How to Master Supply Chain Segmentation for Inventory Optimisation

How to Master Supply Chain Segmentation for Inventory Optimisation

Supply chain professionals are under increasing pressure to align their inventory with dynamic market demands. But with complex product lines, fluctuating customer expectations, and an ever-evolving landscape, a one-size-fits-all approach simply isn’t enough.

That’s where supply chain segmentation comes in — a strategic approach to tailoring your inventory and supply chain processes to better serve specific customer needs, product categories, and channels. It’s a powerful tool that can drive profitability, reduce waste, and increase customer satisfaction by optimising inventory levels to match demand with precision.

In this post, we’ll dive into the various segmentation techniques — from product and customer segmentation to the impact of AI and machine learning on inventory optimisation. We’ll explore how you can harness these strategies to create a supply chain that’s responsive, efficient, and adaptable to market changes.

Key Takeaways:

• Leverage data-driven segmentation: Tailor your inventory strategies to specific customer needs and product types by using detailed data on product complexity, customer behaviours, and demand trends.
• Prioritise demand-driven replenishment: Align your replenishment strategies directly with customer demand patterns, ensuring products are available when needed and avoiding costly overstock situations.
• Utilise AI and machine learning: Implement predictive technologies to refine demand forecasting and improve inventory management, reducing stockouts and excess inventory.
• Segment by product: Optimise inventory based on product stages, ensuring that high-demand or perishable items are replenished more frequently while slow-moving stock is more carefully managed.
• Incorporate multi-tiered segmentation: Use a combination of product, customer, and geographic segmentation to optimise different aspects of your supply chain, enhancing responsiveness and efficiency across markets.
• Tailor service strategies to customer needs: Align your production and service models to the expectations of different customer segments, from in-store buyers expecting high availability to online customers seeking seamless ordering.
• Refine replenishment methods: Adapt replenishment strategies like reorder points, periodic checks, and demand-based triggers to your business’s specific needs, balancing stock levels to meet demand without excess.
• Focus on reducing operational inefficiencies: Identify and mitigate inefficiencies in your supply chain by improving visibility, streamlining processes, and implementing automated solutions.

Defining Inventory Segmentation and Its Role in Aligning Stock with Demand

Understanding Supply Chain Segmentation

In today’s rapidly evolving business environment, supply chains are becoming increasingly intricate. Factors such as expansion, globalisation, outsourcing, rising costs, and the need for customised customer experiences contribute to this complexity. The traditional one-size-fits-all approach is no longer viable, as it often leads to increased inventory costs and fails to meet diverse customer requirements effectively.

Consequently, businesses face continual pressure to devise strategies that accommodate the varied demands of different markets. A pivotal strategy in addressing this challenge is supply chain segmentation. This approach is designed to tailor supply chain solutions to meet the specific needs of various products, customers, and suppliers, based on their value to the organisation. This value might manifest as enhanced profitability, superior customer service, improved strategic alignment, or a combination of these factors.

Best Practices for Demand-Driven Inventory Replenishment Planning

Optimising demand-driven inventory replenishment involves several best practices, including efficient warehouse management, Service-oriented replenishment, improved supply chain visibility, real-time forecasting, and the utilisation of machine learning and AI. These practices are integral to enhancing the precision and flexibility that distinguish businesses in a competitive landscape.

Efficient Warehouse Management

Warehouse management is pivotal to a well-functioning supply chain, especially during replenishment. Advanced automation streamlines warehouse operations, bolstering efficiency across the supply chain. Spatial intelligence and ergonomic design are fundamental to warehouse optimisation, facilitating efficient movement and storage while reducing the time and energy required to fulfil orders. Through intelligent zoning and innovative technologies such as drones for inventory checks, businesses can elevate their warehouse management to a sophisticated level that supply chain professionals value.

Procedure-Oriented Replenishment

Planning for vendor delays early in the process ensures quick back-order fulfilment and minimises time gaps in inventory replenishment. Procedure-oriented replenishment requires a comprehensive analysis of historical data, allowing businesses to design strategies that accommodate variations in delivery times. This proactive approach mitigates the risk of inconsistent stock levels, ensuring a seamless supply chain operation.

Improving Supply Chain Visibility

Enhanced supply chain visibility facilitates real-time adjustments and identifies gaps where time and resource leakages may occur. Transparency in operations fosters efficiency in order fulfilment, demand forecasting, and the management of warehouse and internal stock levels. With improved visibility, businesses can confidently manage their operations, making swift adjustments as needed to maintain optimal supply chain performance.

