Data-driven process redesign: anticipatory shipping in agro-food supply chains

Abstract

Anticipatory shipping uses historical order and customer data to predict future orders and accordingly ship products to the nearest distribution centres before customers actually place the orders. It is a method to meet the increasing customer requirements on delivery service and simultaneously to reduce operational costs. This paper presents a case of anticipatory shipping in the context of agro-food supply chains. The challenge in these chains is the product perishability that leads to product obsolescence in the case of unbalanced supply and demand. This study introduces a data-driven approach that integrates product quality characteristics in data analytics to identify suitable products for anticipatory shipping at the strategic level. It also proposes process redesigns concerning production and transportation at the operational level to realise anticipatory shipping. Finally, using historical data from a Dutch floriculture supplier as input for a multi-agent simulation, the proposed approach and process redesigns are verified. The simulation output shows that anticipatory shipping could increase delivery service level up to 35.3% and reduce associated costs up to 9.3%.

A systematic and network-based analysis of data-driven quality management in supply chains and proposed future research directions

“…A data-driven concept that integrates the product's quality characteristics in data analytics was proposed by Viet et al (2020). Based on the study, the authors redesign the production and transportation model.…”

“…Quality management (QM) is an essential aspect of SC management. Firms must develop a sound quality management system in their SCs for the seamless flow of products and information (Viet et al, 2020;Grandinetti et al, 2020). Considering increasing data-driven technologies and QM tools, this work analyzes the importance of data-driven technologies and quality management in supply chain management.…”

Value of data in multi-level supply chain decisions: a case study in the Dutch floriculture sector

“…A potential strategy for suppliers is to pre-ship their products to temporary storage facilities at RFH cross-docking, from where near-future orders can be fulfilled directly. The pre-ship strategy is also known as anticipatory shipping in the literature (Viet, Behdani, and Bloemhof 2020).…”

Shortening Delivery Times by Predicting Customers’ Online Purchases: A Case Study in the Fashion Industry

“…A genetic algorithm is then applied to optimize AS in the distribution network. Viet, Behdani, and Bloemhof [13] present a model for AS in the agro-food industry. They also apply associate rule mining but add a time threshold to take into account product perishability.…”