Knowledge Management for Profitable Businesses

DOI : 10.17577/IJERTV1IS3240

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Knowledge Management for Profitable Businesses

Mr. M Lakshmi Vara Prasad, Asst Prof, MBA Department, DIET, Anakapalle, (AP), India 531 002

Mr. A Seshagiri Rao,

Research Scholar, Acharya Nagarjuna University,(AP), India – 522 510,


Competitive corporations must be able to locate, capture, store, share and leverage not only data and information but also the inherent k nowledge of the firm. Having said this, if the ma jority of information needed for decision- mak ing exists in the minds of staff, a system is needed to capture and codify this knowledge. The research addresses this within the context of how decision support systems, Artificial Intelligence and Information Technology can assist the transformation process of knowledge. The emergence of new technologies has hik ed the ability of corporations to share k nowledge, not just internally, but with external stakeholders. E-k nowledge network s permit their participants to create, share and utilise strategic k nowledge to enhance operational and strategic efficiency and effectiveness. The proposed e-knowledge network can evaluate and deploy these technologies to enable inter- corporate knowledge sharing. In addition, the imp lications of inter-corporation k nowledge sharing on the supply chain are considered for business process improvement.

  1. Introduction

    Corporations have always attempted to understand if access to quality informat ion and knowledge can help them re main co mpetitive. However, with the adoption of rapidly changing business environments, functional managers are now realising that they need to inculcate an effective knowledge strategy and provide employees with best available knowledge to assist a more co mprehensive decision ma king process.

    Data warehousing initiatives, applying various data mining methodologies, have found common place in many business infrastructures for assisting the decision making process. However, as the vast ma jority of knowledge resides in the minds of emp loyees, the quality of support

    these provide, especially for intensive queries, is to a large e xtent uncertain (Ne mat i, Steiger et al. 2002). Hence, a new system is required that not only locate, capture, store, share and leverage data and informat ion, but also include the aspect of knowledge.

    Knowledge manage ment has recently become an interesting concept, although many corporations are still unable to expla in what knowledge means. More importantly, they are unable to develop and leverage knowledge to enhance corporational performance. This is due to corporations becoming increasingly more co mp le x in structure, knowledge resulting that is fragmented, hard to locate, leverage, share and difficult to reuse (Zack 1999).

    The research focuses on the revelation of knowledge and technology that can contribute to provide in capturing, coding, retrieval, sharing and leveraging of different forms of intelligence, as we ll as different types of knowledge, across a corporation. It raises a number of questions. What is e xplic itly codified knowledge and how should it be managed? What role can technology play? How should a corporation's resources and capabilities be configured? The ultimate goal of these questions is to provide the decision – ma ker with a suitable analysis platform for decision- ma king that improves all phases of the intra-corporation knowledge manage ment process.

  2. Knowledge Management

    Knowledge that assists the decision making process is an obvious vital resource, however, knowledge h as often suffered from under management as per history annuls. It is only in recent years that knowledge has been taken more seriously. This no doubt yielded from a poor understanding

    of what knowledge is and from a lac k of provision, in terms of advice and fra me works, for managing it.

    1. What Is Knowledge?

      Most definitions and elaborations of knowledge seem to cover the same vocabulary, concepts and words. Rather than provide a standard definition, the research addresses the general themes and fundamentals that have become evident in recent years.

      Knowledge goes through a process of sharing tacit with tacit knowledge, tacit to explic it, e xplic it leverage, and e xplic it back to tacit.

      Knowledge can be built and tested.

      Knowledge can be separated from data and informat ion.

      Exp lic it knowledge is normally filte red, stored, retrieved and dispersed across the corporation.

      A culture that does not render and reward the sharing of knowledge cannot expect technology to solve its problems (Srin ivas 2000).

