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Knowledge Management in OSS—an Enterprise Information System for the Telecommunications Industry
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- Systems Research and Behavioral Science Syst. Res. 23,177^190 (2006) Published online inWiley InterScience (www.interscience.wiley.com) DOI:10.1002/sres.752 & Research Paper Knowledge Management in OSS—an Enterprise Information System for the Telecommunications Industry Jiayin Qi1*, Li Da Xu2, Huaying Shu1 and Huaizu Li3 1 School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, China 2 Department of Information Technology and Decision Sciences, Old Dominion University, Norfolk, Virginia, USA 3 School of Management, Xian Jiaotong University, Xian, China Knowledge management in Enterprise Information Systems (EIS) has become one of the hottest research topics in the last few years. Operations Support Systems (OSS) is one kind of EIS, which is becoming increasingly popular in the telecommunications industry. However, the academic research on knowledge management in OSS is sparse. In this paper, a knowledge management system for OSS is proposed in the framework of systems theory. Knowledge, knowledge management, organization and information technology are the four main interactive elements in the knowledge management system. The paper proposes that each subsystem of the OSS is to be equipped with knowledge management capacity, and the knowledge management of the OSS is to be realized through its subsystems. Copyright # 2006 John Wiley & Sons, Ltd. Keywords enterprise information systems; ERP; operations support systems; knowledge management; management information systems INTRODUCTION mance and competitive advantage (Ahn and Chang, 2004; Chuang, 2004; Joshi and Sharma, In recent years, the topic of knowledge economy 2004; Tzokas and Saren, 2004; Badii and Sharif, has attracted much research interest. As a result, 2003; Cavusgil et al., 2003; Choi and Lee, 2002). a substantial number of researches have been For this reason, more and more enterprises have conducted on knowledge management from emphasized the importance of knowledge man- both theoretical and empirical perspectives. agement. Most of them have acquired enterprise Studies show that effective knowledge manage- information systems (EIS) such as ERP as an ment has a positive effect on enterprise perfor- integrated platform with intended applications in knowledge management. Operations Support Systems (OSS) is a main- * Correspondence to: Jiayin Qi, School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, stream technology which supports large-scale China. E-mail: ssqjy@263.net network operation, maintenance and management. Copyright # 2006 John Wiley & Sons, Ltd.
- RESEARCH PAPER Syst. Res. It was put forward by TeleManagement Forum about OSS at www.tmforum.org, but they are not (TMF), an international organization that has typical research papers. been contributing to the information and com- Knowledge may not show its significant value munications services industry for over 15 years. until it is embedded in software products or So far OSS has been increasingly adopted by business processes. Only then can its value be telecom industry with NGOSS (New Generation fully utilized. OSS is the basic software platform Operations and Software Systems) as its next to support value chain management for the generation product. If ERP systems are the EIS telecom industry. OSS should be the enabling mainly help manufacturing industry achieve tools to fulfil effective knowledge management. competitive edge in the global market, OSS plays How could this objective be achieved? The a similar role in the telecom industry. purpose of this paper is to explore a possible Telecommunications industry is a very specific answer to the question. high-tech service industry. The main feature of The paper is organized as follows. ‘Knowledge the telecommunications industry is its tight Management in Systems Perspectives’ section integration of business process and IT applica- presents the implication of knowledge manage- tions; it is very important to use IT to promote its ment in systems perspectives. The relationship competitiveness. OSS is generally considered as among data, information and knowledge, as well a basic EIS which can also support knowledge as the relationship between knowledge manage- management. OSS market and applications are ment and EIS is discussed. In ‘Overview of OSS growing. Taking the Asia Pacific market as an and Knowledge Management in OSS’ sections, example, it generated $8.8 billion of revenues in an overview of OSS and the knowledge manage- 2002. Revenues show an increasing trend and ment in OSS is discussed. ‘Discussion and the market for OSS is expected to grow at a Conclusion’ section provides a summary of the steady pace. The compound annual growth rate paper and future research. (CAGR) of the revenues for the period 2001–2007 is forecasted to be 6.27 per cent. Industry reven- ues are forecasted to rise to $11.87 billion by the KNOWLEDGE MANAGEMENT IN year 2007. SYSTEMS PERSPECTIVES Although OSS has been acquired by many telecom companies, the shortage of scholastic A system is made up of a set of interacting research on OSS is obvious (Li et al., 2003a). elements sharing a particular purpose within a IEEE Xplore provides full text access to IEEE boundary. The interaction among elements forms transactions, journals, magazines and conference the structure of a system. Depending on its proceedings since 1998, plus select contents back boundary, a system can be an economic entity, to 1950, and all the current IEEE standards. Most an inventory system, or a business organization. of the academic publications in telecommuni- Knowledge management is an element of the cations are included in IEEE Xplore. Using organizational management system (Warfield, operations support systems as key word, our 1989). From the point of view of the concept of search matched 189 of 1043417 documents. In whole, a knowledge management system pro- these 189 documents, there is only one paper motes the effective use of knowledge assets of an related to the word knowledge. Searching other enterprise as a whole over time, and is an impetus academic journals, such as Decision Support to the performance of the enterprise. systems, Expert Systems with Application, Knowl- edge-Based Systems, Computers in Industry, Expert Systems, Data & Knowledge Engineering, Advanced Data, Information and Knowledge Engineering Informatics, Logistic Information Man- agement, Information & Management, Telecommu- Prior to discussing knowledge management, the nications Policy from 2003 to 2005, no papers on terms such as data, information and knowledge OSS are found. There are some whitepapers must be defined. The following is a summary of Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) 178 Jiayin Qi et al.
