The Impact of AI on Supply Chain Management

Stable and reliable supply chains are the backbone of a company’s success. From demand and supply planning to transportation and warehouse management, the many components of a supply chain make it vulnerable to risks. Numerous industries are negatively affected by disruptions in their supply chains, including the aerospace, defense, security, manufacturing, and construction industries. As globalization advances, supply chain management across state borders becomes increasingly complex and difficult to control. The rising global demand for high technology products, for instance, requires a rapid, seamless production and delivery of goods. Artificial intelligence (AI) tools can help businesses analyze large amounts of data by utilizing smart algorithms. With AI, businesses are able to improve their management of supply chain risks. Thus, AI can help optimize supply chains and decrease the workload of employees.

An Introduction to Artificial Intelligence and Machine Learning

Machine learning, a subcategory of AI focusing on algorithms and statistical models, can help companies identify salient patterns and influential factors in their supply chains without the intervention of humans. Data scientists train machine learning algorithms with sample data, building a training model, which allows the machine to make supervised and unsupervised intelligent predictions and analyses.

Demand and Supply Forecasting

AI can thus improve supply chain management and mitigate associated risks in several ways. Firstly, AI can improve demand and supply forecasting. Automated demand prediction not only saves time but also increases efficiency. Companies can also avoid understocking or overstocking products with AI-based demand forecasting tools. Furthermore, companies can benefit from enhanced supplier relationship management. Using data such as the supplier name, parent company, country of origin, management rating, timeliness, financial reports, audits, or credit scoring, AI tools can create supplier profiles and generate predictive results about the supplier’s reliability. Hence, companies can mitigate risks such as loss of revenue or even business failure by closely monitoring supplier relationships and interactions.

Transportation and Delivery Planning

AI tools can also help businesses increase efficiency in transportation and delivery planning. Resources and time can be saved by making AI-based predictions about peak hours and the fastest, cheapest, and safest routes. This can be particularly useful for e-commerce businesses, as customer satisfaction and reputation depend largely on efficient deliveries. Additionally, the prompt delivery of products for the aerospace and defense industry is not only critical to companies in this industry but also to national security. Hence, mitigating supply chain risks can be important for government leaders in addition to companies and customers.

Case Example: The Coronavirus and Apple

Supply chains can be vulnerable to multiple disruptions, including natural disasters, terrorist attacks, financial crises, political instabilities, or epidemics. AI tools can help businesses anticipate potential risks and create reactive plans. The 2020 coronavirus pandemic, for instance, has become a challenge to Apple’s business operations. The technology giant is struggling with low production levels for its new iPhones that are scheduled to be released in fall 2020. One of Apple’s primary suppliers is Taiwanese company Foxconn, the world’s largest contract electronics manufacturer. The spread of the coronavirus has stalled the production of electronics in Foxconn’s factories in China. Additionally, global air travel restrictions have largely inhibited face to face meetings between Apple’s and Foxconn’s engineers, which negatively impacts Apple’s product development and manufacturing. Apple subsequently announced that iPhone supplies would be relatively low on the market and that the company is unlikely to reach revenue targets for the first quarter of 2020. Numerous companies in the technology, automotive, and other industries face similar risks, which is why the predictive capabilities of an advanced AI-based risk analysis of supply chains can enhance the management of such crises.

Conclusion: The Benefits of AI-Based Supply Chain Risk Management

An AI-based assessment of suppliers can help companies seek alternative, reliable partners and reroute deliveries during crises. A company with a deeper insight into its supply chain mechanisms may be better equipped to manage potential risks and opportunities than companies without such insight.

About the Author

Yasemin Zeisl

Yasemin Zeisl earned her MSc in International Relations and Affairs from the London School of Economics and Political Science (LSE). Yasemin is fluent in German and English and possesses advanced Japanese language skills.

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