How Automotive Industry is Leveraging Cognitive Automation, AI to Optimize Supply Chains

Summary: Technological advancements are taking the global automotive industry by storm. Read on to understand how the automotive industry is leveraging the prowess of cognitive automation and artificial intelligence (AI) to build resilience and adaptability in supply chains.


Challenges in traditional supply chains 

Globally, supply chain executives face the following key challenges: 

  • Visibility: Information is around but is not being effectively captured, structured, analyzed, or presented to people who need it. 

  • Cost: Shifts in costs - wage inflation in low-cost labor markets, spikes in component prices, and credit freezes - make it difficult for supply chain professionals to keep up.

  • Risk: Globalization, greater supply chain interdependence, lack of standardized processes, insufficient data, dated technologies prevent effective risk management. Customer intimacy: Manufacturers struggle to identify customer needs. Despite rising customer demands, manufacturers are more connected and focused on suppliers. 

Reimagining the traditional supply chain…

Manufacturers are going from relatively short production lines to complex ecosystems of different suppliers and industry players. To cope with this massive disruption, a re-imagination of the traditional supply chain is needed. 

In such challenging times, auto manufacturers need supply chains capable of responding quickly to the ebbs and flows emerging from this uncertainty. They want a supply chain that is more flexible and resilient and is fed by real-time data to navigate current and future disruption.

To understand the situation and plan for what’s ahead, consider this scenario:

Imagine a scenario: A potential customer engages with a chatbot on an auto manufacturer’s social media platform and asks queries about a particular model. The bot forwards this information to the manufacturer’s automated marketing platform, which sends relevant content and promotional offers to the potential customer and arranges a test drive.

The customer, satisfied with the test drive, places an order with the dealer. Again, a chatbot facilitates the transaction, offers an attractive car loan and a vehicle insurance policy tailored to the customer’s driving history.

Based on customers’ previous vehicle purchase history, the chatbot also predicts the kind of accessories that the customer might need and communicates the same to the manufacturing plant. The manufacturing unit keeps the required accessories ready and processes the order the moment customer confirms. This made-to-order approach prevents the inventory from piling up.

This scenario can be enlarged in numerous ways.

Benefits of Cognitive Automation on Supply Chain

So, how can supply chain automation increase the efficiency of the automotive supply chain?

Using exponential technologies to forecast demand accurately has a bullwhip effect along the entire supply chain. Powered by exponential technologies like machine learning (ML) and artificial intelligence (AI), cognitive automation in supply chains can drive competitive differentiation to the next level. It can deliver game-changing improvements with data access and compute power far beyond what can be achieved through human decision-making.

  • Mitigate risks: Most auto manufacturers follow a just-in-time sourcing strategy, which means goods and labor are scheduled to arrive when needed in the production process. Any delay in transit due to supply chain disruption can halt production. When the production stops, losses, both financial and reputational, add up minute by minute. Ensuring end-to-end visibility of the supply chain can minimize these disruptions. Some supply chain solutions can alert professionals through real-time emails and notifications if a shipment has been damaged or will be delivered late. Instead of waiting for goods, manufacturers can take immediate actions to tackle arising issues.

  • Improve product quality: For auto manufacturers, product recalls impact the entire network. In addition to affecting production schedules at plants, they also negatively affect the transport and inventory costs. Having an IoT-enabled warehouse can help manufacturers reduce the number of recalls by ensuring quality control. Also, by installing intelligent sensors, manufacturers can monitor the environment of products-in-transit and receive alerts on critical indicators like temperature or humidity inside a shipping container or truck.

  • Right-size inventory: In the auto business, inventory management is a delicate balancing act. Under-stock and frustrated customers will shop elsewhere; overstock and excessive stock will strain working capital. With correct inventory management, manufacturers can handle challenging and changing customer demands. Supply chain visibility will also support lean methodologies helping manufacturers reduce waste and cut costs.

  • Reduce inefficiencies: The automotive supply chain involves many stakeholders - raw material gatherers, transportation companies, original equipment manufacturers (OEM), and many more. Traditional methods of collaborating among stakeholders are inefficient and often lead to mistakes, missed deadlines, and damaged deliveries. IoT-enabled supply chain visibility platforms display shipment information, offering a holistic view of all products in transit. All stakeholders can easily access the platform simultaneously, enabling seamless information flow.

Conclusion

By identifying and eliminating deep-rooted inefficiencies and chokepoints, exponential technologies like machine learning (ML) and artificial intelligence (AI), cognitive automation drive enterprise-wide visibility into all aspects of the supply chain with a granularity that human minds simply can’t even mimic.

From more accurate capacity planning to improved productivity and from cutting costs to increased output, AI has transformed the competitive landscape and this revolution will intensify in years to come.

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