Launched in fall 2020, the Extensiv Supply Chain Scholarship aims to foster the talent that will drive the future of our industry. Now in its fourth year, the Extensiv scholarship program hopes to inspire fresh ideas and voices in logistics and supply chains.
For the final installment in our scholarship series, we present Alyssa Allred, one of the Spring 2023 Extensiv Supply Chain Scholarship runners-up, and her essay on AI within supply chain management.
Over the past four decades, supply chain management has gained significant interest and recognition. With the introduction of computers in the 1980s, businesses began relying on technology to solve supply chain challenges. This reliance on technology provided businesses with enhanced visibility throughout the entire supply chain and greater control over the movement of goods and services. As the Fourth Industrial Revolution unfolds and as technological advancements persist, supply chain management is bound to undergo transformative changes. Among the various technologies that will shape the future of supply chain management, artificial intelligence (AI) will play a pivotal role in three core areas: demand forecasting, warehousing, and logistics.
Demand Forecasting
Forecasting demand poses a significant challenge for businesses due to the variability and uncertainty involved. Despite the difficulty, businesses that rely on AI technologies improve demand accuracy and mitigate risk. According to McKinsey, AI technologies have improved demand forecast accuracy and helped reduce errors by 30-50% (2). To forecast demand, AI and Machine Learning technologies (ML) will collect data, perform data analysis, create models, and forecast. With AI and ML, businesses account for a wide range of factors including market conditions, seasonality, historical data, and social media posts. AI helps businesses prepare for unexpected events and change course when necessary. During the COVID-19 pandemic, Amazon saw demand for toilet paper increase by 213% (3). Amazon responded to this spike in demand by using “AI-driven predictive forecasting to act quickly and increase adaptability to market fluctuations” (3). By using cloud-based ML, Amazon was able to predict and discover customer habits during this time of uncertainty.
The integration of AI technology has greatly enhanced demand forecasting capabilities. With its ability to analyze and interpret large amounts of data quickly, AI eliminates the need for manual updates of Enterprise Resource Planning Systems (ERP), ensuring real-time accuracy (4). This empowers supply chain leaders to make informed purchasing decisions by providing up to date information on purchasing requirements. By leveraging AI in their demand forecasting, businesses are not only operationally efficient, but also resilient. When threats occur, they are prepared to respond promptly to resolve the issue.
Warehousing
Over the last several years, warehouse automation technologies have developed at a rapid pace. A recent study conducted by Gartner found that “by 2026, 75% of large enterprises will have adopted some form of intralogistics smart robots in their warehouse operations” (3). Robots in warehouses help to maximize throughout, improve operations, and increase overall profits. This summer, while on a business study abroad, I had the opportunity to visit BMW’s Motorcycle Plant in Berlin, Germany. While there, I noticed specific AI technologies being used by BMW to enhance its operations, such as the automated carriages that transport over one million parts daily (5). These carriages follow specific routes to deliver inventory to the right place at the right time. With this process, BMW reduces the amount of manual labor needed so that its employees can focus on more strategic tasks.
AI technology has transformed warehousing by enhancing productivity, safety, and accuracy. Within a warehouse, operations are dynamic and prone to human error. This can lead to increased downtime, waste, and workloads. AI systems help to eliminate these errors by performing more difficult, repetitive tasks. By relying on robots for these tasks, companies can increase productivity. Studies show that “a 1% increase in robot density translates to a 5.7% increase in productivity” (6). In addition, businesses use AI systems to increase warehouse safety and reduce unnecessary human movement. As warehouse managers turn to ML to optimize warehouse routing and robot precision, they can increase efficiency.
Logistics
It is undeniable that the logistics industry is changing quickly. The use of AI combined with big data and human collaboration will drive increased efficiency in every step of the logistics process, from demand planning to last-mile delivery. AI has helped to increase both the accuracy and speed of logistical systems ensuring timely delivery to customers. By analyzing transportation costs and delivery times, AI can optimize routing by recommending the most efficient routes to minimize costs (7). Through route optimization, businesses can increase profitability and efficiency.
During the COVID-19 pandemic, DHL saw an increase in the number of ecommerce clients and faced the challenge of fulfilling client orders in a timely manner. To address this issue, DHL implemented IDEA (an AI software technology) to optimize routes and staff allocation within the warehouse (7). With this technology, DHL was able to reduce “distance traveled by warehouse employees by up to 50% and increase the productivity of individual DHL locations by up to 30%” (7). In the logistics industry, companies that embrace AI are more likely to increase efficiency. AI can help provide “instant accurate information, stream communications, automate routine tasks, and providing comprehensive insights into logistical operations. [As a result], logistics companies can improve performance, increase customer satisfaction, and reduce costs” (9).
Conclusion
Artificial Intelligence is a revolutionary technology that will continue to advance supply chain management. According to studies, it is predicted that by 2030, 30% of current jobs will be automated (8). Companies that embrace AI are more likely to gain a competitive advantage. Within the field of supply chain management, the implementation of AI technology can drive advancements in demand forecasting, warehousing, and logistics. However, it is important to note that while this technology has potential for significant impact in supply chain, it is most beneficial when paired with human interaction. With a human involved at all steps of the process, this technology is more likely to be effective, ethical, and comprehensible. By implementing AI within their operations, businesses can enhance their decision-making capabilities and solidify their competitive advantage.
Sources
- https://www.gartner.com/smarterwithgartner/gartner-predicts-the-future-of-supply-chain-technology
- https://www.mckinsey.com/capabilities/operations/our-insights/supply-chain-40--the-next-generation-digital-supply-chain
- https://www.forbes.com/sites/amazonwebservices/2021/12/03/predicting-the-future-of-demand-how-amazon-is-reinventing-forecasting-with-machine-learning/?sh=41efef381b6b
- https://www.forbes.com/sites/forbestechcouncil/2023/02/06/5-ways-ai-can-benefit-demand-forecasting-and-inventory-planning/amp/
- https://www.bmwgroup-werke.com/berlin/en/unser-werk/technologien/logistik.html#logistik
- https://stefanini.com/en/insights/articles/benefits-of-using-ai-in-warehouse-automation-and-increased-produ
- https://ai.plainenglish.io/the-ai-supply-chain-advantage-how-businesses-are-using-technology-to-stay-ahead-of-the-competition-629de9446661
- https://www.crossrivertherapy.com/research/artificial-intelligence-statistics
- https://dhl-freight-connections.com/en/trends/chatgpt-and-the-like-artificial-intelligence-in-logistics/