      Tacit knowledge is subconsciously understood and used, difficult to articulate and usually developed from imme rsing oneself in an activity for a prolonged period. Exp lic it knowledge can be easily commun icated to others vide a system of language, symbols, rules, equations and objects. It consists of quantifiable data, written procedures, mathe matica l quantification etc (Ne mati, Steiger et al. 2002). Exp licit knowledge is mo re impo rtant for corporations; imagine a corporat ion with no computer software or procedural documentation.

    2. The Knowledge Transformation Methodology

      As mentioned earlie r, knowledge goes through a transformation process, which can be facilitated through the utilisation of Decision Support Systems (DSS), Artificia l Intelligence (AI). The manuscript covers the ma in area of focus, the explication of knowledge, with additional detail of this transformation process to be registered in the following reference (Ne mati, Steiger et al. 2002).

      DSS a re IT and software ma inly designed to help people at all levels of the company, below the e xecutive level, make

      decisions. DSS can play a vital role in the transformation process of e xplicating knowledge, for e xa mple , through the specification of mathemat ical analysis. Specifica lly, the goal of these models, and of the decision variables, need to be explic itly articu lated by the decision-ma ker. Furthermore, the decision maker can also explicit ly articulate the model limitations. This specification of e xplicit knowledge "represents the tacit knowledge the emp loyee has developed over time, within the decision – ma king environment" (Ne mati, Ste iger et a l. 2002).

      DSS can a lso enhance the exp licat ion of knowledge by "elicit ing one or more what-if conditions, representing areas the knowledge worker would like to investigate" (Ne mat i, Ste iger et al. 2002). In effect, the tacit knowledge of historical decisions is changed into explic it form, to be shared and leveraged for improved decision ma king.

      Once this knowledge has been transformed and registered, it can be leveraged by making it available to others when and where they need it. (Nemat i, Ste iger et al. 2002) proposed that "explic it knowledge stored in the form of instances of a mathematica l system (what-if cases) can be leveraged via deductive and/or inductive model ana lysis systems". Model-specific info rmation is applied to a single instance of a model, addressing such questions as "why is this the solution?," "why do the solutions to two model instances differ so much?".

      DSS can also help worke rs to learn, i.e. the process of changing explic it knowledge to imp licit knowledge. Known as internalisation, this process involves the "identifying bodies of knowledge applicable to the particular user's needs" (Warkentin, Sugumaran et al. 2001). It involves extracting knowledge and filtering it to match a particula r issue against the bdy of knowledge. Internalising e xplic it and/or new knowledge may arise through a decision make r modifying his/her internal mental model that is used as his/her performance guide for a specified situation (Ne mati, Steiger et a l. 2002).

      If tacit knowledge has the potential to be explicated and difficult to be articulated, it represents an opportunity lost to utilise that knowledge for improve ment of the decision ma king process. Competitors who are able to achieve this task may attain a competitive advantage (Zack 1999). This knowledge may re ma in tacit due to the corporation possessing no formal structure or language for its articulation. In contrast, inherently inarticulable knowledge that corporations attempt to articulate may have a detrimental effect on organizational performance, as this knowledge can be ultimately lost. Tacit knowledge is an e xtre me ly impo rtant resource as it underpins the decisions staff make for a given situation. Failure to manage it

      properly will lead to a loss of knowledge and failure to benefit fro m the e xperience of others.

      Although exp lic it knowledge represents a fraction of a corporation's intellectual assets, it is apparent it plays a crucial ro le in the knowledge strategy of an corporation. Zack (Zac k 1999) suggests that "appropriately e xplicating tacit knowledge for sharing and re-application is the least understood aspect of knowledge manage ment". However, corporations must not shy from this process as the balance between tacit and explic it knowledge can impact the competitive performance of a corporation. Corporations should therefore focus on determining which knowledge to ma ke e xp licit and wh ich to re main tacit. Providing a suitable set of guidelines for managing this knowledge is a solution to success for any knowledge management initiat ive.

