对知识管理的三种看法

对知识管理的三种看法

Three Views Between Knowledge Management 
 

 

摘要：

 

商务智能的概念(BI)和知识管理(KM)走在一条分离的细线上，他们两人被认为是新的研究领域的业务领域。在文献回顾,没有清晰的定义和关系。研究讨论这两个概念的关系，到目前为止有三个观点来考虑;商务智能作为知识管理的一部分。知识管理和商务智能有相同的目标,为组织提供一个增强决策能力以及获得竞争优势。然而,明确区分这两个是知识管理之间交易的隐性和显性知识以及非结构化数据而商务智能是更注重显性知识及其取向是在技术方面。在文献综述领域，本文旨知识管理作为商务智能的一部分作用,得出这三个观点，获得这两个之间的关系的理解。

 

关键词:知识管理、商业智能、商务智能和知识管理之间的异同点/在商务智能和知识管理间的观点

 

介绍

 

今天的商业世界是一个竞争激烈的竞技场,会议具体和独特的客户需求和管理知识，有效而迅速地找到自己的知识产权已经处于非常重要的地位。为了这些组织而竞争,努力和维持。为了他们的知识优势,商业智能(BI)和知识管理(KM)已注册的生产和管理知识作为他们的主要资本。这两个业务组件之间的关系是重要的区分和确定。

 

摘要：——Abstract:

 

The concept of Business Intellgence (BI) and Knowledge Management (KM) walks on a thin line of separation and both of them are considered a new research area in the field of Business. Upon literature review, there is no clarity on the definitions and relations of these two. Researches have debated on the relations of the two concepts and so far there are three views which have come into consideration; BI part of KM, KM part of BI and an integrated BI and KM. Both KM and BI have the same goals which are to provide the organization with an enhanced decision making capability as well as to gain competitive edge. However, the clear differentiator between these two is that KM deals both tacit and explicit knowledge as well as unstructured data whereas BI is more emphasizing on the explicit knowledge and its orientation is on the technology aspect. This paper aims to look the role of KM as part of BI but upon literature review, it is concluded that all three views are visited to gain comprehension of the relations between these two.

 

Keywords: Knowledge Management, Business Intelligence, Similarities and Differences of BI and KM, relations/views between BI and KM

 

介绍——Introduction

 

The business world of today is an intense arena of competitions, meeting specific and unique customer demands and to manage the knowledge as their own intellectual property efficiently and effectively has become very crucial in order for these organizations to compete, strive and sustain. In order for them to have the intellectual advantage, both Business Intelligence (BI) and Knowledge Management (KM) have been incorporated to produce and manage knowledge as one of their main capital. The relationship between these two business components is significant to be distinguished and established.

 

The relations of BI and KM have been explored by Zarghamifard and Behboudi. They stated that BI and KM are both concept of similarity and these areas of business studies are still at its early stage. The review of the literature shows that there are not enough studies that have been made to clarify the relationship between BI and KM (Zarghamifard et al., 2012). The practitioners of these disciplines are also found to be in a haze when distinguishing KM with BI. Herschel stated that a large portion of professionals in the industry cannot distinguish between these two concepts (Herschel, 2008).

 

Even though BI has proved to be significant in the business world, both of the academics and professionals world have not giving BI its worthwhile focus. Zarghamifard and Behboudi stated that by researching the distinct differences of these concepts, should address this inattentive issue and also should provide some clarity in relationship between these two. In other words, this paper attempts to look the role whether it is BI in KM, KM in BI or both of these concepts can be integrated and supplemented each other to provide one of the integral business intiatives.

 

From the literature, rather than looking BI into KM or KM into BI, most studies pursue the integration of BI and KM. It is a necessity to provide sufficient means for organization to counter the today's business challenges as well as to be very competitive in nature in any business environment. Albescu stated that the progression of Information Technology (IT) and the IT business application for businesses has helped to make this integration to be feasible (Albescu et al., 2008). In order to see the picture of the integration of KM and BI, a review of the literature on the definition of each concept, the comparison in distinguishing its similarities as well as its differences needs to be accomplished and this paper aims to cover this matter. The segregation of this paper as follows; the definition of BI and KM based on the literature available and the explanation of studies related with making the connection of KM and BI.

 

知识管理（KM)的定义——The Definition of Knowledge Managenment (KM)

 

From Behboudi (2009), KM is an area of study where much debacle has been made upon its definition among academicians and it originated from various disciplines. In order for an organization to have its competition edge, many organizations nowadays incorporate KM to manage their intellectual property. KM has been defined in various ways. Among them is the definition of: ""The effective learning processes associated with exploration, exploitation and sharing of human knowledge (tacit and explicit) that use appropriate technology and cultural environment to enhance an organization's intellectual capital and performance". This involve by the integration of multiple perspectives of KM with the perspectives of other multiple discipline (Jashapara, 2004). Another definition can be found from the literature is that KM is the focus of coordinating and integrating individuals' knowledge along with the intention to utilize and manage the organization's knowledge and thus, produce new knowledge (Diakolakis et al, 2004).

