immediate delivery without extra cost at each tier– Systematic Concept 3: “Financial Zero Inventory” by “Cash-To-Cash Time”– Systematic Concept 4: Profitable by the volume and speed from the innovation.During the trial, it should keep checking any of bad influences due to no forecastto both normal manufacturing operation and product change implementation. Theprocedure how the actions were planned is shown in following Figure 10.Fig. 10. Action plan for the extreme of responsiveness strategy.86
  • 86. The four principles of the new operational model were verified if they can workwithout the forecast. It depended just on demand pull at each tier of the supplychain with the inventory as the buffer to compensate lead-time gaps. In this way,it was targeted for a quick delivery everywhere in the operation of demand-supply.Concurrent Engineering by Two-Phase ApprovalThe principles of two-phase approval in Figure 11 are simple. Aiming for earlierimplementation with controllable risks, it needs the planning of new and oldmaterial supply to be quantified to a detailed level. If product version changehappened before the second approval, it can cause the confusion and disaster inglobal manufacturing operation.Fig. 11. Action plan for two-phase approval.As a process modification to try 3D CE, the attempt at two-phase approval shouldbe communicated to all relevant personnel in product creation and demandfulfilment. The time comparison and the amount of material supply should be allbased on the detail of quantified information. 87
  • 87. If affecting as an operation to multiple sites, the risk management should alsobe in place. Of course, its implementation can be adjusted or stopped whenever tofind any issue out of the control. After the result is made available by the trial, itshould be analysed to see if it can be a solution for long-term usage or not.3.2.4 Taking actionThe actions were taken with the process shown in the following Figure 12:Fig. 12. Actions in action research Cycle 2.The process was similar as the research Cycle 1 but with some of newimprovement ideas as a trial. The BOM (Bill-of-Material) in the last prototype-run was not used for the dynamic cut-off window in the 0 series period to avoid orreduce old material liability problem as in Cycle 1, because it was cancelledshortly at the beginning stage due to it being so hard to operate manually. Besides, the concurrent engineering principle was used between R&D andproduct change management with two approvals to product change. The first88
  • 88. approval can be just after the testing was done without problem so as to allowbuying new material and stopping old material purchasing immediately. Thesecond approval can be after all R&D work was done to approve product changefinally. The important thing was to be sure the period between the first and thesecond approval should be shorter than the implementation time of the first site.3.2.5 EvaluationThe result of change implementation time with very low scraping cost can be seenin the following Figure 13 for the platform site (Site 1) and another main site (Site2):Fig. 13. Implementation result of action research Cycle 2 from change notice database.The implementation result provided many meaningful implications for furtheranalysis. It was the first time to have the results shorter than the target time at thefirst site. It was due to two approvals by saving about one month time from theconcurrent engineering with R&D. The lesson was also learned from the material liability problem caused by thecancellation of the dynamic cut-off window. It was found a big amount of liabilityafter the implementation was done. It had to request that the second site return tothe old version in order to consume the old material so that the implementationtime shown in the figure on the right was 34–35 weeks at the second site. 89
  • 89. Without the information from the forecast, it was a lack of a future estimation.Such a situation made it very hard to plan for the next product change comingafter this case.New findings in this action research cycleIn action research Cycle 2, the attempt was actually focused on synchronisation toensure the maximum production capacity as a balance point. Due to the forecastbeing mostly wrong, an attempt was made to live without it as an extension ofCycle 1. With the opportunity of the responsiveness strategy with a larger tolerance,there were also other lessons learned in the analysis to understand the secrets ofglobal manufacturing. As a summary, here are new findings in action research Cycle 2:1. Possible to live without forecast – Just keeping inventory according to maximum production capacity if business strategy can be the extreme of responsiveness strategy.2. Another balance point for synchronisation – However, it can be selected not necessary always at the extreme (OK also with other possibilities).3. Concurrent engineering as synchronisation extended to R&D – possible again applying to other fields in business operation?4. Invisible material liability as an X-ray picture of supply operation – It seems no other options better than a dynamic cut-off window. – It will be much better if information can be visible as a direction for improvements. – Is it possible to use IT solutions to obtain benefits for synchronisation deep into demand-supply chain but without causing too much trouble in the operation?5. The forecast actually as a balance point - With similar principles, the forecast can act as a reference to be a balance point for synchronisation around it dynamically. – The extreme of a strategy can be one of the statuses among a whole operational range. – How to “place” global manufacturing by corporate strategy for other options in the middle?90
