{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T23:49:01Z","timestamp":1773791341949,"version":"3.50.1"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T00:00:00Z","timestamp":1718064000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T00:00:00Z","timestamp":1718064000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001230","name":"Macquarie University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100001230","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SN COMPUT. SCI."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This 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.<\/jats:p>","DOI":"10.1007\/s42979-024-02953-8","type":"journal-article","created":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T07:01:51Z","timestamp":1718089311000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Challenges and Issues in Implementing &amp; Operationalising Big Data Analytics Capabilities in a major Australian Railway Organisation: A Case Study"],"prefix":"10.1007","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8206-3712","authenticated-orcid":false,"given":"Viken","family":"Kortian","sequence":"first","affiliation":[]},{"given":"Souvik","family":"Pal","sequence":"additional","affiliation":[]},{"given":"Nejhdeh","family":"Ghevondian","sequence":"additional","affiliation":[]},{"given":"Norma","family":"Harrison","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,11]]},"reference":[{"issue":"1","key":"2953_CR1","first-page":"23","volume":"37","author":"G Phillips-Wren","year":"2015","unstructured":"Phillips-Wren G, Iyer LS, Kulkarni U, Ariyachandra T. Business analytics in the context of big data: a roadmap for research. Commun Assoc Inf Syst. 2015;37(1):23.","journal-title":"Commun Assoc Inf Syst"},{"issue":"11\u201312","key":"2953_CR2","doi-asserted-by":"publisher","first-page":"985","DOI":"10.1080\/09537287.2017.1336800","volume":"28","author":"R Ramanathan","year":"2017","unstructured":"Ramanathan R, Philpott E, Duan Y, Cao G. Adoption of business analytics and impact on performance: a qualitative study in retail. Prod Plan Control. 2017;28(11\u201312):985\u201398.","journal-title":"Prod Plan Control"},{"issue":"3","key":"2953_CR3","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1111\/isj.12101","volume":"27","author":"PB Seddon","year":"2017","unstructured":"Seddon PB, Constantinidis D, Tamm T, Dod H. How does business analytics contribute to business value? Inf Syst J. 2017;27(3):237\u201369.","journal-title":"Inf Syst J"},{"issue":"5","key":"2953_CR4","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1016\/j.im.2018.01.005","volume":"55","author":"S Krishnamoorthi","year":"2018","unstructured":"Krishnamoorthi S, Mathew SK. Business analytics and business value: A comparative case study. Inform Manag. 2018;55(5):643\u201366.","journal-title":"Inform Manag"},{"issue":"10","key":"2953_CR5","doi-asserted-by":"publisher","first-page":"1868","DOI":"10.1111\/poms.12838","volume":"27","author":"TM Choi","year":"2018","unstructured":"Choi TM, Wallace SW, Wang Y. Big data analytics in operations management. Prod Oper Manag. 2018;27(10):1868\u201383.","journal-title":"Prod Oper Manag"},{"key":"2953_CR6","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.ijpe.2016.03.014","volume":"176","author":"G Wang","year":"2016","unstructured":"Wang G, Gunasekaran A, Ngai EW, Papadopoulos T. Big data analytics in logistics and supply chain management: Certain investigations for research and applications. Int J Prod Econ. 2016;176:98\u2013110.","journal-title":"Int J Prod Econ"},{"issue":"1","key":"2953_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4102\/jtscm.v9i1.165","volume":"9","author":"HW Ittmann","year":"2015","unstructured":"Ittmann HW. The impact of big data and business analytics on supply chain management. J Trans Supply Chain Manag. 2015;9(1):1\u20139.","journal-title":"J Trans Supply Chain Manag"},{"issue":"1\u20132","key":"2953_CR8","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1080\/00207543.2017.1395488","volume":"56","author":"A Gunasekaran","year":"2018","unstructured":"Gunasekaran A, Yusuf YY, Adeleye EO, Papadopoulos T. Agile manufacturing practices: the role of big data and business analytics with multiple case studies. Int J Prod Res. 2018;56(1\u20132):385\u201397.","journal-title":"Int J Prod Res"},{"key":"2953_CR9","unstructured":"van der Meulen, R. and McCall, T. 2018. EMEA Lags Other Regions in Data and Analytics Maturity. Retrieved on Nov 2021 on https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2018-02-05-gartner-survey-shows-organizations-are-slow-to-advance-in-data-and-analytics ,"},{"key":"2953_CR10","unstructured":"Wirth, R. and Hipp, J., 2000, April. CRISP-DM: Towards a standard process model for data mining. In\u00a0Proceedings of the 4th international conference on the practical applications of knowledge discovery and data mining. London, UK: Springer-Verlag."