Improving Data-Driven Decision Making through Human-Centered Knowledge Sharing

This research focuses on human-centered knowledge sharing within data-driven decision-making processes enabled by advanced analytics. The paper describes an exploratory study of an innovative approach to ongoing improvement of complex data-driven decision making processes found in a large retail distribution company by considering a complex interplay of business intelligence (BI) /business analytics, business processes and human-centered knowledge management. Using the relevant IS frameworks as analytical lens the paper investigates the evolving relationship between decision-making and decision-support technology, as well as the relationship among information, decisions and the corresponding business processes in this context. The most important finding of this research is in identification of human-centered knowledge sharing as the key success factor for ongoing improvement of BI-enabled decision making in the case organisation, rather than complex technology. This in turn indicates the significance of various organisational factors, including carefully designed and implemented human-resource (HR) strategies to encourage knowledge sharing among decision makers using advanced analytics systems. Finally, this paper also confirms the latest industry reports that more mature analytical organisations are looking beyond technology and focusing on business-related issues as the next source of competitive advantage, as it was the case with our chosen organisation