Intralogistics in the Food Retail Industry: Mastering Best-Before Dates, FEFO, and High Turnover Rates

The food retail industry places special demands on intralogistics. Hardly any other industry must combine such a high turnover rate with strict requirements for freshness, shelf life, temperature control, and traceability. At the same time, customers expect high product availability, a wide selection, and short delivery times. What seems like a given on the sales floor actually requires precisely coordinated warehousing and material flow processes behind the scenes.

Whether in a food retailer’s central warehouse, a wholesaler’s distribution center, or a food manufacturer’s logistics operations: goods must not only be moved quickly but also identified, stored, prioritized, and delivered according to clear criteria. The best-by date, batch affiliation, and compliance with defined temperature ranges influence nearly every step of the process.

Added to this are seasonal fluctuations in demand, an increasing variety of product assortments, and rising expectations regarding delivery speed. Intralogistics must therefore reconcile different requirements that can often conflict with one another in day-to-day operations. Speed must not come at the expense of product quality; high warehouse utilization must not impair the accessibility of goods; and efficient order picking must not jeopardize traceability.

How can these requirements be reconciled? The key lies in a combination of well-thought-out warehousing strategies, transparent inventory management, suitable warehouse technology, and process control that takes into account the unique characteristics of the food industry.

In the food retail sector, inventory is not defined solely by item number, quantity, and storage location. For many products, the best-by date also determines how long the goods can still be sold or processed. For fresh goods with a short shelf life, this information is particularly relevant for daily inventory management.

The best-by date indicates the date until which a food product retains its specific properties when stored properly. It must be distinguished from the use-by date of highly perishable foods. Products whose use-by date has passed may no longer be sold. When the best-before date has expired, the situation must be assessed differently: The product is not automatically spoiled, but its continued usability must be evaluated in accordance with applicable requirements and the product’s current condition.

For intralogistics, this means: Inventory must be managed in such a way that its shelf life is traceable at all times and can be factored into order fulfillment in a timely manner.

A warehouse management system (WMS) should therefore not only record how many units of an item are available, but also which best-before dates apply to which sub-inventories. Only then can inventory be prioritized effectively, critical remaining shelf lives be identified, and suitable goods be selected for upcoming orders. It is not enough to record the best-by date just once upon receipt of goods. The information must remain available throughout the entire warehousing process: during putaway, stock transfers, replenishment, order picking, and preparation for shipment.

An example illustrates the challenge: There are 300 units of an item in the warehouse. One sub-inventory has a remaining shelf life of ten days, another of 35 days. If both sub-inventories are picked according to the “first-in, first-out” principle without considering the best-by date, there is a risk that the goods with the longer shelf life will be shipped first. The goods with a shorter shelf life remain in stock and continue to lose economic value.

Appropriate inventory management therefore takes into account not only physical availability but also shelf life, order requirements, and, where applicable, customer-specific minimum remaining shelf lives. This combination of inventory information and operational process control is particularly crucial in the food retail sector.

A central principle of food logistics is FEFO—“First Expired, First Out.” This means that inventory with the earliest expiration date is prioritized for removal.

FEFO is often contrasted with the FIFO principle (“First In, First Out”). While FIFO considers the order in which goods are received, FEFO is based on the expiration date or the stored shelf-life information.

For many food products, FEFO is the more appropriate control logic. This is because a shipment that arrived yesterday may have a shorter remaining shelf life than inventory that has been in storage for a longer period. This can happen, for example, when different production batches, suppliers, or production dates overlap. In such cases, FIFO can lead to unnecessary inventory losses. FEFO, on the other hand, supports shelf-life-oriented inventory rotation and helps improve the economic utilization of existing inventory.

Implementation, however, is more challenging than the rule might initially suggest. The system must know the shelf-life data for individual inventory items, generate appropriate picking recommendations, and translate these into actual warehouse processes. At the same time, the selected goods must meet the requirements of the respective order. This is particularly relevant when customers require a specific minimum remaining shelf life. Although inventory with the earliest expiration date must be prioritized according to FEFO, it must not automatically be used for every order. If the goods do not meet the contractually agreed-upon remaining shelf life, a more suitable inventory must be selected or availability must be clarified accordingly.

Physical conditions also play a role. If the FEFO-prioritized inventory is located in a hard-to-reach storage location, while newer goods are available directly at the picking zone, correct retrieval may require additional walking distances or stock transfers. A high inventory turnover rate can only be achieved if the warehouse layout, replenishment strategy, and picking rules are coordinated. FEFO is therefore not merely a function of the warehouse management system. It is an end-to-end process requirement that must extend from goods receipt through warehouse organization to picking and shipping control.

