Knowledge Management (KM) is a strategic tool for building Intellectual Capital (IC) information within an organization. Management using this tool as the most efficient mean for making people as most valuable assets. Efficiency within organisation is not possible unless organization practice BI on the right track. BI is closely associated with success of results generated by KM.An organization may have bulk of information which may arise problems when it comes to part of implementation. BI technologies play crucial rule for better management of such huge information. BI formulates smooth part for practitioners of KM to attain a competitive edge over its competitors. This competitive edge follows competitive personnel with better performance, work efficiency and better customer relationship management.The competitive nature of any organization is boosted up using work practices that involve a high degree of association. However, boosting skills within the organisations is not an easy task. It takes a while before skills cross a certain required threshold where tangible benefit can be obtained.
That is why the knowledge transfer is very important within the organisation especially to explicate the tacit knowledge so it can be learned by any entities in the future. The biggest problem for KM is in a part of people tacit knowledge. Conversely, tacit knowledge can disappear in case of mergers, reorganization’s, and downsizing. The contextual analytics which supported by a cognitive system is an advanced analytics system used to collect tacit knowledge. The contextual analytics techniques like relevancy ranking are used besides those like entity relation modeling, entity extraction, tagging of parts of speech, and so on. Thus, data is analyzed within a confined set of implicit and explicit knowledge. If implicit knowledge and various perspectives are included in this analysis, these contextual analytics may becomes cognitive analytics. This paper will explore the cognitive approach for analysing KM in BI environment.
Business Intelligence
Business Intelligence (BI) comprises important business process which collects and analyzes information for business decisions and actions. Particularly, it emphasizes upon use of information tools to enhance business performance. BI consist of technologies, processes and implications which allows acquiring, storing, retrieving and analyzing data for better decision making. On-Line Analytical Processing (OLAP) is a tool of BI which allows searching and testing relevant data along with computation and identification of relationships. Data Mining identifies trends, patterns and relationship among huge sum of data stored in Data Warehouse. It makes use of statistical and mathematical techniques along with technology. Decision Support System (DSS) is the association of man and machine for provision of authentic and useful information in order to support management in decision making.OLAP is one of the important components of BI used in process. OLAP has several other traditional forms. Some of them are classification, sequential patterns, regression and link analysis.Thus, BI process is a relevant approach to analysis knowledge data that required a proper process to capture and analysis tacit knowledge.
Knowledge Management
Knowledge Management (KM) is a technique of searching, acquiring, organizing and communicating
information and knowledge in organization. The knowledge can be implicit or explicit is relates to the
understanding of leadership, group efforts, individual experience and psyche of employees. Acquisition of relevant information is the process of identifying and capturing material closely associated with current goal. Retrieval of information is the second phase of KM process where organization takes out specific information from multiple sources. The captured knowledge of the organization will be process by using BI, and later by using cognitive approach the tacit knowledge will be used as part of analytic solution.
Cognitive Approach for Capturing Knowledge
Cognitive approach is able to record, analyze, remember, learn, and resolve the problem from the information that are available from the human knowledge and experiences. The current cognitive system also can perform the transferring of knowledge andused to be the best practices in data analysis industries. In these use cases, a cognitive system is designed to build a dialog between human and machine so that the best practices are learned by the system as opposed to traditional method that being programmed as a set of rules. As long as knowledge is probabilistic, it always be influenced by human and social factors, and required a cognitive way to be managed. Cognitive approach is suitable for the “more than one” hypotheses to be analyzed as it is a kind of decision support that allows people to explain new opportunities, which has an impact in a positive manner. Therefore, this paper will explain the used of cognitive approach for managing knowledge in BI environment.
METHODOLOGY
Qualitative research technique has been adopted for this paper. These qualitative techniques include the careful analysis of literature review of previous researches and proposed models of KM and BI. Theoretical framework of the research has also been driven from multiple models of previous researches. Knowledge management and business intelligence has the potential to strengthen the effectiveness and competitiveness of organizations. Thus there is a need of having a Business Intelligence integrated framework of BI and KM for achieving this goal is shownin Figure 1.
Figure 1. Theoretical framework of KM & BI integration to achieve competitiveness
In first phase of methodology is collecting data, where the managers were asked few questions relating to achievement of competitiveness through KM and use of BI in it. Some of the questions are as follow:
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