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Abstract
Every supply chain company wants detailed information on the costs of delivering its products to customers, yet only a handful know how much it costs to serve their customers. The difference between 10 years ago and today is that industry leaders now not only recognise that a company’s profit is often dependent on the costs of serving its customers, but also have available tools and technology to tab into their data for enhanced operational visibility to make better decisions. This paper describes how the supply chain management and logistics industry can calculate the profitability of products, customers and routes using cost to serve technology. The authors describe how advanced analytics and artificial intelligence (AI) break down costs at the customer level, helping organisations set an actionable business plan to increase profits and make customers happy.
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Author's Biography
Daphne De Poot is a senior data scientist at ORTEC where she leads the Data Driven Logistics consulting team in the United States. As an expert in data-driven logistics, she develops and implements analytics solutions to improve supply chain processes and operational efficiency. In her role with ORTEC, Daphne applies analytics to solve business challenges such as providing insights into supply chain performances to enhance visibility and identify improvements, understanding the cost to serve customers, determining accurate fleet sizes and finding the right trade-off between customer service and efficiency. Daphne is a frequent speaker at industry conferences and guest lecturer in academic courses across both the US and The Netherlands. She is a lead instructor for the Georgia Tech Supply Chain and Logistics Institute’s courses within the Supply Chain Analytics Professional Certificate programme. Daphne has an MBA in big data and business analytics from the University of Amsterdam and a MSc in operations research from the Erasmus University Rotterdam.
Noud Gademann is a principal supply chain consultant at ORTEC where he is a member of the Supply Chain Management practice. While he originally specialised in operations research algorithms, he has become an expert in supply chain business modelling and optimisation, leading many supply chain improvement projects in various industries. At ORTEC, Noud is responsible for developing and maintaining state-of-the-art supply chain optimisation knowledge. During the last few years, he has focused on the assessment of companies’ supply chain organisation and its fit with the overall business strategy. One key aspect of such an assessment is the alignment between marketing and sales strategy and supply chain strategy. An important input for this alignment is a good understanding of the relation between product and service offerings and the resulting cost to serve. Noud holds an MSc in applied mathematics from the University of Twente and a PhD from the same university. He is a guest researcher at Eindhoven University of Technology and is involved in several research projects.
Alison Davis is a data scientist at ORTEC where she is a member of the Data Driven Logistics consulting team. She develops analytics solutions to common supply chain-related business challenges. At ORTEC, she works together with businesses to develop and implement analytics solutions that enable data-driven decision making through increased supply chain visibility, cost to serve analyses, and more. Alison has a BSc and MEng in industrial engineering from the University of Louisville, where she researched a machine learning approach to cost to serve modelling.
Citation
De Poot, Daphne, Gademann, Noud and Davis, Alison (2021, June 1). Cost to serve and supply chain optimisation. In the Journal of Supply Chain Management, Logistics and Procurement, Volume 3, Issue 4. https://doi.org/10.69554/ZZOC3699.Publications LLP