While Danone's transformation focused on speed and freshness through network redesign, Goodyear's North American Tire (NAT) division faced a different but equally critical challenge: how to manage overwhelming complexity in product variety and inventory placement. When a new leadership team took the reins at NAT, the division was sliding toward significant losses, with poorly targeted inventory reductions leading to declining service levels and frequent stockouts. Yet within this crisis lay an opportunity to demonstrate how strategic consolidation, customer segmentation, and disciplined planning processes could transform a struggling operation into a profitable powerhouse. Throughout this lesson, you'll discover how NAT's systematic approach to complexity reduction provides a blueprint for managing tens of thousands of SKUs across multiple locations while actually improving customer service.

The NAT transformation reveals a counterintuitive truth about inventory management: having products everywhere doesn't necessarily mean better service. Before the transformation, NAT maintained inventory of all products at all locations, believing this maximized availability. Yet this approach created 5.3 million units of monthly forecast variance and chronic stockouts of popular items while slow-movers gathered dust. The solution required challenging the assumption that all products and all customers needed the same service level. By the end of this transformation, NAT had reduced inventory by 15%, improved forecast accuracy from 60% to 85%, and dramatically reduced variance to just 1.4 million units monthly—all while maintaining or improving service levels for critical customers and products.

The journey to inventory optimization begins with a simple but powerful insight: not all products deserve equal treatment in your distribution network. NAT discovered that attempting to stock every SKU at every location was not only expensive but actually degraded service for high-volume items. When you spread limited resources across 50,000 SKUs, as many distributors do, you inevitably run short on fast-movers while slow-movers consume valuable warehouse space and working capital. The mathematics are compelling: if 60% of your SKUs generate only 15% of revenue—a typical pattern—then maintaining these items at twelve locations means you're tying up twelve times the safety stock for products that rarely sell.

To achieve NAT's 15% inventory reduction, you must first categorize your products using ABC analysis based on both volume and profitability. A-items are your high-volume, high-margin products that customers expect immediately—these typically represent 20% of SKUs but 65% of revenue. B-items are moderate-volume products with steady but less frequent demand, usually 30% of SKUs generating 20% of revenue. C and D items form the long tail: specialty products, obsolete items, or customer-specific configurations that together might represent 50% of your SKUs but only 15% of revenue. NAT's breakthrough was recognizing that C and D items don't need to be immediately available everywhere to satisfy customers.

The consolidation strategy involves creating a single master warehouse for low-volume items while maintaining distributed inventory only for high-runners. When NAT consolidated 30,000 low-volume SKUs from multiple warehouses to a single central facility, they eliminated massive redundancy in safety stock. Consider the mathematics: if you need two weeks of safety stock for a slow-moving item, maintaining it at twelve locations requires 24 weeks of inventory. Consolidating to one location requires only two weeks plus perhaps an extra week for distance—an 87% reduction in safety stock for that item. Multiply this across thousands of SKUs, and you understand how NAT achieved $4.5 million in working capital liberation.

The operational execution of consolidation requires careful attention to three critical factors. First, you must establish clear service level agreements that differ by product category. A-items maintain next-day delivery from local warehouses, B-items ship within 2-3 days from regional centers, and C/D items ship within 5 days from the central facility. Second, you need robust systems to route orders automatically to the appropriate fulfillment location—customers shouldn't have to know or care where products ship from. Third, you must manage the transition carefully, moving products in phases rather than all at once. NAT accomplished this by starting with the slowest-moving 10% of SKUs, proving the model worked, then expanding to additional categories. This phased approach allowed them to throughout the transition.

NAT's second breakthrough involved recognizing that the one-size-fits-all service model was both expensive and ineffective. Before transformation, NAT provided the same service level to every customer, from their largest fleet accounts to occasional retail buyers. This egalitarian approach seemed fair but ignored the economic reality that serving different customers costs dramatically different amounts. A customer ordering full truckloads of popular tires costs far less to serve than one requesting mixed shipments of specialty sizes. By aligning service levels with customer value, NAT discovered they could actually improve satisfaction while reducing costs.

