Optimizing Supply Chains with AI: The Benefits of Automated Order Allocation

Automated order allocation driven by AI is reshaping how supply chain leaders operate, leading to reduced costs, improved fulfillment accuracy, and safeguarded profit margins. This transformation replaces outdated manual processes with intelligent and real-time decision-making techniques.

In recent times, virtually every company seems to be singing the praises of AI. This technology has claimed a spot on every business agenda, featured prominently in annual reports, and dazzled audiences at industry events. Remarkably, it is integrated into about 97% of supply chains, according to findings from Logility’s Supply Chain Horizons 2025 market study.

However, dissecting the layers of AI implementation reveals a more intricate picture. Only a mere 33% of businesses have applied the technology to tackle specific supply chain challenges, such as order allocation or fulfillment. Surprisingly, many sectors continue to rely on old-school methods in critical areas that affect profit margins and customer satisfaction, even amid escalating risks and costs.

Challenges of Traditional Order Allocation Methods

A glance at manual order allocation quickly reveals its downsides. Supply chain leaders acknowledge that these traditional methods are not just exhausting and time-consuming—they also come at a hefty price. Allocators often find themselves wrestling with countless spreadsheets while IT departments scramble to merge fragmented data. Amidst this chaos, managerial decisions often hinge on gut feelings rather than data-driven insights about which orders to fulfill promptly.

Research conducted by Logility paints a stark picture of these struggles: every organization surveyed grapples with significant challenges related to order fulfillment. The average forecast accuracy stagnates at 48%, and on-time, in-full (OTIF) performance limps along at only 52%. Alarmingly, 48% of supply chain leaders admit their planning horizons stretch just a week into the future, leaving them dangerously exposed to unexpected disruptions. In many firms, even fundamental allocation decisions are made based on outdated knowledge and instinct rather than reliable data.

Notably, the financial repercussions of manual order allocation extend beyond overtime costs and additional fees. Companies routinely face penalties for delayed or incomplete deliveries, damaging trust with key accounts. Allocators become stuck in a cycle of reacting to immediate issues, losing sight of strategic opportunities.

Even when zooming in on specific industries or regions, the challenges persist. For instance, in the apparel sector, 67% of companies experience a lack of customer collaboration, making them particularly vulnerable to abrupt shifts in supply or demand. In Germany, 47% of apparel companies struggle with rigid ERP systems, while 54% of their counterparts in India grapple with variable lead times.

The consensus remains clear: manual allocation methods simply cannot cope with the complexities of today’s markets, resulting in heightened risks and narrowed margins.

Shifting to AI-Enhanced Allocation Strategies

The reasons behind the growing interest in AI are abundantly clear. However, despite the enthusiasm, many organizations tread lightly, with 52% citing legacy systems as barriers, 43% concerned about data security, and 40% lacking confidence in AI-generated outputs.

Most businesses currently find themselves in a “show me first” phase of AI integration. This is where Logility’s Intelligent Order Response solution comes into play. Unlike conventional systems that superficially incorporate AI, this AI-native solution is designed from the ground up to continuously and transparently optimize order allocation decisions. It actively evaluates the entire demand and supply landscape, automates the optimization of most orders, and proactively identifies effective solutions for shortages—all while aligning decisions with strategic business goals, such as margin protection and penalty avoidance.

It’s important to clarify that allocators won’t be replaced. Instead, the true advantage lies in how this technology enhances productivity and decision-quality. Intelligent Order Response offers clear, prescriptive recommendations and transparently outlines trade-offs while allowing human allocators to apply their judgment and intervene with manual adjustments when necessary.

With Intelligent Order Response, organizations can enjoy a harmonious blend of human intuition and AI’s unyielding ability to detect patterns, evaluate constraints, and adjust operations dynamically. This model of automated order allocation leads to fewer surprises, reduced fees for expedited shipments, and far less exposure to penalties.

Your Next Competitive Edge: Embracing Automated Order Allocation

In a landscape marked by volatility, supply chain leaders are on the lookout for AI use cases that can genuinely revolutionize operations, starting with vital processes like order allocation. By integrating automated allocation into their workflows, companies can enhance their promise of fast delivery while continually fine-tuning their order fulfillment strategies based on a real-time, comprehensive understanding of their network’s activities.

Given the ongoing disruptions affecting supply chain operations, the potential benefits of automated allocation are urgent:

• Lower costs from penalties, rushed logistics, and lost customers
• Consistent OTIF performance that fosters customer loyalty
• Freeing up talent to drive strategic growth rather than merely managing daily fires
• A more robust foundation for maximizing margins, even under pressure

Consequently, it is high time for organizations to reassess their order allocation strategies, transitioning from fragile practices to a solid competitive edge.

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