- Syst. Res. RESEARCH PAPER Data Processing: Organizing, storing, Data calculating, Retrieving, Reporting Information Information Processing: Reforming, Quantification, Qualification, Clustering, To be communicated learning, Disseminating to others in the form Knowledge of text, computer output, speech and writing words etc. Figure 1. Data, information and knowledge the distinction between data, information and allow for the creation of well-defined transfer- knowledge: able information (Li and Xu, 2001; Li et al., Data are known facts that can be recorded and 2003b). Knowledge discovery (KD) process that have implicit meaning (Elmasri and agglomerates information found by such techni- Navathe, 2004). Information is data placed in a ques as DM in generating domain knowledge meaningful and useful context after that has been (Bendoly, 2003). processed (O’Brien, 2005). Information is user- aimed, providing values and existing in the eyes of the beholder (Spiegler, 2003). Knowledge is Implication of Knowledge Management information synthesized and contextualized to in Systems Perspective provide further value for human activities (Pearlson and Saunders, 2004). The implication of knowledge management has The relationship among data, information and been studied by many authors (Warfield, 1989). knowledge can be depicted as shown in Figure 1. Table 1 summarized the selected findings. Data is the abstract description of objects and is In this paper, knowledge management is the raw material that is used to generate useful studied in terms of systems theory and the information and knowledge. Information is a perspectives listed in Table 1 will be synthe- flow of processed data after being processed. sized. It is emphasized in this paper that Knowledge involves the capacity of gathering knowledge management can be used to effec- and using information. Knowledge becomes tively manage corporate knowledge assets information when it is articulated or commu- especially those knowledge in business pro- nicated to others in the form of text, computer cesses. Therefore, the objective of knowledge outputs, speech or written words (Alavi and management is considered to promote an Leindner, 2001; Spiegler, 2003). enterprise’s core competency. Such an objective Data warehouse is a large-scale storage facility can be achieved with a systematic process of for data. Knowledge warehousing is an exten- creating, maintaining, employing, sharing and sion of data warehousing to facilitate the captur- renewing knowledge. ing and coding of knowledge and to enhance the retrieval and sharing of knowledge across the Knowledge Management Framework organization (Nemati et al., 2002). Online Analy- in Systems Point of View tical Processing (OLAP) is a software application used to explore the data in ways that are decision Viewing knowledge management as a man- oriented (Shi et al., 2005). Data mining (DM) tools made system, the boundary of the system and Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) Knowledge Management in OSS 179
- RESEARCH PAPER Syst. Res. Table 1. Existing research on the implication of knowledge management Author Perspective Implication Siemieniuch and Sinclair (2004) Process Systematic process of applying expertise Kwan and Balasubramanian (2003) Wang and Ariguzo (2004) Mesaric (2004) Fowler and Pryke (2003) Capability Building core competencies through know-how Badii and Sharif (2003) Tzokas and Saren (2004) Nemati et al. (2002) Relationship Converting information to knowledge the elements of the system needs to be deter- 2000). Human knowledge refers to the knowl- mined. Obviously, the boundary of the knowl- edge acquired by a person that can increase edge management system is the corporate productivity and the contribution to the organi- business environment, while the elements in zation. It also includes other individual qualities the system include knowledge architecture, such as experience, judgement and intelligence. knowledge management process architecture, A firm’s organizational knowledge includes organization architecture and IT architecture its norms and business guidelines, corporate cul- (Kim et al., 2003). The other questions of interest ture, organizational procedures, as well as strate- include the interaction among these elements, gic alliance. Technological knowledge includes the structure of the system, and the function of knowledge related to the access, use and innova- the system. tion of production techniques and technology (Xu et al., 2005a,b). The relational knowledge Main Factors Influence Knowledge Management consists of the potential derived from the Knowledge management system is a system to intangible resources related to marketplace, effectively manage knowledge within an enter- such as brands, customer loyalty, long-term prise. Two main factors are considered influencing customer relationship, distribution channels, etc the needs of practicing knowledge management. (Kanjanasanpetch and Igel, 2003). The first factor is competition. If there is a tough The knowledge management process architec- competition in a certain industry sector, managing ture defines a variety of processes involved in the knowledge is generally in high demand. The other life cycle of knowledge, from its creation to factor is the volume of data. If there is a huge termination. Knowledge creation process, know- volume of data that exist within an enterprise, the ledge maintenance process, knowledge distribu- data resource is available which can help convert tion process and knowledge review and revision data into information as well as knowledge. process are the four steps in the entire knowledge management process (Bhatt et al., 2005). Creativ- Elements of Knowledge Management System ity refers to the ability to originate novel Knowledge architecture, knowledge manage- and useful ideas and solution (Marakas, 2003). ment process architecture, organization architec- An organization creates knowledge through ture and IT architecture are the four elements of its employees who are equipped with knowledge knowledge management system. and generate new ideas by breaking down The so-called knowledge architecture is the business thinking that is no longer viable result of classifying organizational knowledge by (Argyris and Schon, 1996; Lynn et al., 1996). one or more dimensions. Fernandez et al. distin- Knowledge maintenance refers to making use of guished knowledge into human knowledge, existing ‘discovered’ knowledge (Bhatt et al., organizational knowledge, technological knowl- 2005). Knowledge distribution means the sharing edge and relational knowledge (Fernandez et al., of knowledge across the organization. Knowledge Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) 180 Jiayin Qi et al.
