Knowledge management as an element of business intelligence

Some researchers see knowledge management as an element of business intelligence. They argue that KM is internal-facing BI, sharing the intelligence amongst employees about how to effectively perform the variety of functions required to make the organization go. Hence, knowledge is managed using many BI techniques. Others contend that a ”true” enterprise-wide knowledge management solution cannot exist without a BI-based metadata repository. They believe that a metadata repository is the backbone of a KM solution. That is, the BI metadata repository implements a technical solution that gathers, retains, analyzes and disseminates corporate ”knowledge” to generate a competitive advantage in the market. This intellectual capital (data, information and knowledge) is seen as both technical and business-related.

Other researchers note that many people forget that the concepts of knowledge management and business intelligence are both rooted in pre-software business management theories and practices. They claim that technology has served to cloud the definitions. Defining the role of technology in knowledge management and business intelligence – rather than defining technology as knowledge management and business intelligence – is seen as a way to clarify their distinction.

The attraction of business intelligence is that it offers organizations quick and powerful tools to store, retrieve, model and analyze large amounts of information about their operations and, in some cases, information from external sources. Vendors of these applications have helped other companies and organizations increase the value of the information that resides in their databases. Using the analysis functions of business intelligence, firms can look at many aspects of their business operation and identify factors that are affecting its performance.

However, the Achilles’ heel of business intelligence software is its inability to integrate non-quantitative data into its data warehouses or relational databases, its modeling and analysis applications, and its reporting functions. To examine and analyze an entire business and all of its processes, one cannot rely solely on numeric data. Indeed, estimates from various sources suggest that up to 80% of business information is not quantitative or structured in a way that can be captured in a relational database. There is too much verbal or documented information that is unstructured or semi-structured information and, hence, not well suited to the highly structured data requirements of a database application.

BI systems are becoming increasingly more critical to the daily operation of organizations. Data warehousing can be used to empower knowledge workers with information that allows them to make decisions based on a solid foundation of fact. However, oftentimes only a fraction of the needed information exists on computers; the vast majority of a firm’s intellectual assets exist as knowledge in the minds of its employees. Researchers now argue that what is needed is a new generation of knowledge-enabled systems that provide the infrastructure needed to capture, cleanse, store, organize, leverage and disseminate not only data and information, but also information and knowledge that is less easy to codify. That is, systems should be designed that provide a unified communications platform for sharing tacit and explicit knowledge derived from BI and KM systems. In these systems, data, documents, stories, videos, knowledge experts and decision models can be identified, mapped and targeted to address new situations.

BI activities should provide knowledge improvement. This means that the effectiveness of business intelligence should measured based on how well it promotes and enhances knowledge, how well it improves the mental model(s) and understanding of the decision maker(s), and how well it improves decision making and, hence, firm performance.  Business intelligence should therefore be viewed as an integral part of KM. This in no way diminishes the importance of BI activities. Rather, it simply places business intelligence into a larger organizational context – BI is one of the many knowledge-based activities creating intellectual capital that can be exploited by a firm.


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