Artificial Intelligence for Supplier Risk Assessment
Technology has been creeping into the automotive supply chain for a while now. It started with electronic invoicing, escalating to computerized shipping, shipment tracking, and real-time inventory monitoring. Now, with the advent of Supply Chain 4.0
, data analytics and Artificial Intelligence (AI) are expected to play a major role in assessing and mitigating supplier risk
With relentless research, AI saw exponential growth in the last decade, and now we can find many techniques used within AI systems. In a supply chain environment, Petri Nets can help trace interactions and assess the dynamic nature of a supply chain. Again, rule-based reasoning techniques can be used when the system must function strictly based on rules, and multi-agent systems can be deployed to manage coordinating or conflicting interactions throughout the supply chain.
All in all, with the use of AI and ML, we can now harness big data from the supply chain systems to prescribe risk-mitigating strategies.
Benefits For Automotive Industry
AI is seeing steady adoption in the automotive industry as an intelligent risk radar. Here are some of the major benefits we can expect:
Improved Transparency in The Supply Chain
AI systems have predictive capabilities, and they have proven to be reliable. By harnessing its power, organizations have successfully turned masses of structured and unstructured data into valuable insights, as has been shown by Audi using it more than 4,000 supplier companies.
The risks in an automotive supply chain are dynamic and change every day. With rigorous data analysis, AI systems have been critical in uncovering risks in complex supplier networks and setting accurate expectations.
Predicting Delivery Disruptions
AI can potentially be used for predicting issues with deliveries based on historical data. This includes deliveries from suppliers to manufacturers, manufacturers to warehouses, distributors, etc. It can also help determine if any alternative plans need to be materialized or backlogs need tending. The direct benefit from this functionality is a highly optimized automotive supply chain as pre-emptive measures give manufacturers enough legroom to make critical business decisions.
A Better Work Environment
AI systems promise a lot more than only exposing supplier risk
. Using this assessment, automotive manufacturers have nudged their businesses to edge towards a higher purpose. With demonstrated ethics in the supplier network, the risk mitigation plan comes bearing fruits, but it also helps drive the company's sales. This leads to an improved brand value which helps attract industry-wide top talent.
Be Proactive, Not Reactive in Mitigating Supplier Risk in Automotive Industry
News about vehicle recalls keeps coming back to the forefront, and the automotive industry must look for more proactive ways to anticipate and mitigate supply chain risks. Even if this can be called a down cycle within the automotive industry, supplier risk professionals must customize their approach to identifying distress signals.
Rather than handling the consequences of dealing with a risky supplier, automotive manufacturers must take precautionary steps to mitigate the costs of distressed supplier relations.
Supplier Risk Assessments Need Modernization
As explained in the previous sections, AI has transformed our supply chains and made them more transparent while aiding in other aspects like route optimization and forecasting customer demands. But it doesn't end here. Assessing supplier risk is still a fresh domain and depends on other modern technologies like IoT
to dent the persisting, non-functional paradigms.
Therefore, we need a comprehensive yet automated approach in supplier risk assessment processes that currently can be delivered by analytics-driven optimization and AI — both key aspects of modernization that thrive on cloud infrastructure
and identify significant impacts on supply chain development and performance.