- Syst. Res. RESEARCH PAPER review and revision is the modification and Both theoretical and empirical researches version management of knowledge. have shown that knowledge management can The organization architecture designs organi- play a key role in creating sustainable competi- zational structure. Organizational structure defi- tive advantages for corporations. In which, the nes the role of each knowledge management team organization architecture is the guarantee of that is responsible for performing or supporting knowledge architecture, knowledge manage- knowledge management process. ment process architecture and IT architecture. The IT architecture is a technical infrastructure Right organization architecture has positive for knowledge management. It defines compo- effects on the other three elements. On the other nents of knowledge management system and hand, knowledge architecture, knowledge man- their relationships. agement process, and IT architecture all have impacts on organization architecture. Organiza- Interactions Among the Elements in tion architecture has to be adapted to meet the Knowledge Management System needs from the three elements too. Knowledge The four elements in knowledge management architecture is the base of knowledge manage- system are interrelated to each other. Knowledge ment process. The fundamental function of the management system can not attain its purpose knowledge management system is to improve without any one of the elements. the business process and to achieve superior The knowledge architecture is the base of the business performance through effective knowl- knowledge management process. The knowl- edge management process. edge management process consists of the main activities in knowledge management. The orga- nization architecture is responsible for perform- Enterprise Information Systems and ing or supporting knowledge management Knowledge Management process. IT architecture is a facilitator for enhan- cing dynamic capabilities through knowledge Enterprise information system (EIS) is an inte- management (Sher and Lee, 2004). grated information system seeking to integrate every single business process and function in Structure of Knowledge Management System the enterprise to present a holistic view of the According to the interaction among the elements business with a single IT architecture. It is a in knowledge management system, the structure powerful and integrated enterprise-level IT archi- of knowledge management system is shown in tecture that is also designed to facilitate knowl- Figure 2. edge management within an enterprise. The Knowledge Management system Organization Architecture Output Input Corporation Corporation’s with superior business Knowledge Knowledge IT Architecture performance operation Architecture Management Process Figure 2. The framework of knowledge management system Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) Knowledge Management in OSS 181
- RESEARCH PAPER Syst. Res. characteristics of EIS include (Ross and Vital, Telecommunications Union (ITU) and the Inter- 2000): national Organization for Standardization (ISO). An EIS is composed of a suite of different The representative standards of OSS are Tele- modules. Typical modules include accounting, communications Management Network (TMN) human resource, manufacturing, logistics, custo- and Simple Network Management Protocol mer relationship management, etc. An enterprise (SNMP). In recent years, the next generation can get its EIS solution through integrating a network (NGN) is coming ever closer. NGN is a number of modules. high speed multi-service packet data network Each module is business process-specific. The capable of supporting the traditional functions use of EIS is associated with business process re- of voice networks, data networks/internets engineering to optimize business processes. and even mobility by providing quality-assured An EIS creates an enterprise-wide transaction transmission, switching and services over IP and structure by integrating modules, data storing/ ATM cores. The competitiveness is in managing retrieving processes, and management and ana- service, not managing network resources. Thus lysis functionality. the OSS has shifted from network-oriented to An EIS is not just a software system; it repre- service-oriented. During the process of develop- sents a new kind of managerial thinking. A ing OSS standards, support has been provided successful implementation of ERP is not only by service providers (SP), network operation related to software selection, but also enterprise providers, equipment manufacturing enter- strategy, enterprise culture, business process prises, and software suppliers. reengineering (BPR), top management support, training and others. Considering the relationship between knowl- Definition of OSS edge architecture, knowledge process architec- ture, organization architecture, IT architecture, OSS stands for Operations Support Systems. OSS and enterprise operations, an EIS supports is a common term for the collection of all the knowledge management that encompasses all support systems required to run a telecom types of knowledge in business operations. The operator’s business. OSS is consisted of four support provided by an EIS to an enterprise’ subsystems: Operation Support System (OSS), knowledge management is embodied in each Business Support System (BSS), Resource Sup- module for specific knowledge management. port System (RSS), and System Support System Each module associates with a specific type of (SSS). The functions of OSS consist of activation, business process, which corresponds to a specific inventory management, fault management, and knowledge management. The knowledge man- workforce management, etc. BSS includes custo- agement of the entire enterprise is realized mer care, multi-service