  • 90. Practical contributionsAll of those new findings were the elements to enhance synchronisation. Thecontributions can be stated as follows so as to show practical business value:1. It was a valuable experience to implement an extreme version of synchronisation (operating even without the forecast). The range of adjusting synchronisation can be thus pushed to the boundary approaching its limits.2. It was a case of understanding the lean or agile thinking to notice its extremes in synchronisation.3. With synchronisation extended to R&D, the total operational range was further thought as a better way.4. Although invisible material liability was a lesson to learn in this case, it can show that synchronisation made huge differences in the results for product change management, and also provided meaningful insights to global manufacturing in general.5. It was the case of facing uncertain future to understand the importance of the forecast - as a reference point in dynamic status.Comparing to the targets of product change management, Table 4 summarises thefindings of the research Cycle 2:Table 4. Targets and new findings in action research Cycle 2.Strategic Targets in Product Change Management The Implications of New Findings from the ResultsExecuting corporate strategy: responsiveness. Possible to live without forecast as an extremeTrial of four systematic concepts but actually to the Another balance point for synchronisation at theextreme of responsiveness opposite extremeTrial of concurrent engineering Concurrent engineering as synchronisation extended to R&D Invisible liability as an X-ray picture of supply operation The forecast actually as a balance reference point in dynamic business3.3 Research Cycle 3 - shortening product change timeIn this strategy choice of action research Cycle 3 a technology leader with a newproduct or a significant change of an existing product quickly goes to market to 91
  • 91. capitalise on a booming business. It was the focus moved to making productchange as fast as possible even to accept a much bigger scraping cost. Obviously, it was not same as the strategy of cost-effectiveness in Cycle 1 orresponsiveness in Cycle 2. The Cycle 3 in Figure 14 was a case in product changemanagement including a big innovation. In this strategy, a revolutionary solutionwas expected.Fig. 14. The action research for faster innovativeness.All three extreme strategy choices were for different business reasons. In order toavoid the confusion, other formats of similar statement about those strategies arelisted in following Figure 15.Fig. 15. A new choice of business strategy.92
  • 92. Not as easily understandable as other two options, innovativeness can help atechnology leader to achieve technical advance, and then to use that advance as aweapon in tough competition. It was not the same as effectiveness orresponsiveness, which can be for lean or agile manufacturers without the need formore explanations. It was a strategy used in action research Cycle 3 to doeverything (even to accept much larger operational risk and scraping costs) just sothat product change was made quickly. For this case only, the target was to makethe innovation speed of new product to the market as fast as possible. Choosing the extreme strategies can be a natural way when starting to seekmore alternatives. This research cycle became very exciting because it presentedthe opportunity to try something different from the two previous cycles.3.3.1 Pre-StepBy using innovativeness as the strategy, it should keep old material as little aspossible to get rid of the previous version quickly as a lean effect. But, it alsorequires new material as much as possible to enter market faster with the newversion as an agile purpose. The review of research conditions in context analysis:– It was essential to achieve a fast product innovation with shorter time to the market. In a certain situation, it was also extremely vital in global competition for the company to do all possible efforts for it.– Profitable innovation is an important competence for the company.– Innovativeness as a strategy: a bigger scraping cost was acceptable for a faster speed of product changes.– The inventory of ready products in the outbound warehouse (HUB) was a new condition to the demand-supply network with the possibility to watch product version change at the HUB (but not version modification for small changes).– The forecast was used again in the MRP system, even though it could be still wrong.– Planning BOM of the last prototype run was applied again during the 0 series period for material preparation but not as a dynamic cut-off window (actually as a fixed cut-off window with material version changeover date selected earlier but without any modification). 93
  • 93. – It was using the safety inventory of ready product in HUB to avoid the risk of the 0 series run failing.– The implementation result can be evaluated in a new way to consider the product version change at both production and HUB inventory.It was a valuable opportunity to study a new extreme strategy – theinnovativeness as another alternative outside the box of lean or agilemanufacturing!3.3.2 DiagnosisA new process was needed to develop what was achieved in the previous cyclesfor an even faster implementation of product change. The complexity of thedynamic cut-off window and the two approvals can be improved with moredisruptive intentions. A simpler way was tried during the 0 series period just bystarting implementation activities directly. With its bigger risk covered by readyproduct inventory, it can go beyond the limits of normal operational process forradical changes never done in the past. The outcome of diagnosing can be shownas follows:– “Actual” implementation of product change started before 0 series.– Fixed cut-off window better than dynamic cut-off window?It was an opportunity to go beyond normal limitations in manufacturing operationfor more creative improvements. The strategy of innovativeness was thus as thethird factor to affect the balance of synchronisation efforts.3.3.3 PlanningThe safety inventory of products and the bigger scraping cost were accepted.Radical changes can be made to the product change process. Of course, theevaluation after the trial or implementation should also be made carefully. Eachstep of the action plan was aligned using the following procedure in Figure 16:94
  • 94. Fig. 16. Action plan for faster innovativeness.Even if the 0 series fails, product delivery to the customers can still be ensured bya HUB inventory of ready products. The worst situation can be the scraping costfrom unusable new material and production stop due to lack of old material.However, it can be recovered with only limited damage in a short period of thetrial.3.3.4 Taking actionThe actions were taken following the process shown in the Figure 17 below:Fig. 17. Actions in action research Cycle 3. 95