In addition to the best-before date, batch management is an essential component of food logistics.
Batches make it possible to assign goods to specific production or manufacturing contexts. In the event of a quality deviation, a recall, or another safety-related incident, it must be possible to trace which inventory is affected and where the corresponding goods were delivered.

The traceability requirements stem, among other things, from the relevant food safety regulations. According to principle set forth in Article 18 of EU Regulation No. 178/2002, food businesses must generally be able to trace from whom they sourced food and to which businesses they delivered it. Depending on the product, process, and business relationship, additional documentation and labeling requirements may apply.

For intralogistics, this means that batch information must not be managed in isolation within inventory management, quality assurance, or production documentation systems. It must be linked to actual inventory levels and goods movements. When a pallet is received, the batch must be uniquely identified. If a pallet is split across multiple storage locations, the assignment must not be lost. The same applies to replenishment movements, partial withdrawals, mixed pallets, and the fulfillment of customer orders. It becomes particularly challenging when an item is available in multiple batches simultaneously. The system must then be able to distinguish which quantity belongs to which batch and which units were actually picked. Simple item inventory management is not sufficient for this.

In practice, therefore, unambiguous identification and posting processes are essential. Depending on the requirements, barcodes, GS1-compliant identification standards, suitable scanner solutions, or other automatic identification methods may be used. What matters most is not so much the specific technology as the reliability of data capture during ongoing operations. Traceability must work in both directions. On the one hand, it must be possible to determine from which delivery and batch existing inventory originates. On the other hand, it must be possible to trace which customers or downstream locations received goods from a specific batch.

A robust database can significantly reduce the effort involved in the event of a recall. Instead of preemptively blocking large portions of the product range, affected inventory and goods movements can be narrowed down more precisely—provided that the recorded data is complete, accurate, and available in a timely manner. Traceability is thus not merely a matter of documentation. It directly influences how quickly a company can respond to discrepancies, identify affected goods, and maintain delivery capability for unaffected inventory.

Not all food products can be stored and transported under the same conditions. Dry goods, fruits and vegetables, dairy products, meat, fish, and frozen goods have different requirements regarding temperature, humidity, storage duration, and handling.

Many distribution centers therefore operate with separate temperature zones.
In addition to uncooled storage areas, there are refrigerated zones and frozen storage areas, whose specific temperature requirements depend on the product, legal regulations, and operational specifications. This separation has a direct impact on warehouse organization. Goods must be assigned to the appropriate storage areas. Routes between the zones must be designed as efficiently as possible, and the time sensitive products spend outside the specified temperature conditions must be limited.

The challenge is not limited to the actual storage process. Goods receipt, quality control, order picking, and loading are also temperature-critical process steps.

For example, if goods are left in an uncooled staging area for an extended period, this can compromise product quality. Equally problematic are poorly coordinated handoffs between warehouse areas and shipping. Especially with high order volumes, even short delays can add up. A well-thought-out intralogistics concept therefore takes into account not only the storage capacity of the individual temperature zones but also their throughput, the handoff points, and the timing of the processes. Added to this are technical and organizational requirements. Refrigerated and frozen storage areas require suitable warehouse equipment, temperature-resistant equipment, and processes that function reliably even under demanding environmental conditions. Depending on the application, factors such as icing, condensation, limited visibility, or the load-bearing capacity of equipment and components must also be taken into account.

Temperature control must also be documented and monitored to the extent required for the respective products and processes. Deviations should be detected promptly and addressed according to defined procedures. Digital data collection can help link relevant information to goods movements and inventory levels. The central task is to align temperature requirements with intralogistics objectives. High throughput rates are only meaningful if the goods remain within the specified conditions throughout the entire material flow.

In the food retail sector, time windows for many processes are tight. Stores require regular restocking deliveries, food service establishments must ensure product availability, and online orders should be fulfilled as quickly as possible. At the same time, inventory levels often need to be managed in a way that prevents both excessive capital tied up in inventory and avoidable write-offs. The result is significant operational pressure. Goods receipt, putaway, restocking, order picking, and shipping must be closely coordinated. Delays in one stage of the process quickly affect downstream areas.

This is particularly evident in order picking. Here, various requirements come into play: Orders must be picked completely and correctly, best-before dates and lot specifications must be adhered to, and the prepared goods must be available in time for loading. A high turnover rate is therefore not achieved solely through faster picking movements. It also depends on the quality of inventory data, the organization of storage locations, and the availability of suitable replenishment stock.

If a picking station runs out of stock even though the item is still available in the warehouse, this results in additional walking distances and wait times. If an employee must first search for suitable FEFO stock because the storage location information is incomplete, the process is further prolonged. If multiple orders with different remaining lead time requirements are processed simultaneously, the complexity increases even further.