 

KM has processes which have been categorized by Bhatt (2001) into five categories: 1) Creation of Knowledge, 2) Validation of Knowledge, 3) Presentation of Knowledge, 4) Distribution of Knowledge and 5) Activities of Knowledge Application. Bhatt interpreted the KM as the definition and management of knowledge in various perspectives rather than just a simple process of capturing, storing and disseminate knowledge. In relation to the core competencies of an organization are deeply rooted into the organization's practices, the pattern of communication between the people, methods and technologies can be change through stages and this can only be achievable if the change to the culture of an organization has been made. It has been imperative for organizations to add value by create, validate and apply new knowledge into their business processes, products and services in tackling today's complex, dynamic and progressive business scenario.

 

商务智能（BI)的定义——The Definition of Business Intelligence (BI)

 

There are several of the definitions of BI in the academics literature even though this field of study is relatively new to the academics and the industry. In relation to this, the definition and concept is still vague at best, and there is no genuine single definition that can define BI and describe its concept in its entirety (Zarghamifard et al., 2012). However, in order to have some clarity of BI, few definitions from the literature is examined in this section. From the literature, the definition of intelligence is comprehension of past followed by the current awareness of today's happenings and the future prediction of tomorrow's dynamic opportunities (Vandergriff, 2009). Marren (2004) took BI as a simple application of collection, analysis and utilization of strategic information in making wise and profitable business decisions.

 

Another definition of BI is that, the combination of collecting data, storing data and KM with analytical tools to produce a presentation of internal information to business's strategist and decision makers (Vinekar et al, 2009). White (2005) defines BI as the business processes analysis and information production in order the assist the practitioners of business comprehend and improve its business processes to the optimal level of operations. However, a recent of definition of BI is as follows: "as the discovery and explanation of hidden, inherent, and decision-relevant contexts in large amounts of business and economic data" (Herschel, 2008). Herschel made this definition by referencing it to Gartner's outlook of BI where it as a collection of every technology that collects and process data to improve decision making in order to gain the competitive edge for the organization through the maximum use of large amounts of data. The technologies mentioned are the modelling of business rule, the profiling of data, data warehousing, data mining and online analytical processing. Herschel also states that the emphasis of technology-oriented aspects of BI is the main works of researchers in the development of the BI framework.#p#分页标题#e#

 

商务智能和知识管理的关系——The Relationship between BI and KM

 

In this section, the relations between BI and KM are examined through the literature. Zarghamifard and Behboudi have provided a table which illustrates the connection of BI and KM through the literature. From the table, it is shown that BI and KM shares similar objectives. Like many other business endeavour, the focus is mainly divided into two; to further enhance the performance of the business and to obtain competitive edge. McCarthy (1999) stated that the objective of KM is to optimize the comprehension of the environment which the business operates in meeting the goals and objectives of the organization. He stated that this is similar to the objective of BI where BI is the made up of Customer, Rival and Market Intelligence. Henceforth, the objective of application of BI is to assist decision-making, to make the business expansion and observe other rivals of the business. This makes up the distinct commonalities between BI and KM but he also stated that there are two basic differences between them: 1) the value of the BI, its product and analysis of opportunity is found within its usability as decision making tool, and 2) KM's value is seen through the organization's capability to recognize, define, capture and recycle knowledge along with its identified best practices that will minimize the organization's time, resources (human, financial etc) and effort.

 

Relations of BI and KM Through Literature Table by Zarghamifard and Behboudi (2009)

 

Wang and Wang (2008)also made some commonalities and differentiation of BI and KM using literatures. KM is summed up as the utilization of knowledge through a collection of practices of creating, developing and applying the knowledge to improve and optimize organization performance. The commonalities found between BI and KM where the latter enhance the organization's utilization of available information and knowledge. They also stated that the differentiation of KM and BI lies in the types of information or knowledge that it utilizes. KM focuses subjective knowledge from the human perspective, unlike BI, where it deals with objective data or information. Hence, many model found in KM focuses on the non-technology orientation and takes consideration of tacit and explicit knowledge in the justification of one's personal view of the truth by a dynamic and complex human process. In other words, BI unable to deal with unstructured and tacit knowledge as KM does.

 

From the technology aspect, information technology (IT) plays an integral role in KM. Numerous documents, information, data, expertise, blogs, wikis, emails, social networks etc., which are represented by KM which constantly overload individuals in organization, has created the challenge to filter out the significant knowledge from the large pool of mixed unwanted data and wanted knowledge or information. This is in correlation of KM in combining the unstructured data with the structured information through the process of creation, collection, manage, usage, recycle, share and leverage. Whereas in BI, data is collected, organized structures and mined to assist businesses in its decision making. Hence, KM has many similarities to BI, in a sense that they both are about filtering out the unwanted information, define all variables that makes up the equation and assist and improve the decision making (Blank, 2010).

