Disclaimer: The views expressed are personal and drawn from the author’s professional experience in large-scale supply chain environments. No proprietary data is referenced.
Introduction
In the evolving world of supply chain strategy, oversized inventory is often left behind. These bulky, non-conveyable SKUs place a heavy burden on both fulfillment operations and transportation costs. Yet many networks default to third-party carriers — even when internal capabilities could offer more cost-effective and scalable alternatives. Based on years of network modeling and strategic planning, this article explores how fulfillment systems can reclaim capacity, reduce cost per package, and create smarter flows for first-party oversized goods.
The Oversized Inventory Challenge
Oversized, or non-conveyable, inventory presents one of the most complex challenges in modern fulfillment. These SKUs typically bypass standard sortation systems and require unique handling, storage, and transportation workflows. In many networks, these products are routed through third-party delivery providers by default, increasing both cost-per-package and delivery variability.
Industry data shows that non-conveyable items typically incur 2–3x higher processing costs than standard packages. Peak season volume can surge 3–3.5x over regular weekly averages. Items often exceed dimensional thresholds (37–59 inches) or weights over 50 lbs, which introduces complex handling, limited routing options, and specialized equipment needs. Additionally, middle-mile bottlenecks are often more pronounced than the last-mile ones in the oversized segment.
The Missed Opportunity in 1P Fulfillment
Many supply chains underutilize their own fulfillment network when managing non-conveyable inventory. While third-party carriers offer broad reach, in-house capabilities often go untapped — especially during non-peak seasons. Detailed cost-benefit analysis reveals significant opportunities to shift non-conveyable items back into first-party fulfillment nodes, unlocking savings and improving asset utilization.
Scenario Modeling and Cost Impacts
By modeling fulfillment scenarios — from full third-party reliance to partial or full in-house fulfillment — a clear picture emerges. Key variables include PO volume attainment, labor capacity, transportation cost per unit, and contractual constraints. Simulations suggest up to $300M+ in annualized savings when oversized inventory is handled internally under optimal conditions.
When modeling cost impacts, key variables should include:
– Seasonal utilization levels
– Labor productivity between conveyable vs. non-conveyable SKUs
– Transportation cube utilization and fill rate
– Network sort density and transit times
The most significant cost savings — $5 to $6 per package — are realized when existing network connectivity and facility capacity allow for regional fulfillment. In some lanes, optimized internal routing has been shown to improve delivery speed by 1–2 days.
Reallocating Capacity and Smoothing Peaks
Off-peak season presents a unique opportunity to reroute non-conveyable volume to underutilized facilities. This improves asset utilization and decreases third-party costs. Aligning PO cycles and fulfillment cadence enables smarter carrier planning and fewer empty miles.
Dynamic routing systems can shift oversized volumes based on capacity availability and regional peak patterns. Planning fulfillment from nodes with complementary seasonal peaks improves throughput and stabilizes costs. Additionally, flexible arrangements between internal and external carriers are key to maximizing cost efficiency without service compromise.
Navigating Trade-offs
Shifting flow internally is not always feasible. Carrier contracts, labor schedules, and regional coverage must all be considered. However, simulation-based planning helps pinpoint when internal fulfillment becomes the superior option.
Design for Flexibility
The future of oversized fulfillment lies in building a flexible network that can shift between 1P and 3P fulfillment based on volume, seasonality, and cost triggers. Such networks are better positioned to control cost-per-package over time.
Conclusion
Oversized goods require thoughtful network design rather than default settings, with data-driven modeling revealing significant hidden capacity within existing networks. Success depends on building integrated planning capabilities that account for seasonal shifts, regular capacity reviews, and continuous cost monitoring. Standardizing operations at key hubs while maintaining workforce flexibility and smart routing technology is crucial for optimal oversized inventory performance.
Author Bio:
Debanshu Sharma is a Senior Supply Chain Manager with over 15 years of experience in logistics strategy, fulfillment operations, and network design. He holds an MBA from the Stephen M. Ross School of Business at the University of Michigan. Debanshu specializes in cost modeling, transportation planning, and simulation-based optimization, and is passionate about sharing practical, data-driven insights with the global supply chain community.
