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Published: May 29, 2024
Over time, the world witnessed the revolution of Supply Chain Management (SCM) in the name change, from Industrial Management to Production Management to Operations Management, to be the present name (Soni & Soni, 2019). With the changing in designation, the scope of the field is also evolving thanks to advanced technology, especially Artificial Intelligent (AI). According to Balan (2019), “Artificial intelligence refers to a broad group of technologies, among which range the following: computer vision, natural language, virtual assistants, robotic process automation, and advanced machine learning” (p.17). Recently, AI adoption to SCM has gained the public attention due to its diverse of application and potential. AI can help boost work productivity, cut costs, and improve work efficiency. In short, AI makes human life easier.
However, it raises a concern about the job displacement and the need of workforce declining. This essay will discuss the innovation of AI to SCM in companies in terms of Inventory, Warehousing, and Transportation, and conclude with the concern that AI is more and more displacing human jobs.
Our world had gone through a severe Covid-19 pandemic which greatly impacts on driving enterprises to change their supply chains management. Recently, a survey of 200 senior- level supply chain executives conducted by Ernst & Young Canada (2023), in late 2020 and September 2022, has found that strategic planning can help the enterprises more resilient, collaborative and networked with their customers, suppliers and stakeholders. During the survey, 52% of executives have disclosed that they started their strategic planning up to the year of 2025 on robotic warehouses and stores, transportation solution and fully automatic planning.
Typically, Amazon, IBM, or Walmart, etc. are considered pioneers in data analytics, robotic warehouse and delivery drone.
Approaching AI in inventory control and planning can reduce sustainable cost and increase revenue of enterprises. As AI can collect and analyze automatically historical, present, and future data, it provides precise and reliable forecasting demand, which allows enterprises to optimize their sources in terms of inventory or customer orders (Dash et al., 2019). Advertising campaigns or entertaining programs on social media are being running with underlined machine learning engine to analyses customer’s activities (Bughin et al. 2017, as cited in Dash et al., 2019). From there, the enterprises can have evidence of consumers’ near-real-time demand for their inventory planning. Walmart, one of the largest retailers, is another example of investing on Big Data analytics to catch customers’ preferences and behaviours for inventory management to reduce overstock and remain sufficient stock on most in-demand products (ProjectPro, 2023).
However, an occurring challenge that may put Walmart on risk of falling behind its competitor is the limited number of professionals with experience in cutting-edge analytics and programming language like Python and R (ProjectPro, 2023). Therefore, any new team members join Walmart must participate in their designed program to gain the necessary knowledge in big data analytics. To gain such remarkable result in the industry, enterprises require experts in understanding and utilizing analysing data. Retraining workers to capture such dynamic complexity database is also a fundamental.
Another advanced branch of AI, robotics, is also a promising approach to help perform heavy and repetitive tasks with high precision and speed. Thus, the use of robots in warehouse potentially helps increase efficiency and productivity, reduce manual labour costs (Dash et al., 2019). Let’s look inside Amazon’s warehouse where there are more than 200,000 mobile robots working alongside with hundreds of thousand human workers. Their mobile robots carry shelves of products from worker to worker to help pick, pack and ship the items. This is operating in a massive warehouse where Amazon workers used to walk more than miles a day for order-picking (Rey, 2019). Higher expectations may require in workers to work along with automated tasks in the warehouse. “The robots have raised the average picker’s productivity from 100 items per hour to a target of 300 to 400”, (Scheiber, 2023). Also, there are always issues during performing of Amazon picking and stowing robots that only can be solved by workers (Rey, 2019). Hence, as per Amazon CEO, “Amazon announced plan to upskill 100,000 of its US employees, including warehouse workers” (Bezos, 2023). This is a great chance for company’s employees to develop their technical skill to move into better-paying jobs.
Additionally, it is essential to adopt AI and machine learning to avoid cost adding and shorten delivery time in logistic management. At the meantime, AI and machine learning can analyse and predict the duration of delivery. This helps to facilitate the delivery to customer timely and meet the requested delivery date as agreement (Dash et al., 2019). Also, other advanced technology in transportation solution, such as drone delivery, driverless truck, etc., which is safer, faster and economic for enterprises. After Amazon successfully delivered a pilot to Cambridge, there is a surge in this area (Dash et al., 2019). However, Amazon’s drone still cannot cross the stress and cannot come near or fly over people. It needs six people to monitor each flight, including observers and ground station operators, which proves that the innovation is still on experiment procedure and requires a lot of workers involving on its performance (Hollister S., 2023). Therefore, Human intervention is still needed to monitor and troubleshoot issue to ensure the ongoing operation of enterprises.
Overall, the impact of AI in SCM has been and will be significant. AI is step by step replacing non-customer-facing jobs in a positive way. It not only brings benefit to a company but also creates more job opportunities to company’s workers. By investing state-of-the-art technology to warehouse, inventory or transportation, company can reduce physical workload, minimize human error, eliminate manual jobs, and save time, which is benefit to the business development and expansion. At the same time, workers have precious opportunity to be retrained and to upgrade themselves to an advanced level. By enriching knowledge in data analysis, basic coding, programming language, engineering, etc., employee will be able to master in AI implementation. Thus, to achieve the best success of technology adoption to the SCM, it should be the collaboration from both AI and human workers.
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