ASML Cuts Jobs Despite Record Backlog
Chipmaking equipment giant ASML is cutting 1,700 jobs, primarily in the Netherlands, despite having a record €38.8B order backlog. The move signals a strategic shift from headcount growth to operational leverage and automation, even amid unprecedented demand, suggesting a focus on long-term efficiency.
* The job cuts, impacting about 4% of ASML's workforce, are concentrated in management and leadership roles within the Technology and IT divisions, primarily in the Netherlands and the U.S. The company aims to reduce organizational complexity, allowing engineers to focus more on innovation. * ASML's fourth-quarter net bookings surged to a record €13.2 billion, nearly doubling analysts' estimates and pushing the total order backlog to €38.8 billion. This backlog provides strong visibility for sales into 2027, with Extreme Ultraviolet (EUV) lithography system capacity fully booked through that year. * The surge in orders is largely driven by the demand for AI-related chips and high-performance memory like HBM and DDR5. Notably, for the first time, orders from memory chip customers (56%) surpassed those from logic chip customers in the fourth quarter. * Key customers driving this demand include TSMC (for Nvidia's AI accelerators), Samsung, SK Hynix, and Intel, all of whom are expanding their capacity for advanced chip production. * Despite the strong demand, ASML's revenue from China is expected to decrease from 33% of sales in 2025 to around 20% in 2026 due to U.S.-led export restrictions on its most advanced EUV tools. * For complex, long-cycle sales common in the semiconductor industry, sales operations best practices include segmenting customers into tiers, detailed analysis of sales team activities to increase customer-facing time, and establishing rigorous performance management with key metrics tracked throughout the sales pipeline. * Forecasting models suited for long hardware sales cycles include time-series analysis (like ARIMA) for businesses with historical data and lead-driven forecasting that uses CRM data on conversion rates and deal sizes. AI-powered forecasting is also becoming more prevalent, using machine learning to detect complex patterns and incorporate external economic data. * CRM automation is critical for managing complex sales by handling repetitive tasks like lead assignment, follow-ups, and updating deal stages. This allows sales representatives to focus on high-value activities and relationship building, which is crucial for deals with multiple stakeholders and extended evaluation periods.
