The Hidden Costs of Bad Slotting in the Warehouse

By Evan Danis, Corporate Marketing Manager, Lucas Systems

Slotting optimization is often overlooked when discussing warehouse efficiency, yet poor slotting can have significant direct and indirect costs. When products are stored inefficiently, warehouses experience increased labor costs, reduced productivity, higher equipment wear, inventory shrinkage, and more errors. A Deloitte report noted that slotting optimization can deliver 10-20% savings on warehouse operating costs.

It’s a difficult and potentially expensive problem. For some retailers for instance, the diverse SKU portfolio available to B2C customers, coupled with the randomness of ordering patterns, can be a challenge when considering product placement in the DC. In addition, we see many inefficiencies in workflows for DCs, where they try to incorporate new requirements for both B2C and B2B customers in legacy systems with dated or inflexible configurations.

Furthermore, large scale moves during core hours can impact picking SLA’s and moves outside of core hours can incur premium rates of OT. In slotting, as with other warehouse execution operations, organizations need to focus on continuous optimization and operational transformation. That means DCs need tools that can help them manage the week-to-week, day-to-day, even the hour-to-hour changes that occur in the DC. Before we talk about answers, let’s break down the cost factors and quantify their impact on operations.

Why optimizing slotting is your first step to labor savings

Labor is the single largest expense in most warehouse operations, with order picking alone accounting for 50-70% of total operating costs. When slotting is suboptimal, pickers must travel longer distances to retrieve items, reducing their efficiency. For example, if a picker typically completes 100 picks per hour but poor slotting reduces this to 80, productivity drops by 20%. What’s the possible annual additional labor cost caused by a 20% drop in picking productivity due to poor slotting? Well, let’s assume for the example:

• Full labor cost per hour: $40
• Pickers per shift: 30
• Shifts per day: 2
• Total pickers per day (30 x 2): 60
• Work hours per picker per day: assume 8 hours

At the lower rate, which includes inefficient slotting, it takes 1.25 hours to complete what previously took just 1 hour, adding 0.25 extra hours per 100 picks. Over an 8-hour shift, a picker completes only 640 picks instead of 800, meaning they’d need 10 hours to maintain previous output—an extra 2 hours per day. In a 2-shift operation with 30 pickers per shift (60 total), that adds up to 120 additional labor hours daily. Over the course of a year (5 days a week, 52 weeks), that totals 31,200 extra hours. At a full labor rate of $40/hour, the result is an estimated $1.25 million in additional labor costs annually—all due to inefficient slotting.

Restocking inefficiencies also drive-up labor costs. If high-demand items are stored in hard-to-reach locations or frequently require replenishment due to small bin sizes, warehouse workers spend unnecessary time on putaway and restocking tasks. Studies suggest that a 10-20% increase in travel time due to inefficient slotting can result in thousands—or even millions—of dollars in additional annual labor costs, especially in high-volume distribution centers.

The hidden drag on warehouse performance

Bad slotting directly impacts a warehouse’s ability to meet demand efficiently. When workers take longer to locate and retrieve items, the overall lines picked per hour decline. Over time, this slowdown can lead to missed shipping deadlines, increased reliance on overtime labor, and potential disruptions in the supply chain. For warehouses processing thousands of orders per day, even a minor decrease in throughput can translate to significant financial losses.

For instance, if a warehouse typically processes 10,000 orders daily and slotting inefficiencies slow the process by 5%, that’s 500 fewer orders shipped per day. Over a month, this could mean 15,000 delayed orders, resulting in dissatisfied customers, increased customer service inquiries, and even lost business.

Slotting slipups can equal costly order errors

Slotting inefficiencies often contribute to mispicks, which lead to incorrect shipments and increased return rates. For example, placing nearly identical SKUs (e.g., same brand and packaging, but different flavors or sizes) in adjacent locations increases the chance of picking the wrong item, especially under time pressure. The cost of a single mispick ranges from $22 to $100 when factoring in labor, reprocessing, reshipping, and lost customer goodwill. In a warehouse processing thousands of orders daily, even a 1% mispick rate could result in hundreds of costly errors per week. Let’s do a general breakdown of what that could look like. Mis-slotting often increases picking errors by 1-3%. For a warehouse processing 1,000 orders/day, even a 2% error rate jump could result in 20 extra order errors/day. Assuming $30 per error (returns, customer service, re-picks), that’s $219,000/year.

Returns not only increase operational costs but also impact customer satisfaction and brand reputation. With e-commerce giants setting the bar for fast, accurate deliveries, businesses with high error rates risk losing customers to competitors.

The bigger picture: Slotting optimization as a cost-saving strategy

While slotting inefficiencies can quietly drain warehouse resources, the good news is that optimization strategies can reverse these costs. Implementing data-driven slotting techniques and automation tools like voice-picking or warehouse execution software, can significantly enhance efficiency.

Investing in warehouse slotting optimization can yield substantial returns. Studies suggest that effective slotting can improve picking productivity, reduce travel time by 20%, and cut mispick rates in half. In a high-volume warehouse, these improvements can translate into six- or seven-figure cost savings annually.

For example, Lucas Systems’ Dynamic Slotting software leverages advanced machine learning algorithms to continuously recommend optimal inventory locations based on key factors like SKU velocity, SKU affinity, product characteristics, slot information, and pick paths. The system generates intelligent, data-driven recommendations that identify the product moves with the highest potential payback, giving warehouse teams clear, actionable insights. Managers can visualize opportunities using intuitive heatmaps, helping them pinpoint areas where slotting adjustments will have the greatest impact.

Beyond automated suggestions, Dynamic Slotting includes powerful analysis tools to support decision-making. Staff can run “what-if” scenarios on specific SKUs or locations to evaluate the potential effects of different slotting strategies. As products, orders, and warehouse processes evolve, Lucas AI continuously adapts, ensuring slotting recommendations stay aligned with changing operational needs.

By optimizing slotting decisions, it can increase productivity by 5-20%, while also improving overall space utilization within the warehouse. The software enhances ergonomics and worker safety by strategically placing products to minimize unnecessary movement and strain. Additionally, it supports higher picking accuracy and reduces the likelihood of inventory errors and product damage, helping warehouses maintain smoother, safer, and more cost-effective operations.

Bad slotting is an often-overlooked cost driver in warehouse operations, affecting labor, productivity, equipment, inventory, and order accuracy. By recognizing these hidden costs and investing in strategic slotting optimization, warehouses can enhance efficiency, reduce operational expenses, and improve customer satisfaction. Given the direct and indirect financial impacts, businesses that prioritize slotting strategies stand to gain a competitive advantage in an increasingly demanding supply chain landscape.

Evan Danis is a marketing and communications leader with over 25 years of experience driving strategy, content, and brand engagement across healthcare, technology, and government sectors. As Corporate Marketing Manager at Lucas Systems, Evan specializes in messaging that aligns with business goals, producing content for digital campaigns, thought leadership, and internal communications. A skilled storyteller and public speaker, he’s also hosted national award ceremonies and podcasts, and taught marketing, communication and advertising at the collegiate level.