- Supply Chain
- Industrial Demand Flexibility
AI Supports Supply Chain Adaptation to COVID-19-Related Impacts
Today’s supply chains have been strained in unprecedented ways by the coronavirus outbreak. Demand shocks have reduced distributor profitability and capacity, leading to cost overruns or product waste. However, new supply chain models based on AI techniques are reducing transport and storage costs. These lessons are applicable across supply chains strained by the demands of the current crisis.
New AI-Based Supply Chain Interventions Can Help
AI is enabling smart warehousing through accurate predictive inventory purchasing and storage of short-cycle products while minimizing shortfalls. Amazon’s AI-enabled shipping centers are widely known in this regard, but US-based Ryder also offers smart warehouse solutions that generate 20% operational savings.
Similarly, enterprise software vendor C3.ai has developed an AI-powered inventory optimization application that allows real-time inventory monitoring across replacement parts, components, and finished goods—categories that are often obscure in traditional systems. C3.ai’s application uses machine learning algorithms to crunch data from production orders, purchase orders, and supplier deliveries to glean stocking recommendations. In crisis situations, this advanced technology can help avoid massive overstock as demand fluctuates.
Distribution as a Service Provides Opportunities to Adapt
In some cases, AI-based distribution is evolving into an as a service model. A popular app in China called Pinduoduo uses predictive AI to crowdsource wholesale purchasing, delivering food to restaurants through predictive logistics, warehouse leasing, and just-in-time transport. This model has higher costs than pure e-commerce companies that don’t take inventory, but it compensates with higher quality control. Barriers to this model exist in higher cost, more regulated markets like the US, where companies like Farm’d crowdsource using a localized approach to reduce transport and storage costs.
AI Presents Future Opportunities in Decarbonization and Efficiency
These applications show the potential for more efficient and robust distributor operations across sectors. For distributors, a first step in this transformation is greater supply chain digitization to enable automation, task integration, and data collection. Smart warehousing holds great promise as a predictive, waste-reducing response to crisis-level consumer patterns. Now more than ever, distributors should begin the transformation necessary to improve the efficiency, resiliency, and carbon profile of supply chains.