provisioning, service through the integration of individual knowledge assurance, and billing, etc. RSS handles network management module. resource management, operation information management, customer basic information man- agement and customer service information, etc. OVERVIEW OF OSS SSS deals with log file, system parameters, etc. Figure 3 provides a framework of OSS in which Evolution of OSS OSS and BSS are the main functions. The main functions of OSS include, In the 1980s, the basic standard of OSS was determined. The main usage is to manage net- * Customer care: provide an interface to the works. In the beginning of 1990s, OSS standard customers for all issues related to customer has placed emphasis on both network systems order, sales, billing, and problem handling. and network management. A substantial amount * Multi-service provision: activate instances of of work has been completed by the International service for particular customers. Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) 182 Jiayin Qi et al.
- Syst. Res. RESEARCH PAPER Customer/Market OSS BSS Customer Care Activation Multiservice Inventory Provision Management EAI Service Assurance Fault Management Billing Workforce Management Planning & Administration RSS Network resource Operation information management management Customer basic Customer service information management information management SSS User Management Backuping Log file System monitoring system parameters Versioning Figure 3. OSS structure * Service assurance: monitor and uphold the * EAI (Enterprise Application Integration): quality of the delivered services. automate the exchange of data between inter- * Billing: charge for the service. nal applications. * Planning and administration: plan, design and * Activation: execute a service in an optimal and administer the services and infrastructures. well-defined order Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) Knowledge Management in OSS 183
- RESEARCH PAPER Syst. Res. * Inventory management: keep track of the Features of OSS equipment such as where it is, how it is confi- gured, and its status. OSS is a kind of EIS, which is applied to tele- * Fault management: handle alarms. communications industry. Corresponding to the * Workforce management: manage and sche- characteristics of EIS, OSS’ characteristics can be dule teams of technicians, installers and engi- described as, neers. The key idea of OSS is the modularization of telecommunications operation management. Tel- In this paper, a network operator is defined as ecom operators face a lot of uncertainty. The a telecommunication service provider with a appearance of new services is very quick. The network infrastructure and provides multiple modular design of OSS is considered a necessity services. It could be a network, a fixed-line access (Wade, 2000). network of any kind, or a mobile 2/2.5/3G OSS realizes the end-to-end customer business mobile network. This type of network operator is operation processes. TOM is an important refer- named as telecom operator throughout the ence function model for OSS planning. The TOM paper. Of course, the research is related to Ser- model contains a detailed description of the most vice Provider (SP) and Content Provider (CP) important processes involved in running a telecom with no infrastructure of their own although operator’s operation. Service fulfilment, service their tasks are simpler since they only manage assurance, and billing are the three basic customer services and IT infrastructure. business operation processes. OSS implementation will inevitably consider business process reengi- neering (Wade, 2000; Huang et al., 2003). TOM and OSS OSS is a highly integrated software architec- ture. Integrating multi-sections’ businesses in a OSS is intended to cover TOM (Telecom Opera- single software platform efficiently for improv- tions Map) provided by the organization ing customer service is one of the aims of OSS. TMForum. TOM model focuses on the opera- This task requires a high level of integration tional processes within the telecommunication among each subsystem. industry. It was designed as a blueprint for pro- OSS is not just a software system, but also cess direction and a starting point for developing represents managerial thinking. Using TOM as and integrating OSS. The relationship between an important reference model, OSS encourages TOM and OSS is shown in Figure 4. telecom operators pay more attention to the FAB (fulfilment, assurance and billing) is the customers rather than just do billing as in the core area of operations for telecom operators. FAB past (Walsh, 1998). defines the process for fulfilling an order, assuring Generally speaking, OSS can work not only for the defined level of performance and facilitating telecom operators, but also for those other enter- billing for the services provided. FAB is carried prises with characteristics resemble to that of out through the following vertical processes: telecom operators with special network resources, Customer interface management process: It is special service flow, and value chain based on responsible for the dialogue with customer. these network resources and service flows; for Customer care process: It deals with the custo- example, large power plants (Feng et al., 2001), mer needs, ways to identify the needs and how to traffic management (Takahashi, 1998), and others achieve it. (Miyamoto et al., 1997; Sherif and Ho, 2000). Service/product development and operation process: It handles how the service is offered and how to achieve it. Objectives of OSS Network and systems management process: It handles resources required for achieving the As for the motivation for OSS’ implementation, service offered to the customer. there are six main reasons (Schroter, 1998): Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) 184 Jiayin Qi et al.
