Word Cloud, Pareto and Fishbone: Towards less computation-intensive data-driven project management

Abstract

This study aims to explore how to enable more efficient strategizing in a less computation-intensive yet data-driven manner. The methodology would serve as a preliminary means to identify key factors prior to further data mining. With data set for Quality Education from 2013-2018 obtained from existing literature and meta-analysis literature on disruptive technologies, we use three techniques to discover key important factors leading to the evolution/development of disruptive technologies from 2013-2018. Text processing is used to generate word clouds. Subsequently, word cloud data is fed to project management tools (Pareto chart and Ishikawa diagram) to discover in greater detail, associative key influencing factors. Significance lies in the less computation-intensive yet data-driven methodology, which falls under hybrid semi-automated mining; acknowledging the contribution of human heuristics. We hope this hybrid semi-automated method would provide a preliminary means to gauge what would be interesting for further mining.