Emergence of information technologies has transformed the way business marketing is done and how business enterprises are managing the resources and information. Trend of globalization has induced the fierce competitiveness among business enterprises within domestic and international markets. The major quest for the technologies is not limited to strategic value of an organization but also empower the organization work context by utilizing its resources. Knowledge management has emerged as the latest techno-management trend for improving the work process and creating value for business organization operations. Knowledge management offers various techno-managerial implications to business organization for strategic development. However, there are scarce evidences on business intelligence, strategic management decision support related to business organization adopting these offerings. Major objective of Business Intelligence is to extract the information and find the hidden knowledge from all sources of data. Business Intelligence offers to make decision for enhancement of any organizations goal. The broad overview of research articulates an understanding of government based organizations about the adoption of Knowledge management based Business Intelligence solutions and its challenges. Data mining is playing a key role in Knowledge Management based systems for business organizations and its implication lies in the implementation of data mining algorithm for exploring the huge amount of data, which determines the pure knowledge.
Majority of the government organizational data remains in either unstructured form such as raw form of data (i.e. internal or external document) or with its employees in the form of experience. Knowledge management process deals with extraction of both tacit and explicit knowledge of organization for improving the performance of organization. However Business Intelligence (BI) on the other hand gained its importance with constant enhancement in technologies and tools for extracting the hidden knowledge and patterns. Hence it can be argued that both Business Intelligence and Knowledge Management are complimentary to each other for extracting and managing the knowledge. Thus it’s very imperative for government organizations to have an integration of both Knowledge Management (KM) and Business Intelligence (BI) processes for enhancing the performance of the organization with respect to make organization decision for competitive environment and utilizing the organizational tacit knowledge.
The paper focuses on how BI and KM integration affect the government business organization while discussing its implementation challenges. The paper tries to analyze the correlation between Knowledge Management and Business Intelligence and exploring a road map for data mining based framework for Knowledge Management focusing government based organizations. Current situation of knowledge management strategic decision making and role of knowledge must need to be addressed before proposing any framework for government organization. Paper provides a detailed extensive literature review which aims to describe the basics of Knowledge Management based systems and integrating Business Intelligence with Knowledge Management. Study will draw a distinction between individual and organizational knowledge as well as whether knowledge is playing a key role in strategic development or not?
INTRODUCTION
In the era of knowledge and technical innovation, it has been widely accepted that intangible assets of any business organization will be key to its success. Knowledge is supposed to be most important asset of any business organization, which has the largest influence on competitiveness, strategic development, and growth. Every organization has individual and organizational knowledge either in the form of raw data or information. Raw data or information retains within organization in the form of implicit knowledge and with limited resources. These information or raw data needs to be processed to acquire knowledge through the use of knowledge management & data mining approach. Further knowledge can be made accessible to all through knowledge management process. Several environmental factors around which each business operates are: globalization, fierce competition, changes in organization structure, growth of information technology, and advent of knowledge management process. Thus, emergence of Knowledge Management discipline has changed the direction of business strategic planning. In the context of business organization, knowledge management is used to acquire the knowledge and experiences it for strategic development. Reuse of preciously acquired knowledge can be beneficial for preventing past failure and used as a guideline for fixing recurrent issues. It has been claimed that in business enterprise the knowledge not only embedded to document and repositories but also with enterprise routine, process, and practices.
Thus, knowledge is recognizing itself as one of the most important assets of any organization. Knowledge is acquired through the processing of available data of organization using data mining approaches. Data mining is a tool for processing the data to find out the relationship within the data that can be beneficial for the user. Data mining has the potential to use is as a powerful tool for the business intelligence but yet not fully recognized. With the proliferation of the new technologies data mining has experienced an exponential growth and became an integral part of Knowledge Management system. Data mining algorithms are applied to explore the underlying data of business organization and after processing it determines the effectiveness of knowledge.
The major focus of this paper is role of Knowledge Management and Business Intelligence Processes for government based organization. Government based organizations means functional government agencies, various departments who perform public services. The paper aims to find how government organization managers adopt both KM and BI processes in public sector. Study aims to find out the interrelationship between Knowledge Management and Business Intelligence, and utilize it for strategic development and decision making.
In government based organization, there are extensive amount of data which is used within organization for business policy management, organization decision making, and growth & development of organization. Since environment changes in any organization drastically, thus any change in the data also reflects the change in the system. The change can be related to various categories such as:
- Change in the quantity of data, it means with the growth in any organization amount of data will be increased substantially.
- With the increased amount of data, the correlation between data also changes it means the relationship between application system also changed.
Therefore these organization need to understand the data, process and mine the data to acquire knowledge from the large amount of data and extract intact and practical knowledge from random, vague, incomplete, and huge amount of data. This extracted knowledge can be utilized for decision making business intelligence. Primarily in the Knowledge management process, knowledge discovery process needs to apply data mining algorithms. Varieties of algorithms are available in data mining such as genetic algorithm, decision making, neural network, and fuzzy logic.