- Syst. Res. RESEARCH PAPER Customer TOM Customer Interface Management process Sales Handling Order Handling Problem Collection Invoicing Management Qos Customer Customer Care Process Development Service Planning Configuration Service Resolution Service Problem Management Service Quality Discounting Rating OSS and Service/Product Development and Operations Process Development Network Planning Provisioning Network Management Network Inventory & Restoration Network Maintenance Management Network Data Network and Systems Management Process Physical Network and Information Technology Figure 4. TOM and OSS (1) rapid development and deployment of new level improvement (Giannelli et al., 1990); services (Everitt and Virgin, 1996); (2) cost reduc- (6) efficient network resource and customer tion through operation automation; (3) business resource management (Appel and Polosky, process integration (Xia and Rao, 1997); 1988; Kittel et al., 2000). (4) uniform software platform (Furley, 1996; The objective of OSS is to achieve superior Appel and Polosky, 1988); (5) customer service performance, which is embodied in higher Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) Knowledge Management in OSS 185
- RESEARCH PAPER Syst. Res. average revenue per user (ARPU), better ser- different vendors and assemble their own solu- vices, higher customer satisfaction, and improv- tion (Li and Whalley 2004). ed asset utilization, etc. Industry deregulation, globalization, and IP make the telecommunication industry full of intensified competition. The telecommunication KNOWLEDGE MANAGEMENT IN OSS market involves a shift from a stable market to an increasingly user-driven market place. The suc- Business Environment in cess of a telecom operator will entirely depend Telecommunications Industry on the operator’s ability to create services and applications that are embraced by the users. The telecommunications environment can be Same as the success brought by knowledge characterized by its inherent distributive, contin- management to the manufacturing sector, know- uous expansion in the size of network, and ledge management is increasingly helping the the particular importance of fault-tolerance telecomm sector to keep sustainable competi- requirement. These characteristics are reflected tiveness and competency. in the design of software systems. Software sys- tems in telecommunications have to cope with the Knowledge Management in BSS universe of telecommunications protocols, numer- ous hardware platforms, and network architec- BSS focuses on developing the core business by ´ tures (Cselenyi et al., 1998). The characteristics of defining marketing and offering strategies, new telecommunications software systems include products implementation and managing existing high software cost, concurrency, distributivity, products. Customer interface management pro- reliability, diversity and complexity (Patel, 2002). cess and customer care process are the two major Except the above-mentioned industry charac- aspects involved in BSS. Dialogue carrying, ser- teristics, telecom operators are facing more and vice ordering, service activation, trouble admin- more challenges nowadays. Factors such as istration, and billing account review make up all globalization and technology innovation repre- the activities in BSS. sent radical challenges to telecom operators. They Staff knowledge, organizational knowledge, must be more and more competitive to survive. and relational knowledge form the know- Today’s telecommunication market introduces ledge architecture of BSS. There is a plenty of more competitions; meanwhile offers more choi- staff knowledge involved such as sales staff’s ces for customers, lower price and the pressure to experience. There are also rich organizational improve service quality for operators. As the knowledge existing in the customer interface previous monopoly situation is no longer exist, management process and customer care process. new entrants come into the market. In emerging Deeper customer knowledge can give rise carriers economy, state-owned operators are fully or an edge in developing pricing models (Limbach, partially privatized in order to survive better 2004). In addition, relational knowledge exists in (Stienstra et al., 2004). BSS such as reputation, brands, customer loyalty Globalization promotes the domestic competi- and distribution channel knowledge. Those are tion. Global telecommunication market gives the important factors influencing CRM. opportunities to some operators because of the Successful sales experiences can be acquired economies of scale in telecommunication net- and shared among the employees in the sales work, such as BT and Vodafone. It also brings and marketing department. Replication, imitation, radical domestic competition since more new elicitation and innovation will be the main acti- entrants enter to the market. vities for knowledge creation. Some knowledge on Internet technology causes an extraordinary routine problems, success experience, standard growth of the Internet and IP services and business process, can be considered as existing applications. Customers are increasingly free ‘discovered’ knowledge to be maintained and to choose different service components from reused. Sharing of existing knowledge distributes Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) 186 Jiayin Qi et al.
