Tammy Max, Director of Technical Content at Accuris
The semiconductor industry – which produces many of the vital components for electronic products – has recently experienced widespread consolidation through merger and acquisition (M&A) activity. Over the past several years, there have been several notable semiconductor acquisitions, including Intel’s purchase of Mobileye for $15.3 billion and Analog Devices’ acquisition of Linear Technology for $14.8 billion.
M&A can benefit companies and investors in many ways, including reduced costs and increased effiencies, but it can pose significant challenges to the supply chain. In an industry where supply-chain disruptions are already common – mostly due to natural disasters, geopolitical tensions, and factory closures – M&A adds an extra layer of complexity. Electronic products manufacturers, the key customers for semiconductors, face production delays and shortages due to these industry shifts.
Why does M&A cause supply-chain disruptions?
A product’s Bill of Materials (BOM) doesn’t change. With M&A part numbers and manufacturer names do change. As a result, semiconductor components impacted by M&A will have multiple identifiers, including their original identity and any subsequent post-acquisition identities.. This can lead to confusion and critical disruptions in a supply chain.
For example, obsolescence and product change notices (PCN) – the documents issued by manufacturers to inform customers about changes to products or manufacturing process – are usually communicated under their current identifier. The internal dynamics of companies, including their previous M&A history and the use of distributor or legacy part numbers, compound the issue of proper identification.. This confusion may cause production line-down situations or could even force a redesign in the middle of an electronics manufactuer’s product lifecycle.
Electronic product manufacturers can address these issues with best practices that capture manufacturer and part-number changes over time. For example, it’s often beneficial to assign internal part numbers — which allows for more than one manufacturer or part-number identifier for the same part – in internal systems such as PLM(product lifecycle management) platforms and product libraries.
In the past, not tracking part/manufacturer changes over time required significant manual work to assure PCN/EOL notices were not missed due to using legacy part numbers, and often lead to duplication of part numbers and missed opportunities to consolidate volumes for purchasing power.
The good news is that artificial intelligence (AI) technology can help combat these challenges and streamline the process of uncovering identity discrepancies, preventing disruptions.
