Chapter9TheFrameworkofInformationProcessing Network for Supply ChainInnovation in Big Data EraChian-Hsueng ChaoAbstract The challenges of the global marketplace and the growing complexityofbusiness philosophies and technologies mix, the enterprises are forced to utilizeknowledge, capabilities, and resources to be found within and outside theirinformation processing networks. The enterprises are demanding more than justaccess to data, they want processed and refined big data and information to helpthem to reach more responsive and effective tactical decisions. Under this para-digm shift, data and information-oriented productivity depends on the sharing ofknowledge and skills among workers, so that enterprise strategies can be driven bythe collectiveintelligence and competenceofthe groupto face business challengesand enable organizational learning and innovations. In the cloud computing andbig data era, management of enterprise knowledge to create business values andcompetitive advantages is especially important for supply chain practices. Thispaper focuses on the development of enterprise information processing networkand application framework that bind organizational strategies, business processes,data, information,technologies, and peopletogethertobetter utilizeknowledge inbusiness practices.The ultimate goal is thetransformation of an enterprise networkinto a knowledge network for supply chain organic innovations!Keywords Information processing network·Knowledge management.Supplychain management·Big data analyticsC.-H. Chao ()Department of Information Management, National University of Kaohsiung, 700Kaohsiung University Rd, Nanzih District, 81l, Kaohsiung, Taiwan, R. O. Ce-mail: cchao@nuk.edu.tw77L.Uden et al. (eds.), The 3rd International Workshop on Intelligent DataAnalysis and Management, Springer Proceedings in Complexity,DOI:10.1007/978-94-007-7293-9_9, Springer Science+Business Media Dordrecht 2013
Chapter 9 The Framework of Information Processing Network for Supply Chain Innovation in Big Data Era Chian-Hsueng Chao Abstract The challenges of the global marketplace and the growing complexity of business philosophies and technologies mix, the enterprises are forced to utilize knowledge, capabilities, and resources to be found within and outside their information processing networks. The enterprises are demanding more than just access to data, they want processed and refined big data and information to help them to reach more responsive and effective tactical decisions. Under this paradigm shift, data and information-oriented productivity depends on the sharing of knowledge and skills among workers, so that enterprise strategies can be driven by the collective intelligence and competence of the group to face business challenges and enable organizational learning and innovations. In the cloud computing and big data era, management of enterprise knowledge to create business values and competitive advantages is especially important for supply chain practices. This paper focuses on the development of enterprise information processing network and application framework that bind organizational strategies, business processes, data, information, technologies, and people together to better utilize knowledge in business practices. The ultimate goal is the transformation of an enterprise network into a knowledge network for supply chain organic innovations! Keywords Information processing network Knowledge management Supply chain management Big data analytics C.-H. Chao (&) Department of Information Management, National University of Kaohsiung, 700, Kaohsiung University Rd, Nanzih District, 811, Kaohsiung, Taiwan, R. O. C e-mail: cchao@nuk.edu.tw L. Uden et al. (eds.), The 3rd International Workshop on Intelligent Data Analysis and Management, Springer Proceedings in Complexity, DOI: 10.1007/978-94-007-7293-9_9, Springer Science+Business Media Dordrecht 2013 77
78C.-H. Chao9.1IntroductionToday, the Supply Chain Management (SCM) is a boundary-spanning,channel-unifying, dynamic, and coevolving philosophy of inter-enterprise man-agement. The major contribution of today's supply chain model is to improve andenhancing collaboration between businesses and their trading partners [1]. Intoday's business practices, competing for supply chain requires the alignment ofcorporate strategies to what the organization knows, or developing knowledgemanagement (KM) capabilities to support a desired supply chain solution.Man-agement of organizational knowledge for creating business values and generatingcompetitive advantages is critical for organizational survival. A good knowledgemanagement should support people to access and learn from past and presentorganizational business practices/strategies and to apply the lessons learned whenmaking future decisions.Therefore,a successful knowledge-oriented business fororganizations should link supply chain management, relationship management,and knowledge management to function in an adaptive way to cope with everychanging business challenges.9.2TheBigDataImpactsBig data,as the nextfrontier for innovation, competition, and productivity [2] willhavetremendous impact on ourdaily life.Inbigdata era,theflowof data can beamong different devices and in different types. The data can be any type with anyforms, such as business data, social network messages, blog, forum, web page,multimedia, SMS, email, sensor data (e.g.NFC, GPS, RFID, M2M), and so forth.Because the data came froma variety of sources,thebig data is considered to beatthe scale of up to Zettabyte.Therefore, timely and cost-effective analytics overbig data is now a key ingredient for success in many businesses, scientific andengineering disciplines, and