- Syst. Res. RESEARCH PAPER knowledge at the organizational level. Due to the strategy, some intangible resources will inevitably fact that the telecommunications industry changes be used. And a successful strategy will also create rapidly, new services, new regulation policies, new intangible resources. These intangible new market environments, all require continual resources are relational knowledge. revision of existing knowledge. Knowledge can be created from studying BSS is at the front-end in serving customers previous successful service offering. The enligh- for telecom operators. Due to the competition tening effect can create new types of human, in telecommunications industry, organizational organizational, technological and relational structures have increasingly been adjusted to knowledge. All of the knowledge can be acquired customer-oriented. All of these request organi- and reused. Sharing such knowledge can further zational knowledge process. diffuse knowledge across the enterprise. Telephone call centre, interactive voice OSS is operated at the back end which response (IVR), computer telephone integration provides decision support for BSS. Knowledge (CTI), predictive dialers, wireless agents, e-mail, sharing and creating are essential to such deci- web self service, text chat and web collaboration sion support function. For reducing ‘noise’ and make up the technology to complete customer eliminating barriers across sectors, smooth com- communication. IP based call centre, operational munication is required. Organizational structure, CRM and interactive CRM, billing system, and based on traditional command and control, must performance management are sets of software to shift to an open and collaborative structure. support the business operation process. The The analytical CRM is an outstanding compo- integration of these technologies and sets of nent to support service/product development software forms the IT architecture of BSS. process. Decision support system (DSS) and expert system (ES) are both common tools. Knowledge Management in OSS Knowledge Management in RSS OSS focuses on planning, developing and delivering services and products in operation RSS focuses on planning, developing and deli- domain. Service/product development and vering resources needed to support services and operation process are the operational processes. products in the operations domain. Network and OSS deals with service generation and network systems management process is the operational resource planning. process in RSS. Human knowledge, organizational knowledge, Human knowledge, organizational knowledge technological knowledge and relational knowl- and technological knowledge are the main types edge are all involved in OSS. Those previous of knowledge. Those previous network resource service cases, as well as proven cross-selling rules planning cases and the accumulated network are human knowledge. How to organize service/ resource management strategy form the major product development, operation process, and human knowledge. Database, data marts and data network, is considered as organizational knowl- warehouses about services and products represent edge. In addition, culture, regulations, and the major organizational knowledge. Some inno- partnerships are considered as organizational vation techniques are technological knowledge. knowledge as well. There are many innovative Organizational structure has influence on RSS, techniques and skills involved with these which but the degree of influence is much weaker than are considered as technological knowledge. Inter- that to OSS and BSS. Database, data mart and data estingly, the greater the scope of services offered, warehouse are the three data storages in RSS. and the greater the range of quality and price options, the more efficient (and cost efficient) the Knowledge Management in SSS use of the network resources. Service innovation is a key factor for revenue growth of a telecom SSS is of significance to OSS as an EIS. A variety of company. For designing a successful marketing technological knowledge is involved with this Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) Knowledge Management in OSS 187
- RESEARCH PAPER Syst. Res. system including operating systems methods and edge management process, requiring organiza- techniques. In general, organizational structure tional learning, open organization structure has relatively minor influence on it. and certain IT architecture. RSS involves human knowledge, organizational knowledge and tech- Summary nological knowledge. Organizational structure has a less significant influence on it. Data mani- BSS, OSS, RSS and SSS are integrated into a single pulation tools are needed. Technological knowl- OSS through system integrator (SI) software. edge is the main type of knowledge involved in Knowledge management varies among different SSS for which organizational structure has minor components in OSS. BSS and OSS involve with effect on it. The summary of knowledge manage- types of knowledge throughout the entire knowl- ment in OSS is described in Table 2. Table 2. Summary of knowledge management in OSS OSS\ Knowledge Knowledge Organization IT Function KM Architecture Management Architecture Architecture Process BSS Human knowledge, Create, maintain, Team management, Call centre To provide organizational distribute and revise project manager, CTI, operational customer knowledge, knowledge to support communicate with CRM, interactive service relational customer interface knowledge management process software vender CRM, billing effectively and customer care system, etc process OSS Human knowledge, Create, maintain, Team management, Analytical CRM, To support the organizational distribute and revise project manager, DSS, etc. customer service knowledge, knowledge to support communicate with provision technological service/product software vender effectively knowledge, development and relational operation process knowledge RSS Human knowledge, Create, maintain, Team management Database, data To support the organizational distribute knowledge mart, warehouse, above activities knowledge, to support network etc. effectively technological and systems knowledge management process SSS Technological Revise knowledge to Team management OS, such as Unix To support the knowledge support OSS’ regular operation etc. above activities effectively OSS Human knowledge, Create, maintain, Team management, Enterprise To gain superior In knowledge, distribute and revise project manager, Information advantage general knowledge, knowledge to support communicate with Systems (EIS) through organizational the horizontal business software effectively knowledge, process of fulfilment vendor providing technological assurance and billing end-to-end knowledge, (FAB) customer service relational knowledge Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) 188 Jiayin Qi et al.