  • 95. The radical change in business process was planned and verified in the researchCycle 3 with the intention seeking a breakthrough effect in product innovation.The BOM (Bill-of-Material) in the last prototype run was used as a planningBOM to buy new material and stop old material purchasing even before the 0series. The version change date was input into MRP without moving as a fixedcut-off window. Due to the unknown result of the 0 series (to approve productchange or not), ready product inventory at the HUB was used as safety inventory.Product in HUB inventory should be consumed by itself without any chance oftransferring it to other sites. If the 0 series run fails, another prototype or/and 0 series run will be needed,which, according to the modification, can be large or small. New material can bescraped if it is not used in the next new BOM. However, product delivery will notbe delayed due to safety inventory in HUB, but production can be stopped due tono material of old version. It was thus beyond the limits at the material supply side involving the risksalmost at a not acceptable level.3.3.5 EvaluationThe result of implementation time can be seen in the following Figure 18 forplatform site (Site 1) and another main lean site (Site 2):Fig. 18. Implementation result of action research Cycle 3 from change notice database.96
  • 96. The analysis of implementation result indicated the challenge of productinnovation due to its complexity in global manufacturing environment. The resultwas different from the perspective of production or HUB at the first site. From aproduction perspective, it was a very quick change done just after the approval –never working at such a fast speed in any previous cases. But from the view ofHUB, product inventory was still consumed with a long period and showedalmost no difference to past cases. The business benefit of cost saving from thisproduct change can be achieved only after product version change done at HUB,but not just in production. Besides, the version change was selected as a fixeddate, so the unbalanced material caused a higher scraping cost in this case (eventhough it was expected). Actually later in the practice, it was forbidden to usesuch an extreme way again without waiting for the 0 series result. But, this lessonhad provided an unusual experience on how to move beyond the limits of productchange management. The opportunity of innovation oriented manufacturing in arevolutionary way was remained for further research.New findings in this action research cycleIn this case of innovativeness strategy, the product change was happening quicklyin material inventory and production. The balance to equalise material supply forthe changeover moment was not achieved. It was an impressive scraping cost toshow such an unbalanced status of demand-supply: How big could the amounts ofrelated components be if synchronisation was not done properly. Besides, thesituation in product inventory reflected synchronisation equally important to all indemand-supply chain. It can imply the value of synchronisation better if it is donenot just for a certain moment or a special part of enterprise ecosystem. As a summary, here are the new findings of action research Cycle 3:1. The strategy of innovativeness emphasised as an independent option - It is not same as the innovation in lean or agile strategy to be its ingredient.2. Actual implementation of product change not so faster – As seen from this example, it can be very important how to evaluate the improvements properly to get an accurate picture.3. An unbalanced status in the supply without synchronisation – But, it can also be a great opportunity if synchronisation can be properly done. 97
  • 97. 4. Demand-supply chain always considered as a whole – As in many other examples, the whole demand-supply chain should be re-engineered not just for a company or a department.Practical contributionsAll of those new findings were valuable lessons for synchronisation. Thecontributions can be stated as follows so as to show practical business value:1. This cycle was a case to introduce the third factor into operational synchronisation for business complexity shown in an innovative way. Although the innovation would increase the uncertainties in strategic planning, this third factor can describe the real challenges in global manufacturing often truly driven by such a strategy.2. The lesson learned from the evaluation of the final result can indicate that the expectation of improvements should be ensured by a right way to do synchronisation in a big picture of the total range – not just a part of it.3. This cycle was also as a case to show an unbalanced status in the material supply if synchronisation was not done properly. It was obviously better if synchronisation can be done not just during a changing period but also during a normal time of healthy global manufacturing.4. It was increasingly noticed that as the range of synchronisation gets bigger and bigger, it approaches a total range, which was one of the reasons that finally led to synchronisation. It was learning by doing to find a new way in line with those action research cycles for a breakthrough.Comparing to the targets of product change management, Table 5 summarises thefindings of the research Cycle 3:Table 5. Targets and new findings in action research Cycle 3.Strategic Targets in Product Change Management The Implications of New Findings from the ResultsExecuting corporate strategy: innovativeness The strategy of innovativeness with possibility to be(product change as fast as possible). an extremeDisruptive changes in the process Actual implementation of product change not fasterTrial how to use ready-product inventory in product An unbalanced status in the supply if there is nochange management synchronisation Demand-supply chain always considered as a whole98
  • 98. 4 Discussion4.1 Answering research questions4.1.1 Research question 1Research Cycle 1 included the case company aiming all of its actions tominimising costs (Figure 19). The case company executed a strategy of costeffectiveness. Minimising inventory and scrapping costs required swiftcomponent control in the whole demand-supply chain. This chapter answersresearch question one by describing the results obtained through research Cycle 1,including both the positive and negative impacts of this trial.Fig. 19. Focus of research Cycle 1.As a starting point for this cycle, forecasts were not accurate and scrapping costswere a challenge. Lean aims to minimise costs. This research identified that it isbeneficial to accept that forecasts are not always accurate and find ways tonavigate in this type of reality. Before, in the case company, components had set minimum inventory levels.New order was placed once going below this minimum. Order sizes were setbased on pre-calculated batch sizes. The company moved from this type ofsolution to a weekly assessment. Inventory levels and forecasts were followed ona weekly basis, and were further used for necessary orders. This resulted in 99