government endeavors [3]. The characteristics of bigdata analytics are variety, speed, and with big volume, and therefore the manip-ulation of data relies on intelligent approaches to deal with growing structured,semi-structured or unstructured big data. Currently, the cloud computing andparallel computing do much of the work in big data analytics.For the past few decades, enterprises have constantly reinvented themselvesthrough a series of business and technological innovations to fit into the globalspectrum of business.The increasing adaptivity and responsiveness of businesspractices has led to the role of big data analytics in business practices. Big dataanalytics relies heavily on the interpretation of data into useful knowledge forenterprise or supply chain to make more responsive and effective tactical decisions.Information, such as demographics, consumers'behaviors,and numerous otherbusiness statistics,and the associated processing power arecritical for the survivalof enterprises in business.With the global deployment of computers,mobiledevices,and interconnecting networks,participants canwork collaboratively,share
9.1 Introduction Today, the Supply Chain Management (SCM) is a boundary-spanning, channel-unifying, dynamic, and coevolving philosophy of inter-enterprise management. The major contribution of today’s supply chain model is to improve and enhancing collaboration between businesses and their trading partners [1]. In today’s business practices, competing for supply chain requires the alignment of corporate strategies to what the organization knows, or developing knowledge management (KM) capabilities to support a desired supply chain solution. Management of organizational knowledge for creating business values and generating competitive advantages is critical for organizational survival. A good knowledge management should support people to access and learn from past and present organizational business practices/strategies and to apply the lessons learned when making future decisions. Therefore, a successful knowledge-oriented business for organizations should link supply chain management, relationship management, and knowledge management to function in an adaptive way to cope with every changing business challenges. 9.2 The Big Data Impacts Big data, as the next frontier for innovation, competition, and productivity [2] will have tremendous impact on our daily life. In big data era, the flow of data can be among different devices and in different types. The data can be any type with any forms, such as business data, social network messages, blog, forum, web page, multimedia, SMS, email, sensor data (e.g. NFC, GPS, RFID, M2M), and so forth. Because the data came from a variety of sources, the big data is considered to be at the scale of up to Zettabyte. Therefore, timely and cost-effective analytics over big data is now a key ingredient for success in many businesses, scientific and engineering disciplines, and government endeavors [3]. The characteristics of big data analytics are variety, speed, and with big volume, and therefore the manipulation of data relies on intelligent approaches to deal with growing structured, semi-structured or unstructured big data. Currently, the cloud computing and parallel computing do much of the work in big data analytics. For the past few decades, enterprises have constantly reinvented themselves through a series of business and technological innovations to fit into the global spectrum of business. The increasing adaptivity and responsiveness of business practices has led to the role of big data analytics in business practices. Big data analytics relies heavily on the interpretation of data into useful knowledge for enterprise or supply chain to make more responsive and effective tactical decisions. Information, such as demographics, consumers’ behaviors, and numerous other business statistics, and the associated processing power are critical for the survival of enterprises in business. With the global deployment of computers, mobile devices, and interconnecting networks, participants can work collaboratively, share 78 C.-H. Chao
799TheFrameworkofInformationProcessingNetworknetworkedresources,exchangeknowledge,andimprovecorporateorsupplychainperformance.Corporate and supply chain strategies canbe driven by the collectiveintelligence of groups to better meettoday's business challenges.9.3 The Value of Data and Information in Supply ChainMentioning about the values,Porter's value chain[4] concept is well adopted byorganizationstoprofiletheircompetitiveness andbusinessvalues.Thevaluechaindivides the organization into a set of generic functional areas, which can be furtherdividedinto a series ofvalueactivities.An enterprisewill beprofitableaslongasitcreatesmorevaluethanthecostof performing itsvalueactivities[5].Tomodela business system,the effortfor theseparation ofa complexpartfrom the whole inwhich we are interested is called an Abstraction. This is a very practical meth-odology for the modelling of a complex system,especially in the supply chainmodelling effort.Through abstractions, any complex business object in a systemcan be denoted as a black box that produces certain outputs regardless of itsinternal complexity.Andlater,whennecessary,thisabstractobjectcanbefurtheranalyzed and broken down into several sub-objects. Therefore we can modelsupply chain business process integration based on value chain as shown inFig.9.1.In Fig. 9.1, recall that Porter's value chain described an enterprise as a set ofgeneric functional areas (such as inbound logistics, operations, marketing,out-bound logistics, etc.).Porter also recognized linkages outside the enterprise, asnfHuman Resource ManTechnological DevelopmProSale&ServicDmthound Logis(Executive)LogistiMfiddleManaoeInformatioUpDownStreamStreamABPABPoILS&SOLFig. 9.1 Global network of value chain in abstract business process (after Gale and Eldred,1996modified)