- Syst. Res. RESEARCH PAPER DISCUSSION AND CONCLUSION ment process. Journal of Enterprise Information Man- agement 18(1): 28–46. Cavusgil S, Calantone R, Zhao Y. 2003. Tacit Knowl- An integrated OSS is a combination of applica- edge transfer and firm innovation capability. Journal tions that interact with each other to enable sup- of Business & Industrial Marketing 18(1): 6–21. port, administration and management of services Choi B, Lee H. 2002. Knowledge management strategy for telecom industry. It includes systems that and its link to knowledge creation process. Expert manage the networking infrastructure, planning Systems with Application 23(3): 173–187. Chuang S. 2004. A resource-based perspective on tools, billing systems, customer care, trouble knowledge management capability and competitive management tools and the like. It is the funda- advantage: an empirical investigation. Expert Sys- mental integrated software platform for telecom tems with Applications 27(3): 459–465. operators. It is an EIS used in the telecommuni- ´ ’’ ’’ Cselenyi I, Szabo R, Szabo I, Latour-Henner A, cations industry. Bjorkman N. 1998. Experimental platform for tele- communications resource management. Computer Although there are some researches on the communications 21(17): 1624–1640. knowledge management in EIS, especially in ERP, Elmasri R, Navathe S. 2003. Fundamentals of Database there are only limited researches on knowledge Systems. Addison Wesley: Boston. management in OSS. In this paper, an overview of Everitt H, Virgin M. 1996. Full services network knowledge management in OSS and its frame- operations and management. Proceedings of IEEE Network Operations and Management Symposium, work is provided. Future research will be focusing vol. 4, pp. 15–19. on knowledge management in OSS implementa- Feng Q, Bai X, Cao Y, Jin Y. 2001. Models of electric tion, key knowledge management techniques in market operation support system based on UML. OSS (Liao, 2003; Sher and Lee, 2004), knowledge Proceedings of IEEE 2001 International Conference on version management in OSS, etc. Computer Networks and Mobile Computing, pp. 13–18. ´ ´ Fernandez E, Montes J, Vazquez C. 2000. Typology In this paper, a knowledge management model and strategic analysis of intangible resources: a in OSS with systems point of view is proposed. resource-based approach. Technovation 20(2): 81–92. A knowledge management framework for OSS in Fowler A, Pryke J. 2003. Knowledge management in systems perspectives is also developed. public service provision: the child support agency. International Journal of Service Industry Management 14(3): 254–283. Furley N. 1996. OSS architecture framework. Proceed- REFERENCES ings of IEEE Network Operations and Management Symposium, vol. 3, pp. 15–19. Ahn J, Chang S. 2004. Assessing the contribution Giannelli M, Pileri S, Saracco R. 1990. Operations of knowledge to business performance: the KP3 support systems in Italy: experiences and perspec- methodology. Decision Support Systems 36(4): 403– tives of integration. Proceedings of IEEE International 416. Telecommunication Symposium, pp. 572–576. Alavi M, Leidner D. 2001. Knowledge management Huang T, Lee C, Chen Y, et al. 2003. A new architecture and knowledge management systems: conceptual to operation support systems. Proceedings of IEEE foundations and research issues. MIS Quarterly 10th International Conference on Telecommunications, 25(1). pp. 1236–1242. Appel J, Polosky M. 1988. Pacific Bell’s network and Joshi A, Sharma S. 2004. Customer knowledge devel- systems concept of the 90’s. IEEE Journal on Selected opment: antecedents and impact on new product Areas in Communications 6(4): 627–632. performance. Journal of Marketing 68(4): 47–59. Argyris C, Schon D. 1996. Organizational Learning. Kanjanasanpetch P, Igel B. 2003. Managing knowledge Addison Wesley: Reading, MA. in enterprise resource planning (ERP) implementa- Badii A, Sharif A. 2003. Information management and tion. Proceedings of IEEE Engineering Management knowledge integration for enterprise innovation. Conference, pp. 30–35. Logistics Information Management 16(2): 145–155. Kim Y, Yu S, Lee J. 2003. Knowledge strategy planning: Bendoly E. 2003. Theory and support for process methodology and case. Expert Systems with Appli- frameworks of knowledge discovery and data cations 24(3): 295–307. mining from ERP systems. Information & Manage- Kittel A, Gudur J, Gundlapudi S, Lederman A. 2000. ment 40(7): 639–647. GNI-building integrated OSS infrastructure from Bhatt G, Gupta J, Kitchens F. 2005. An exploratory the ground up. Proceedings of IEEE Network Opera- study of groupware use in the knowledge manage- tions and Management Symposium, pp. 945–946. Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) Knowledge Management in OSS 189
