A Comparative Study Of Two Knowledge Discovery Tools: Barchart Versus Scatterplot
Free (open access)
M Handzic, B Lam, A Aurum & G R Oliver
This paper reports the results of an empirical examination of the effectiveness of two knowledge discovery tools (barchart and scatterplot) in the context of a sales forecasting task. The main results of the study indicate that both tools were reasonably suitable for well conveying associations among task variables and offering improvements in prediction accuracy when compared to a naive predictor. There is however, still much ground for improvement towards a theoretical optimal case. In addition, findings show that a scatterplot was significantly more beneficial than a barchart in enhancing forecasters’ knowledge and performance of the task. This superiority can be potentially explained in terms of the favorable aspects of Cartesian graphs and the greater concentration required for using the tool. 1 Introduction Experts predict that the turbulence brought about by mega trends of globalisation, digitalisation and transformation will continue to increase over the next few decades, the complexity of business will be even higher, and uncertainty worse than ever [32, 37]. Ongoing economic, technical and social transformations place enormous pressure on organisations survive the new-age economy [14, 36]. Knowledge management is an emergent response to the need to accelerate both the creation and application of knowledge for successful competitive advantage. Various disciplines are contributing to academic literature on knowledge management [13, 15]. The common task of all is to determine best ways to cultivate, nurture and exploit knowledge at both individual and collective levels.