Start Date

11-12-2016 12:00 AM

Description

This applied research focuses on knowledge-intensive business processes (KIBPs) supported by Business Intelligence and Analytics (BI&A), here termed BI&A-supported KIBPs. Examples of these processes include customer-support services, risk and assurance processes, and design of marketing campaigns. This research aims to investigate an industry-informed research challenge of ongoing improvement of BI&A-supported KIBPs, in particular the role of BI&A in process improvement. This paper presents a qualitative research case study, conducted in a large retail distribution company, using a theoretical lens of Work Systems Theory (WST). We describe an innovative approach to ongoing improvement of BI&A-supported KIBP and confirm an important role played by BI&A in this context. Informed by these research insights, we then propose a new theoretical model of ongoing improvement of BI&A-supported KIBP and explain its significance using relevant literature. The model is also highly relevant for industry practitioners looking for new sources of competitive differentiation, beyond BI&A technology.

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Dec 11th, 12:00 AM

Improvement of Knowledge-Intensive Business Processes Through Analytics and Knowledge Sharing

This applied research focuses on knowledge-intensive business processes (KIBPs) supported by Business Intelligence and Analytics (BI&A), here termed BI&A-supported KIBPs. Examples of these processes include customer-support services, risk and assurance processes, and design of marketing campaigns. This research aims to investigate an industry-informed research challenge of ongoing improvement of BI&A-supported KIBPs, in particular the role of BI&A in process improvement. This paper presents a qualitative research case study, conducted in a large retail distribution company, using a theoretical lens of Work Systems Theory (WST). We describe an innovative approach to ongoing improvement of BI&A-supported KIBP and confirm an important role played by BI&A in this context. Informed by these research insights, we then propose a new theoretical model of ongoing improvement of BI&A-supported KIBP and explain its significance using relevant literature. The model is also highly relevant for industry practitioners looking for new sources of competitive differentiation, beyond BI&A technology.