Proactive replenishment control is therefore a key lever. The system should identify which items are needed at the picking stations, when stock needs to be replenished, and which suitable inventory is available for this purpose. Order release also plays a role. If too many orders are sent to picking at the same time, this can lead to overcrowded staging areas, conflicting material movements, and delays in shipping. A release schedule that is coordinated in terms of timing and capacity helps distribute the workload and avoid bottlenecks.

Short delivery times also heighten the importance of reliable master data and clear prioritization rules. Express orders, regular store deliveries, and time-sensitive fresh items may require different processing priorities. These must be defined in such a way that operational control remains transparent and does not lead to conflicting movement orders. The goal is not to accelerate each process step in isolation. What is crucial is a stable overall flow in which goods are made available in the correct order, with the appropriate characteristics, and at the required time.

Demand in the food retail sector is by no means consistent. Holidays, barbecue and gardening seasons, vacation periods, promotional weeks, and seasonal products lead to significant fluctuations. Added to this are short-term changes in demand, such as those caused by weather events or special market conditions.

These fluctuations have a direct impact on intralogistics. Certain items must be moved in significantly larger quantities within a short period of time, while other products continue to be in demand at the usual frequency. At the same time, incoming shipments may be delayed, and available warehouse space may be utilized to varying degrees.

A particular challenge is that additional volumes do not automatically lead to more available processing capacity. Storage locations, picking areas, conveyor systems, personnel, and loading docks remain limited. When several high-demand product categories simultaneously reach high throughput levels, bottlenecks quickly arise. Shelf life also influences the planning of seasonal inventory. For non-perishable dry goods, larger stocks can be held for a relatively long time under suitable conditions. For fresh foods, such a strategy is only useful to a limited extent. Here, sales forecasts, delivery frequencies, and warehouse capacities must be more closely coordinated.

Therefore, historical sales data, current order trends, and information on expected promotional volumes are relevant for planning. The more readily this information is available, the easier it is to prepare for staffing needs, warehouse space allocation, and replenishment processes. From an operational perspective, it is not enough to simply absorb seasonal peaks with additional labor. The order in which orders are processed, the allocation of picking stations, and the distribution of goods to appropriate warehouse areas must also be taken into account.

A flexible warehouse organization can help position items with particularly high temporary demand closer to the picking zones. This requires that such adjustments do not compromise FEFO logic, batch separation, or temperature requirements.

Seasonal resilience thus results from a combination of planning, flexible processes, and sufficient transparency regarding actually available capacities.

The requirements described above illustrate why simple inventory management is insufficient for many food companies. The key is the link between information about the goods and the specific workflows in the warehouse.

A warehouse management system plays a central role in this. It maps inventory levels and storage locations, processes goods movements, and supports the control of put-away, stock transfers, replenishment, and order picking. When properly configured, it also takes into account best-before dates, batches, restricted stock, and other relevant characteristics of the goods. It is important to distinguish this system from others. An Enterprise Resource Planning (ERP) system typically manages overarching commercial and logistical data. A Warehouse Management System (WMS) controls warehouse processes in greater detail. A Transportation Management System (TMS) supports the planning and execution of shipments. Depending on the system landscape, tasks and functions may be distributed differently.

For the food industry, it is particularly important that the relevant information remains consistent across all systems. A correctly recorded best-by date is of little use if it is not taken into account during order transfer. Reliable batch assignment is only helpful if it is maintained during stock transfers and partial withdrawals. And precise inventory management does not resolve bottlenecks if replenishment control does not respond to the actual requirements of order picking.

The quality of master data forms an essential foundation for this. Items must be stored with the relevant logistical properties. These can include, for example, packaging units, dimensions, weights, temperature requirements, shelf-life rules, and batch management specifications. Physical goods movements must also be reliably tracked. If pallets are moved without the transaction being promptly recorded in the system, a discrepancy arises between the digital inventory and the actual situation in the warehouse. Such discrepancies lead to time-consuming searches, picking errors, and unnecessary interruptions.

Automated identification, mobile data capture, and appropriate integration of the relevant systems can help reduce such sources of error. However, the appropriate technical solution depends on the size of the operation, the product portfolio, the warehouse structures, and the existing processes. A high-performance system is therefore not an end in itself. Its value is demonstrated by whether it provides the right information at the right time and supports employees in executing processes error-free.

Technical requirements vary significantly depending on the food processing facility. A central warehouse with high pallet throughput has different requirements than a picking warehouse with many small-part items or a distribution center with multiple temperature zones. When selecting suitable warehouse technology, therefore, storage capacity and potential throughput are not the only decisive factors. Equally important are the product mix, access frequency, turnover profile, shelf-life requirements, and the necessary flexibility to handle fluctuations in demand.