},{"key":"2953_CR11","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1016\/j.procir.2019.02.106","volume":"79","author":"S Huber","year":"2019","unstructured":"Huber S, Wiemer H, Schneider D, Ihlenfeldt S. DMME: Data mining methodology for engineering applications\u2013a holistic extension to the CRISP-DM model. Procedia CIRP. 2019;79:403\u20138.","journal-title":"Procedia CIRP"},{"key":"2953_CR12","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.ijpe.2016.08.018","volume":"182","author":"S Akter","year":"2016","unstructured":"Akter S, Wamba SF, Gunasekaran A, Dubey R, Childe SJ. How to improve firm performance using big data analytics capability and business strategy alignment? Int J Prod Econ. 2016;182:113\u201331.","journal-title":"Int J Prod Econ"},{"issue":"8","key":"2953_CR13","doi-asserted-by":"publisher","first-page":"1049","DOI":"10.1016\/j.im.2016.07.004","volume":"53","author":"M Gupta","year":"2016","unstructured":"Gupta M, George JF. Toward the development of a big data analytics capability. Inform Manag. 2016;53(8):1049\u201364.","journal-title":"Inform Manag"},{"key":"2953_CR14","doi-asserted-by":"publisher","DOI":"10.1108\/IJOPM-02-2015-0078","author":"F Kache","year":"2017","unstructured":"Kache F, Seuring S. Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. Int J Oper Prod Manag. 2017. https:\/\/doi.org\/10.1108\/IJOPM-02-2015-0078.","journal-title":"Int J Oper Prod Manag"},{"key":"2953_CR15","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.datak.2018.04.006","volume":"117","author":"S Nalchigar","year":"2018","unstructured":"Nalchigar S, Yu E. Business-driven data analytics: a conceptual modeling framework. Data Knowl Eng. 2018;117:359\u201372.","journal-title":"Data Knowl Eng"},{"issue":"3","key":"2953_CR16","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1016\/j.ejor.2018.11.074","volume":"281","author":"Y Tim","year":"2020","unstructured":"Tim Y, Hallikainen P, Pan SL, Tamm T. Actualizing business analytics for organizational transformation: a case study of rovio entertainment. Eur J Oper Res. 2020;281(3):642\u201355.","journal-title":"Eur J Oper Res"},{"issue":"3","key":"2953_CR17","doi-asserted-by":"publisher","first-page":"142","DOI":"10.3390\/info11030142","volume":"11","author":"K Kr\u00f3l","year":"2020","unstructured":"Kr\u00f3l K, Zdonek D. Analytics maturity models: an overview. Information. 2020;11(3):142.","journal-title":"Information"},{"key":"2953_CR18","unstructured":"Microsoft Ignite, 2021. What is the Team Data Science Process? Retrieved on Nov 2021 on https:\/\/docs.microsoft.com\/en-au\/azure\/machine-learning\/team-data-science-process\/overview"},{"key":"2953_CR19","doi-asserted-by":"crossref","unstructured":"Lavin, A., Gilligan-Lee, C.M., Visnjic, A., Ganju, S., Newman, D., Ganguly, S., Lange, D., Baydin, A.G., Sharma, A., Gibson, A. and Gal, Y., 2021. Technology readiness levels for machine learning systems.\u00a0arXiv preprint arXiv:2101.03989","DOI":"10.21203\/rs.3.rs-133138\/v1"},{"key":"2953_CR20","unstructured":"https:\/\/github.com\/microsoft\/MLOps MLOPS Framework"},{"key":"2953_CR21","unstructured":"TDWI Website https:\/\/tdwi.org\/pages\/assessments\/adv-all-tdwi-analytics-maturity-model-assessment.aspx?m=1 Retrieved on March 2021."},{"key":"2953_CR22","unstructured":"TDWI Website (tdwi.org). Building a Data-Literate Organization, Research paper, March 2021. Fern Harper."},{"key":"2953_CR23","unstructured":"https:\/\/www.tcs.com\/content\/dam\/tcs\/pdf\/Deakin-TCS-Report.pdf Retrieved October 2022"},{"key":"2953_CR24","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1016\/j.jbusres.2016.08.011","volume":"70","author":"N C\u00f4rte-Real","year":"2017","unstructured":"C\u00f4rte-Real N, Oliveira T, Ruivo P. Assessing business value of Big Data Analytics in European firms. J Bus Res. 2017;70:379\u201390.","journal-title":"J Bus Res"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-024-02953-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-024-02953-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-024-02953-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,11]],"date-time":"2024-06-11T07:27:20Z","timestamp":1718090840000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-024-02953-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,11]]},"references-count":24,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["2953"],"URL":"https:\/\/doi.org\/10.1007\/s42979-024-02953-8","relation":{},"ISSN":["2661-8907"],"issn-type":[{"value":"2661-8907","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6,11]]},"assertion":[{"value":"20 May 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 May 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 June 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"639"}}