After a product lifecycle management (PLM) system has been implemented and used for a while, the accumulated data within the system becomes valuable. This data not only supports daily operations but it also has the potential to help companies to better understand historical performance and predict the future, if it can be interpreted properly. In fact, reporting and analytics has been a part of some PLM offerings for a while. For instance, Siemens PLM Software has included this capability in its Teamcenter solution since 2006. However, because most PLM adopters are still focusing on improving product design and development productivity, analytics remains a relatively quiet area.
Recently, following a series of activities such as PTC's acquisition of Relex Software Corporation (a vendor focusing on providing analytics in product reliability and safety), Aras and Microsoft's collaboration on enterprise business intelligence (BI) for product-driven companies, and Oracle Agile PLM 9.3 highlighting its product risk management capability as the extension of its analytics platform, PLM analytics may receive more attention from the PLM community.
Although the PLM industry has not reached a consensus on the definition of PLM analytics, it doesn't prevent us from discussing what insights PLM users should expect after mining through available data within a PLM system. The main purpose of this article is to propose a framework that may help you comb through possible areas that PLM analytics may apply to.
Recently, following a series of activities such as PTC's acquisition of Relex Software Corporation (a vendor focusing on providing analytics in product reliability and safety), Aras and Microsoft's collaboration on enterprise business intelligence (BI) for product-driven companies, and Oracle Agile PLM 9.3 highlighting its product risk management capability as the extension of its analytics platform, PLM analytics may receive more attention from the PLM community.
Although the PLM industry has not reached a consensus on the definition of PLM analytics, it doesn't prevent us from discussing what insights PLM users should expect after mining through available data within a PLM system. The main purpose of this article is to propose a framework that may help you comb through possible areas that PLM analytics may apply to.
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