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How to reduce new product introduction (NPI) times for a shorter time to market

Reading time: 47 minutes


Accelerating new product introduction (NPI) and getting to market faster will continue to challenge chipmakers as new markets emerge and technologies expand demand. The Internet of Things (IoT), artificial intelligence (AI) and autonomous vehicles are driving new market segments outside of the tech industry, shortening lifecycles, and increasing product complexity. If AI and IoT growth continue to materialize as expected, semiconductor companies must be ready to pursue innovations that help their customers take products to a new level. Businesses that can't introduce new products quickly and keep up with demand increase their risk of losing market share to competitors that adapt faster to changing market demands.

How product lifecycle management (PLM) can improve semiconductor NPI process

The lack of a flexible and agile system leads to inefficient use of resources, missing deadlines, quality and supplier issues and delays, and, ultimately, fewer NPIs. Drive differentiation for your products in this changing market with better management of increasingly sophisticated products and processes.

Leveraging product lifecycle management (PLM) for NPI means:

  • Seamlessly manage NPI product and project deliverables with the ability to adapt quickly to changing business needs and priorities

  • Boost revenue streams through enhanced contract bidding capabilities, exploring greater business opportunities

  • Develop accurate, timely forecasts and fully understand your capacity to fulfill new or changing orders

  • Provide adaptive machine learning solutions with functionality to integrate AI/ML into their products

The benefits of product lifecycle management (PLM) software for semiconductor companies

Product lifecycle management (PLM) software enables semiconductor companies to ensure data integrity. Organizations today rely on data-driven decisions, and AI and ML will continue to drive the importance of clean, quality data. Product data is full of inaccuracies, inefficiencies, and performance errors without an interface between electronic design automation (EDA) tools, and PLM tools. Data that is managed from concept to delivery in an integrated and structured way enables decision-makers to access the data they need at the right time to make good decisions. With a single source of truth, productivity flows across all systems. Companies can take control of product data and processes, including EDA design and verification, complex packaging, embedded software, documentation, and BOI data, harmonizing all data and manufacturing process information for the entire product lifecycle.

Shorten new product introduction (NPI) time and improve innovation

Reduce both new product introduction (NPI) time and cost. With lifecycle management, semiconductor companies gain the flexibility to adapt to business changes and manage all of the challenges of product development by connecting manufacturing process and data management to collaboratively create, validate and optimize manufacturing plans concurrently with product designs. By reducing the wasted time passing data from team to team, NPIs can get to market faster and enable the team to focus on continuous innovation.

How to meet consumer demand and accelerate time to market

Demand is surging in the semiconductor market due to increased adoption of IoT, 5G, autonomous cars, and AI, and will likely continue for the foreseeable future. Better manage the semiconductor lifecycle to reach the next generation of productivity improvements to achieve time-to-market objectives and drive growth through innovation. Take advantage of business opportunities faster and adapt quickly to changing business needs with digitalization.

Achieve higher product quality and a lower new product introduction time

It's challenging to balance competing priorities like lowering new production introduction (NPI) time and cost against delivering zero-defect chips with high complexity. Successfully meeting them depends on reducing the high degree of fragmentation and lack of digitalization in design and manufacturing systems. The lack of digitalization hinders data integrity, secured intellectual property (IP), re-use and end-to-end traceability while accelerating technical debt within companies.