networked resources, exchange knowledge, and improve corporate or supply chain performance. Corporate and supply chain strategies can be driven by the collective intelligence of groups to better meet today’s business challenges. 9.3 The Value of Data and Information in Supply Chain Mentioning about the values, Porter’s value chain [4] concept is well adopted by organizations to profile their competitiveness and business values. The value chain divides the organization into a set of generic functional areas, which can be further divided into a series of value activities. An enterprise will be profitable as long as it creates more value than the cost of performing its value activities [5]. To model a business system, the effort for the separation of a complex part from the whole in which we are interested is called an Abstraction. This is a very practical methodology for the modelling of a complex system, especially in the supply chain modelling effort. Through abstractions, any complex business object in a system can be denoted as a black box that produces certain outputs regardless of its internal complexity. And later, when necessary, this abstract object can be further analyzed and broken down into several sub-objects. Therefore we can model supply chain business process integration based on value chain as shown in Fig. 9.1. In Fig. 9.1, recall that Porter’s value chain described an enterprise as a set of generic functional areas (such as inbound logistics, operations, marketing, outbound logistics, etc.). Porter also recognized linkages outside the enterprise, as Up Stream ABP Down Stream ABP Information Information IL O S & S OL Firm Infrastructure Marketing Outbound Logistics Inbound Logistics Sale & Service Operations Human Resource Management Technological Development Procurement (Executive) (Base Management) (Middle Management) Information Fig. 9.1 Global network of value chain in abstract business process (after Gale and Eldred, 1996–modified) 9 The Framework of Information Processing Network 79
80C.-H. Chaothey relate to the customer's perception of value. Therefore, it is also an openstructure, and the network can be developed in a fractal pattern just like theextended value chains.To this point, a Porter value chain is an abstraction of abusiness process, because an enterprise is a business process entity in a globalinformation-processing network.Therefore there is a different from the originalmodel proposed by Gale and Eldred [6], which focused on the process view ofabstraction instead of the global supply chain value management scheme.Again, the term “abstraction" is used here to describe the generalization of anybusiness process for the modelling purpose. Through this characterization, abusiness process can be generalized into what we call the Abstract BusinessProcess (ABP).The Abstract Business Process is just like a business process whichcan be decomposed into several sub-processes, which is, an ABP is made up oflower level ABPs.This interconnected value chain system can act as a supplychain or information processing network that encompasses the modern businessworld, and participating organizations can readily extend their technologies andknowledge to their partners. The extended enterprise aspect enables supply chainintegration and more effective outsourcing solutions for both internal and externalstakeholders [7]On the other hand, the rapid growth of the Internet brought about new businessphilosophies and fostered the growth of new strategic alliance,data, information,and business process integration across the borders ofenterprises.The informationprocessing view of an organization has been considered one of the most influentialcontributions to the contingency literature [8]. In this philosophy, informationprocessing network provides the channels for exchange and processing of infor-mation in a global system.The primary role of the information processing networkis to provide information exchange among its subsystem-the informationprocessingnodesasshowninFig.9.2In Fig. 9.2, the information processing network view of "virtual enterprise" canbe from different divisions, departments, or organizations.The information-pro-cessing nodes within the network areresponsiblefor sending,receiving,selecting,producing, and communicating (i.e. exchange data and information)with otherinformation processing nodes. An organization's value chain consists of allactivities performed to design, produce, market, deliver, and support its productand service. For the analysis of business data communication, the informationprocessing network connects its nodes, which in turn, are organized into businesscomponents.Thebusiness components of the organization include people,pro-cesses, events, machines,and information that interact and combineto produce theoutputs (e.g.information,product, service)of the organization.Recalled that a knowledge-enabled organization is a learning organization, onewhere all employees are using theirknowledge, skills, and learning to meet today'sbusiness challenges and to create new opportunities for the future. Therefore, thevalue is created whenever information flows through the information processnodes and the information processingnetwork.Inbusiness practices,collaborativeproblem solving,conversations, and teamwork generate a significant proportion of
