Company Overview

The automotive component manufacturer is a significant player in the automotive industry, specializing in the production of critical auto components. The company’s expertise lies in delivering mechatronic solutions—which are integrated systems combining mechanics, electronics, and computing—to various sectors, primarily focusing on:

• • Automotive Industry: Supplying parts and systems that are essential for the functioning of vehicles. This includes components related to auto electrical systems, emission control, and fuel efficiency. 
  • Global Reach: The manufacturer operates on a global scale, providing these solutions to Original Equipment Manufacturers (OEMs) in both consumer and industrial markets. 
  • Sustainability Focus: The manufacturer is committed to helping its clients reduce emissions and improve fuel economy, aligning with global trends toward more environmentally friendly automotive technologies. 

Project Goals

The project, undertaken by us, was aimed at addressing two primary objectives:

    1. Procurement Cost Optimization: 

• • • Objective: The primary objective of this goal was to identify hidden opportunities to reduce procurement costs. By reducing procurement costs, the manufacturer can improve its profitability without needing to increase prices or cut other costs, which might affect product quality or operational efficiency. Procurement costs, being a significant component of the manufacturer’s overall expenses, have a direct impact on its profitability. Therefore, finding ways to minimize these costs without sacrificing quality or operational efficiency was crucial.
    • Scope: The focus was on finding areas where costs could be minimized without compromising on quality or operational efficiency. The project required a detailed examination of the procurement process, focusing on the prices paid for parts and components. This involved analysing historical data, comparing costs across different suppliers, and identifying parts where there might be price discrepancies or overpayments

    2. Risk Mitigation in Sourcing: 

• • • Objective: The objective here is to mitigate the risks associated with relying on single-sourced parts. In any manufacturing environment, especially in the automotive sector, depending heavily on a single supplier for critical components can expose the company to significant risks. These risks include potential supply chain disruptions, price volatility, and lack of leverage in price negotiations.
    • Scope: The first step was to identify parts and components that were being sourced from a single supplier. This analysis was crucial to understanding where the manufacturer might be vulnerable to supply chain risks. The project aimed to explore and identify alternative vendors who could supply the same or similar parts to actively reduce the dependency on any single supplier. The alternative suppliers identified had to meet the same quality standards and delivery schedules as the original suppliers to ensure there were no disruptions in the production process.

Challenges Faced by the Manufacturer

The manufacturer faced several challenges in achieving these goals, primarily due to the complexity of its operations:

• • Complexity of Managing Tens of Thousands of Parts: The company deals with tens of thousands of parts, each with its own set of characteristics and requirements. Managing and optimizing procurement for such a large number of items is inherently challenging. These parts vary widely in terms of size, material, function, and supplier base. This diversity adds another layer of complexity to the procurement process. With such a large number of parts, gathering, analysing, and interpreting procurement data becomes a daunting task.
  • Dynamic Pricing: The prices of parts fluctuate over time due to various factors such as market demand, raw material costs, and supplier pricing strategies. Keeping track of these changes and making informed procurement decisions requires robust data analysis. Different suppliers may charge different prices for the same part, depending on their pricing strategies, cost structures, and negotiation dynamics with the manufacturer. Identifying and addressing these inconsistencies is critical for cost optimization.
  • Supplier Cost Comparison: Comparing costs across multiple suppliers for the same or similar parts can be difficult, especially when dealing with such a large and diverse portfolio of components. Suppliers often have complex and opaque pricing structures that make it difficult to compare costs directly. Identifying the most cost-effective suppliers requires detailed analysis and strategic decision-making. Some parts may involve complex cost structures, including tooling costs, setup fees, or volume-based pricing tiers. These factors need to be accounted for in any cost comparison, adding to the complexity.
  • Risk of Single-Sourced Parts: Relying on a single supplier for critical parts exposes the company to significant risks. Any disruption in the supplier’s operations—such as production delays, strikes, or financial difficulties—could lead to supply shortages, halting the company’s production lines. If a single supplier fails to deliver parts on time, it can cause cascading delays across the production process, leading to missed deadlines and potential financial penalties.

