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Bridging the Gap: Strengthening OEM – Supplier Relationships in the Electric Vehicle Era

Introduction

For over a decade, automotive original equipment manufacturers (OEMs) have utilized performance scoring systems to maintain steady supplies for production. Tools such as claw-back clauses, penalty fines, and “speedy points” have become standard features of these relationships, ensuring that suppliers meet stringent requirements.

However, the relationship between OEMs and their suppliers is undergoing significant transformation. As OEMs pivot toward electric vehicles (EVs), the industry is experiencing an “arms race” fueled by aggressive demand models and shifting priorities. This evolution has introduced unprecedented uncertainty in their demand forecasting, creating ripple effects throughout the supply chain.

The Impact of Inaccurate Forecasting

The shift to EV production has complicated demand forecasting for OEMs. Balancing legacy internal combustion engine (ICE) production with EV ramp-ups has led to unreliable Electronic Data Interchange (EDI) releases. This inaccuracy often leaves suppliers struggling to align with fluctuating and often unrealistic projections.

As one executive explained, “With the addition of electric vehicle demand in addition to the existing ICE vehicle forecasts, we have found that the OEM forecasts are much less realistic and cause additional issues when we negotiate our contracts.”

The financial burden of these inaccuracies is significant. Suppliers face surplus production, inflated storage costs, and unutilized inventory, all of which erode profitability. A Tier 1 automotive manufacturer succinctly summarized the frustration: “I can’t wait for the year-end when I don’t have an extra million parts I don’t need.”

A Strained Relationship Between OEMs and Suppliers

The rising tension between OEMs and suppliers is highlighted in Plante Moran’s 2023 North American Automotive OEM – Supplier Working Relations Index® (WRI®) Study. The study cites increasing friction over cost recovery, supply chain disruptions, and production scheduling.

Suppliers are not only navigating these challenges but also making critical working capital investments to meet EV production requirements. Balancing these long-term commitments with short-term operational viability remains a delicate task.

Turning This Challenge Into A Collaborative Opportunity

The question arises: How can suppliers effectively address the challenges of inaccurate forecasts while fostering stronger collaboration with OEMs?

Strategic iQ and OneStream Software offer transformative solutions which can help Tier 1 Automotive Manufacturers with the ability to bridge this gap through innovative analytic tools and advanced forecasting capabilities:

1. Strategic iQ’s Planning Factory (For Automotive)

Strategic iQ’s Planning Factory delivers a foundation for Unified Business Planning by centralizing and enhancing the Sales & Operational Planning (S&OP) Process. This solution allows Parts Manufacturers to develop multiple Demand Models and evaluate them against the potential profitability by part by customer.

  • Key Features:
    • Part-Level Profitability down to Bill of Material. Customers can re-forecast monthly with Actual (not Standard) Profitability insights.
    • Automated EDI release integration alongside IHSMarkit Take Rates and capacity data.
    • Variance analysis dashboards for immediate visibility into forecast accuracy.
  • Impact: Suppliers can transition to a driver-based forecasting model, enabling rapid updates and improved responsiveness to evolving demand and efficiency performance.

2. Sensible Machine Learning (SML)

OneStream Software’s Sensible Machine Learning solution enhances forecast accuracy using artificial intelligence and machine learning. By analyzing historical data and incorporating various user-defined factors, SML delivers precise and actionable projections.

  • Key Benefits:
    • Proven forecast accuracy improvements of over 10% in proof-of-value studies.
    • Ability to generate thousands of forecast models to identify the most reliable outcomes.
    • These models can be used retroactively to support an OEM-Supplier conversation around the financial effect of the OEM’s EDI Release inaccuracies. 

Transforming Supplier-OEM Conversations

The combination of SiQ’s Planning Factory (SPF) and OneStream’s Sensible Machine Learning (SML) empowers suppliers with actionable insights and faster forecast generation. This enables them to initiate data-driven discussions with OEMs about program performance and demand projections.

Suppliers can use these tools to address critical findings from the WRI® Study:

  1. Enhancing Forecast Sharing
    SPF and SML allow for detailed, accurate forecasts that align with both short-term and long-term manufacturing strategies. By improving the transparency and accuracy of forecast information, suppliers can better adapt to uncertainties related to EV adoption, supply chain disruptions, and new technologies.
  2. Reducing Cost Burdens
    These tools support cost reduction initiatives by improving efficiency and aligning costs with accurate demand forecasts. Suppliers can present detailed data to OEMs to advocate for cost recovery and inflation-driven adjustments, fostering a more equitable relationship.

A Path Forward for Automotive Suppliers

As the automotive industry continues its transition to EVs, the relationship between OEMs and suppliers must evolve. Accurate forecasting and improved collaboration are essential for navigating the challenges of this shift.

By leveraging Strategic iQ’s Planning Factory and OneStream’s Sensible Machine Learning, suppliers gain the tools needed to recalibrate their approach, reduce (or recover) costs, and strengthen relationships with their OEMs. With these solutions, suppliers can position themselves as proactive partners, ready to adapt to the demands of a rapidly changing automotive landscape.