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5 Reasons Why Industry Knowledge Is Essential when Implementing PLM Solutions

Lionel Grealou PLM 3 minutes

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Image Credit: PEXEL

PLM knowledge typically sits at the intersection of industry delivery framework, product development processes, business operation platform and applicative functionality, configuration and customization, integration and enterprise IT. Organizations hold knowledge through their execution models and framework, and through their primary resources: people. One way or another, anyone directly involved in PLM implementations will relate to both business and IT interactions about current working methods, platform or new capabilities, data quality implications, cascading business needs into technical and functional requirements.

Functional experts, a.k.a. process SMEs, are often expected to define how business users are to operate and ultimately help them learn how to use effectively a given PLM solution and platform. Their expertise must include how to use a given PLM toolset; they need to understand the related industry and organizational languages, as well as which relevant data structures and processes. 

In this post, I highlight 5 reasons why industry knowledge is critical to align new working practices to tool or functional best practices. 

How to functionally manage CAD, CAE or BOM data might have a lot in common from one industry or another; there will also be specific industry-driven difference as business knowledge requirements typically vary based on industry and PLM scope. As a matter of fact, new product development processes have multiple flavors based on the product context: this includes, albeit is not limited to, legislative, material compliance, quality and conformance, FMEA, CAPA, NCR and other traceability requirements across the product lifecycle.

Among other delivery roles, the functional or process SME is typically responsible to translate and align contextual industry requirements with a given PLM platform or interface; working with solution architects and business analysts to define the most relevant target processes. Industry knowledge is essential across the following 5 perspectives:

  1. NPI / NPD delivery requirements
  2. Industry drivers and strategic outsourcing
  3. Legislation requirements
  4. Compliance and traceability requirements
  5. Best practice industry processes

1. NPI / NPD delivery requirements

New product introduction and development frameworks are industry specific; they contribute to bridging business strategy with manufacturing operations, aligning how functions collaborate across the wider enterprise when creating new products and associated services.

Delivery scope, approach and timeframe are typically product specific, hence industry specific. The most prominent difference refers to the product development cycles as NPI frameworks significantly differ in duration from one industry to another, such as 2-4 years for the automotive industry, 10-25 years for the aerospace industry, or 40-60 years for the nuclear industry.

2. Industry drivers and strategic outsourcing

Every industry has its own specific drivers. Such drivers characterize how an industry operates and its attractiveness level as defined per Porter’s five forces analysis framework. Industry drivers include product and range modularity, how discrete products are outsourced and assembled, how assets are monetized, how organization grow within an industry, how they develop sustainability strategies, competitive positioning, pricing models, etc.

Each organization within a given industry will have multiple interpretation or adaptation of these business drivers based on their own maturity, size, strategic objectives and sub-industry sector.

3. Legislation requirements

Every industry is required to align to multiple legislation and regulation requirements relating to their product manufacturing and delivery operations: from training and safety equipment to testing products to ensure that they meet minimum safety standards, product warranties, working conditions, quality and delivery assurance procedures, environmental norms, trading standards, etc.

4. Compliance and traceability requirements

Product certification is critical to demonstrate alignment to standards and quality requirements. Manufacturers must produce and keep the relevant traceability records and certificates of compliance to prove that products have been inspected and tested as required. These also offer a verification of the process rather than the product alone.

Compliance might also include secret data access restriction to align to ITAR regulation or other legislation. Non-compliance might have severe warranty, financial and competitive implications.

5. Best practice industry processes

Best practice can often be found in isolated processes or activities such as material management or supply chain integration. To be effective in a given organization, best practice activity needs to be appropriate for the business sector, linked to strategy and deliver a competitive advantage and sustainable growth.

For example, discrete and process manufacturing both rely on BOM data; they however have significant differences: discrete manufacturers focus on component availability and have a highly complex BOM to support multi-step assembly and part / component management, whereas process manufacturers focus on mixing ingredients based on a formula or recipe and produce goods in batch series.

What are your thoughts?


This post was originally published on Momentum-PLM on 24 November 2020.

Disclaimer: articles and thoughts published on v+d do not necessarily represent the views of the company, but solely the views or interpretations of the author(s); reviews, insights and mentions of publications, products, or services do neither constitute endorsement, nor recommendations for purchase or adoption. 

About the Author

Lionel Grealou

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Lionel Grealou, a.k.a. Lio, helps original equipment manufacturers transform, develop, and implement their digital transformation strategies—driving organizational change, data continuity and process improvement, managing the lifecycle of things across enterprise platforms, from PDM to PLM, ERP, MES, PIM, CRM, or BIM. Beyond consulting roles, Lio held leadership positions across industries, with both established OEMs and start-ups, covering the extended innovation lifecycle scope, from research and development, to engineering, discrete and process manufacturing, procurement, finance, supply chain, operations, program management, quality, compliance, marketing, etc.

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