Abstract
This is a review of Nitsche’s “Exploring the Potentials of Automation in Logistics and Supply Chain Management: Paving the Way for Autonomous Supply Chains.” The article is the introduction to a special issue of the journal Logistics devoted to the automation of logistics and supply chain management. It describes the motivations for doing so and the particular areas of logistics most amiable to automation. The article then describes five levels of automation that are available for supply chain managers, then concludes with brief summaries of the other papers in this special issue.
This review begins with an outline of the major concepts used in the paper, then examines how supply chain management theory applies to these concepts. The managerial implications of this paper are explored, and the article is summarized. Finally, the coverage of the issues surrounding automation is appraised.
Author’s Purpose
The purpose of "Exploring the Potentials of Automation in Logistics and Supply Chain Management: Paving the Way for Autonomous Supply Chains" (Nitsche, 2021) is to serve as an introduction to a special edition of the Logistics journal devoted to how and why logistics and supply chain management systems should be automated. As it is an introduction, it defines some of the concepts used in the other six papers in the special issue. Based on these six papers, the author derives a five-level system describing the degree of automation present in any logistics or supply chain management system. This five-level system is sequential, meaning that it describes a progression pointing to the ultimate state of automation, which the author believes to be completely autonomous self-directed systems. The author completes this introduction by providing brief summaries of the other papers contained in the special issue.
Background of the Issue
Logistics and supply chain automation is defined as “the partial or full replacement or support of a human-performed physical or informational process by a machine. This includes tasks to plan, control or execute the physical flow of goods as well as the corresponding informational and financial flows within the focal firm and with supply chain partners.” (Nitsche et al., 2021, p. 225).
Prior to the COVID-19 pandemic, the motivations for automating logistics and supply chain systems were to improve supply chain responsiveness and resilience while minimizing operating costs. COVID-19 provided another motivation: eliminate the dependency on human control and input. COVID-19 thus moved the goalpost from automation to being fully autonomous. (Wuest et al., 2020, p. 6-7)
Automation comes in many forms, and Nitsche (2021, p. 5) defines five levels of automation. Ranking these from most amount of human involvement to least, these levels are:
Remote control – this is the least amount of automation necessary for remote work; humans are involved with every decision.
Systems for assisting the user – all steps in the process being automated are predefined; there is no ability to adapt to unforeseen circumstances.
Semi-automated systems with no self-learning – the ability to manage new situations is through “if-then” decisions, but the decisions themselves are predefined.
Semi-automated systems with self-learning - human intervention is only necessary in complex situations, and intervention becomes less frequent the longer the system is online.
Autonomous systems - human intervention is extremely rare; the system is self-learning, and is integrated into other relevant systems.
The author notes that fully autonomous systems are best able to overcome situations such as the COVID-19 pandemic, since fully autonomous systems remove the impact that ill employees had on supply chain responsiveness and resilience.
Application of Relevant Supply Chain Management Theory
There are several goals for automating logistics and supply chain management. Of course, there are the desires to minimize costs and increase productivity. This latter desire is expressed through the concepts of supply chain resilience and supply chain responsiveness.
Supply chain resilience is the ability of the supply chain to “heal from disruptions.” The company must be able to respond to various types of disruptions and to quickly return to pre-disruption levels of throughput. One way of doing this is to use multiple suppliers and to trace dependencies among these suppliers – in other words, use a contemporary supply chain which involves multiple partners.
For an automated supply chain to be resilient, the company must have insight into the activities of its supply chain partners. This can hinder the conversion to automation, for it requires the company’s logistics automation system to work with those of its supply chain partners. This problem is not addressed in (Nitsche, 2021).
Supply chain responsiveness is the speed at which a supply chain can deliver demand. It can be calculated as the time needed to fulfill orders. In a sense, resilience is the opposite of responsiveness: responsiveness is the speed at which a supply chain operates under normal circumstances whereas resilience is the speed at which the supply chain recovers from abnormal circumstances.
There are numerous ways an automated supply chain furthers the goal of responsiveness. For example, the automated system can track items as they move through the supply chain. When a bottleneck occurs (Quigg, 2022, p. 59), depending on the level of automation the system can alert workers or interface with the appropriate supply chain partner’s supply chain system, thus resolving the bottleneck before this responsiveness issue becomes a resilience issue.