Solutions Proposed by Us

To address these challenges, our company proposed and implemented the following solutions:

1.Identification of Price Anomalies:

• • Analysis Process: A thorough analysis of the purchase prices of various parts was conducted from different vendors. This involved comparing prices for the same parts across multiple suppliers to identify any anomalies—instances where the price from one vendor was significantly higher or lower than the average. This comparative analysis was crucial in highlighting discrepancies—whether certain suppliers were consistently charging more than others for the same part. The distribution of prices for each part was analysed across different suppliers. This helped to visualize how prices varied and to spot outliers—suppliers whose prices deviated significantly from the norm.
  • Key Finding: The analysis uncovered that a substantial portion of the procurement budget was being spent on suppliers who charged higher prices. These suppliers were receiving a larger share of the orders, possibly due to historical relationships, perceived reliability, or lack of visibility into more cost-effective alternatives. Conversely, suppliers who offered lower prices were not being fully leveraged. This underutilization could have been due to various reasons, such as lack of awareness of their pricing, concerns about quality or delivery times, or simply inertia in changing established procurement practices.
  • Strategic Opportunity: The primary strategic recommendation was to rebalance the procurement shares among suppliers. This involved shifting a portion of the orders from high-priced suppliers to those offering the same parts at lower prices, without compromising on quality or delivery schedules. By demonstrating the ability to shift volumes to lower-priced suppliers, the manufacturer could also gain leverage in negotiations with higher-priced suppliers, enhancing cost savings. The analysis projected that by implementing this strategic reallocation, the company could reduce its overall procurement costs by 3% to 5%.

2. Clustering of Parts:

The clustering of parts was a crucial component of the procurement cost optimization strategy. This method involved categorizing parts based on their unit rate per gram using an innovative RGB classification system, which allowed for a clear visual representation of cost efficiency across different parts.

• • RGB Classification System: The solution involved classifying parts based on their unit rate per gram using a color-coded system. The unit rate per gram was chosen as the core metric for classification. This metric was calculated by dividing the price of a part by its weight, providing a standardized way to compare parts of varying sizes and materials.

• • 1. Green Parts: Parts classified as green were those with a lower price per unit weight compared to others. These parts were deemed cost-effective, indicating that the company was sourcing them at competitive rates. The green classification suggested no immediate action was needed for these parts.
    2. Blue Parts: Blue parts represented those with a normal price per unit weight, falling within an acceptable range. Parts in the blue category were not overpriced but were also not the most cost-effective. They were within the normal pricing range for their category, suggesting that the procurement process for these parts was generally efficient.
    3. Red Parts: Parts that were identified as red had a higher price per unit weight than expected. The red classification flagged these parts as expensive, indicating potential issues in procurement, such as overreliance on a single supplier, lack of competitive bidding, or unnoticed price increases.

• • Outcome of Clustering: 

1. 1. 1. Identification of Alternative Vendors: The analysis focused on parts in the red category, where the company was paying a premium compared to the expected price per unit weight. These parts were scrutinized to understand the underlying reasons for their high costs. The analysis often revealed that other suppliers could provide the same parts at a significantly lower cost, without compromising on quality or delivery times. These findings enabled the manufacturer to diversify its supplier base, reducing dependency on higher-cost suppliers.
      2. Targeted Cost Reduction: By focusing on the parts classified as red, the team identified specific areas where costs could be reduced. This targeted approach ensured that the company could achieve meaningful savings without a broad, non-specific cost-cutting strategy that might negatively impact quality.

Insights and Values Delivered

The project yielded several valuable insights and tangible benefits for the manufacturer:

The project yielded several valuable insights and tangible benefits for the manufacturer:

    1. Cost Savings:

• • • Data-Driven Savings: By leveraging data analytics, we were able to uncover hidden savings opportunities within the manufacturer’s procurement process. The identification and correction of price anomalies alone were projected to reduce incoming material costs by 3-5%.
    • Broad Impact: These savings were not limited to a few parts but were spread across various components, significantly impacting the company’s overall procurement costs.

   2. Supply Chain Optimization:

• • • Risk Reduction: By identifying and engaging alternative suppliers, the manufacturer reduced its reliance on single-sourced parts. This diversification of suppliers not only mitigated risks but also provided the manufacturer with more bargaining power and flexibility in its procurement process.
    • Strategic Procurement: The insights from this project enabled the manufacturer to adopt a more strategic approach to procurement, focusing on long-term cost efficiency and supplier relationship management.

    3. Vendor Analysis and Optimization:

• • • Clustering for Better Decision-Making: The clustering of parts based on their price per unit weight allowed the manufacturer to make more informed decisions when selecting suppliers. This approach highlighted suppliers who were overcharging and identified those offering competitive pricing.
    • Continuous Improvement: The project set the stage for ongoing analysis and optimization, enabling the manufacturer to continually assess and refine its procurement strategy in response to market changes and supplier performance.

Conclusion:

This project for the manufacturer, conducted by us, was a comprehensive effort to optimize procurement costs and reduce risks associated with single-sourced parts. Through meticulous data analysis, the project identified significant cost-saving opportunities and provided the manufacturer with actionable insights to enhance their procurement strategy. By implementing these recommendations, the manufacturer stands to achieve substantial cost reductions while maintaining a robust and resilient supply chain.