  3. Inte r-Corporation Knowledge Sharing

    The manuscript has so far discussed how knowledge can be managed to support decision-making within a corporation. This section will now discuss how the emergence of new technologies can enhance a corporation's relationship with its stakeholders. The final part of the manuscript will address how new technology, specifically web -enabled, can enhance the utilisation and application o f knowledge, for inter-corporation knowledge sharing. This study e xa mines the way corporations are restructuring internal and external re lationships, and creating "e-knowledge networks", e xisting in a v irtual environ ment, to coordinate the communication of data, information and knowledge.

    Much like an intra-corporation knowledge warehouse, the ama lga mation of knowledge networks and the Internet effectively create one, whole virtual repository, allowing all partic ipants to create, share and use strategic knowledge to collaboratively improve operational and strategic efficiency and effectiveness. The prima ry focus of this integrated, virtual community is rooted on the explic it knowledge contained in the repository, rather than the renderers, decision-ma kers or the tacit knowledge they may hold (Zack 1999).

    In addition to capturing, storing and retrieving informat ion, a corporation must be able to lever this information to specific processes and unknown situations. Specific contextual knowledge could be fully e xp loited to reflect the full range of corporation knowledge, as it can provide significant opportunities for competit ive advantage.

    A community of practice is defined as "an informal set where much knowledge sharing and learning takes place" (Merali, Davies 2001). The Vice President of Ranba xy

    Labs describes such communities as "peers in the e xecution of real work. What holds them together is a common sense of purpose and a real need to know what each other knows"(Verna 2000a).

    In essence, the group acts like an informal network, with each representative sharing a common agenda and interest. The importance of these networks becomes viable when individuals attempt to elic it in formation fro m others who do not share mutual interests and agendas. "Commun ities of practice and social networks underline the impo rtance of the link between social capital and knowledge resources" (Merali, Dav ies 2001).

    Most knowledge management initiat ives attempt to register informat ion relating to specific user profiles and queries. However, "the bigger challenge is to capture and reapply knowledge that is generated during knowledge work" (Merali, Davies 2001). Although DSS can effectively handle this created knowledge in a number of ways (refer back to 2.1) Mera li (Me rali, Dav ies 2001) proposes that the ma jority of knowledge created through this process norma lly tends to rema in private. This could be due to the following:

    "A lack of context within wh ich to articulate personalized lea rning" (Mera li, Davies 2001).

    "The amount of time and effort mandated to analyse and record what has been learnt" (Merali, Davies 2001).

    "Articulating particular sections of knowledge may not be culturally legit imate, challenging what the corporation knows may not be socially or politica lly correct" (Zack 1999).

    "Making private knowledge public could result in a redistribution of power that may be resisted in corporation cultures" (Zack 1999).

    Co mmunit ies of practice are viewed as a means to overcome these barriers to knowledge sharing. The research now discusses how e-knowledge networks, supported by the Internet, can enable the creation of a "virtual community of practice" (Merali, Dav ies 2001).

    Inter-corporation systems are "networks of company systems that permit corporations to share information and interact electronically across boundaries" (Warkentin, Sugumaran et al. 2001), the common mediu m be ing the Internet. Corporations are now adopting a fresh approach to knowledge, that is, "knowledge equals power, so share it

    and it multip lies" (Verna 2000b). Their a im is to increase efficiency and speed of response in dynamically changing ma rkets and imp rove a corporation's relat ionship with its stakeholders (Walsham 2001).

    E-knowledge networks are formed through the ama lga mation of knowledge management and inter- corporate systems. The adoption of the Internet has provided a platform for the continuous and unattended e xchange of information and knowledge refe rencing ma rkets, customers, de mand, inventories and so forth. These platforms enable the sharing of valuable knowledge, often created through technologies viz., decision support systems, intelligent agents and data warehouse technologies, with their strategic partners, thereby initiat ing improved corporations effectiveness. One such e xa mple o f intelligent agents is the Jasper II system, comprising intelligent software agents that "retrieve, summarise and inform other agents about information deemed to be of value to a Jasper II user" (Merali, Davies 2001).