  • 99. smaller batch sizes, more swift reaction on changes in demand and productvariations, and less scrapping. In the case company, the old way was that new product version’s introductionto production was considered only after obtaining approval of zero-series. Inorder to speed up new product versions entering production, and improvetransparency towards suppliers, ramp-up is now considered already during thezero-series. Changes in a product result in changes in the BOM. The company firstanalyses the critical components of the new BOM version. Component is criticalif it is expensive, or it has a long lead time from order to delivery. In order tominimise scrapping in product change situations, it is necessary to identify thecomponents with the longest lead times. This decides the earliest possible pointwhen one can move to a new product version. One week’s margin is utilised todecide the product version change moment. The zero-series of the new version isfollowed, and ramp-up is postponed weekly until zero-series approval. Assuppliers are now informed already in the beginning of zero-series, the supplierswill have time to react accordingly. This in turn reduces the liability and possibleliability related costs. The case company uses the term of dynamic cut-off windowfor the new way. Negative aspects: People complained that dynamic cut-off window causesconfusion as it changes every week. Manual way of changing target dates for newproduct versions was seen non-suitable  new ways desired and IT tool would bepossibly of benefit.4.1.2 Research question 2In research Cycle 2 the case company aimed at diminishing order delivery period(Figure 20). In this trial, the case company aimed at strong concurrency inengineering to get order delivery period as short as possible. This chapter answersresearch question two by describing the results obtained through research Cycle 2,including both the positive and negative impacts of this trial.100
  • 100. Fig. 20. Focus of research Cycle 2.Quick delivery (agility) strategy was utilised and the case company consideredwhether it would be possible in some situation to live without forecasts andaccept high inventory. Higher component inventory enabled greater tolerance. The old way of doing things included new product versions going throughzero-series, production and testing, and if the results were ok, documentation andapproval process followed. Documentation and approval took about 3–4 weeks.Only once R&D approved new production version, the company started buyingnew material and stopped buying old material. Downside of the old way was thatthis waiting time of 3–4 weeks can be considered as waste from the perspective ofproduct change management. The new way, tried during this research cycle, aimed to speed up the processby involving R&D to give earlier signal to product changes, so that the supply-chain management people could start their work earlier. After Zero-seriesproduction testing proved acceptable, buying new material was started and buyingold material finished. Documentation and approval process was conducted inparallel by R&D. Negative aspects: Using dynamic cut-off window was abandoned in this case.As a consequence the liability of the case company increased as the company hadcommitted to buy components for the need of a certain period. This experimentcaused delays at other sites, even if the situation was ok at the main site. This typeof situation might cause other sites having to switch back to producing an oldproduct version. 101
  • 101. Without forecasts in the system, visibility over coming changes was lost.Now it was understood that a forecast would act as a reference point forequalising supply. This situation would also influence other companies, aside thecase company.4.1.3 Research question 3Research Cycle 3 concentrated on shortening product change period (Figure 21).The case company executed a strategy of innovativeness making product changesas fast as possible. The trial clarified whether a ready-product inventory could beused to speed up product change. This chapter answers research question three bydescribing the results obtained through research Cycle 3, including both thepositive and negative impacts of this trial.Fig. 21. Focus of research Cycle 3.Normally scrapping costs are minimised. In the research Cycle 3, scrapping costswere accepted, while everything was arranged to make product changes as quickas possible. This approach significantly differs from lean and agile. Unit-level ready products were used as inventory. This way the companycould stop buying old material earlier and avoid problems in delivering tocustomers. Before starting zero-series, product new version changeover date wasselected and fixed. This fixed cut-off window enabled suppliers to deliver theexisting order plus liability. No further orders were placed for the old material,102
