Challenges and Issues in Implementing & Operationalising Big Data Analytics Capabilities in a major Australian Railway Organisation: A Case Study

Abstract

AbstractThis study examines the implementation of a Big Data Analytics (BDA) project within a major Australian freight and railway organisation. It also identifies the issues and challenges with data collection, data cleaning, data modelling, and data science software, and implements these models to deliver tangible business results. In addition, the project highlights the potential gains that a data analytics project, integrated with a data-driven culture, can provide through significant operational efficiencies and financial gains. Prior to 2019, the company had little exposure to Predictive Analytics. This study shows how the development of data science capability enables the creation of advanced predictive models, particularly in this case study, for the prediction of train wheel wear, and therefore a significant reduction in maintenance expenses Furthermore, a Data Analytics Maturity Assessment was conducted to determine the requirements to become a data-driven organisation. The outcome of the assessment was compared to recent global studies, and it was found that the organisation examined was significantly behind its counterparts in the areas of resources and analytic capabilities, and therefore required investment in these areas. Further studies to examine the degree of Data Analytics maturity within the Australian context are suggested. Organisations striving to become more data-driven need to plan and allocate resources for capability development in infrastructure, data management, employee quantitative skills, and governance.