Responsiveness is a process performance metric (Quigg, 2022, p. 63), and automated supply chain systems should be able to calculate this metric since, again, it tracks items as they proceed through the supply chain. This is done by barcodes, RFID tags, etc. The automated system should present this information in the forms of dashboards or reports.
Managerial Implications of Article Findings
There are several important lessons a manager can extract from this paper. The paper includes a comprehensive definition of logistics and supply chain management automation, and a list of the advantages that automation can bring to the supply chain is provided (improved responsiveness, improved resilience, and minimized costs). All these advantages are the results of the successful completion of an automation process, but where to start the process?
For companies that have not yet begun logistics automation, the paper includes a wealth of information. While the paper does not include a step-by-step explanation of the process, it does describe the portions of logistics systems that are most amenable to automation (fulfillment, data exchange, and management). These are places to start. Automating a supply chain can be a lengthy process, and the process is described by various levels of automation (remote control, user assistance, semi-automated systems without self-learning, semi-automated systems with self-learning, and ending with fully autonomous systems). While the author recommends targeting a fully autonomous system, many benefits can be achieved at an earlier level.
The article explains some of the ways to measure the qualities of a proposed automation solution (technical maturity, system interoperability, data security, and quality). Finally, the article lists the people whose commitment is essential for the successful automation of their logistics system (top management, affected employees, and other stakeholders).
None of the disadvantages of automation are addressed in this paper. There are no estimates of either the total cost of ownership, or the financial benefits that come with automation, or the completion time. Also left unmentioned are the advantages and disadvantages to performing the automation using internal resources (software engineers, etc.) versus external contractors.
Given that modern supply chains consist of multiple partner companies acting in concert, the automation systems of the partner companies must be compatible. If not, human intervention is required for data entry or software engineers must develop “adapters.” Finally, there is no discussion of the need to thoroughly evaluate automation solutions before they go into production. Such systems are prone to hysteresis (feedback loops), which is the bane of many automated financial trading systems.
Finally, the paper makes a serious assumption about the abilities of fully autonomous systems. Can a fully autonomous system really anticipate black swan events and respond appropriately? We cannot expect fully autonomous systems to be omniscient, nor would we want them to be.
Summary of the Article and its Context
This article serves as the introduction to a special issue of Logistics devoted to logistics and supply chain management automation. The motivation for logistics automation lies in the need to reduce costs while increasing supply chain resiliency and responsiveness. The COVID-19 pandemic only increased the desire to not only automate logistics systems but to make them fully autonomous.
While automation can be applied throughout logistics, there are three fundamental dimensions that show the most improvement in operational effectiveness: fulfillment, data exchange, and management. For a company with no logistics automation, these three areas are considered the best places to start.
The article then lists five levels of automation (remote control, user assistance, semi-automated systems - no self-learning, semi-automated systems - with self-learning, and autonomous systems) with decreasing levels of human interaction. It is the last stage, fully autonomous systems, which provides the most durability against situations like the COVID-19 pandemic.
As mentioned above, this article is the introduction of a special issue of Logistics devoted to logistics automation, and there are six other papers in that special issue that address a wide range of subjects, from the impact of cloud storage and the internet of things on automation to the use of autonomous trucks for last mile delivery. This article concludes with brief summaries of those other six papers.
Conclusion
Nitsche’s paper (Nitsche, 2021) includes valuable information about logistics automation, most importantly on the various levels of automation. The paper is one sided in that it covers the advantages of automation while glossing-over the disadvantages. The lack of discussion on the drawbacks of automated systems, especially fully autonomous systems, is troubling, and thus this paper cannot be recommended as a reliable source of information for supply chain managers considering automation.
References
Nitsche, B. (2021). Exploring the potentials of automation in logistics and supply chain management: Paving the way for autonomous supply chains. Logistics 5(51), 1–9. https://doi.org/10.3390/logistics5030051
Nitsche, B., Straube, F., & Wirth, M. (2021). Application areas and antecedents of automation in logistics and supply chain management: A conceptual framework. Supply Chain Forum Int. J. 22(3), 223–239. https://doi.org/10.1080/16258312.2021.1934106
Quigg, B. (2022). Supply Chain Management (1st ed). McGraw-Hill Create. https://bookshelf.vitalsource.com/books/9781307866025
Wuest, T., Kusiak, A., Dai, T., & Tayur, S.R. (2020, May 5). Impact of COVID-19 on manufacturing and supply networks—The case for AI-inspired digital transformation. SSRN Electron. J. 2020. https://dx.doi.org/10.2139/ssrn.3593540
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