Modern supply chains have become more complex and costly than ever due to globalization, increasing customer expectations, sudden demand fluctuations, and unexpected disruptions. Fluctuations in fuel prices, high inventory carrying costs, inefficient logistics operations, and a lack of visibility put significant pressure on companies' profitability.
While traditional optimization methods provide benefits up to a certain point, smarter solutions are needed to cope with this complexity and achieve real cost advantages. This is where artificial intelligence (AI) offers revolutionary opportunities to reduce costs by shifting supply chain management (SCM) from reactive approaches to a proactive, predictive, and automated model. In this article, we will examine with concrete examples how artificial intelligence can be used to reduce costs at different links of the supply chain.
To reduce costs, you first need to understand where they arise. The main cost items in the supply chain include:
Artificial intelligence has the potential to intervene in each of these cost items with intelligent solutions.
AI provides cost optimization at many points in the supply chain with its data analysis, learning, and automation capabilities:
Problem: Inaccurate forecasts lead to unnecessarily high inventory levels or failure to meet demand, resulting in customer loss. Both are costly.
AI Solution: Machine Learning (ML) algorithms analyze numerous factors such as historical sales data, seasonality, promotions, market trends, weather, and even social media sentiment to generate much more accurate demand forecasts.
Cost Advantage: Inventory levels are optimized, excess inventory carrying costs decrease, and the risk of stockouts is reduced.
Problem: Maintaining the right amount of inventory at the right time and place is a critical balancing act.
AI Solution: AI considers accurate demand forecasts, lead times, production capacity, and variability to determine the optimal safety stock and reorder point for each product and location. It can automate ordering processes.
Cost Advantage: Storage costs decrease, the risk of product obsolescence/spoilage drops, and working capital is utilized more efficiently.
Problem: Factors such as fuel prices, traffic congestion, delivery windows, and vehicle capacity directly affect logistics costs. Especially last-mile delivery can be costly.
AI Solution: AI-based route optimization software dynamically plans routes for the fastest and lowest-cost delivery by using real-time data (traffic, weather, etc.). It optimizes fleet utilization.
Cost Advantage: Fuel consumption and emissions decrease, vehicle idle time is reduced, delivery times improve, and driver efficiency increases.
Problem: Unexpected breakdowns of critical equipment in logistics fleets (trucks, ships, etc.) or warehouses (conveyors, forklifts, etc.) halt operations and lead to high repair costs.
AI Solution: ML models analyzing data from IoT sensors detect potential malfunctions in advance, enabling proactive maintenance planning.
Cost Advantage: Unscheduled downtimes and emergency repair costs decrease, equipment lifespan extends, and operational continuity increases.
Problem: Unreliable or underperforming suppliers can lead to delays and additional costs.
AI Solution: AI can predict risks by analyzing supplier performance data, financial status, and market news. It can offer recommendations for selecting optimal suppliers or diversifying sources.
Cost Advantage: Supply chain disruptions are reduced, costs due to quality issues decrease, and better supplier terms can be negotiated.
Problem: In-warehouse layout, picking routes, and manual processes can lead to inefficiency and high labor costs.
AI Solution: AI can optimize warehouse layout, determine the most efficient picking routes, manage autonomous mobile robots (AMRs), and even automate quality control processes.
Cost Advantage: Labor efficiency increases, picking times shorten, warehouse space is utilized more effectively, and error rates decrease.
Problem: Administrative processes such as order intake, invoice processing, and customs document preparation are slow and prone to errors when done manually.
AI Solution: Using NLP and ML, automatic data extraction, validation, and transfer to relevant systems are automated.
Cost Advantage: Administrative workload and costs decrease, processes speed up, and data entry errors are eliminated.
To fully leverage AI's potential in reducing supply chain costs:
At Corius, we combine our deep expertise in the supply chain and logistics sector with our advanced artificial intelligence and data analytics capabilities. Whether it's developing a custom optimization solution for you or empowering your existing systems with AI, we are your transformation partner throughout the entire process, from strategic planning to implementation and continuous improvement. Our goal is to increase your operational efficiency and help you achieve tangible cost advantages through technology.
Artificial intelligence is a powerful tool for managing complexity in supply chains and identifying and eliminating hidden costs. From intelligent demand forecasting to optimized logistics, predictive maintenance to automated processes, AI applications enable companies to build more resilient, efficient, and ultimately more profitable supply chains. Embracing these technologies is becoming not just an advantage, but a necessity in today's competitive environment.
To discuss in more detail how you can reduce costs in your supply chain with artificial intelligence, contact us.
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