Reluctant to Share, Essay Example

An Exploration of Knowledge Transference in a Capitalist Context

Abstract

During the course of this paper, we will examine the nature, theory, and practice of knowledge transfer and come to a conclusion about the current usefulness of increased cooperative knowledge management in today’s world. After these aspects are addressed, we will discuss the new quantitative measurement systems, the facilitative factors upon which they depend, and what this means for companies and for the field of Knowledge Management as a whole.

Introduction

Globalization has brought the consideration of cooperation and knowledge sharing to the business foreground as “the ability to capture and subsequently share knowledge among a wide spectrum of individuals is becoming a more and more vital component of any institution’s success” (Kourik & Maher, 2008, 6). As Chan, Oerlemans, and Pretorius (2009) illustrate through their quantitative research and analysis of the results produced by knowledge transfer across different Science Parks, both benefits and hazards are natural byproducts of organizational progress. The selection of appropriate action or (in some cases) inaction is a highly individualistic company decision which necessitates a cost-benefit analysis to knowledge transfer. A subcategorization of ‘intended’ and ‘unintended’ knowledge transfer, according to their quantitative research, is an unavoidable factor in success. During the course of this paper, we will examine both perspectives on knowledge transfer, discuss, and come to a final conclusion regarding its potential usefulness. Perhaps a more pressing concern for the field of Knowledge Management (KM), which this essay also examines, is whether knowledge transfer should occur at all.

Theory

It was once written “I think, therefore I am”. In other words, the only certainty possible is achieved through personal knowledge in the vein of quantum theory rather than through the transference of information from a different perspective. Although these observations were originally made regarding the status of reality, similar debates have raged as to what comprises knowledge and what is only information and how much of either can actually be passed from person to person.

In a 2009 article in Implementation Science, the authors assert that relevant knowledge can be passed in an environment of supportive, positive, and employee-utilizing management. According to the article’s business management perspective, the importance of knowledge was divided into areas of use, need, acquisition, and sharing and was depicted as a cyclical input-feedback process with multiple layers with vision, leadership, and learning culture at the core of KM. Perhaps one of its greater theoretical contributions is the inclusion of intra-organizational knowledge sharing as an important part of the cycle. Whether or not industries intend to engage in knowledge transfer across company lines, knowledge transference within the company is a crucial step to ensuring harmony and productivity on the smaller scale. However, according to this knowledge input-feedback cycle, innovation is a product of knowledge sharing (French, Thomas, Baker, Burton, Pennington, & Roddam, 2009).

Practice

Benefits

Inhibitions of organizational systems to employ cooperative knowledge communication often stem from a fear of replicating information, especially in fields, like Advertising, which rely on the uniqueness of a concept to convey an appropriate message and produce an influential response. Landaeta’s results produced evidentiary support to the contrary:

“It can be suggested that knowledge transfer across project efforts can positively influence the capabilities of projects … In particular, it was found that projects that exerted a large effort transferring knowledge across projects were to a limited extent likely to influence their body of knowledge… it was also found that the higher a project’s body of knowledge obtained from other projects, the more likely a project can generate high performance” (2008, 35).

However, the managerial concerns and sensitive nature of knowledge transfer warrant an explanation of recommended practices. First, knowledge “brokers” should be selected. These select, motivated, and able few will typically have experience in similar inter-system collaboration, an open and perceptive mind, and good social skills. When presented with the proper supportive environment for knowledge sharing, the average project participants will exceed expectations with very little guidance (Landaeta, 2008).

Hazards

The discussion of knowledge sharing has already briefly emphasized the importance of organizational support for innovative approaches to knowledge absorption. The primary hazard when considering cooperative brainstorming, group decision making, and knowledge sharing is a result of distrust. After a lifetime of socialization that teaches the “dog-eat-dog” nature of business and the work environment (especially in a Capitalist or individualistic economy), most employees are reluctant to take risks. This reluctance naturally grows as job permanency and the status of perceived employee value are threatened. Distrust- compounded by opportunistic behavior- provides the greatest impediments to successful knowledge sharing (Chan et al., 2009). Thus, the potential for innovation is dependent upon several subjective and highly personal criterions.

Immediately following the realization of the benefits and challenges of new technologies and processes, there comes the need to tailor these advances to specific organizational needs and to optimize their contributing potential. This may consist of reducing the application of these advances to only the areas exhibiting the greatest need, requesting more compact, user-friendly, or economical variations, or even discarding them altogether. Thus any advances are judged warily and often adopted at a point in time which has already seen them begin to be obsolete. In the rapid-fire pace of technology and research today, companies frequently rely on pilot testing as an initial indicator of potentiality (Kourik & Maher, 2008). This, in turn, necessitates continued communication regarding the practicality of the knowledge transfer itself. In essence, knowledge transfer is ironically facilitated as a primary way to gauge the practicality of other knowledge transfer measures.

Measurement

Companies wishing to quantitatively measure the effectiveness of knowledge transfer may look to Competency Management Systems (CMS). These systems facilitate and measure the progression of information transfer across communities or companies- but are acknowledged to be complex and time-demanding. For the CMS newcomers, the INTEROP Network of Excellence (NoE) provides the next evolution in these systems. Where the predecessors had been overly detailed and harder to administer than face-to-face research, the NoE simplified, collected, measured, and evaluated the progress of knowledge transference and absorption. Mindful of the time constraints of supervisors and managers, this particular study described how the INTEROP NoE can be used to create a Knowledge Map which visually represents the amounts of knowledge gained in different categories. This Knowledge Map derives from a KM analysis of the ontology of the information in a process which greatly resembles that of data mining (Velardi, Cucchiarelli, & D’Antonio, 2008).

