Unlocking Cost Efficiency and Capacity Forecasting

The Challenge

Overpaying for Foundry Capacity: Our fabless customer lacked visibility into the foundry’s internal cost structures and the hidden profit margins baked into those prices. Without understanding these internal costs, they often found themselves overpaying for wafer production.

Limited Insight into Future Capacity Expansions: While historical and current capacity data is available, the company had no clear way of forecasting future capacity expansions or investments in new technology nodes. Public announcements are often skewed by political and market influences, leading to uncertainty in planning for future supply needs.

The Solution

To address these challenges, the company utilized TechInsights’ Semiconductor Manufacturing Economics (SME) Cost and Price Models to gain insight into foundry internal costs and predict future capacity developments.

Cost and Price Models for Accurate Cost Analyses

• By using the Cost and Price Models, the company gained visibility into the internal cost structures of its foundry suppliers now and in the future, including wafer fabrication, test, assembly, and packaging for various device types.
• The purchasing-volume-based pricing feature allowed the company to estimate costs at different production volumes, helping them negotiate more effectively and avoid overpaying for capacity.

300mm Watch Fab Database for Capacity Planning

• To solve the issue of unclear future capacity, the company used the Fab database in conjunction with the Cost and Price Models. This gave them detailed insights into when and where investments would be made in wafer fabs for specific technology nodes through 2030, providing them with the information needed to strategically plan for future demand.

The Results

Enhanced Negotiation Power and Cost Savings: By understanding the internal costs of their foundry suppliers, the company was able to negotiate better terms, reducing costs and preventing overpayment. With transparent pricing data at their fingertips, they were no longer in the dark about profit margins and could secure more favorable deals based on volume and future commitments.

Improved Capacity Forecasting: With access to the Fab database, the company was able to accurately forecast when specific global fabs would expand capacity or invest in new nodes. This foresight allowed them to de-risk their supply chain, ensuring that they could secure the capacity they needed well in advance of changes in markets, natural disasters, or international politics.

By leveraging the Cost and Price Model along with the Fab database, the company gained critical insights into foundry cost structures and future capacity developments. As a result, they optimized their procurement process, reduced costs, and improved their ability to plan for future production needs, ensuring a competitive edge in the fast-moving semiconductor market.