  • 102. and at a certain point during zero-series, order for new material was placed. Thisleft the company with the possibility of zero-series failing, resulting in a secondzero-series and stopping production due to old material running out. This experiment enabled the case company to understand the demand-supplychain better from a wider perspective, thus providing beneficial learning. Negative aspects: This experiment had more negative impacts than positiveones, and consequently this approach was banned after the experiment. From thebusiness perspective, there was no improvement in the sense of cost savings. In this case, at the point when purchasing of old components was stopped, thelevel of different components was not equal, resulting in expensive scrappingcosts. The difference in the levels of different components is caused by differentbuyers buying in the components they are responsible for in different pace andtheir activities not being coordinated. 4.2 Managerial implicationsThe results of this study provide tips for global high tech companies. These largeinternational companies typically have manufacturing sites in different parts ofthe world. Based on the results, mental shift from local optimisation to a globalone is required for efficient manufacturing operations. Companies have traditionally considered their strategy as a choice betweenminimising costs, quick delivery, and rapid product change. Also, companies havebelieved that one single strategy is adequate and applicable to all of their products.However, according to this study, different products may have a different strategy.This allows companies to flexibly react to the needs of different customer groups,business environments, and different competitors. Strategy can also be changedrelatively often, monthly, weekly, or even daily. Companies must consider all the three elements of minimising costs, quickdelivery, and rapid product change and to find an adequate balance among thesein order to succeed (Figure 22). The arrows in the figure represent flexibility inchanging strategy. There can be different strategy for different products andcompetitive situations. In addition, companies have multiple partners andconsequently a suitable balance is required for the entire demand-supply chain.Forecasts are an important, powerful tool for influencing the supply operations, asforecasts give information for suppliers. A company should try to make relevantinformation, including product change management, visible for both the companyitself, and the entire supply chain. This would make it easier for the 103
  • 103. subcontractors to optimise the entire chain if it has adequate access to criticalinformation. Two-way communication is required to fully optimise the entiredemand-supply chain.Fig. 22. Flexible optimisation on situation basis.Once optimising the entire supply-chain, in modern business environment, time isa vital competitive factor and companies must be swift in their moves. Thisresults in optimisation on time basis becoming a key. This type of time-basedoptimisation means synchronisation of R&D, production, material handling, andrelated planning. Special attention should be paid to bigger events, such as newproduct launches, and significant engineering changes, as they have a wideinfluence. Based on the results of this study, companies must harmonise their productportfolio globally, including all their sites. Once the same product version is at allsites, they can help each other from components supply viewpoint, andconsequently product changes can be taken through quicker. Companies must also equalise material status for supply, and follow it weekly.This is as different components of a same product must be seen as dependent oneach other, not separately, meaning that if you cannot buy component A, there isno point buying components B, and C either. In a situation with too manycomponents, the component you have least determines the equalised level. Ifthere are any components more than the equalised level, those can be consideredas waste. The difference between the equalised level and the original forecastedlevel can be considered as tolerance margin increasing agility. However, if thecompany prefers lean over agility, this type of tolerance should be avoided.104
  • 104. Above described new kind of thinking require developing IT tools to supportglobal visibility and operations. These IT solutions would enable changingstrategy often, even on product basis, resulting in business model agility. The fast industrialisations of R&D achievements constantly into a full scaleof own global manufacturing is a stronger competitive advantage in case company,comparing to others in the industry with the production mostly in an outsourcedway. The big difference of the speed can bring the success or the failure as theinnovation in the industry. If such an advantage is not fully utilised or even gonein the future, the lost of leading position could happen as one of the reasonscoming from this battle field. 4.3 Scientific implicationsThe systematic review of the literature identified a number of important researchgaps as the opportunities to make scientific contributions. It was lack of academicstudies as either or both outside-in and inside-out manners to develop newthoughts along with product innovation in lean or agile manufacturing. Theinnovation itself was emphasised later even as an independent strategy to affectmanufacturing operation beyond the lean or agile thinking box. No matter howharder to show 3-dimensional world, business complexity should be consideredand handled in a fresh thinking of right way similar as the Figure 23 (not enoughwith a 2D view to different 3D realities):Fig. 23. Business complexity as 3-dimensional world out of lean or agile thinking box.Those are the knowledge gaps indentified as an approach to describe businessoptimisation studied by the research with sufficient scientific purposes: 105
  • 105. – Is one strategy only to avoid “stuck in the middle” still valid or just suitable in some conditions?– What can be a new thinking beyond traditional lean or agile manufacturing theories?– How to ensure a balance at strategy level to reduce the risk of business failures?– What should be the key of optimisation in high-tech manufacturing?– What could be an alternative way with more details to the forecast research?– How the radical innovation is emphasised and used as a must in high-tech industry?Traditionally, it was thought a company can have only one strategy and thatstrategy is valid for a long period of time. Porter (1980 & 1998) emphasised thatto be successful over the long-term, a firm must select only one of the threegeneric strategies. Otherwise, with more than one single generic strategy the firmwill be "stuck in the middle" and will not achieve a competitive advantage. Heargued that firms that are able to succeed at multiple strategies often do so bycreating separate business units for each strategy. Similar idea (Treacy et al. 1993)also indicated that a company should have a clear position among the followingchoices to avoid the stuck-in-the-middle situation due to a lack of focus:– Operational Excellence– Customer Intimacy– Product Leadership.This study indicates the contrary: a company must excel with flexibleoptimisation choosing from multiple strategies on situation basis. A companyshould not be stuck in the middle, or only good at one of these strategic choices.For example, lean and agile ingredients should be simultaneously embedded. Thisaims to break the boundaries even further, because some literature uses the termleagility to describe the simultaneous combination of these two (Mason-Jones etal. 2000). In most literature, the rapid product change viewpoint is not as common aslean or agile studies (Gunasekaran, 1999). This thesis demonstrates that it is notenough to work on the two dimensions of lean and agile, but rather introduces athird dimension of the innovation – rapid product change. Consequently, themanufacturing strategy should be seen as a multidimensional playground, wherethe optimum can be different in different situations.106
