Optimize

/ˈɒptɪmʌɪz/
verb
1. make the best or most effective use of (a situation or resource).
(Oxford Languages)

One of the biggest challenges in supply chain management is understanding counterintuitive principles—like the “bullwhip effect.” This concept is so difficult to grasp that a “Beer Game” simulation was created to show how minor demand fluctuations can wreak havoc upstream.

Equally perplexing is inventory optimization. Many assume that increasing inventory is necessary to improve service levels. But businesses that get inventory optimization right can boost service levels by 3-5% while reducing overall inventory by 15-30%.

“Wait, what? Doesn’t reducing inventory hurt service levels?”

This common reaction highlights a misunderstanding about how inventory should be managed. To clarify, let’s explore how modern inventory optimization strategies help businesses achieve high order line fill rates (OLFR) while improving efficiency and profitability.

Why Inventory Optimization Matters More Than Ever

Today’s businesses face ongoing supply chain disruptions, demand volatility, and increasing pressure to free up working capital. To stay competitive, companies must adopt inventory advanced inventory optimization strategies that:

• Improve product availability without overstocking
• Reduce waste and excess holding costs
• Increase working capital efficiency
• Balance profitability with customer service excellence

Rethinking Traditional Inventory Segmentation

If you’re still relying on ABC inventory segmentation, you may be experiencing excess inventory or stockouts. While ABC classification was effective decades ago, it’s too simplistic for today’s complex supply chains.

Planners using ABC often apply the same inventory policies across diverse SKUs, leading to inefficiencies. It worked for inventory management, but not for true inventory optimization.

A Better Way: Inventory Mix Optimization

Unlike ABC, which segments SKUs into broad categories based on business value, inventory mix optimization categorizes items by service class. This approach enables businesses to tailor inventory policies to different types of products, such as:

• High-margin items
• Critical spare parts
• Long-tail, low-demand SKUs
• Private label vs. branded products

Using advanced AI-powered inventory planning tools, businesses can apply stock-to-service curves to optimize safety stock levels at each SKU-location. This allows companies to achieve higher service levels for critical products while reducing excess inventory for slow-moving items.

Real-World Results: Lubinski’s Inventory Optimization Success

Lubinski, the exclusive importer of Citroën and Peugeot vehicles in Israel, transitioned from ABC-based inventory planning to an AI-driven inventory mix optimization system. With 20,000 parts in stock—75% of them slow movers—Lubinski sought to improve efficiency without compromising service levels.

Through a guided supply chain assessment, Lubinski compared their traditional approach to a data-driven inventory optimization model. The results were transformative:

• 25% reduction in overall inventory costs
• 33% fewer rush orders
• €1.5 million in freed-up working capital
• Sustained 95-96% service levels
• Significant planner productivity improvements

Their new system became nearly self-sufficient, allowing planners to focus on strategic initiatives rather than manual inventory management. One planner even remarked,

I wish we had done this sooner!”

The Future of Inventory Optimization

Lubinski’s success is not unique. Hundreds of businesses worldwide are achieving similar results by embracing AI-powered inventory optimization. Unlike a classroom simulation, our guided assessments use real-world data to drive actionable improvements.

In today’s fast-moving and unpredictable supply chain landscape, companies that optimize inventory effectively will have a competitive edge. The key to success? Adopting a service-driven approach that ensures availability where it matters most—while keeping inventory lean and efficient.

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