Utilising Machine Learning and AI

AI enhances supply chain operations by establishing feedback loops between demand, inventory, and sourcing. Machine learning processes data on sales orders, seasonal peaks, and demand history, presenting it in a comprehensive format. By employing AI and machine learning in inventory replenishment, businesses can accurately predict demand fluctuations, fine-tuning inventory levels to create an efficient and responsive supply chain.

Real-Time Forecasting

Real-time forecasting updates and automates the supply chain, eliminating bottlenecks and unnecessary delays. This foresight allows businesses to anticipate market needs, adjusting inventory levels instantaneously to ensure product availability when and where it is needed. Such agility sets apart the exceptional from the ordinary in supply chain management.

By meticulously applying these strategies, companies can achieve inventory segmentation optimisation and enhance their supply chain segmentation efforts, ensuring they remain agile and responsive to market demands.

Exploring Types of Supply Chain Segmentation and the Importance of Customer Segmentation

Supply chain segmentation is a transformative strategy that can greatly enhance business efficiency and responsiveness by tailoring operations to the precise needs of diverse market segments. Understanding the different types of supply chain segmentation is essential for implementing the most effective strategies.

1. Product-Based Segmentation

Product-based segmentation involves categorising supply chain processes based on the unique attributes of the products, such as size, perishability, or value. This method enhances the efficiency of production, storage, and distribution by tailoring operations to meet the specific needs of each product group. It is particularly advantageous for organisations managing diverse product portfolios, as each category may require distinct handling, storage, or shipping solutions. Key considerations for product segmentation include:

• Total number of SKUs
• Pricing structures of SKUs
• High-margin versus low-margin products
• High-volume versus low-volume products
• Movement rates, such as fast-moving versus slow-moving goods
• Lifecycle variations, including perishable versus non-perishable items
• Quality differentiation, such as low-quality versus high-quality products

2. Channel-Based Segmentation

Channel-based segmentation focuses on tailoring supply chain operations to the specific requirements of different sales channels, such as retail, wholesale, or e-commerce. Businesses that operate across multiple platforms benefit from this approach, as it allows for precise inventory and logistics optimisation to meet the unique demands of each channel. Essential factors for channel-based segmentation include:

• Lead time expectations
• Direct-to-consumer versus business-to-business models
• Offline versus online sales
• Single-source versus multi-source channels
• Use of in-house distribution networks versus third-party logistics providers

3. Geographic Segmentation

Geographic segmentation addresses regional variations in demand, supply chain infrastructure, and regulatory compliance. By adapting operations to the unique characteristics of different regions, businesses can improve delivery speed, lower transportation costs, and align with local laws. Critical factors for geographic segmentation include:

• Local regulatory and compliance requirements
• Regional variations in customer demand
• Transportation and logistics capabilities within each region

4. Service Level-Based Segmentation

Service level-based segmentation focuses on aligning supply chain resources with the varying service expectations of customers. Whether offering expedited shipping, premium handling, or standard delivery, this approach ensures supply chain activities are aligned with specific service promises. Differentiation points within this segmentation include:

• Premium versus standard service offerings
• Same-day versus standard delivery options
• Customisation requirements based on customer preferences

5. Industry-Based Segmentation

Industry-based segmentation divides supply chain operations according to the distinct needs and challenges of each industry served. This strategy enables businesses to comply with unique regulatory requirements and tailor their processes to meet industry-specific operational demands. It ensures that the supply chain is both compliant and optimised for each sector’s unique environment.

How the ABC/XYZ 9 box method can classify inventory levels

The ABC/XYZ 9-Box Method for Classifying Inventory Levels in Supply Chains

Defining the ABC/XYZ 9-Box Method

The ABC/XYZ 9-box method is a robust analytical framework that merges ABC analysis, focused on inventory value contribution, with XYZ analysis, which assesses demand variability and predictability. By combining these methodologies, a 3×3 matrix is created, classifying inventory into nine categories. This classification enables precise management strategies tailored to the unique characteristics of each inventory type.

ABC Analysis evaluates inventory by its value and frequency of use:

• A: High-value items contributing disproportionately to overall value, typically the top 20%.
• B: Medium-value items with moderate frequency, contributing about 15% of total value.
• C: Low-value, high-frequency items that account for the remaining 5% of value.

XYZ Analysis considers demand patterns:

• X: Items with stable demand and high forecast accuracy.
• Y: Items with moderately variable demand and medium predictability.
• Z: Items with highly volatile demand and low forecast accuracy.

This combined matrix ensures nuanced strategies for balancing operational efficiency, cost control, and service level optimisation.

