Sales and Fulfillment
Leveraging AI to Enhance Inventory Management Efficiency
The supply chain is an umbrella term for all activities that are performed to convert raw material into the final product and place it in the hands of the customer. It is a system of interconnected operations that manage the movement of goods, services, information, and finances from their source to the end user. This includes planning, implementing, and overseeing the entire process. Supply chain management (SCM) refers to methodologies a business adopts to enhance the efficiency of its supply chain.
A typical supply chain goes through the following stages:
Step 1: Planning: It involves demand forecasting in the supply chain, capacity planning, inventory management, and determining the optimal supply chain network.
Step 2: Sourcing: Sourcing entails identifying and selecting suppliers who will provide the necessary raw materials, components, or services.
Step 3: Manufacturing: It is the process of converting raw materials or components into finished products. It includes production scheduling, quality control, maintenance, and production efficiency.
Step 4: Delivery (Logistics): Logistics refers to the movement of goods, including transportation, warehousing, inventory management, and order fulfillment.
Step 5: Returns: It refers to the return of goods from customers to suppliers.
Step 6: Inventory management: It involves keeping track of stock levels to avoid stockouts or excess inventory. It includes monitoring raw materials, work-in-progress, and finished goods in warehouses and distribution centers.
Step 7: Customer service: It includes activities like order processing, customer support, and communication to ensure that customer needs and expectations are met throughout the supply chain.
Supply chain activities are driven by various political and global forces, weather, natural events, customer needs, and more. Managing different activities while taking into account the above factors is a nightmare for businesses. This is the reason that companies are turning to Artificial Intelligence (AI) to boost the efficacy of supply chain management. Data shows that 85% of leaders in engineering product development, supply chain, and manufacturing have already adopted AI or are planning to do so. . AI-based SCM aims to establish a central control, or link the production, shipment and distribution of a product.
Role of AI in supply chain management
By leveraging AI, supply chains can achieve a strategic advantage through heightened efficiency and significant cost reduction, creating a foundation for sustainable growth.
Some of the areas where AI plays a role are:
Visibility
Supply chain teams can use AI to track materials, products, and shipments in real time, gaining end-to-end visibility and enabling them to streamline coordination between stakeholders, identify bottlenecks, and manage disruptions.
Automation
Robotic Process Automation (RPA) bots take over routine processes like data entry, invoice processing, etc. Automation reduces errors and boosts the speed and efficiency of processes.
Demand forecasting
Artificial intelligence (AI) plays a pivotal role in demand forecasting by scrutinising customer data, historical data, market trends, and a multitude of external factors, including economic indicators. Advanced machine learning (ML) algorithms are leveraged to produce precise forecasts, which are instrumental in optimising inventory levels. The adaptive nature of ML allows for continuous refinement of these forecasts, empowering businesses to proactively adjust their inventory to align with real-time demand. This dynamic approach significantly reduces waste and prevents costly stockouts or overstocking scenarios. Furthermore, the implementation of automated replenishment systems streamlines inventory management processes, leading to enhanced operational efficiency.
Logistics management
Logistics management, a critical component of supply chain management, can greatly benefit from AI. Dynamic routing algorithms improve transportation efficiency while reducing delays, costs, delivery times, etc.
AI plays a vital role in optimising production schedules, minimising idle times while maximising resource utilisation.
Predictive maintenance
The use of AI tools facilitates preventive maintenance of machinery and equipment by monitoring them in real-time. AI tools provide insights on which corrective action can be taken to prevent equipment failure. This reduces downtime and costs and increases the lifespan of equipment.
Order processing
Order processing is a complex process that can be streamlined by integrating AI. AI-based order processing involves automated order entry and order verification. ML algorithms can detect anomalies and patterns and prevent frauds. AI algorithms can optimise order routing and fulfillment to enhance customer experience.
Customer service
AI algorithms analyse vast volumes of customer data and provide accurate insights. Businesses can provide personalised products and experiences to customers based on these insights. AI-based chatbots and virtual assistants are available 24/7 to address customer queries and provide them with the required support. Bots deliver exceptional customer experiences through human-like interactions.
In Conclusion
AI in the supply chain can optimise capabilities required for accurate capacity planning, enhanced supply chain forecasting, improved productivity, minimised expenses, and greater output while meeting sustainability goals. By integrating AI in SCM businesses can achieve agility, speed, and cost savings thereby gaining a competitive edge.
How can Infosys BPM help?
Infosys BPM offers customised supply chain management solutions to businesses. Our AI-based supply chain management solutions foster growth, reduce costs and enhance productivity. We offer agile solutions that provide a competitive advantage to our clients.