    It is quite apparent corporations need to be fle xible and be able to identify exp loitable situations. These goals can be achieved by imple menting electronic systems that generate immed iate knowledge (rea l time) about unified functions and processes, customers, markets, supply chain partners, vendors and dealers (Warkentin, Suguma ran et al. 2001).

    Furthermore, a strategic relat ionship can provide access to diffe rent sources of knowledge, not duplicates of this knowledge (Day, Schoema ker, P. J. H. et al. 2000). Such systems permit corporations to be dynamic and fle xib le, allo wing rapid changes in their strategies and performance. Corporations can use this knowledge to auger new internal and external structures and relationships, leading to further improve ments in knowledge, thus realizing further strategic improvements.

  4. e-Knowledge Networks for Business Improvement.

    This research now discusses one long-term alliance, suggested by Warkenti (Warkentin, Sugu maran et al. 2001), as a trend like ly to emanate from imp le menting strategic e-knowledge networks in the context of supply chain. The supply chain process involves corporations acquiring resources and providing goods or services, (Johnson, Scholes 1999). Progressive supply chain manage ment attempts to improve the co-ordination "across the supply chain to create value for customers, wh ile increasing the profitability of every link in the chain" (Warkentin, Sugu maran et al. 2001). It is this symbiotic aspect that addresses the role of shared knowledge, enabling the analysis and management of all sup ply change

    activities. In other words according to Choi et al. (Choi, Budny et al. 2004) the supply chain encompassing knowledge is referred to as knowledge supply chain and in this context they define knowledge as technologies, inventions and know-how that assist businesses bring products to markets. The material flow is the physical flow of material and the knowledge flow is simila r to the flow of technique that connects the parts together. Figure 1 illustrates a materia l flow in a typical supply chain. It shows how materia l moves from supplier to customers and at every stage a reasonable yield is added to the materia l, wh ilst, a network generates value not just through goods and services, but also through knowledge. Knowledge becomes a mediu m of e xchange in its own right, with success rested on building a rich web of trusted relationships. The supply chain network proposed by Warkentin (Warkentin, Sugu maran et al. 2001) is e xtended to emphasise the marking of a va lue network fo r a co mp le x e-business environment. In support of this trend towards e- networks, additional focus has been rested to the implications on the value chain. Verna (Verna 2000b) states "the traditional vie w of value chain is outdated by the new enterprise structure of the value network".

    Figure 1: A Typical Supply chain

    Before the advent of the Internet, the traditional view of the supply chain was that of ineffic ient co mmunication and allocation. Info rmation flowed in a linear fashion, possibly upstream or downstream. In addit ion, a further drawback was the missed connection to one's consumers, as corporations were forced to communicate through wholesalers, distributors and retailers. Dispersion of informat ion beyond one link in the supply chain was limited through a lac k of formal re lationships. Furthermore, the "info rmation flow through linkages was constrained in lieu of a lack of standard data representation schemes, hence, the sharing of informat ion beyond immed iate supply chain partners was impossible" (Warkentin, Suguma ran et al. 2001).

    The traditional vie w of knowledge was to hoard it and if corporations were to share this valuable informat ion, a competitive edge would be lost (Ve rna 2000b). Moreover, the consensus among new economy corporations is to

    provide an open environment for the sharing of informat ion. Corporations are encouraged to work "in c lose co-ordination to optimise the flow in the entire supply chain" (Warkentin, Suguma ran et al. 2001) The concept of the e-supply chain asserts a new relationship between suppliers, partners and customers as well as coordination of processes, information systems and inter-corporation problem solving (Manthou, Vlachopoulou et al. 2004). The e-supply chain is the backbone of a virtual network, linking each participant as one robust unit. The chain co mprises a series of value-added stages, starting with the supplier and ending with the end-user. The focus of the e-supply chain is on the multi-direct ional flo w of information; each stage is a supplier to its adjacent downstream stage and a customer to its upstream stage. Each partic ipant is hence able to assume many roles with in the supply chain, but the ultimate re lationship boils down to a supplier and a consumer role . Tradit ionally, de mand informat ion passed through many layers, with each layer eroding the quality of informat ion. The variances in this information resulted poor production scheduling and inefficient resource allocation, resulting in e xcessive inventory throughout the chain (Warkentin, Suguma ran et al. 2001). In contrast, the e-supply chain asserted by Manthou (Manthou, Vlachopoulou et al. 2004) utilises information and knowledge as a substitute for inventory, competing on agility and speed and witnessed customer collaboration as a competitive, strategic asset. Figure 2 illustrates the creation of knowledge in a corporation. Here, it is argued that a typical corporation is closed loop i.e., it can acquire knowledge through external factors only. Having said this, it must be emphasized that effectively managing and retriev ing the existing knowledge – wh ich could be in the form of data and experts knowledge – could be the main focus.

