Accelerated AI & ML adoption can reduce supply chain disruptions and enhance delivery efficiency

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In the post-pandemic phase, there have been significant changes in the way companies are demanding supply chain management services. For them, it’s no longer about visibility anymore. It’s about how visibility can be leveraged to ensure seamless supply chain services devoid of any major hitch. Advanced technologies have made it possible for supply chain management companies to align the operational capacity with the varied demand spectrum.

The interplay of various interconnected entities is the essence of supply chain operations. New-age digital technologies such as artificial intelligence (AI) and machine learning (ML) play a critical role by offering visibility and strengthening predictability so that the stakeholders involved in a particular supply chain journey can align their resources with the evolving realities. 

Managing sudden operational or transport-related interruptions are integral parts of the deliverables of supply chain management service providers. An effective technology integration ensures that all the stakeholders are in sync with the exigencies and are adequately prepared to factor in the changes. That’s how disruptive impact on the supply can be minimized. 

Technology adoption can strengthen the discoverability of resources and services across the supply chain. At a time when the asset-light business model is gaining currency in the supply chain narrative, new-age technologies such as AI can develop a strong backbone for an effective rollout of the business model. 

Meanwhile, sweating the assets being the key determinant of the supply chain efficiency, the supply chain management companies need to aggressively leverage advanced technologies to strengthen their transit intelligence, routing as well as route optimizing capabilities. 

Time sensitiveness of goods and demand for shorter transit time play a pivotal role in formulating the supply chain and distribution strategy. For e-commerce and e-grocery players, shorter transit time strengthens their competitive edge in the market. To meet such efficiency-led demand, supply chain companies need to keep the variable components in the operational dynamics under control. AI and ML with predictive capabilities help in tackling these components, thus making the supply chain operations resilient. By adopting these advanced technologies, supply chain management companies can mitigate interruptions and enhance responsiveness.  

Al and ML add to the accuracy and efficiency of the predictive mechanism. At a time when operational complexities are increasing and the margin of error is decreasing, tech-empowered supply chain operations can lead to enhanced productivity, superior capacity planning, improved inventory management, process automation, and reduced uncertainties. By analyzing historic data, AI predicts future customer demand trends which leads to lower inventory holding costs. 

Leveraging data and algorithms, AI and ML enhance the delivery process and improve demand forecasting. Having said that, in some cases, AI and ML haven’t been able to deliver the desired results due to a lack of quality and standardized data. To eliminate data silos, the supply chain companies need to train their employees in capturing data and maintaining communication with all the key supply chain stakeholders.

The domestic logistics sector has been a late adopter of AI or ML. As the speed of delivery has become critical, supply chain management companies need to accelerate the adoption of these new-age technologies.

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