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Insight from data analytics with an automotive aftermarket SME
Author(s) -
Smith Wayne S.,
Coleman Shirley,
Bacardit Jaume,
Coxon Syd
Publication year - 2019
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2529
Subject(s) - automotive industry , big data , data science , data analysis , analytics , complement (music) , the internet , business analytics , computer science , business , engineering , data mining , marketing , business model , world wide web , electronic business , biochemistry , chemistry , complementation , gene , phenotype , aerospace engineering
There is enormous general interest in the automotive sector, and there are many sets of informative data openly available to the public. Companies involved in the automotive aftermarket sector have access to further masses of data, and this can be analysed to provide valuable insights to complement those obtainable from the internet and popular press, discovering hidden knowledge and financial benefit within the data by using statistical analysis, big data analytics, and data science. This article gives examples of insight derived from data giving great value to stakeholders in the sector. The examples are followed by a discussion of the issues involved in applying data science and ensuring that solutions are implemented and are sustainable within the business partner companies.