The logistics industry is rapidly changing and moving towards automation to leverage large-scale operations. Today more and more businesses are going digital as it gets complex to interpret a large amount of data irrespective of any sector. Some industries are already leveraging modern technologies to maintain their large-scale operations and improve productivity through automation.
The supply chain industry has been severely affected by the pandemic and the consequent disruptions that have forced it to rethink and adopt smart contingency plans. If the whole supply chain process gets automated then various challenges in the logistics industry can be solved, this can be done by integrating AI and data analytics.
As per STATISTA, the adoption rate of artificial intelligence (AI) is predicted to grow for companies operating in supply chains from 2022 to 2025. In 2022, 11% of decision-makers believe that AI is crucial for the logistics industry, and is anticipated to increase by 38 % by 2025. Do you wonder what reasons contribute to the adoption of Artificial Intelligence and data analytics in the logistics industry?
Let’s figure out how big Data Analytics and AI contribute to supply chain optimization-
Better Inventory Management
Integrating AI technology will foster inventory management by adjusting stock and order requirements through demand analysis. It will give a tentative idea of stock requirements and lower the risk of inventory stockouts. While data analytics analyzes data from various sources and offers real-time insights regarding inventory.
Demand Forecasting and Planning
Through their algorithms, AI and data analytics, help predict the demand for the product by analyzing historical data and market trends. It helps warehouse employees make informed decisions and plan the inventory needs accordingly. Such predictions increase customer satisfaction by meeting their demand on time and boosting sales further.
Greater Visibility of Transportation Routes
AI with its data analytics and algorithms offers real-time data regarding weather conditions and traffic patterns, this helps decision-makers adjust or change the routes which will lead to improved delivery time and thus enhance the overall efficiency of the supply chain.
Automate Scheduling for the Supply Chain Loading Process
To gain direct, real-time visibility into the loading process, today’s advanced supply chain firms employ a combination of hardware, software, and supply chain data analytics. The information acquired can also be utilized to avoid mishappening or unexpected issues by sending alerts through notifications to take quick corrective actions.
Cost Optimization
Data analytics by analyzing historical data can help identify the operations that are incurring huge costs and give ideas for the areas for cost reduction. It proves to be helpful for decision-makers in optimizing procurement, production, and distribution processes. Therefore, applying AL and analytics in the supply chain helps analyze economic profit-enhancing benchmarks.
Final Words
The benefits that artificial intelligence offers to logistics are unmatchable and can’t be ignored. Today for supply chain industries, integrating AI can lead to staying ahead of the competition. By leveraging technologies, logistics can achieve an incomparable level of efficiency, optimized operations, and increased customer satisfaction.
We at Canopus Infosystems, can help you optimize your supply chain operations by leveraging the powerful combination of AI and data analytics, and help you to accelerate your shift towards a self-drive supply chain.
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