The intent of having this category is to cover business processes other than product development and introduction processes that are managed within a PLM system. For example, sourcing can be a task managed in a product development project. However, within the project management environment, the main interests include managing those involved in the assigned task and being updated on the current status of the task. However, there might be other data (e.g., transactional data and communication records with suppliers) in the sourcing process that are not included in project management. If interpreted appropriately, this additional data may reflect valuable information that will improve sourcing practices. Some examples include: What is the most efficient way to invite suppliers in a bid? Who are the most responsive suppliers?
Depending on the scale of a PLM system being used in an organization, the types of analytics that can be performed may vary. Based on data availability, companies need to use their own judgment to discover what insights they can acquire from PLM data. Possibilities may be located in ideation and conception process, manufacturing process management, sourcing, and others. In order to make the analytics more powerful, data from other systems, such as enterprise resource planning (ERP) systems and supply chain management (SCM) systems may be involved.
People: Measuring Employee Performance and More
There are two situations that come to mind when thinking about the "people" element in PLM analytics:
1) Recently, the PLM industry started talking about the concept of "people PLM" following the discussion of using Web 2.0 capabilities in PLM.
2) About two months ago, I had a chance to talk to a project delivery team for a large industrial equipment manufacturer in China. One interesting topic discussed during the meeting was that the project delivery team was exploring the possibility of using PLM data to evaluate productivity and performance of the company's engineers.
It is true that PLM data is generated by system users and almost every data and document entry is associated with users. It makes sense that an organization evaluates its designers by the number of parts they borrow from existing designs, the number of their designs being reused by others, and the number of their designs becoming corporate standards.
It is important to remember that as PLM systems (as innovation platforms) are strengthened by embracing Web 2.0 capabilities, knowledge collaborations may surge. Hence, employees' participation and contribution to knowledge sharing and exchange might be included in performance evaluation in the future. Following this idea, PLM analytics along with the "people dimension" will become useful when companies include knowledge management methodologies in their PLM strategies.
Depending on the scale of a PLM system being used in an organization, the types of analytics that can be performed may vary. Based on data availability, companies need to use their own judgment to discover what insights they can acquire from PLM data. Possibilities may be located in ideation and conception process, manufacturing process management, sourcing, and others. In order to make the analytics more powerful, data from other systems, such as enterprise resource planning (ERP) systems and supply chain management (SCM) systems may be involved.
People: Measuring Employee Performance and More
There are two situations that come to mind when thinking about the "people" element in PLM analytics:
1) Recently, the PLM industry started talking about the concept of "people PLM" following the discussion of using Web 2.0 capabilities in PLM.
2) About two months ago, I had a chance to talk to a project delivery team for a large industrial equipment manufacturer in China. One interesting topic discussed during the meeting was that the project delivery team was exploring the possibility of using PLM data to evaluate productivity and performance of the company's engineers.
It is true that PLM data is generated by system users and almost every data and document entry is associated with users. It makes sense that an organization evaluates its designers by the number of parts they borrow from existing designs, the number of their designs being reused by others, and the number of their designs becoming corporate standards.
It is important to remember that as PLM systems (as innovation platforms) are strengthened by embracing Web 2.0 capabilities, knowledge collaborations may surge. Hence, employees' participation and contribution to knowledge sharing and exchange might be included in performance evaluation in the future. Following this idea, PLM analytics along with the "people dimension" will become useful when companies include knowledge management methodologies in their PLM strategies.
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