Exploiting Business Intelligence for Strategic Knowledge Management: A German Healthcare Insurance Industry Case Study

Exploiting Business Intelligence for Strategic Knowledge Management: A German Healthcare Insurance Industry Case Study

Martin George Wynn (University of Gloucestershire, Cheltenham, UK) and Daniel Brinkmann (University of Gloucestershire, Cheltenham, UK)
Copyright: © 2016 |Pages: 14
DOI: 10.4018/IJBIR.2016010102
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Abstract

In the German healthcare industry, Business Intelligence systems play a crucial role. For one major health insurance company (discussed here as an alias - AK Healthcare), the deployment of Business Intelligence applications has supported sustained growth in turnover and market share in the past five years. In this article, these tools are classified within an appropriate conceptual framework which encompasses the organisation's information infrastructure and associated processes. Different components of the framework are identified and examples are given - systems infrastructure, data provision/access control, the BI tools and technologies themselves, report generation, and information users. The use and integration of Business Intelligence tools in the strategy development process is then analyzed. Finally, the key functions and features of these tools for strategic knowledge management are discussed. Research findings encompass system access, report characteristics, and end-users profiles and capabilities.
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Theoretical Framework

There are various definitions of Business Intelligence (BI) in existing literature. BI has become an important IT tool or mechanism that can help organizations to manage, develop, and communicate intangible assets such as information and knowledge. It is often considered essential for organizations operating in the current knowledge-based economy (Alnoukari, 2009). BI is discussed by Gansor, Totok, & Stock (2010) as an analytical process that transfers internal and external data into appropriate knowledge to support decision-making. The term BI has also been defined as the collection, saving, analysis, and provision of data to support the decision-making processes of a company (Seufert & Oehler, 2009).

This article assumes that relevant strategic data will be stored in a structured way in a data warehouse – a “subject-oriented, integrated and time-variant collection of data in support of management’s decisions” (Inmon, 2002, p. 31). This is most likely to be the case in organisations that do not have one large integrated software package – an enterprise resource planning system - fulfilling their systems needs, where there may be less of a business case for a data warehouse. It is more prevalent in organisations – like AKH – where a best of breed systems strategy has been pursued, resulting in a range of different applications and data sources. In such situations, the data warehouse (DWH) is often a key component of overall systems strategy; and it is also the base infrastructural element of a BI system, allowing storage and structuring of data from various systems and external sources, supporting the provision of key management information (Figure 1).

Figure 1.

Typical systems architecture underpinning BI tools deployment

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