Demand volatility

Fluctuations in customer demand make forecasting difficult. Without enough inventory, a business may lose sales or end up with dissatisfied customers. With too much inventory, it faces high holding costs. The products may become obsolete or unusable—a major risk for perishable goods.

Supply chain disruptions

Sometimes suppliers are unable to deliver goods due to unforeseen circumstances such as natural disasters, labor strikes or other global events. If no contingency plan is in place, disruptions can lead to stockouts and prevent businesses from fulfilling orders.
 

Supply chain complexity

A supply chain may involve multiple suppliers, production facilities, warehouses and distribution centers. Its elements might be spread across different geographical locations. These networks are known as multi-echelon supply chains. Decisions made at one echelon can significantly affect others. The more complex the supply chain, the more challenges a business may face in predicting lead times, costs and reliability.
 

Product complexity

If a business offers a wide range of products with different variants, inventory needs become more challenging. Each product variant may have different lead times, suppliers and demand patterns, which complicates inventory management and demand forecasting.
 

Seasonality

Demand for a product can rise or fall at different times of the year, depending on holidays, weather or special events. Without careful planning, businesses can be underprepared—or end the season overloaded with unsold inventory.
 

Changing business models

Changing business models, driven by factors like e-commerce growth and direct-to-consumer sales, make inventory management more complex. For example, omnichannel retail requires businesses to balance stock across multiple sales channels and fulfillment locations.
 

Changing customer demands

Customers are seeking personalized products, greater variety and fast, on-time delivery. This means businesses need new approaches to forecasting, stock management and distribution networks.
 

Reduced holding costs

Accurately forecasting demand and maintaining optimal stock levels limit the expenses associated with excess inventory. Such costs include storage, insurance and potential losses if products are at risk of obsolescence.
 

Reduced chance of stockouts

Inventory optimization makes it more likely that products will be in stock when customers want them.
 

Operational efficiency

Inventory optimization helps streamline supply chain processes, which in turn reduces labor and handling costs. It might minimize the risk of rush orders or expedited shipping costs that might arise from poor inventory planning.
 

Improved cash flow and profitability

Optimized inventory levels free up working capital that can be invested in other areas of the business. By balancing inventory costs with service levels, businesses can maximize their bottom line.
 

Enhanced supply chain resilience

Inventory optimization reduces a businesses’ vulnerability when confronted with supply chain disruptions. By making sure there is a buffer stock to meet demand during unexpected events, the business can continue to fulfill its orders in challenging times.
 

Customer satisfaction

With fewer stockouts and delays, customers are more likely to get the products they want when they want them.
 

Informed decision-making

Data-driven inventory optimization provides insights that allow businesses to see their products, customers and operations in a more complete way.
 

Greater sustainability

Inventory optimization can improve sustainability efforts and might decrease a business’ environmental footprint. It reduces waste by helping businesses avoid overproduction and expedited shipping. It may also limit the space required for storage, leading to lower energy use.
 

ABC analysis

ABC analysis is a method of categorizing inventory items based on their value and importance.

A items are high-priority goods that need to be watched carefully due to their high value or fast turnover. B items are of moderate value and turnover rate. C items are low-value goods with slow turnover rates.

Use case: This inventory optimization approach is useful for businesses with large inventories because it helps them to focus resources on profit-generating A items.

Economic order quantity (EOQ)

EOQ is a model used to minimize total inventory costs. Ordering small numbers of items too frequently, or ordering too many items and having to store and hold them, can lead to high expenses. By calculating the EOQ, businesses can identify the most cost-effective number of items to order.

Use case: EOQ is most useful when businesses have predictable demand and constant lead times.
 

Just-in-time (JIT) inventory

This optimization process aims to keep in-process inventory and carrying costs as low as possible. Materials are ordered and received only when they are needed in the production process. This approach means businesses have fewer goods to store and, often, less waste. But it also requires accurate demand forecasting and reliable suppliers.

Use case: JIT is useful for businesses with limited storage space or those dealing with perishable goods.
 

Multi-echelon inventory optimization (MEIO)

As mentioned, multi-echelon supply chains can involve multiple entities spread across many locations. While some inventory optimization methods address each location separately, MEIO considers the connections between different echelons. MEIO practices can be used to gain a holistic view of the supply chain.

Use case: MEIO is particularly useful for businesses with complex, multi-tier supply chains where inventory decisions at one stage impact others.
 

Vendor-managed inventory (VMI)

With VMI, the supplier has access to the distributor's inventory data and is responsible for maintaining the inventory levels required by the customer. The supplier decides when to replenish and how much to ship, based on agreed-upon parameters. This approach can lead to more accurate inventory decisions as suppliers often have better forecasting capabilities and a broader view of market demand.

Use case: VMI is effective for businesses looking to reduce inventory management costs and improve supplier relationships.
 

Enterprise resource planning (ERP) systems
 

ERP systems connect many business processes into one complete system to streamline activities across an organization. When it comes to inventory optimization, ERP systems can provide real-time visibility into inventory levels, sales, orders and deliveries. They can automate routine tasks such as purchase orders, saving time and reducing human error.
 

Inventory management software

Inventory management software, often included within an ERP system, is specifically designed to track and manage inventory levels, orders, sales and deliveries. It can provide detailed reports on inventory turnover, product performance and other metrics. These inventory management systems help businesses identify trends, forecast demand establish pricing and optimize stock levels.
 

Artificial intelligence
 

Artificial intelligence (AI) and machine learning (ML) can be used to find complex patterns in large datasets. The process can combine historical sales data, market trends, weather patterns and economic data to deliver more accurate insights. This allows businesses to anticipate changes in demand and adjust their inventory levels accordingly.
 

Internet of Things (IoT) devices

In inventory optimization, IoT devices like radio frequency identification (RFID) tags or smart shelves can help track inventory levels in real time. This can give managers and planners early warning of potential stockouts or overstock problems. It also provides greater supply chain transparency and efficiency.
 

Cloud computing
 

Cloud platforms offer scalable and accessible inventory optimization tools. They can improve real-time collaboration and data sharing across an organization and its supply chain. They are sometimes more affordable than on-premises tools, as they eliminate the need for large upfront investments in hardware and software.