This paper is based on government based organizations, in which Knowledge Management process needs to implement for strategic development and decision making, and organizational development for the social and economical growth of the organization as well as improve its competitiveness in the era of globalization. Research aims to monitor, explore the evolution of business intelligence and Knowledge management implementation as a means to improve the work practice of business organization. The fundamental purpose of the paper is to discuss the need of integrating KM and BI for exploiting structured & unstructured raw data, implicit information of the organization and its challenges. This will helpful for creating an integrated knowledge based decision support system framework for government based organization which integrates both Business Intelligence and Knowledge management.
LITERATURE REVIEW
Most researchers and practitioners agreed on the practical implication of knowledge as one of the important assets of any organization. Knowledge Management and Business Intelligence are the two major areas of researchers concern. Knowledge management is a tool for empowering the knowledge within the organization, and useful for decision making. However, Business Intelligence has affected the business world the most for transforming the raw data into knowledge. This can be used for prediction analysis. A dearth research has been performed to explore Knowledge Management, Business Intelligence and its applicability within various application domains.
Authors have analyzed that Business intelligence is the broad categorization of applications of processing large amount of data for any organization to make prediction analysis. Operations such as OLAP (online analytical processing), data warehousing, data reporting, and business rule modeling are used by Business Intelligence. However, Knowledge Management is the process of knowledge acquiring and creation, knowledge sharing and dissemination and knowledge application. Authors have suggested that both Business Intelligence and Knowledge management are influenced by environment of the organization. The success ration of Knowledge Management is directly proportional to employee attitude. Thus, there is a need of common platform for the organization where both employer and employee can share the knowledge.
Author has proposed a scheme for transforming Knowledge Management into Business Intelligence. Author has also briefed certain parameters for implementing them to organization for a common workflow. However, the new or new solution cannot be added directly for the adoption purpose. Tacit knowledge plays a vital role in all the phases of any newly innovative process and implementation of tacit Knowledge Management and can be helpful for handling new problems.
Author has proposed a memory model for linking individual knowledge to knowledge managements. However, the practical implication of this model is very weak. Outcome of knowledge management process over business intelligence and organizational performance with the help of influential variable. Therefore, it can be concluded that any knowledge management based system is a handy tool for achieving completive advantages. Some of the attempts have been done by the authors to integrate knowledge management for real time Business Intelligence and its benefits. Focused on tacit knowledge and explained it as a vital component for organization. However, management of tacit knowledge is a challenging task. Thus, there is the need of a common framework where tacit knowledge can be categorized into various degrees.
Both knowledge management and business intelligences are different from each other in terms of common foundation. Thus the interrelation between knowledge management and business intelligence needs to be explored. Simply an insight can be concluded that business intelligence is used for transforming data to knowledge, whereas Knowledge Management can be used as a tool for knowledge acquisition, knowledge sharing and to create new knowledge.
The advantages and disadvantages of Knowledge Management, Business Intelligence and further proposed KMBI framework for the integration of Knowledge Management and Business Intelligence. This framework consist of three different layers namely data, presentation, and function integration.
With reference to various contexts, articles, paper reviewed, and application of Knowledge management it is analyzed that data mining is widely used toll for Knowledge Management and Business Intelligence both. Since both Knowledge Management and Business Intelligence are correlated and can be integrated for the better performance of an organization. Both are complimentary of each other, thus both can result in more effectiveness for government based business organization.
MANAGING THE KNOWLEDGE
Knowledge is defined as the mix frame of facts, expectation, skills, and combination of relevant information collected through experience, study, and reasoning, for enhancing the ability of decision making and evaluating the right context. However data, information and knowledge are the key terms which are the set member of knowledge management and may used interchangeably. Several arguments are made by the researchers about these terms, and defined as:
Data can refer to unprocessed, unstructured collections of random facts; Information refers to structured and processed data having some sense to the user, whereas Knowledge refers to the most refined and highly useful data for decision making and problem solving.
Various researchers have proposed several classification methods for classifying the knowledge. The classification of knowledge is helpful to the organizations for processing and managing their various available knowledge resources. Most widely accepted classification of knowledge is: Explicit and Tacit knowledge.
Explicit knowledge contains the knowledge, which has been already processed in the form of visual, text, diagrams, tables, manuals, and specific documents. Acquisition of explicit knowledge is easy, since it is in the form of table, manuals, and document; so as easy to manage too. In case of government based business organization explicit knowledge may contain such as business specification, product specification, contracts, and customer data.
However, tacit knowledge refers to most valuable knowledge as it is in the form of experience, skills, and communications. It remains as understanding of people and expressed in the form of language. Tacit knowledge is very beneficial to find best solutions and managing the organization on the basis of previously known knowledge. The only issue with tacit knowledge is, it cannot be articulated as it remains in the form of experience and skills. Since, tacit knowledge is personal, as it is retained in mind in the form of experience, skill and perceptions, hence very tough to manage, share and articulate it. In case of government based organization tacit knowledge may include work such as process, project dealing, problem solving, and expert opinions.
Some authors have proposed that some part of the tacit knowledge can be acquired and converted into explicit knowledge. Several authors have proposed an hierarchy to have an understanding of data, information and knowledge types as shown in figure 1.
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