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OEMs Think They Have High Obsolete Inventory. Why They're Wrong.

In the intricate world of automotive manufacturing, Original Equipment Manufacturers (OEMs) grapple with a persistent challenge – managing Superseding SKUs (Stock Keeping Units) and the resultant accumulation of obsolete inventory. A Superseding SKU refers to a newer version of a product that replaces the older version, often due to evolving consumer preferences. However, some OEMs face a unique complication where the connection between superseding SKUs and their root SKUs is not seamless, leading to inflated obsolete inventory. Beyond the direct costs incurred, this challenge ripples across the supply chain, impacting the timely assembly of inventory-loaded vehicles that are shipped across the globe. SkuCaster, fortified by a self-learning AI model, emerges as a beacon of hope by addressing the core roots of this challenge and streamlining the intricate logistics of mounting inventory-packed vehicles for efficient delivery to dealers.

OEM challenges with superseded SKUs

The Intricacies of SKU Superseding and Supply Chain Challenges

The conundrum of SKU superseding and obsolete inventory generation stems from the dynamic nature of consumer preferences. OEMs endeavor to anticipate shifting demands and align their production accordingly. However, as consumer tastes evolve, certain vehicle features and components may lose their charm, necessitating the introduction of new SKUs. This phenomenon sets off a series of challenges:

  1. Pervasive Obsolete Inventory: The outgoing SKUs leave behind an inventory surplus that becomes obsolete. This burden translates into storage costs, write-offs, and potential markdowns.

  2. Impaired Supply Chain Flow: The transition from old SKUs to new ones disrupts the supply chain. Production delays ensue, impacting the timely availability of vehicles and parts.

  3. Challenges in Compatibility: Introducing new accessories or components might necessitate alterations to vehicle design and assembly. This poses quality control concerns and generates additional costs.

  4. Global Coordination Struggles: Orchestrating SKU shifts across diverse international branches presents a challenge, given the diverse regulatory frameworks and consumer behaviors.

SkuCaster's AI Model: Forging Efficient Supply Chains


The crux of SkuCaster's transformative influence lies in its self-learning AI model, a dynamic entity fueled by data-driven insights. The journey of this AI model begins with data – a trove of market trends, consumer behaviors, and pertinent OEM factors. The AI model undergoes meticulous data cleansing and mapping, ensuring it is fed accurate, coherent, and relevant data. This process is akin to preparing a blueprint before constructing a building; it establishes a robust foundation for informed decision-making.


As the AI model ingests this data, it evolves into a predictive engine. By analyzing historical data, market trends, and myriad variables, the AI model forecasts the trajectory of SKUs – predicting those that will thrive and those that will fade into obsolescence. This predictive prowess empowers OEMs to make prudent decisions, thwarting the risks of obsolete inventory accumulation and optimizing their SKU lineup.



OEM Parts Superseding SKUs

The Chain Reaction: SkuCaster's Impact on Supply Chain Logistics

While SkuCaster addresses SKU management head-on, its transformative influence extends beyond inventory walls. Let's delve into the logistical realm of shipping and supply chains:

  1. Precise Inventory Mounting: With SkuCaster's insights, OEMs accurately anticipate which parts will gain traction. This precision translates into better-informed inventory mounting for vehicles bound for shipment.

  2. Efficient Aircraft Loading: For entities that transport vehicles via planes, such as automakers utilizing cargo planes, SkuCaster's predictions enhance loading efficiency. The precise allocation of parts ensures minimal waste of space and weight, optimizing cargo load.

  3. Minimized Overheads: As obsolete parts are curtailed, the weight of redundant parts in cargo is mitigated. This directly reduces costs associated with shipping excess inventory and maintaining unnecessary weight.

  4. Responsive Dealership Fulfillment: By avoiding superseded SKUs, OEMs ensure that the mounted inventory is precisely aligned with dealer demands. This streamlines the replenishment process and accelerates time-to-market.

Conclusion: A Holistic Transformation


In the automotive industry's quest for operational excellence, SKU management is a linchpin. SkuCaster, propelled by its self-learning AI model, offers a comprehensive solution to the SKU superseding challenge. Beyond eliminating costs and optimizing SKU assortments, it introduces efficiency and accuracy into supply chain logistics.


As OEMs worldwide adopt SkuCaster, they embrace a transformation that transcends traditional inventory management. SkuCaster ushers in a new era, one characterized by precision, responsiveness, and efficiency in supply chain logistics. The ripple effect of accurate SKU predictions and informed inventory mounting reverberates across continents, enhancing global OEM operations, streamlining supply chains, and ensuring that vehicles arrive at dealerships with the right parts. With SkuCaster as a guide, the once-problematic landscape of SKU superseding and supply chain inefficiencies transforms into a future marked by efficiency, profitability, and sustained success.

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