  • 106. With above thoughts, this provides newness into scientific thinking. Inmodern high tech business, the competitive situation is turbulent, resulting inpressures for changing manufacturing strategy more often and even to haveseparate strategies for different products or product groups. A single strategy for acompany or a business unit is not functioning well anymore. An unbalanced statusfrom one of the three elements at the strategy level can cause a disaster forcorporate business. For example, Toyota has been proud as the lean & TQC (TotalQuality Control) benchmarks in the industries, as well as its Prius Hybrid modelsleading the innovation in the car industry. However, its business growth withoutproven design quality to ensure a proper supply & delivery expansion (similar tothis study also as a bigger scale actor in another industry) brings Toyota intotremendous troubles. It has made loss during the two last years, after 70 years ofoutstanding financial results. Toyota is still struggling to recover from its recalldisaster and regain a reputation that has made it the biggest car company in theworld. This dissertation is thus highlighting that the optimisation of enterprisestrategy within multidimensional playground should be conducted on time basis.This view is in line with the fact that time has become an increasingly importantfactor in high tech business (Christopher 1998). Flexible optimisation in a timelyway is thought as a total synchronisation concept, which has been researchedfurther in recent years as next big outcome. This dissertation confirms the findings of Einhorn (1986) from decisionresearch about accepting error to make less error. In dynamic business nowadays,one has to accept inaccurate forecasts due to unpredictable business environment.After it, the opportunities will be identified to ensure the company (or its unit) notstuck in the middle or any “end” point of multi-strategy scope. Such scientificimplications can guide the research leading to more solutions. Finally, the radical innovation should be used as a must in high-tech industryto measure and lead business performance in “Red Ocean” of the competition,which is not emphasised enough in the most of manufacturing theories. It can notbe outside of the research even its focus as the optimisation for manufacturingoperation or demand-supply network. 4.4 Reliability and validityIn order to evaluate the results, it is needed to check the validation of the researchquality. The definition of validation can be found from many academic resources 107
  • 107. for different fields. Robert K. Yin (1994) also presents four complementary waysto judge the quality of empirical case study research: (1) reliability, (2) constructvalidity, (3) internal validity, and (4) external validity. It should be applied here toguide the discussion. In general, reliability is the ability of a system to perform and maintain itsfunctions in routine circumstances, as well as hostile or unexpected circumstances.Reliability is necessary for validity and it is easier to achieve although it does notguarantee validity. Stated another way, reliability can be associated with randomerror and validity with systematic error. In general, validation is the process of checking if something satisfies acertain criterion. Validation implies one is able to testify that a solution or processis correct or compliant with set standards or rules. With the confirmation byexamination and provision of objective evidence, it should conform to user needsand intended uses. The particular requirements implemented through the processcan be consistently fulfilled. Validity can be extended to internal validity as internal design of the studyand external validity as external generalisation made from results. Internalvalidity is a form of experimental validity if it properly demonstrates a causalrelation between two variables. External validity is also a form of experimentalvalidity if the experiment’s results hold across different experimental settings,procedures and participants. The meaning of the above figure can be understood easily without the needfor further explanations. There is a format to review the dimensions of research quality to check thereliability and validity as following Table 6:108
  • 108. Table 6. Dimensions of research quality in the evaluation (format from Collin, 2003).Quality Case study tactic (Robert K. Appearance in this studydimension Yin, 1994)Reliability -Develop case study protocol -For all product change cases, the implementation targets of -Develop case study version changeover time and scraping cost are applied in the database same way. -A database of CN (Change Notice) and IN (Implementation Notice) is well constructed.Construct -Use multiple sources of -Many sources of knowledge or information were checked inValidity evidence theoretical and industrial trend review. -Establish chain of evidence -The research is a continuous development based on the -Have key informants review existing body of knowledge. draft case study reportInternal -Do pattern matching -The flexible optimisation or synchronisation is a pattern-likeValidity -Do explanation building way suitable to many solutions. -Do time series analysis -The systematic principles were built as the abstraction from action research cycles and product change cases (even some were not selected as the cases for research cycles). -Time series analysis was in line with action research cycles.External -Use replication logic in -Replication logic was used in