Building Supply Chain Resilience through Virtual Stockpile Pooling

Abstract

Stockpiling inventory is an essential strategy for building supply chain resilience. It enables firms to continue operating while finding a solution to an unexpected event that causes a supply disruption or demand surge. While extremely valuable when actually deployed, stockpiles incur large holding costs and usually provide no benefits until such a time. To help to reduce this cost, this study presents a new approach for managing stockpiles. We show that if leveraged intelligently, stockpiles can also help an organization better meet its own regular demand by enabling a type of virtual pooling we call virtual stockpile pooling (VSP). The idea of VSP is to first integrate the stockpile into several locations’ regular inventory buffers and then dynamically reallocate the stockpile among these locations in reaction to the demand realizations to achieve a kind of virtual transshipment. To study how to execute VSP and determine when it can provide the most value, we formulate a stylized multi‐location stochastic inventory model and solve for the optimal stockpile allocation and inventory order policies. We show that VSP can provide significant cost savings: in some cases nearly the full holding cost of the stockpile (i.e., VSP effectively maintains the stockpile for free), in other cases nearly the savings of traditional physical inventory pooling. Last, our results prescribe implementing VSP with many locations for large stockpiles, but only a few locations for small stockpiles.

Managing supply chain resilience to pursue business and environmental strategies

“…Kamalahmadi and Parast (2016) raised a fundamental question about the relative importance of flexibility versus redundancy strategies and provided guidance on the appropriate use of either overarching strategy according to the situation. In answering this question, Liu, Song, and Tong (2016) report that redundancy-based strategies lead towards a higher value of SCR. Whereas Tang and Tomlin (2008) highlighted that flexibility-based strategies have deeper impacts on mitigating the risk.…”

“…;Wilson (2007);Cutter et al (2008); Ponomarovand Holcomb (2009);Das, (2015);Liu et al (2016);Rajesh (2016);Chen et al (2017);Macdonald, Zobel, Melnyk, and Griffis (2018);Ramezankhani, Torabi, and Vahidi (2018) 3Customer service level Sheffiand Rice(2005); Datta et al (2007);LodreeandTaskin (2008); Wilson (2007); Spiegler et al (2012); Cardoso et al (2015); Manning and Soon (2016); Rajesh (2016) 4 Minimum total Cost Ratick, Mecham, and Aoyama (2008); Carvalho et al (2012); Macdonald and Corsi (2013); Cardoso et al (2015); Das (2015); Liu et al (2016); Manning and Soon ((2004); Jüttner andMaklan (2011); Brandon-Jones et al (2014); Soni et al (2014); Fiksel et al (2015); Chowdhury and Quaddus (2016); Rajesh (2016) 7 Inventory gap Tomlin (2006); LodreeandTaskin (2008); Wilson (2007); Spiegler et al (2012); Das (2015) Kamalahmadi and Parast (2016); Sodhiand Lee (2007) 8 Maximum on-time deliveries Schmitt and Singh (2012); Spiegleret al (2012); Chowdhury and Quaddus (2016); KamalahmadiandParast (2016); Manning and Soon (2016); Spiegler, Potter, Naim, and Towill (2016) 9 Supply flexibility Tang and Tomlin (2008); Skipper and Hanna (2009); Soni et al (2014); Das, (2015Cabral et al (2012); Carvalho et al (2012); Spiegler et al (2012); Chowdhury and Quaddus (2016); Ramezankhani et al (2018) 14 Transportation flexibility Glickman and White (2006); Ishfaq (2012); Azadehet al (2014); Fiksel et al (2015)15 Redundancy rateChristopher and Lee (2004); Ponomarovand Holcomb(2009); Spiegleret al (2012); Ivanov et al (2014); Rajesh (2016) 16 Risk-sharing rate Soni et al (2014); Fiksel et al (2015); Chowdhury and Quaddus (2016for preparation that exceeds demand (holding cost) Lodree andTaskin(2008)28Per unit cost for preparation that falls short of demand (shortage cost) LodreeandTaskin (2008);Namdar et al (2018) …”

Emergency department resilience to disaster‐level overcrowding: A component resilience framework for analysis and predictive modeling

“…Recent top-level operations management research has primarily focused on resilience as it pertains to supply chain disruptions, critical infrastructure, and quality disruptions (Ambulkar et al, 2015;Besiou, Pedraza-Martinez, & Van Wassenhove, 2014;Kim et al, 2015;Liu et al, 2016;Su, Linderman, Schroeder, & Van de Ven, 2014). However, there is an insufficient operations management research on the resilience of the health care systems (Besiou et al, 2014).…”

“…We also incorporate into our research effort the notion of resilience or the ability of a system to resist against and then recover from the impact of a disruption (Bruneau et al, 2003;Nemeth, Wears, Woods, Hollnagel, & Cook, 2008). Resilience measures have been previously used to assess the dynamic response of systems like supply chains or critical infrastructure networks to various types of disasters (Ambulkar, Blackhurst, & Grawe, 2015;Kim, Chen, & Linderman, 2015;Liu, Song, & Tong, 2016), but they have not yet been applied to the problem of understanding and addressing ED overcrowding.…”

Dynamic Complexities in a Supply Chain System with Lateral Transshipments

“…In addition, lateral transshipments enhance the system resilience of supply chain systems in the presence of disruptions due to inventory pooling [8,9]. In practice, collaboration programs with lateral transshipments have been implemented in numerous areas, such as retail, the energy industry, and the automotive industry [10,11].…”