Product Lifecycle Management Platforms For Discrete Manufacturers

Forrester's reference customers for one vendor in this market were unanimous. All of them said they would buy again, and they endorsed continuity of support, security, clear communication, customer service, and issue resolution without exception.

Unanimity in a reference exercise is rare enough to be worth interrogating rather than admiring. It can mean a genuinely excellent supplier relationship. It can also mean a customer base with nowhere else to go.

In product lifecycle management, both are usually true at once, and understanding why explains more about this category than any tier placement.

What PLM holds

A discrete manufacturer builds things assembled from parts: vehicles, aircraft, medical devices, industrial equipment, electronics. PLM is the system of record for what those things are.

That means the product structure and bill of materials, engineering change management, computer-aided design file management and versioning, requirements, test results, supplier and component data, compliance documentation, and the configuration of every variant ever built.

Forrester's current evaluation scores thirty six criteria, and the two Aras took maximum scores in describe the discipline better than a feature list would.

Traceability, assessed as how well the platform enables traceability from requirements through design features, test cycles, and certification.

Ideation and requirements management, assessed on how effectively the platform captures requirements to initiate new product design.

Read those together and PLM is a chain of evidence. A requirement produced a design decision, which produced a part, which was tested this way, which satisfied that certification. Every link recorded, every link connected.

Traceability is the product

The reason traceability rather than document management is the real capability comes down to what happens when something goes wrong.

A component fails in the field. The manufacturer needs to know which units contain that component, which suppliers provided it in which production windows, what the design intent was, what testing it passed, and whether the failure indicates a design fault or a manufacturing one. The answer determines whether this is a service bulletin or a recall of forty thousand units.

Regulatory approval works the same way in reverse. A medical device or an aircraft component is certified against evidence that specific requirements were met by specific design features validated by specific tests. That evidence has to be producible years later, to an auditor who was not there.

And liability follows both. In a dispute about a product that injured someone, the question is what the manufacturer knew, when, and what it did about it. The PLM record is the answer.

None of that is knowledge management or file storage. It is a legally consequential chain that has to survive scrutiny, and it is why this category is structurally different from the content and collaboration platforms it superficially resembles.

Three evaluations, and a market that widened then narrowed

The Forrester Wave: Product Lifecycle Management For Discrete Manufacturers, Q4 2017, authored by Nate Fleming, evaluated seven providers against twenty criteria: Aras, Autodesk, Dassault Systèmes, Oracle, PTC, SAP, and Siemens.

The Q1 2023 edition, published on 23 March 2023, expanded to ten providers against thirty five criteria: Aras, Autodesk, Dassault Systèmes, Duro, Oracle, Propel, PTC Arena, PTC Windchill, Siemens, and Sopheon. PTC Windchill placed as a Leader and was identified as the sole market leader in long product lifecycle design.

The Q3 2025 edition assessed eight vendors against thirty six criteria.

Seven, then ten, then eight. Criteria from twenty to thirty six.

The 2023 expansion is the interesting movement. Duro, Propel, and Sopheon are cloud-native entrants aimed at a market the incumbents served awkwardly: smaller manufacturers and hardware startups that need product data discipline without a multi-year enterprise implementation.

PTC appearing twice in that edition, as Arena and Windchill, is unusual and honest. They are genuinely different products serving different buyers, and evaluating them as one would have described neither.

The contraction back to eight suggests Forrester tightened the inclusion criteria toward enterprise-scale discrete manufacturing rather than that the newer entrants failed.

Inside The Forrester Wave: Product Lifecycle Management Platforms For Discrete Manufacturers, Q3 2025

Siemens placed as a Leader with Teamcenter, taking the highest possible score in eleven criteria and the highest score in the strategy category, and was recognised as a Customer Favorite on the unanimous reference feedback described above. Forrester noted that it reinforces its vision for transforming the PLM foundation of smart manufacturing with a pragmatic, transparent roadmap.

Pragmatic and transparent are unusual words to find in a strategy assessment, and in this category they are compliments. A PLM roadmap that promises a rearchitecture is a roadmap promising a migration, and migrations here are measured in years.

