Pub Date : 2021-03-22DOI: 10.1515/9783110671124-204
A. Ndiaye
Tomorrow’s supply chain is expected to provide many improved benefits for all stakeholders, and across much more complex and interconnected networks than the current supply chain. Today, the practice of supply chain science is striving for excellence: innovative and integrated solutions are based on new ideas, new perspectives and new collaborations, thus enhancing the power offered by data science. This opens up tremendous opportunities to design new strategies, tactics and operations to achieve greater anticipation, a better final customer experience and an overall enhanced supply chain. As supply chains generally account for between 60% and 90% of all company costs (excluding financial services), any drive toward excellence will undoubtedly be equally impactful on a company’s performance as well as on its final consumer satisfaction. This book, written by Nicolas Vandeput, is a carefully developed work emphasizing how andwhere data science can effectively lift the supply chain process higher up the excellence ladder. This is a gap-bridging book from both the research and the practitioner’s perspective, it is a great source of information and value. Firmly grounded in scientific research principles, this book deploys a comprehensive set of approaches particularly useful in tackling the critical challenges that practitioners and researchers face in today and tomorrow’s (supply chain) business environment.
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Pub Date : 1900-01-01DOI: 10.1515/9783110671124-202
{"title":"About the Author","authors":"","doi":"10.1515/9783110671124-202","DOIUrl":"https://doi.org/10.1515/9783110671124-202","url":null,"abstract":"","PeriodicalId":288751,"journal":{"name":"Data Science for Supply Chain Forecasting","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125017339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1515/9783110671124-006
{"title":"6 Model Optimization","authors":"","doi":"10.1515/9783110671124-006","DOIUrl":"https://doi.org/10.1515/9783110671124-006","url":null,"abstract":"","PeriodicalId":288751,"journal":{"name":"Data Science for Supply Chain Forecasting","volume":"255 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114340754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1515/9783110671124-020
{"title":"20 Demand Drivers and Leading Indicators","authors":"","doi":"10.1515/9783110671124-020","DOIUrl":"https://doi.org/10.1515/9783110671124-020","url":null,"abstract":"","PeriodicalId":288751,"journal":{"name":"Data Science for Supply Chain Forecasting","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115890965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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