ABSTRACT
The extreme demand volatility caused by corona virus 2019 (COVID‐19) overwhelmed most preemptive measures enacted by firms to mitigate disruptions in their supply chains. This led to the rapid implementation of reactive measures to provide business continuity. The operations and supply chain management literature has grouped these reactive techniques into those that involve the reconfiguration of firm resources and those that involve changes to its decision‐making processes. Unfortunately, little of this work has empirically assessed the efficacy of individual reactive techniques on business continuity after the onset of a disruption such as COVID‐19. The research reported in this paper addresses this gap through an experimental design and discrete‐event simulation to empirically test the impact on firm outcomes of resource reconfiguration techniques versus those related to adaptive decision‐making processes. Data from a canned foods manufacturer is used to populate the simulation and isolate the impact of these reactive changes implemented in March 2020 at the beginning of the COVID‐19 disruption on the attainment of business continuity in the 3 months following the COVID‐19 disruption. The results show that for this company, decision‐making changes—specifically changes to planning process cadence and time horizon—had more impact on business continuity than those focused on resource reconfiguration (increasing capacity through stock keeping unit (SKU) prioritization and increasing the number of shifts). These results, in addition to qualitative data collected from company executives to provide context for the modeling results, are used to provide insights that are generalizable to many firms.
ABSTRACT
Healthcare providers' preparedness and response plans are crucial to effectively cope with infectious disease outbreaks such as COVID-19. These plans need to provide strategic and operational actionable insights to guarantee the availability of essential resources when needed. This study uses a simulation-optimization approach to (i) determine an optimal replenishment policy to restock personal protective equipment (PPE) items, and (ii) determine proactive demand planning for critical resources such as the number of beds, and ventilators. This model leverages a Simio-MATLAB integration to complete simulation and optimization tasks. © 2022 IEEE.
ABSTRACT
Purpose>This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.Design/methodology/approach>This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.Findings>Supply chain agility is a complex and demanding challenge facing most firms operating postpandemic. Yet the response to these challenges is fairly ubiquitous by firms, meaning there are some generic steps all firms can make to improve.Originality/value>The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.
ABSTRACT
Purpose>This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.Design/methodology/approach>This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.Findings>Supply chain agility is a complex and demanding challenge facing most firms operating postpandemic. Yet the response to these challenges is fairly ubiquitous by firms, meaning there are some generic steps all firms can make to improve.Originality/value>The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.
ABSTRACT
The extreme demand volatility caused by COVID-19 overwhelmed most preemptive measures enacted by firms to mitigate disruptions in their supply chains. This led to the rapid implementation of reactive measures to provide business continuity. The operations and supply chain management literature has grouped these reactive techniques into those that involve the reconfiguration of firm resources and those that involve changes to its decision-making processes. Unfortunately, little of this work has empirically assessed the efficacy of individual reactive techniques on business continuity after the onset of a disruption such as COVID-19. The research reported in this paper addresses this gap through an experimental design and discrete event simulation to empirically test the impact on firm outcomes of resource reconfiguration techniques versus those related to adaptive decision-making processes. Data from a canned foods manufacturer is used to is populate the simulation and isolate the impact of these reactive changes implemented in March 2020 at the beginning of the COVID-19 disruption on attainment of business continuity in the three months following the COVID-19 disruption. The results show that for this company, decision-making changes ? specifically changes to planning process cadence and time horizon ? had more impact on business continuity than those focused on resource reconfiguration (increasing capacity through SKU prioritization and increasing the number of shifts). These results, in addition to qualitative data collected from company executives to provide context for the modeling results, are used to provide insights that are generalizable to many firms. This article is protected by copyright. All rights reserved