As Lionel Grealou, business advisor and founder of Xlifecycle Ltd, often put it: “PLM is a child of many parents” as its definition and ownership can drastically vary from one organization to another. The key message is that every product innovation, engineering, or manufacturing-related organization has a PLM strategy - independently of whether it is called “PLM” or else.
The fact is that many organizations call it something else since - probably due to software editors and vendors - PLM is often historically associated with a technical system or an enterprise platform. Others refer to it as “product data management”, a.k.a. PDM. As a matter of fact, PLM is often a debated topic among pundits and marketers. One can argue that sometimes there is a little bit of a PLM identity crisis; solving this is mostly a matter of contextualization, scoping clarity, terminology alignment, and continuous stakeholder alignment.
PLM is about looking at the ‘big picture’ of how an organization innovates and delivers its products to cost, quality, and time. It is not about building technical solutions or integrating every system with everything - unless of course you are a PLM vendor or a system integrator... In essence, PLM (or PDM) is about joining the dots and connecting people through trusted, reliable, and consistent data. When it comes to data, the bill of materials (BOM) is typically regarded as the lifeblood of product development and any complex engineering programme.
Rob Ferrone, Quick Release_ founding director, a.k.a. the original Digital Plumber, interchangably defines PDM and PLM as:
“the science around management of product data across the lifecycle, where the backbone is the BOM and the layers are data / people / process / system, in the most efficient and effective way possible in order to maximise the physical world outcomes (quality, cost, timing)."
So, where to start when driving value from PLM? As Simon says, let’s start with WHY...
Why do organizations need PLM?
Broadly speaking, PLM is an enabler and a business strategy. It takes time and focus to drive business alignment beyond engineering processes and data. PLM is in fact rooted in the organizational operating model; it should therefore be carefully defined in context of the ways of working, governance, and cultural values of the business. Adopting an external definition, if not appropriate or simply lacking clarity, might slow down or even hinder adoption.
PLM process and data implications are huge are typically relate to five key considerations:
1. Who / which function owns which data and processes? (Typically, a shared ownership somewhere at the intersection of product quality, operations, and program management.)
2. Who are the business decision makers when it comes to making solution investment and validate process trade-offs.
3. What data quality standards exist, and how they are embedded into the processes and governance?
4. How are technical solutions supporting the above, and who owns the suitability and sustainability of such solutions?
5. What levels of automation and integration are required, and how are these orchestrated to ensure some effective and sustainable data continuity?
PLM is not *only* about a technical solution to securely store data on a cloud-based server or with a globally accessible database. It is about a structured ecosystem and connected approach to product data management across the wider business functions. If data brings value to the business, one must be able to qualify and quantify it - initially based on plausible hypotheses, and subsequently backed up with relevant evidence.
How to define an effective PLM strategy?
Such evidence goes beyond existing KPIs, possibly into cross-functional success factors that did not initially exist. Diagnostic and fixing tangible pain points or bringing to life new business capabilities is what PLM / PDM is about. It often starts with people collaboration and by addressing data gaps or duplication and putting this in context of a business or functional scorecard based on the relevant analytics to drive decisions.
When implementing change, it is often recommended to “follow the data” and accordingly map the relevant value streams across business functions - from one team to another, from one platform to another, etc. It might sound obvious, but an effective PLM or PDM strategy is one that resonates with its key stakeholders - especially decision makers and budget owners who are willing to invest into this scope as they aim to:
1. Build effective and efficient processes, driving positive user experience, and continuous improvement.
2. Mine value from connected data sets, as an enabler to effective team collaboration.
3. Drive better real-time (or near real-time) analytics to bring enterprise and supply chain operations to the next level.
4. Align on process definition and improvement to focus on value-added activities.
The PLM strategy starts with a business capability map, often reaching out to ERP, MRP, MES, and CRM scope. Business maturity and development plans drive capability maturity expectations. Diving into each capability requires a holistic enterprise architecture approach to define the required master data strategy, process, and people implications.
What constitutes the scope of PLM?
An effective PLM strategy includes a clear scope and stakeholder map, in addition to having a clear prioritization criteria and implementation roadmap. While appointing a global PLM process owner in the business is not always possible (wanted, or even needed), gaining and managing a cross-functional consensus is critical to implement the PLM roadmap and drive the required business change.
PLM refers to a process-centric approach to data improvements. Beyond configured BOM data, PLM refers to product data assets from business requirements to milestone deliverables, CAD and embedded software data, quality and compliance artefacts, product waivers, deviations, and concessions, change management, supplier performance KPIs, product costing, weight and balance data, color variants, etc.
Investing in PLM often means aligning stakeholders up to board level with an aligned scope, a robust strategy, a credible roadmap, coupled with a clear business case and ROI. Expected business benefits range from process and resource efficiency, to reduced time to market, increased product quality, reduced recall, future cost avoidance, etc.
How QR_ can help
Uniquely positioned as the ‘business integrator’, we can manage the business relationship at all levels, assessing and negotiating process trade-offs, supporting, or even acting as product owners, driving the decision-making process, supporting BOM operations and delivery alignment (including contributions to technical solution design and business change authority).
Ferrone R (2022); Digital Plumbing: Diagnosing and Fixing Enterprise Data Leaks
Grealou L (2022); Industry Reflections 8: Effective Enterprise Data Governance
Grealou L (2016); What PLM Identity Crisis? virtual+digital