Aras also placed as a Leader, with maximum scores in seven criteria including the two traceability and requirements criteria described above. Forrester recorded its vision as empowering a community of innovators with a data-driven, AI-enabled approach, and noted above-par adoption relative to other vendors evaluated.

Forrester's positioning statement for Aras contains a qualifier worth reading carefully: it is best suited to very large manufacturers with complex products and the ability to support distinctive capabilities in their PLM instance.

The ability to support is the operative phrase. Aras is architecturally flexible, which means capability you can build rather than capability you receive. That is a genuine advantage for an organisation with the engineering capacity to exploit it, and a liability for one expecting to configure a product rather than extend a platform.

That distinction, between platforms you configure and platforms you build on, is the most consequential architectural choice in this category and it does not appear in a feature comparison.

The data outlives the system

Long product lifecycle design being called out as a distinct market segment in 2023 points at what makes PLM unlike any other enterprise system.

An aircraft is supported for decades. An industrial machine, a rail vehicle, a medical imaging system, a defence platform, all similar. The manufacturer remains responsible for spares, service documentation, safety notices, and configuration control across a fleet built over a span of years, each unit potentially different.

Which means the PLM system has to answer questions about a product built in 1998 that is still in service, using data created by engineers who have retired, in file formats from software that no longer exists, describing suppliers who have been acquired twice.

Three consequences follow, and they should shape a buying decision more than they usually do.

Migration is existential rather than inconvenient. Moving PLM means moving the evidence chain, and if the chain breaks in transit the traceability that justified the system is gone. That is why switching in this category is rarer than in almost any other enterprise software market, and it explains a portion of any unanimous reference result.

Format longevity matters. Design data locked in a proprietary format is readable as long as the vendor supports the format. Over a forty-year product life that is a real assumption to be making.

And vendor durability is a genuine criterion. Choosing a PLM platform is a bet that the supplier will exist, and will still support your data, longer than most commercial relationships last.

Forrester's crediting of Siemens for continuity of support reads differently in that light. Continuity is not a service quality attribute here. It is a risk control.

Where AI actually lands

Aras taking a maximum score in ideation and requirements management, assessed partly on the use of generative technology, points at the near-term application in this category, and it is narrower than the marketing.

Requirements are text. Large volumes of it, frequently inconsistent, often duplicated across documents, sometimes contradictory. Finding conflicts, identifying gaps, mapping requirements to existing design elements, and generating first-draft specifications are language tasks a model does well.

Traceability analysis is the second plausible application. Asking which requirements lack test coverage, or which design changes affect a certification basis, is a graph query over structured data that a well-designed system can already answer and a conversational interface makes accessible to people who cannot write the query.

What AI is not doing in this category is designing. Engineering decisions in regulated products carry accountability that sits with a named engineer, and generated geometry that nobody can explain is not certifiable.

That constraint is worth holding when a vendor demonstrates generative design. The demonstration is real. The path from demonstration to a part on a certified assembly runs through a qualification process that has not changed.

The European regulatory pressure

For a European manufacturer, the demand driver over the next few years is regulatory and it lands directly on PLM.

Ecodesign requirements and the digital product passport initiative will require manufacturers to provide structured, machine-readable information about products covering materials, composition, repairability, recyclability, and supply chain provenance, accessible across a product's life.

That data does not exist in most manufacturers' systems in a usable form today. It exists partially in PLM, partially in supplier documents, partially in enterprise resource planning, and partially nowhere.

Assembling it is a product data problem before it is a compliance problem, and PLM is the only system that holds the product structure it has to attach to. That makes the passport obligation a substantial forcing function for PLM investment in a way that no efficiency argument has managed.

The organisations that get ahead of it will be the ones that treat it as an extension of the traceability chain they already maintain, rather than as a separate reporting exercise bolted on afterwards. The chain already runs from requirement to certification. Extending it to materials and end-of-life is the same discipline applied further.

Forrester does not endorse any vendor named here, and tier placement should not be read as a recommendation to buy.