Conventional racked warehouses, for example, can be a sensible choice where different items must remain flexibly accessible. Dynamic warehouse solutions or automated systems can help reduce travel distances and improve space utilization when used with suitable products and stable throughput profiles. Automated conveyor and sorting technology can support the flow of materials between individual process areas. However, every technical solution also comes with its own set of constraints. High storage density can affect the accessibility of individual stock items. Automated systems require suitable interfaces and must be integrated into the overarching process control system. In refrigerated and frozen storage areas, the specific environmental conditions must also be taken into account.

Particularly when it comes to FEFO requirements, it is important to assess how flexibly the system can manage different expiration dates and batches. A technical solution must not only handle high volumes but also enable the correct selection and retrieval of goods.

During seasonal peaks, the question also arises as to how well a system can handle fluctuating load profiles. A solution that operates very efficiently under consistent workload may place additional demands on buffer space, order control, or personnel when volumes fluctuate significantly. Automation should therefore always be based on an analysis of the actual processes. The first step is to identify bottlenecks, sources of error, and unnecessary movements. Only then can one assess whether an organizational adjustment, an improvement in system control, or a technical investment promises the greatest benefit.

To assess the performance of their intralogistics, food companies need meaningful key performance indicators. It is not enough to look solely at the number of picked items or the number of pallets moved daily. High performance is only sustainable if the quality of the processes is also up to standard. Incorrectly assigned batches, inappropriate shelf lives, or inaccurate inventory levels can cause financial losses and impair delivery capabilities.

Relevant key performance indicators may include:

• Throughput: How many pallets, cartons, or order items are moved per unit of time?
• Picking accuracy: What percentage of orders are picked completely and correctly?
• Inventory accuracy: How closely do the inventory levels recorded in the system match the actual quantities?
• Write-offs due to best-by dates: What product losses result from expired best-by dates or insufficient remaining shelf life?
• Delivery readiness and on-time delivery: How reliably are orders made available in full and at the agreed-upon time?
• Replenishment performance: How often do wait times or interruptions occur at the picking stations?
• Temperature deviations: How often do significant deviations occur, and how are they addressed?
• Traceability: How quickly can affected batches and associated goods movements be identified?

These metrics should not be viewed in isolation. For example, an increase in picking performance may go hand in hand with a decrease in accuracy if employees are working under high time pressure. Better warehouse utilization, in turn, can lead to longer access routes. Losses due to best-before dates must also be analyzed in detail. Not all write-offs originate in the warehouse. Sales forecasts, purchasing decisions, supplier terms, and actual demand also play a role. However, intralogistics can help make existing inventory visible in a timely manner and prioritize picking accordingly.

A meaningful system of key performance indicators therefore links operational performance, product quality, inventory management, and delivery service. This makes it possible to identify conflicting objectives and implement improvements where they will actually have an impact.

Intralogistics in the food retail industry is an interplay of many interdependent processes. Shelf life, batch management, temperature requirements, and high turnover rates cannot be optimized independently of one another. Every decision regarding storage location allocation, order release, or replenishment can have an impact on other process steps.

An efficient organization therefore begins with a clean data foundation. Best-before dates and lot numbers must be reliably recorded and remain traceable across all relevant goods movements. Building on this, inventory strategies such as FEFO must be consistently implemented and aligned with actual customer requirements. Equally important are clearly defined processes for refrigerated and frozen sections, proactive replenishment control, and capacity planning that accounts for seasonal peaks. Warehouse technology and automation can support these processes but cannot replace a well-thought-out organizational structure or reliable data quality.

Particularly crucial is the ability to consider operational performance and product safety together. Fast goods movements are not an end in themselves. They must ensure that the right products arrive at the right recipient in the appropriate quantity, with sufficient shelf life, and in compliance with the relevant quality requirements.

In the food retail industry, intralogistics is far more than just the organization of storage locations and goods movements. It forms the operational foundation for ensuring that freshness, availability, traceability, and cost-effectiveness remain compatible with one another.

Best-by dates and FEFO determine which inventory should be removed and when. Batch management creates the foundation for targeted traceability. Refrigerated and frozen logistics require consistent monitoring of temperature conditions. At the same time, short delivery times and seasonal spikes in demand must be managed without compromising process quality and inventory transparency. The key prerequisite is an intralogistics system in which the physical flow of goods and digital process control are seamlessly integrated. When inventory is reliably identified, withdrawal rules are tailored to the goods, and replenishment, order picking, and shipping are coordinated, throughput and delivery service can be improved, and avoidable product losses can be reduced.

For companies in the food retail sector, this means: It is not the speed of a single process step that determines a warehouse’s performance, but rather the interplay of all processes. Only when shelf life, product quality, inventory management, and material flow are considered together can an intralogistics system be created that consistently meets the industry’s specific requirements.

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