multiple cases of productValidity multiple case studies changes. -Use case study protocol -Generalisation in action research approach is very limited even with many other product cases ongoing at the same time.But, the business situation has been becoming more and more dynamic in globalmanufacturing, which should be as a factor in the consideration (such as Toyotawith profit loss also in 2008 after 70 years of positive results). Here are the keypoints to discuss validation and reliability in further details for this research withthe above concerns:– The research scope was defined at the beginning for a narrow range within suitable industries. It was related to those large corporations who engage in high-tech manufacturing on a global scale. They should have a demand- supply network already as part of their strategy-driven operation with minimum product variation. It is now still valid with all the limitations verified earlier because some companies can be far away to such a maturity if they do not yet meet these pre-requisites. As a concern of validation, they are as essential conditions for repeatable results of product change management or operational improvement towards total synchronisation. 109
  • 109. – Due to the importance of IT support increasing dramatically, it can be another factor in the consideration of validation and reliability. For a global operation, such a competence should be good enough in order to avoid the trouble of synchronising in a manual way. A comparable level of IT competence should be needed along with business re-engineering in the company. Besides, it can also be interesting for business application suppliers or consultant companies as a great opportunity for business concept innovation and technology development direction.– For a company in the competition, a different strategy should be used as a situational choice on a case-by-case basis. A business benchmark sample cannot be copied exactly to other companies, even though it was successful under certain conditions. Even for those benchmark companies, they can not keep a same result to themselves.– This research proposes a new approach to dealing with the traditional problem of inaccurate forecasts in today’s more dynamic nature environment. Attention should be paid to more than the improvement of forecast accuracy alone if it is not working so well in business practices.Guessing the possible direction of the plane and its speed difference to the rocketor the missile is a challenge. It can hit the target only if they “meet” in theshooting. It can be quite sure that at least there would be no big chance of hittingthe plane if one just targets its current position, a situation that is similar to justmaking a copy in a dynamic business. Therefore, the degree of validation and reliability should be dependent on theabstracting level of the solutions. As a result-oriented way, the copy cannot bringgreat success in business because there can be no exactly same situation alwayskept to any companies or even the enterprise benchmark itself. To deal withbusiness uncertainties, there is a need for abstracting the solutions, such ashappens with time-based optimisation by multiple strategies. When applying it tothe manufacturing operation, it should be as a pattern, with those principles beingthe baseline only. The nature of autonomic features should be considered inbusiness for the success. 4.5 Research contribution & discussionNew contributions of the research can be summarised as a base of further work inthe future. It includes not only the insight to some arguments of management110
  • 110. theory, but also own discovery from this research. Each point is detailed with theexplanations to provide an overall view of research results as Table 7:Table 7. Summarising new contributions from the research.New Contributions of Own Insight & Discovery The Explanations from Research ResultsAccept inaccurate forecast for the focus moving An empirical research truly aiming for alternativeto seek alternative solutions solutions how to survive by synchronising demand- supply pace & flow even with “extra” product changes A practical reference to support the arguments in this fieldIntroduce and prove three ingredients in A study sticking on the complexity of real business andmanufacturing strategy (especially with the its key challenge.innovation emphasised) An independent “driver” separated from the leagility for the innovation in manufacturing operation as a strategy – deserving its research much more than what happened in the past.Research the reasons and the solutions for A deep understanding to tangible or intangible statusproduct innovation challenges caused by supply of demand-supply details as the 1st report trying tolead-time gaps and material liability reduce liability effect in product changes Also as the 1st report about empirical research details of using product changes to study manufacturing improvementsIdentify a good opportunity to develop new theory A simple idea leading to new thoughts of a theory:of total synchronisation and IT solution (business How the principles to achieve no-scraping cost statusintelligence automation) as its utilisation in global in product change (equal to ideal synchronisation) arescale for leading companies repeatable and applicable to normal time of global manufacturing?For those leading companies in global business, the innovation should beemphasised as a must at strategy level. The research brings it into whole thinkingof manufacturing operation, which can be seen just a corner for the company orits demand-supply network. The innovation can affect much wider range ofcorporate performance. It explains why lean or agile strategy always has itsdrawbacks. Besides, product change is only one of the forms for the innovation when itwill have radical effects of the differentiation (such as advanced technology, costsaving in big scale …). As a companywide view, any of similar efforts to bringradical differentiation for the company to achieve new competitive advantage isthe definition so called “innovation”. It is the key of surviving in global 111