    Figure 2: Protocol for Knowledge Creation

    Knowledge creation would ensure by assisting the corporation in identifying skill gaps or knowledg e gaps between what a corporation has as a whole and what it may need to face new challenges. It would also ma ke it easy to identify what areas a corporation should either focus on or outsource its activities to. It must be emphasized that just leveraging knowledge in a corporation may not be enough

    because of the dynamic and ever changing world we are in. And so, this should be comple mented by inculcating a learning environment by fostering and rewarding individuals. The key to a successful corporation is how effectively it brings together the skills it harbours.

    The resulting fresh flows of strategic supply chain knowledge tend to crystallize new strategic relationships in the e-ma rketplace. These flows may represent "knowledge created by analytical processes conducted by automated informat ion min ing algorith ms" (Warkentin, Sugu maran et al. 2001). What is most significant about e-knowledge portals is that they permit fresh inter-corporation informat ion and knowledge flow, effect ively fac ilitating manage ment of the supply chain. However, if a corporation is to gain ma ximu m benefit fro m these newly created flows of information and knowledge, they must use it strategically.

  5. Conclusions

The motivation of this paper is to draw attention to important aspects of technology in capturing, codifying and disseminating knowledge throughout corporations. It not only reflects the need to store different forms of knowledge but also diffe rent types of knowledge.

However, it should be re me mbe red that an overemphasis on technology might force a corporation to concentrate on knowledge storage, rather than knowledge flow. New insights and opportunities are available to corporations if they are able to integrate knowledge across shared and diffe rent contexts. The Internet has enabled the creation of virtual c ivilizat ions, networked through technologies only available just a few years ago. Now that the internet is becoming the standard form of collaboration between corporations, the trend of the e-knowledge network looks set to continue. While technology can greatly enhance a corporation's knowledge management strategy, it does not necessarily ensure that a corporation is managing its resources and capabilities in the appropriate way. However, technology is vital to enable the capturing, inde xing, storing and distribution of knowledge across and with other corporations. Knowledge can be viewed in a number of other contexts, it is vita l that each is addressed if a corporation is to improve performance.

  • Successful knowledge strategies rest on whether corporations can link their business strategy to their knowledge require ments. This articulation is vital to the allocation of resources and capabilities for e xplicating and leveraging knowledge.

  • The competitive va lue of knowledge must be addressed to assess areas of weakness. Strategic efforts

    should be made to close these knowledge gaps to ensurethat the corporation remains competitive. The strategic value of knowledge should be addressed, focusing on the uniqueness of knowledge.

  • Finally, a corporation needs to address the social aspects affecting knowledge init iatives, name ly cultural, politica l and reward systems. Beyond the management roles proposed in this research work, the environment should promote co-operation, innovation and learning for those partaking in knowledge based roles.

Knowledge is mo re than a fad; it is now at the centre of a corporation's strategic thinking. The essence of any knowledge management strategy can be summed up by the following quote, from the Father of Management – Peter F Drucke r (Drucker 1993) A co mpanys key to success resides not so much in its work and capital as in the capacity to treat knowledge, corporate knowledge, be it e xplicit or tacit.


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International Journal of Engineering Research & Technology (IJERT)

ISSN: 2278-0181

Vol. 1 Issue 3, May – 2012

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