Products are developed (designed and engineered), manufactured and managed throughout their lifecycle through a collaborative approach across a combination of functions (people, departments, organizations), processes and IT tools.
Every manufacturing organization that create products “does” some sort of Product Life-cycle Management (PLM); it might be fully enabled by tools and technology or not. Business benefits, effectiveness and efficiency will link to the PLM maturity (is it fit for purpose or not?) and its level of adoption (is it used properly or not?). Also, the relative maturity of one domain vs another, or one capability vs another, will inform about the overall maturity.
Whether product portfolios are managed on paper (without IT solutions, or using Excel type of tools) or using advanced IT-integrated solutions, the same PLM principles apply:
- PLM is an enable to manage complex enterprise data that relates to the product realization (BoM, product configuration, attributes, requirements, cost, etc.)
- Engineering data is mastered in PLM, manufacturing and service data is typically mastered in Enterprise Ressource Process (ERP); it varies based on make-to-buy strategies, product complexity, manufacturing complexity, functional inter-dependencies, etc.
- PLM enables effective and efficient product realization (not only product creation); it accelerates maturity growth in product development projects by providing means to control key parameters of New Product Introduction (NPI).
- Virtual design and validation simulation enables faster developments while reducing the cost of new product introduction (greater simulation accuracy, faster product validation and verification, better outcome quality, reduction in number of physical prototypes, greater data visibility and traceability, etc.).
- PLM is equally about engineering and product efficiency – enabled by better processes, better ways of working (organizational structures and culture); with the support of some IT tools.
Product efficiency is about make-to-buy strategies, purchasing coordination, effective cross-functional design reviews (part of a robust new product introduction framework), product quality management, error avoidance or control, quality assurance, complexity management (ie simplification and control), effective data search ability, alignment to compliance requirements and standards, data re-use optimization, on-time delivery and mis-revenue avoidance.
Engineering efficiency is easier to measure (eg resource efficiency by number of heads or work hours reduced for non value-added activities) and improve than product efficiency.
Product efficiency has the potential to yield more tangible benefits: for instance, it can contribute to improve revenue with open innovation, access to new solution networks, enhance products and associated services, increase sales (top line improvement) and efficiency through better delivery and engagement model, healthier competition, reduction of poor quality (bottom line improvement) by 2 to 3 fold by reducing direct and indirect material cost.
Digital technologies are disrupting and changing businesses, and this include PLM tools and technologies, capability solutions and their integration to Enterprise-IT. Product innovation, development and manufacturing are at the forefront of the ‘digitalization‘ of product realization lifecycle. Bridging functional silos, integration of data, processes, business and IT is ‘stimulating’ innovation in product and service delivery.
What are your thoughts?
This post was originally published on LinkedIn on 12 November 2015.