  • 111. competition especially essential to be leading companies. Otherwise, lack of thisingredient in company’s strategies is a clear sign to the failure or already as a pathto the end of industrial life cycle. The innovation is the big thing to determine the winner in global competitionsooner or later, which is proved by many facts as the life cycle of industry. It isthe time to deal with the complexity of three-dimensional world in real businessand explore a new academic theory for it (such as the effort leading to “totalsynchronisation” oriented by the innovation in this research). 4.6 Future researchThis study presents new understanding on time-based optimisation of minimisingcosts, quick delivery, and rapid product change. Further research is howeverrequired to fully utilise the presented ideas, especially for what with theinnovation as a driving force. For further abstraction, a so called “totalsynchronisation” concept is under development as next big outcome of theresearch. In order to better manage in global business, new IT solutions areneeded to support this new thinking, requiring future study. The lack of studiesabout business intelligence automation can be a new opportunity of research field.In addition, the potential of web 2.0 for harnessing the creativity of people tosupport the type of optimisation discussed in this thesis would be a good topic forfuture study. The simulation about mobile phone industry by Reiner et al. (2009)can be an interesting sample if applicable in mobile infrastructure manufacturingalso as research tool even though big differences do exist. This thesis has been conducted in a single company and one businessenvironment, having more cases and expanding to new business areas would bean interesting topic for future study. Besides, the tendency of overusing the strategy of minimising costs duringeconomic hard times, often results in losses to those leading companies. Globalbusiness is constantly under a turbulent change that has become normality, but is,however, too often ignored. “Wonderful” periods between two economicdowntimes have become shorter and shorter. Too often companies use excusesthat now we have to tighten our belts, accept slower operational speed, lessproduct innovations and lower employee motivation as the times are harder.Instead the companies should accept the reality. People expect that they can applythe other strategies again when a good time is coming. As a result, their leadingposition in the industry gets literally lost. The leader status is not simply112
  • 112. maintained by making structural changes in the business sector e.g. with bigacquisitions. The target of total synchronisation concept is to break such thinkingand study right manner - always with multi-strategies in mind. It will help leadingcompanies or new-coming challengers in the industry to win in globalcompetition. This is why these aspects should be studied further. 113
  • 113. 114
  • 114. 5 SummaryThe main motive for this research arises from the fact that ICT has developed intoa turbulent, high clock-speed sector. Industrial globalisation has greatly changedhigh-tech companies while they have created significant operations in multiplecountries. Because poor visibility and massive uncertainty are part of theoperational nature, new challenges arise continuously for companies who want tointernationalise their demand-supply network. ICT companies face challenges in an unpredictable business environment,where demand-supply forecasting is not accurate enough. How to optimallymanage product change process and demand-supply chain in this type ofenvironment? Companies face pressures to simultaneously be efficient,responsive and innovative, i.e. to minimise costs, and shorten order delivery andproduct change periods. The effects of changes in essential parameters of inventory level, orderdelivery period, and product change time were studied in this dissertation for areal demand-supply chain of a significant international actor. Secondly, based onthese analyses, this study attempted to find new means of dealing with complexissues in the unpredictable business environment. This thesis included three action research cycles. Each action research cyclesought answers by going into one extreme of minimising costs, diminishing orderdelivery period, or shortening product change periods. In practice, these researchcycles included the case company changing their business accordingly for each ofthese cases. Conducting required changes in the case company were economicallysignificant trials. The results of this doctoral dissertation provide tips for global high techcompanies. Large international companies typically have manufacturing sites indifferent parts of the world. According to the results, mental shift from localoptimisation to a global one is required for efficient manufacturing operations. Companies have traditionally considered their strategy as a choice betweenminimising costs, quick delivery, and rapid product change. Also, companies havebelieved that one single strategy is adequate and applicable to all of their products.However, according to this thesis, different products may have a different strategy.This would allow companies to flexibly react to the needs of different customergroups, business environments, and different competitors. In addition, strategycan be changed relatively often, monthly, weekly, or even daily. 115
  • 115. Companies typically have multiple partners and consequently a suitablebalance is required for the entire demand-supply chain. Forecasts are an important,powerful tool for influencing the supply operations, as forecasts give informationfor suppliers. A company should try to make relevant information, includingproduct change management, visible for both the company itself, and the entiresupply chain. This would make it easier for the subcontractors to optimise theentire chain if it has adequate access to critical information. Two-waycommunication is required to fully optimise the entire demand-supply chain. Based on the results of this doctoral thesis, companies must harmonise theirproduct portfolio globally, including all their sites. Once the same product versionis at all sites, they can help each other from components supply viewpoint.Consequently, product changes can be taken through quicker. Global productportfolio harmonisation can be seen as a new normal situation for the high techbusiness. This would enable further optimisation, covering all global operations.116
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  • 133. 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)