Discussion

The constant industrial focus tends to regard knowledge in ways which reflect the potential benefits at present and the long-term expected pecuniary compensation only. In reality, one key benefit of knowledge transfer both within and between companies is not acknowledged. If the nature of knowledge is as French et al. (2009) claim, then greater amounts of research in all arenas will inevitably serve to increase the understanding of the employees of any working capacity and to increase company knowledgeability of the company concerning the nature of their clientele. Irfan and Shaikh (2009) call this resulting pool of knowledge an information repository. This increase is dependent upon the ability and willingness to allow beneficial knowledge imprinting, the support of influential person(s), the organization of the project’s direction, the appropriate division of labor, the positive and proactive address of set-backs, and the efficient and productive transfer of knowledge between the parties (Landaeta, 2008). The concept mirrors the resolution to create libraries to educate and ultimately benefit the country’s entire population in a Socialist world of knowledge (Irfan & Shaikh, 2009).

The greatest imposition to this utopian realization of information repositories is distrust. Opportunism presents a paradox for employees: embody Capitalist ideals of success or trust co-workers and collectively produce a higher standard of work and life. The characteristics of knowledge provide the greatest insight into this quandary. One characteristic, appropriability, refers to the exclusivity of private goods; the other characteristic, rivalry, might be defined as healthy competition, the progress of one individual in a capacity of noninterference with the felicity of others. Through the establishment of public schools, libraries, and mail systems, the fathers of America clearly intended to exclude knowledge from the realm of appropriable goods and also provide an environment of rivalry (Chan et al., 2009). However, knowledge as a commodity decreases in value with availability, making a limited amount of appropriation necessary to every nation’s ability to compete in a rapidly globalized market of knowledge and information. Rivalry and appropriability both depend upon a delicate balance of inclusion and exclusion. This provides a unique insight into the advantage of keeping the balance in organizations of a Capitalist structure.

Technology Component

The application of technology is an integral component of effective knowledge management; it is, in fact, perhaps the single most important component. Generally speaking, there are two types of knowledge that must be “managed”: explicit knowledge and tacit knowledge. Tacit knowledge –that which is less quantifiable- is an area of KM that requires the most human interaction and interpersonal communication. Explicit knowledge –that set of information that is quantifiable and categorizable- is more readily and properly addressed with computer systems and other technological advances. This side of KM –the need for the storage and warehousing of data, along with the means with which to transmit and transfer said data- is at the core of Knowledge Management itself.

It is imperative that an effective manager understand the significance of, and necessity for, adequate KM integration. Further, it must be clear that the wide array of available technologies in the KM field are not KM itself, but are merely tools that      help facilitate effective integration of KM processes and functions. Data Capture and Data Warehousing are among the more significant aspects of KM, as well as among the most expensive. In many cases, the companies with the lowest expenditures on IT are often among those with top-performing IT departments, while companies with the highest expenditures often have under-performing IT departments (Malhotra, 2005).

These figures are not meant to imply that managers should immediately slash their IT budgets and expect their IT departments to suddenly start performing at peak efficiency. Rather, they simply serve as a reminder that most problems in business are not solved by throwing money at them. It is imperative that managers understand not just what KM is on a conceptual level, but why their company is integrating KM solutions. With the vast array of services available, all clamoring for the limited KM dollars, it is the effective manager who best understands the specific needs of his or her company, and tailors KM solutions to fit those needs.

Conclusion

Modern secondary students are expected to select their degree and career before graduation and are essentially- albeit silently- informed that only the studies essential to their future career are worth their time. However, as the facts of knowledge sharing have demonstrated, collaboration can often be positively affected by such discarded knowledge. This KM concept is called spillover (Chan et al., 2009). In a broader sense, Knowledge Management expresses the business end of Philosophy, Sociology, and Psychology. Sadly, like Philosophy itself, the best approach to advances in knowledge transfer is to invest as little in a new theory as possible until it can be fleshed out enough to be put to use and eventually be replaced again. It is the cyclical nature of knowledge and of progress which present challenge and make them both immortal.

References

Chan, K., Oerlemans, L., & Pretorius, M. (2009). Explaining Mixed Results on Science Parks   Performance: Bright and Dark Sides of the Effects of Inter-Organisational Knowledge Transfer Relationships. South African Journal of Industrial Engineering 20 (2): 53-67.   Retrieved from Academic Search Complete database.

French, B., Thomas, L., Baker, P., Burton, C., Pennington, L., & Roddam, H. (2009). What can management theories offer evidence-based practice? A comparative analysis of measurement tools for organizational context. Implementation Science, 28 (4). Retrieved from Academic Search Complete database.

Integrating knowledge management technologies in organizational business processes: getting real-time enterprises to deliver real business performance. (2005). Journal of Knowledge Management, 5(1), Retrieved from http://km.brint.com/RealTime.pdf

Irfan, R., & Shaikh, M. (Feb. 2009). Enhance Knowledge Management Process for Group Decision Making. Proceedings of World Academy of Science, Engineering & Technology (38). Waset.org.

Kourik, J., & Maher, P. (Nov. 2008). Does Practice Reflect Theory? An Exploratory Study of a Successful Knowledge Management System. Proceedings of World Academy of Science, Engineering & Technology (35).

Landaeta, R. (2008). Evaluating Benefits and Challenges of Knowledge Transfer Across Projects. Engineering Management Journal, 20(1), 29-38. Retrieved from Academic Search Complete database.

Velardi, P., Cucchiarelli, A., & D’Antonio, F. (2008). Monitoring the status of a research community through a Knowledge Map. Web Intelligence & Agent Systems, 6(3), 273-294. doi:10.3233/WIA-2008-0141.