A data science and open source software approach to analytics for strategic sourcing |
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| Institution: | 1. Data Science, 84.51°, United States;2. Logistikum, University of Applied Sciences Upper Austria, Austria;3. Mississippi State University, United States;4. California State University Long Beach, United States;1. Department of Computer and Information Science, Higher Colleges of Technology, Dubai, United Arab Emirates;2. Faculty of Business and Information Technology, University of Ontario Institute of Technology, Oshawa, Ontario, Canada;3. Department of International Studies, Glendon College, York University, Toronto, ON, M4N 3M6, Canada;4. Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, B3H4R2, Canada;5. Faculty of Management, Dalhousie University, Halifax, Nova Scotia, B3H4R2, Canada;1. Center for the Advancement of the Humanities and Social Sciences, National Taiwan University, 9F., No. 97, Sec. 1, Roosevelt Rd., Taipei 10093, Taiwan (R.O.C.);2. Department of Library and Information Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan (R.O.C.);3. Center for Research in Econometric Theory and Applications, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan (R.O.C.);1. College of Business, California State University, Chico, 400 West 1st Street, Chico, CA 95929, United States;2. Leeds School of Business, University of Colorado, Boulder, 995 Regent Dr., Boulder, CO 80309-0419, United States;3. Business School, University of Colorado, Denver, 1475 Lawrence St, Denver, CO 80202, United States;4. Department of Information Technologies, HEC Montréal, 3000 Côte-Sainte-Catherine Road, Montréal, QC, H3T 2A7, Canada;5. SCH Media Labs, Soonchunhyang University, 22, Soonchunhyang-ro, Eumnae-ri, Sinchang-myeon, Asan-si, Chungcheongnam-do, Republic of Korea;1. UniSA STEM, University of South Australia, Australia;2. Experience Matters, Australia |
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| Abstract: | Data science has emerged as a significant capability upon which firms compete. Although many data scientists and the high-performing companies that employ them seem to have developed robust methods to employ data sciences practices to achieve competitive advantages, there have been few attempts at defining and explaining how and why data science helps firms to achieve desired outcomes. In this paper, we describe how data science, which combines computer programming, domain knowledge, and analytic skillsets to scientifically extract insights from data, can be used to help meet the growing demand of analytic needs across an organization’s value chain. This is done through the illustration of an applied data science initiative to a strategic sourcing problem via the use of open-source technology. In doing so, we contribute to the growing data science literature by demonstrating the application of unique data science capabilities. Moreover, the paper provides a tutorial on how to use a specific R package along with an actual case in which that package use used. |
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| Keywords: | Data science Strategic sourcing Purchasing portfolio Supply chain management Open source R programming Decision support |
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