- RESEARCH PAPER Syst. Res. Kwan M, Balasubramanian P. 2003. Knowledge scope: through knowledge management. Information & managing knowledge in context. Decision Support Management 41(8): 933–945. Systems 35(4): 467–486. Sherif M, Ho S. 2000. Evolution of operation support Li F, Whalley J. 2004. Deconstruction of the telecom- systems in public data networks. Proceedings of munications industry: from value chains to value IEEE Symposium on Computers and Commuications, networks. Telecommunications Policy 26(9–10): 451– pp. 72–77. 472. Shi Z, Huang Y, He Q, Xu L, Liu S, Qin L, Jia Z, Li J, Li H, Xu L. 2001. Feature space theory-a mathematical Huang H, Zhao L. 2005. MSMiner-a developing foundation for data mining. Knowledge-Based Systems platform for OLAP. Decision Support Systems. 14(5–6): 253–258. Siemieniuch C, Sinclair M. 2004. A framework for Li H, Xu L, Wang J, Mo Z. 2003a. Feature space theory organizational readiness for knowledge manage- in data mining. Expert Systems 20(2): 60–71. ment. International Journal of Operation & Production Li T, Yang N, Wu H. 2003b. Operation Support Management 24(1): 79–98. Systems—Theory, Strategy and Practice. Renmin Post Spiegler I. 2003. Technology and knowledge: bridging & Communications Press: Beijing. a ‘‘generating’’ gap. Information & Management 40(6): Liao S. 2003. Knowledge management technologies 533–539. and applications-literature review from 1995 to Stienstra M, Baaij M, Van Den Bosch F, Volberda H. 2002. Expert Systems with Applications 25(2): 155–164. 2004. Strategic renewal of Europe’s largest telecom Limbach I. 2004. Mobile OSS: fitting the bill. Total operator (1992–2001): from herd behavior towards Telecom April: 30–31. strategic choice? European Management Journal 22(3): Lynn G, Morone J, Paulson A. 1996. Marketing 273–280. and discontinuous innovation: the probe and learn Takahashi H. 1998. A study on designing driver’s process. California Management Review 38(3): 8–37. operation support system using driving environ- Marakas G. 2003. Decision Support Systems in the ment-driver-vehicle interaction model. Proceedings Twenty-first Century. Prentice-Hall: Upper Saddle, of IEEE World Conference on Computational Intelli- NJ. gence, pp. 177–182. Mesaric J. 2004. Knowledge management—necessity Tzokas N, Saren M. 2004. Competitive advantage, and challenge in small and medium enterprise. knowledge and relationship marketing: where, Proceedings of 26th International Conference on Infor- what and how? Journal of Business & Industrial mation Technology Interfaces, ITI, pp. 481–485. Marketing 19(2): 124–135. Miyamoto Y, Hayshi M, Koyano K, et al. 1997. Wade V, Richardson T. 2000. Workflow-a unifying Development of operation support systems for technology for operational support systems. Proceed- refuse incineration plant. IEEE Proceedings of 26th ings of Network Operations and Management Sympo- SICE Annual Conference, pp. 1053–1056. sium, pp. 231–246. Nemati H, Steiger D, Iyer L, Herschel R. 2002. Walsh D. 1998. Operations support systems: caught in Knowledge warehousing: an architectural integra- the winds of change. Proceedings of IEEE Network tion of knowledge management, decision support, Operations and Management Symposium, p. 255. artificial intelligence and data warehousing. Decision Wang S, Ariguzo G. 2004. Knowledge management Support Systems 33(2): 143–161. through the development of information schema. O’Brien J. 2005. Introduction to Information Systems. Information & Management 41(4): 445–456. McGraw-Hill: Boston. Warfield J. 1989. Societal Systems. Intersystems Pub- Patel A. 2002. Current status and future directions of lications: Salinas, CA. software architecture for telecommunications. Com- Xia Q, Rao M. 1997. A hybrid intelligent system for puter Communications 25(2): 121–132. process operations support. Proceedings of IEEE Pearlson K, Saunders C. 2004. Managing and Using International Conference on System Man Cybernetics, Information Systems. Wiley: New York. pp. 2097–2102. Ross J, Vitale M. 2000. The ERP revolution: surviving vs Xu L, Li Z, Li S, Tang F. 2005a. A polychromatic sets thriving. Information Systems Frontiers 2(2): 233–241. approach to the conceptual design of machine tools. Schroter A. 1998. Introduction to the network infra- International Journal of Production Research 43(12): structure warehouse. Proceedings of IEEE Network 2397–2422. Operations and Management Symposium, pp. 210–219. Xu L, Li Z, Li S, Tang F. 2005b. A decision support Sher P, Lee V. 2004. Information technology as a system for product design in concurrent engineer- facilitator for enhancing dynamic capabilities ing. Decision Support Systems. Copyright ß 2006 John Wiley & Sons, Ltd. Syst. Res. 23,177^190 (2006) 190 Jiayin Qi et al.
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