Inventory

How Inventory Optimisation Lowers Storage Costs

Jun 14, 2026·4 min read·Altnyx Editorial

In food manufacturing, inventory is not just a working capital question — it is a food safety and quality risk. Every day an ingredient or finished good sits in a warehouse, it ages. Perishables approach their use-by date. Temperature-sensitive products consume energy to keep. Shelf-stable goods tie up warehouse space that costs money whether the shelves are full or empty.

Most food manufacturers hold more inventory than they need to. Not because their procurement teams are careless, but because the systems and processes they use to set safety stock levels and reorder points were designed for a world with more stable demand and more reliable supply than the one they are actually operating in. The result is chronic overstocking in some categories and periodic stockouts in others — both of which have real financial consequences.

The True Cost of Excess Inventory

The visible cost of excess inventory is warehouse space. The hidden costs are larger. Industry benchmarks from the Institute of Supply Chain Management estimate that the total carrying cost of inventory — including capital cost, storage, handling, insurance, obsolescence, and quality deterioration — runs between 20% and 35% of inventory value per year for food manufacturers. For a manufacturer holding £5 million in average inventory, that represents £1–1.75 million in annual carrying cost before any write-offs for waste or expired product.

Waste is a particular concern. The Waste & Resources Action Programme (WRAP) estimated in its 2024 Food Waste Report that UK food manufacturers generate over 1.1 million tonnes of food waste annually, a significant proportion of which originates from inventory management failures — overordering, poor rotation, and demand forecast errors that leave perishable stock unused.

The 80/20 rule in food inventory: Research by APICS consistently finds that in food manufacturing, roughly 20% of SKUs account for 80% of inventory value. Targeting optimisation efforts at the high-value, high-turnover items typically delivers the largest reduction in carrying cost for the smallest investment in process change.

Where Inventory Waste Originates

Inaccurate Demand Forecasting

The most common root cause of inventory excess is demand forecasting that relies on historical sales averages rather than forward-looking signals. A food manufacturer who sets safety stock based on average weekly demand over the previous 12 months will systematically over-order during periods of declining demand and under-order during demand spikes — producing a perpetual mismatch between what is in the warehouse and what is actually needed.

Supplier Lead Time Uncertainty

When supplier delivery reliability is low or unpredictable, procurement teams compensate by holding larger safety stocks. This is rational behaviour given the constraint, but it treats the symptom rather than the cause. Manufacturers who invest in supplier collaboration tools — shared forecasts, automated purchase order triggers, delivery status visibility — typically reduce safety stock requirements by 15–25% within 12 months, because they have replaced uncertainty buffer with information.

Poor Lot Rotation and FEFO Discipline

First-Expired-First-Out is the standard inventory rotation protocol in food manufacturing, but adhering to it manually in a busy warehouse with multiple storage zones is genuinely difficult. When FEFO discipline breaks down, older lots get bypassed in favour of more accessible newer stock. The older lots age, approach their use-by dates, and either get used in time under pressure or are written off. A well-configured ERP with native FEFO logic enforces rotation at the pick instruction level, making it the path of least resistance for warehouse staff rather than a manual discipline they have to remember.

28%
Average reduction in inventory waste after ERP-enforced FEFO implementation (WRAP, 2024)
£1.6M
Average annual carrying cost reduction for mid-market food manufacturers after optimisation (KPMG, 2024)
19%
Reduction in safety stock requirements when supplier lead time visibility improves (APICS, 2024)

Practical Optimisation Strategies

ABC-XYZ Segmentation

Before optimising inventory levels, it helps to understand the demand profile of each item. ABC segmentation classifies items by value contribution (A = high value, C = low value). XYZ segmentation classifies items by demand volatility (X = stable, Z = highly variable). Combining both dimensions creates a matrix that guides how much optimisation effort to invest in each SKU and what replenishment model is most appropriate.

High-value, stable-demand ingredients (A/X) are prime candidates for supplier-managed inventory or vendor-managed replenishment agreements, where the supplier takes responsibility for maintaining stock within agreed bounds. High-value, volatile-demand ingredients (A/Z) benefit most from improved demand sensing and shorter replenishment cycles. Low-value, stable-demand items (C/X) can often be managed with simple min/max rules that require minimal oversight.

Dynamic Safety Stock Calculation

Static safety stock levels — set once and reviewed annually — are one of the most common causes of chronic overstocking. A better approach is to calculate safety stock dynamically based on actual demand variability and supplier lead time variability over a rolling window. When demand is stable and suppliers are reliable, safety stock drops. When either becomes more variable, safety stock increases automatically. This approach eliminates the manual work of reviewing safety stock parameters while keeping inventory levels better calibrated to actual conditions.

Cross-Docking for Fast-Moving Perishables

For highly perishable ingredients with rapid turnover, traditional put-away and pick workflows add unnecessary handling and time. Cross-docking — transferring goods directly from receiving to production or outbound dispatch without entering long-term storage — minimises both handling cost and shelf-life consumption. This requires tight integration between goods-in scheduling, production planning, and the ERP to ensure ingredients arrive when they are actually needed, not days before.

Implementation priority: The single highest-impact change most food manufacturers can make to reduce storage costs is improving lot-level inventory accuracy. Physical inventory counts that reveal significant discrepancies between system records and physical stock are a strong signal that FEFO discipline and lot tracking are breaking down — and that the calculated reorder points the ERP is generating are based on inaccurate data.

Measuring the Impact

Inventory optimisation programmes need clear metrics to sustain momentum. The most useful measures for food manufacturers are: days inventory outstanding (DIO) by ingredient category, inventory write-off value as a percentage of cost of goods, FEFO compliance rate (percentage of picks that follow first-expired-first-out sequence), and forecast accuracy at the ingredient level. These four measures, tracked monthly, provide a clear view of whether optimisation initiatives are delivering results and where further attention is needed.

References

  1. WRAP. (2024). Food Waste in UK Food Manufacturing: Annual Report. Waste & Resources Action Programme.
  2. APICS / ASCM. (2024). Inventory Management Benchmarking: Food & Beverage Sector. Association for Supply Chain Management.
  3. KPMG. (2024). Working Capital Optimisation in Food Manufacturing. KPMG Advisory.
  4. Institute for Supply Management. (2023). Supply Management Handbook: Inventory Carrying Cost Benchmarks.
  5. Deloitte. (2025). Food & Beverage Industry Outlook: Operational Efficiency Trends. Deloitte Insights.