they relate to the customer’s perception of value. Therefore, it is also an open structure, and the network can be developed in a fractal pattern just like the extended value chains. To this point, a Porter value chain is an abstraction of a business process, because an enterprise is a business process entity in a global information-processing network. Therefore there is a different from the original model proposed by Gale and Eldred [6], which focused on the process view of abstraction instead of the global supply chain value management scheme. Again, the term ‘‘abstraction’’ is used here to describe the generalization of any business process for the modelling purpose. Through this characterization, a business process can be generalized into what we call the Abstract Business Process (ABP). The Abstract Business Process is just like a business process which can be decomposed into several sub-processes, which is, an ABP is made up of lower level ABPs. This interconnected value chain system can act as a supply chain or information processing network that encompasses the modern business world, and participating organizations can readily extend their technologies and knowledge to their partners. The extended enterprise aspect enables supply chain integration and more effective outsourcing solutions for both internal and external stakeholders [7]. On the other hand, the rapid growth of the Internet brought about new business philosophies and fostered the growth of new strategic alliance, data, information, and business process integration across the borders of enterprises. The information processing view of an organization has been considered one of the most influential contributions to the contingency literature [8]. In this philosophy, information processing network provides the channels for exchange and processing of information in a global system. The primary role of the information processing network is to provide information exchange among its subsystem—the information processing nodes as shown in Fig. 9.2. In Fig. 9.2, the information processing network view of ‘‘virtual enterprise’’ can be from different divisions, departments, or organizations. The information-processing nodes within the network are responsible for sending, receiving, selecting, producing, and communicating (i.e. exchange data and information) with other information processing nodes. An organization’s value chain consists of all activities performed to design, produce, market, deliver, and support its product and service. For the analysis of business data communication, the information processing network connects its nodes, which in turn, are organized into business components. The business components of the organization include people, processes, events, machines, and information that interact and combine to produce the outputs (e.g. information, product, service) of the organization. Recalled that a knowledge-enabled organization is a learning organization, one where all employees are using their knowledge, skills, and learning to meet today’s business challenges and to create new opportunities for the future. Therefore, the value is created whenever information flows through the information process nodes and the information processing network. In business practices, collaborative problem solving, conversations, and teamwork generate a significant proportion of 80 C.-H. Chao
819TheFrameworkof InformationProcessingNetworkInformationProcessingNodesInformationProcessingNodesReceiveSendProcessProcessChannelOperationOperationNetworkProcessProcessReceiveSendProcessProcess+1StateStateVirtualProcessIntegration(Inter-enterpriseProcessing)EnterpriseCEnterpriseAEnterpriseBCustomer ServiceProductionLogisticsProcessingProcessingProcessingFig.9.2Theinformationprocessingnodesforvalue creationtheknowledge assets that exist within a firm or entire supply chain.With networkconnectivity,the virtual enterprise can work collaboratively to share knowledgeand best practices that enable supply chain“"co-evolving."The beauty of a supply chain knowledge network is that the true value of theinformation surpasses the conventional boundaries that often restrict employeesthinking [9]. The information-processing nodes within each network in eitherorganization can work collaboratively to achieve strategic goals in the newlyjoined network.Therefore, values include all information that flows through anorganization and between an organization and its suppliers,its distributors,and itsexisting or potential customers.Indeed, data and information defines businessrelationships
the knowledge assets that exist within a firm or entire supply chain. With network connectivity, the virtual enterprise can work collaboratively to share knowledge and best practices that enable supply chain ‘‘co-evolving.’’ The beauty of a supply chain knowledge network is that the true value of the information surpasses the conventional boundaries that often restrict employees’ thinking [9]. The information-processing nodes within each network in either organization can work collaboratively to achieve strategic goals in the newly joined network. Therefore, values include all information that flows through an organization and between an organization and its suppliers, its distributors, and its existing or potential customers. Indeed, data and information defines business relationships. Enterprise A Enterprise B Enterprise C Operation Process Send Process Receive Process State Information Processing Nodes Send Process Receive Process Operation Process State Information Processing Nodes Channel Network Production Processing Logistics Processing Customer Service Processing Virtual Process Integration (Inter-enterprise Processing) Fig. 9.2 The information processing nodes for value creation 9 The Framework of Information Processing Network 81