SKU Management: How to Optimise Your Catalogue and Supply Chain

Managing an extensive product catalogue may seem like a way to boost sales by offering greater variety. However, without clear criteria around profitability and turnover, poor SKU management often leads to the opposite outcome: excess stock, inaccurate forecasting and unnecessary operational complexity that hinders overall supply chain efficiency.

In this article, we’ll explore the risks of SKU proliferation, the most effective segmentation methods, and the tools that help you make data-driven decisions, complete with numerical examples and real use cases.

What Is an SKU and Why Is It the Core Unit in Logistics and Planning?

SKU stands for Stock Keeping Unit, which refers to the smallest inventory unit a business manages. It’s a unique code that combines reference, format, flavour, size, or any other relevant attribute for sales and logistics. Working with SKUs allows each supply chain process to calculate precise quantities, timelines and costs. That’s why the SKU is the common operational currency across departments, if just one SKU is understocked or overstocked, the entire value stream is affected.

Beyond inventory control, SKU is also the base unit for defining product mix, setting safety stock policies and calculating margins per line. When the number of SKUs increases without assessing profitability or turnover, visibility fragments and decision-making becomes reactive. Effective SKU management is therefore the foundation of accurate demand planning and efficient execution in both production and warehousing.

Why SKU Proliferation Threatens Operational Efficiency

The rise of e-commerce and customisation has led many companies to expand their catalogues to target increasingly niche markets. This trend, known as SKU proliferation, increases the volume of master data, planning parameters and picking operations, resulting in more failure points and higher capital tied up in stock.

As references multiply, forecasting errors rise because historical demand becomes diluted. Each new SKU introduces additional changeovers in production, more dispersed transport routes, and extra warehouse locations, all driving up handling and logistics costs. In short, uncontrolled proliferation undermines efficiency from forecasting through to final delivery.

How an Oversized Catalogue Impacts Forecasting, Inventory and Production

As the number of SKUs grows without a clear strategy, complexity increases across the supply chain. Each additional SKU requires its own forecast, stock parameters and often unique setup in the factory and warehouse. This results in more data to manage, more potential failure points, and production capacity fragmented into micro-batches. The consequence? Less accurate planning, higher inventory levels, and suboptimal resource use. Let’s take a closer look at how these impacts play out in forecasting and operating costs.

Why Forecast Error Increases with More SKUs

Statistical models need a solid history to identify patterns. When a reference only sells a few dozen units a month, noise outweighs the signal and MAPE (Mean Absolute Percentage Error) can exceed 40%. Aggregation (SKU → family → category) becomes less reliable if the terminal branches have sparse data, reducing the trustworthiness of high-level forecasts.

The Hidden Costs of Setup and Capacity Complexity

Every new SKU means more format, colour or recipe changes. In sectors with costly setups (e.g. paints, cosmetics, food), line downtime rises, effective capacity drops, and order queues grow. Plants shift from efficient batch production to micro-lots, increasing energy use, waste, and cleaning costs. In the warehouse, atomisation increases locations, picking paths, and errors. In transport, incomplete loads result in half-empty lorries.

The Most Effective SKU Segmentation Methods

There’s no one-size-fits-all method for classifying and managing large catalogues. The key lies in combining techniques based on volume, demand variability, and network complexity.

At the operational level, companies often rely on value-turnover matrices (ABC-XYZ) to set service policies, and multi-echelon inventory optimisation (MEIO) to define safety stock levels across the supply chain. Knowing when to apply each approach makes the difference between bloated inventories and a supply chain running on just the right capital.

When to Use ABC-XYZ vs. MEIO

The ABC-XYZ matrix is ideal when your main goal is to differentiate service levels and replenishment cycles without complex calculations. Use it when operating in one or a few locations, with short lead times and low inter-node correlation. By combining volume (A-B-C) with variability (X-Y-Z), you might, for example, set daily reviews for an A-X item and produce a C-Z only to order, reducing waste and idle machine time.

MEIO, on the other hand, is most valuable when managing multiple centres with significant demand interdependencies. If your network suffers stockouts in one node while others hold surplus, MEIO calculates the global optimum for safety stock, factoring in transit times and consumption correlation. It’s especially useful in geographically dispersed chains, long procurement cycles, or asynchronous demand channels (e.g. physical retail vs e-commerce).

Practical Example: Calculating Turnover and Margin to Decide Whether to Retain or Delist an SKU

Let’s say SKU is classed as C-Z: it sells 500 units per year with a margin of €8 per unit and holds 250 units in average stock. That’s a turnover of 2 times per year and a gross contribution of €4,000. If the annual holding cost for that stock is €4,500, the product destroys value. Based on this segmentation, you’d either delist the SKU or shift it to make-to-order, freeing up capital and capacity for higher-return A-X items.

What Are the Benefits of Cutting Low-Value SKUs?

Removing low-margin, slow-moving SKUs frees up factory and warehouse space, reduces capital tied up in inventory and lightens operational complexity. Cutting just 10% of the catalogue can, according to FMCG benchmarks, reduce total inventory by up to 18% and improve OTIF (On-Time In-Full) by around 3 points, because stock is concentrated on items that customers actually want.

With fewer SKUs, factories group production into longer runs, increasing OEE (Overall Equipment Effectiveness) and reducing changeovers, waste and energy consumption. In warehouses, low-rotation locations are freed up, picking paths are shorter, and the risk of obsolescence or expiry drops. The overall impact? Greater liquidity and agility, plus more capacity headroom to launch new, high-potential SKUs.

Tools and Dashboards for SKU Management: What Software Helps You Decide with Data?

For a basic audit, spreadsheets may suffice. But dynamic segmentation and continuous policy adjustment call for more advanced tools. The most effective option is a supply chain planning solution with integrated analytics. These platforms connect sales, inventory and capacity in a single data model. They provide real-time Pareto curves showing volume, margin and turnover; automatically recalculate ABC-XYZ matrices with customisable thresholds; and simulate the impact of delisting an SKU on inventory and service levels.

Additionally, a BI dashboard is essential to visualise key KPIs and apply filters by product family, channel or region. When linked to RPA (Robotic Process Automation), the system can trigger alerts, for instance, if an SKU shifts from B-Y to C-Z, a notification prompts a review to consider delisting or shifting to make-to-order. Combining SCM software, BI visuals and RPA alerts shifts decision-making from gut feeling to real-time data, accelerating catalogue rationalisation and capital efficiency.

How Smart SKU Management Powers Your Supply Chain

Simplifying your catalogue and segmenting SKUs by value and turnover is one of the fastest ways to unlock capital and boost operational efficiency. When you eliminate low-contribution items, inventory aligns with real demand, production becomes more stable, and warehousing becomes more efficient.

At the same time, forecast accuracy improves because models focus on data-rich time series, reinforcing the reliability of your entire supply plan. These benefits are amplified when powered by planning software that connects sales, inventory and capacity data, automates ABC-XYZ or MEIO classifications, and runs instant what-if simulations.

In short, data-driven SKU management turns dead stock into cash, creates room for innovation, and, above all, aligns your commercial strategy with your operational reality. Ready to audit your catalogue?

At Imperia, we offer a comprehensive supply chain optimisation platform that helps our clients boost their efficiency. If you’d like to know how we can help, don’t hesitate to request a free consultation with our experts. We look forward to speaking with you!