The customer segmentation process begins with comprehensive profitability analysis that goes beyond simple revenue ranking. You must calculate the true profit contribution of each customer after accounting for all costs to serve: order processing, special handling requirements, payment terms, returns processing, and technical support. NAT's analysis revealed a stark reality that many companies discover: 20% of customers generated 75% of profits, while the bottom 50% of customers contributed only 5% of profits but consumed 30% of service resources. This Pareto distribution is remarkably consistent across industries, yet most companies continue treating all customers equally.

Creating service tiers requires careful balance between differentiation and fairness. NAT established three tiers with clear value propositions for each. Platinum customers—the top 20% by profitability—received 24-hour delivery on all items, dedicated account management, customized billing, and first priority during shortages. These customers justified the premium service through their volume, payment reliability, and strategic importance. Gold customers—the middle 30%—received next-day delivery on A/B items and 3-day delivery on C/D items, with online account management and standard billing terms. Bronze customers—the remaining 50%—received 2-day delivery on popular items and 5-day on specialty items, with self-service ordering and prepayment requirements for custom items.

Let's examine how this customer segmentation strategy might be discussed internally before implementation:

• Victoria: I don't understand how we can tell half our customers they're getting slower service. Won't they just go to competitors?
• Ryan: Actually, when we surveyed Bronze-tier customers, 60% said they'd prefer a 5% discount with longer delivery times over our current service.

The final element of NAT's transformation—and often the most challenging culturally—involves implementing a disciplined Sales and Operations Planning (S&OP) process that dramatically improves forecast accuracy. Before S&OP implementation, NAT suffered from the same ailment plaguing many companies: 5.3 million units of monthly forecast variance with sales providing overly optimistic projections, operations understating capacity, and nobody taking ownership for accuracy. The S&OP process forced accountability and transparency, reducing variance to just 1.4 million units within eighteen months. This 74% improvement in forecast accuracy freed up millions in working capital while virtually eliminating stockouts on critical items.

The monthly S&OP rhythm creates a structured dialogue between commercial and operational functions that breaks down silos and forces collaborative decision-making. Week 1 focuses on demand review where sales presents updated forecasts based on customer intelligence, market trends, and promotional plans. Crucially, these aren't wish lists but commitments—sales leaders must sign off on forecasts and are measured on accuracy, not just whether they exceed them. Week 2 involves supply review where operations presents capacity constraints, production schedules, and inventory positions. Week 3 brings pre-S&OP reconciliation where gaps between demand and supply are identified and options developed. Week 4 culminates in an executive S&OP meeting where senior leaders make strategic trade-offs between service, cost, and working capital.

The transformation from 60% to 85% forecast accuracy requires three fundamental changes in organizational behavior. First, you must establish single-number forecasting where all functions work from the same demand projection. Before S&OP, NAT's sales team maintained optimistic forecasts for commission planning while operations kept conservative forecasts for production scheduling—neither bearing any relationship to actual demand. The S&OP process forced agreement on one number that everyone owned. Second, you need to measure and publish forecast accuracy by product, customer, and salesperson, creating transparency that drives improvement. NAT posted accuracy scores publicly and included them in performance reviews, making it socially unacceptable to consistently miss forecasts. Third, you must create mechanisms for rapid response when demand deviates from forecast, such as weekly deviation meetings and preset escalation triggers.

The mathematical impact of improved forecast accuracy on inventory requirements follows a precise relationship. Safety stock requirements are calculated using the formula: Safety Stock = Z-score × Standard Deviation of Demand Error × Square Root of Lead Time. The Z-score represents the desired service level—for example, a Z-score of 1.65 provides 95% probability of not running out of stock. As forecast accuracy improves from 60% to 85%, the standard deviation of demand error decreases by approximately 40%. This means you can reduce safety stock by 40% while maintaining the same service level, or alternatively, dramatically improve service levels with the same inventory. For NAT, with $30 million in inventory, this improvement freed up $12 million in working capital—cash that could be redeployed for growth initiatives or returned to shareholders.