 

It is found that some definitions of BI is more focused on explicit knowledge and based on the technology orientation. BI defined as a tool to improve decision making and gain competitive edge through the finding, analysing and comprehension of the hidden wanted data with the usage of all available technologies which captures and analyse data (Herschel, 2008). Herschel also states that some researchers put an emphasis on BI's technology orientation aspect.

 

However, there is a debate where BI produces knowledge. McCarthy (1999), states that the outcome of BI is called an Opportunity Analysis and once it is defined, becomes the intellectual property of an organization, which is actually; knowledge. He stated that both KM and Bi have similarities in their objectives which is to gain competitive edge and also took the consideration of both of them have similar processes. McCarthy also cited some differences between those two from other researchers in relation of the concept of knowledge sharing.

 

There are some studies which points out that KM is a component of BI which can be found through literature reviews. The studies which are investigated by Herschel (2008), stated that KM is an internal component of BI, which perform the various functions required for the business effectively by intelligence sharing in its organization. Therefore, BI techniques facilitate the management of knowledge. There are also studies where it puts on the emphasis of the existence of KM solution is based on the metadata database of BI. The KM solution is supported mainly by the BI database which helps the organization obtain its competitive edge by capturing, analyses and share the intellectual property of the organization. The intellectual property which consists of either data, information or knowledge or all of them is seen to having the relation of technical and business aspects.

 

There are also studies recommended that BI and KM are to be integrated because of the commonalities that both of these concept shared; the incorporated learning practice in an organization as well as the making decision in an effective manner. There are some frameworks which has been developed to facilitate the integration between KM and BI but there is no consensus has been reach to fully agree whether each of the frameworks are in relation with each other or to be subset of other developed BM/KI frameworks. The frameworks which pointed out by Herschel (2008) are; 1) Conceptual Models of Malhotra's; a proposed general integration models between KM and BI which tackles on the matter of handling routine information processing and non-routine unstructured of data comprehension. The second model which is called the White's flowchart model facilitates the decision making through the usage BI in the KM context. Herschel also stated that researchers are in a debate whether the BI and KM are itself is a technology or the technology is a separated element which plays a role in BI and KM.

 

However, different views between BI and KM have been found through the literature. There are several research which can be found in the literature points out that of an excellent KM to be developed, BI is an important element where the researches sees the BI as an integral part of KM. Herschel (2008) iterated that the activities of BI should lead to the enhancing of knowledge. The effectiveness of the knowledge enhancement and promotion, the enhancement or improvement of the mental model(s), decision maker's comprehension and the effectiveness of decision making enhancement which resulted in excellent business performance are the scales that act as the measurement of the effectiveness of BI. In this view, BI is seen as an important element of KM.

 

The role of BI and KM has been expressively covered and examined by researchers. Another researcher, White (2005) to into consideration that in order to assist the comprehension of business practitioners and to enhance and maximize business processes, BI acts as applications that facilitates business process analysing and information production. The data stored in a data warehouse is processed to produce the information. White argued that BI acts as a central element in KM. However, he stressed out that in order to achieve this endeavour, it must operate in parallel with other applications such as business process management, business planning software, portals, collaborative software and content management systems to able to assist in more data in timely manner.

 

The summary of different view between KM and BI (Zarghamifard et al.; 2009)

 

总结——Conclusion

 

The area of BI and KM can considered as new field of research which it is still in its preliminary stages. The definitions of each concepts and their relations are still distinctively defined which resulted in confusion of those two because of the commonalities that both of them shared shared. It has its differences but it really is on a thin line of separation. Reviews of literature have been conducted and the brief study analysis is being performed on the KM and BI study area which emphasizes on the relations between those two. It is found through the literature as well that there have not been any agreements in distinguishing the relation between these concepts nor the manner of how it should be. So far, there are three views between BI and KM that has been established. First, KM can better with BI by being an important part and element of KM. Some believe that BI and KM should be integrated but their commonalities and differentiation should be taken into consideration. Zarghamifard and Behboudi (2009) debated that in terms of business intelligence and decision making, knowledge is a very important part of these two. In managing the intellectual property, they viewed BM and KI as important to be integrated together for it to be the important and critical part of knowledge ownership management. The third view, the KM plays an important role for BI where it assists BI to become more effective in a business.

 

So far, there is no distinctive model which properly defines BI and KM and distinguishes its relationship among them. Only few studies shown that BI is an important part of KM, vice versa and the integration among the two. Future study endeavours should explore more of the subject matter in order for these two concepts to fully comprehensive and distinct relations between them can be established.