How the 9-Box Method Classifies Inventory Levels

1. Raw Materials Allocation Inventory management begins with categorising raw materials by their production value and demand predictability. High-value raw materials with stable demand (AX) require precise monitoring and synchronisation with production schedules to minimise inventory carrying costs. Conversely, low-value yet volatile items (CZ) necessitate redundancy or safety stock buffers to mitigate potential supply chain disruptions. This dual approach ensures critical inputs are always available while optimising costs.
2. Work-in-Progress (WIP) Segmentation Work-in-progress inventory represents an opportunity to streamline operations by evaluating items’ completion stages and value potential. Stable, high-value WIP items (AX) are prioritised for integration into lean manufacturing processes to maximise throughput efficiency. For WIP items with moderate value and variable demand (BY), scenario planning is employed to address bottlenecks and maintain production flow despite fluctuations. This ensures operational efficiency across varying production stages.
3. Finished Goods Optimisation Finished goods require careful alignment with market demand profiles and profitability metrics. High-value items with stable demand (AX) are positioned for seamless distribution, leveraging forecasting and inventory management tools to maintain optimal service levels. Meanwhile, low-value goods subject to volatile demand (CZ) are managed through strategic regional segmentation and demand-pull systems, reducing overstock and ensuring responsiveness to customer needs.
4. Safety Stock Management Effective safety stock strategies depend on balancing demand variability with item criticality. Predictable, high-value items (AX) can maintain optimised safety stock levels, reducing unnecessary inventory while safeguarding against disruptions. For less critical items with volatile demand (CZ), flexibility is achieved through adaptive strategies such as vendor-managed inventory (VMI) or dynamic safety stock buffers. This ensures operational continuity without excessive inventory investment.
5. Excess or Obsolete Inventory Mitigation Managing excess or obsolete inventory is crucial for maintaining financial health and operational agility. High-value items with unpredictable demand (AZ) are candidates for strategic markdowns or liquidation, recovering valuable working capital. Stable yet low-value items (CX) are better suited for repositioning in alternative markets or implementing long-tail sales strategies. This targeted approach minimises waste and maximises profitability across inventory types.
6. Transit Inventory Visibility Transit inventory requires visibility and strategic utilisation to support supply chain efficiency. High-value items with stable demand (AX) benefit from rigorous tracking systems and synchronisation with demand forecasts to minimise delays and ensure availability. For volatile items with varying levels of importance (BZ, CZ), dynamic routing and real-time risk mitigation strategies are deployed to maintain flexibility and prevent disruptions. This enhances the reliability of inventory flows across the supply chain.

Strategies and Methodologies for Leveraging Cost-to-Serve in Effective Replenishment Planning

In the realm of supply chain segmentation, leveraging cost-to-serve becomes pivotal for devising effective replenishment strategies. Here, we explore four primary inventory replenishment methods and their operational dynamics.

Reorder Point Strategy

The reorder point strategy necessitates the selection of a stock level that signals when inventory replenishment should occur. For example, if you maintain a stock of 1,000 pillows, the reorder point might be set at 200 pillows. Upon reaching this threshold, the inventory is reviewed to determine replenishment needs. Establishing a maximum inventory level prevents overstock, ensuring that replenishment occurs when inventory falls below the minimum threshold. In this scenario, if the minimum is 200 and the maximum is 1,000, the reorder quantity would be 800 pillows. This method requires a robust IT system for real-time inventory monitoring.

Periodic Strategy

The periodic strategy involves replenishing inventory at predetermined intervals. For instance, you might review inventory levels every three months to decide on replenishment. If inventory levels remain adequate, no order is placed until the next review cycle. Even if stock depletes before the scheduled interval, replenishment occurs only at the designated review points. This approach demands precise planning to align with supply chain segmentation, particularly when forecasting demand and managing inventory segmentation optimisation.

Top-Off Strategy

Also known as lean time replenishment, the top-off strategy capitalises on periods of slow picking operations to replenish stock to optimal levels in forward pick locations. This method employs minimum and maximum thresholds akin to the min/max replenishment strategy. It is particularly effective for businesses with short picking windows, such as those dealing with high-demand, high-velocity SKUs. By utilising slow demand periods to top off inventory, this strategy enhances efficiency during peak times.

Demand Strategy

The demand strategy is straightforward: replenishment is driven by demand. Restocking or reordering aligns strictly with what is necessary to fulfil orders. This approach necessitates meticulous planning to accommodate future demand fluctuations. Maintaining a safety stock is crucial, serving as a buffer to adapt to random shifts in supply and demand, thereby mitigating the risk of stockouts during sudden demand surges.

By integrating these methodologies within a framework of supply chain segmentation, businesses can optimise their replenishment planning, ensuring that inventory segmentation optimisation aligns seamlessly with market demands and operational efficiency.

Tim Richardson
Development Director
Iter Consulting