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Unsurprisingly, the three traditionally technically and commercially leading PLM solutions top the analyst and research firm ABI's new evaluation, "Competitive Assessment." It is thus about PTC, Siemens Digital Industries Software, Dassault Systèmes and their platforms. The analyst writes that their survey of PLM players, "provides an in-depth and unbiased review of the solutions offered by 11 product lifecycle management (PLM) vendors." The analysis focused on ten criteria segmented across innovation and implementation. These include the product's distribution offering, customized solution, use of new technologies (AI, generative AI, AR/VR), compliance compliance and external software integrations. Additionally, the report evaluates tangible impact, industry penetration, software scalability, user experience, and market share. The companies evaluated and ranked are in order from top to bottom as follows: * Market leaders: PTC, Siemens, Dassault Systèmes * Mainstream players are: Autodesk, ARAS, SAP, Infor, Oracle. * While Epicor, Propel, and NEC fall under the label, "followers". ”Overall, the PLM software market is a well-defined ecosystem with clear industry leaders for both process and discrete manufacturing industries. PLM vendors are benefiting from the emerging trends of SaaS deployment along with low or no code customization, enabling more fluid and personalized experiences. Vendors that prioritize and invest in these trends are increasingly competitive, but the strongest solutions come from vendors that provide the full suite of core capabilities along with innovation,” explains James Iversen, industrial and manufacturing industry analyst at ABI Research. As noted above, PTC - with the Arena, Windchill and Windchill+ platforms - tops the competitive assessment, and it led the implementation criteria with, “strong user experience and tangible impact as the criteria that drove the score. PTC had a great innovation ranking, placing second, with strong scores in distribution offerings and compliance.” Siemens Digital Industries Software is placed by ABI as second overall, with Teamcenter and the new SaaS variant of this PLM suite, Teamcenter X. However, on the innovation side, it was considered the leading solution. The highest scores came from new technology and external software integration. For implementation, Siemens scored second highest, with the most notable criteria being scaled solutions and market share, with Siemens leading the pack. Dassault Systèmes’ 3DEXPERIENCE app ENOVIA finished third in both innovation and implementation, leading to an overall “bronze medal.” DS scored highly across the board; but did not become the sole leader in any criterion. The highest scores were for distribution offers, customized solutions and external software integrations. Click on the headline to read the full article on PLM&ERP News.

New Beyond PLM blog - Why Cloud-Native PLM Comparison Requires Attention to Detail? Selection of PLM technologies and software can be a daunting process. In a competitive market of PLM vendors, the decisions are often hard, products have similar technologies and process names, which are hard to quantify and compare. I have my readers often contacting me with questions about PLM technologies, systems and vendors and asking to help them to understand the difference in how they call it – I need a “Explain this as if I was five” overview. When all systems support item and BOM management, document control, ECO process and integrations with CAD systems, how to choose the right system? Product lifecycle management (PLM) vendors providing PLM software to support product data management and product lifecycle including overall product development process and business processes support provides you with the enormous amount of product marketing materials to help you to understand the differences between various business systems – document management, PLM system and others. How to chose and who can provide good materials? The technology can create a difference. This is where many CAD and PLM software vendors are moving when they want to show the differentiation and convince why one or another PLM software platform is better. Cloud and modern PLM software technologies and tools rightfully taking a leadership role in explanation of differentiation between solutions. In the past decade, it was a trend to call software “true cloud” solution. I recall some debates about true cloud solutions back 5-10 years ago. If you like to compare arguments – What can we learn from “true cloud” PLM and ERP debates. Another article from the same era – All PLM systems are not created equal by Arena Solution (dated 2015) My attention was caught by PTC article – How Cloud Native Solutions Transform Product Development. It brings a comparison table. I found the comparison provided by PTC article interesting, but oversimplified and not providing a good guidance to companies to make the right decision. In my blog today, I wan to provide more commentaries and detailed guidance to companies that need to choose about their next PLM system. Let me go with each of these 7 comparison criteria. Learn more... https://lnkd.in/ee5y_kWt #plm #cloud PTC Gartner #plmplaybook

Thanks Oleg. I believe a lot of decision makers in the move to cloud based systems are not aware of this…. “Use of Cloud-Native Technologies Will Be Pervasive, not Just Popular. Gartner analysts said that more than 85% of organizations will embrace a cloud-first principle by 2025 and will not be able to fully execute on their digital strategies without the use of cloud-native architectures and technologies.” “Adopting cloud-native platforms means that digital or product teams will use architectural principles and capabilities to take advantage of the inherent capabilities within the cloud environment,” said Govekar. “New workloads deployed in a cloud-native environment will be pervasive, not just popular and anything noncloud will be considered legacy.” “By 2025, Gartner estimates that over 95% of new digital workloads will be deployed on cloud-native platforms, up from 30% in 2021.”

Mid-Year Check 2024: The State of PLM Vendors As we are at the midpoint of 2024, it is a good time to take a look at PLM vendors and market to provide a quick review of what vendors are offering and what is on their mind. Keep in mind that my article research and summary is not scientific, but mostly insight and thoughts based on what I read and hear. Here are some of the references: my article following CIMdata PLM Market and Industry Forum 2024 in Ann Arbor. Also my top 5 takeaways form CIMdata forum. Check presentations by Peter Bilello and Stan Przybylinski I also recommend you to attend the webinar hosted by Aras’ and moderated by Aras’ CMO Josh Epstein – Pulling Digital Thread. A few other places to check is my webinar with Adam Keating of CoLab and MJ Smith about PLM and System of Engagement. I also recommend you to check TEC reports about Dassault Analyst event in Paris by Predrag (PJ) Jakovljevic, CIRM. Also, check Siemens PLM Software Realize Live event 2024 in Las Vegas as well as my notes from Autodesk University PLM Summit 2023 in Las Vegas. Recent SAP PLM update made by Ismail Serin about SAP PLM Strategy can be found here. Last, but not least PTC LiveWorx event, which is not happening this year, but you can find my notes from 2023 here. One size doesn’t fit all in PLM business and PLM software. It is extremely important to get a balance perspective of tools, vendors’ strategies and directions for both short and long term. Product Lifecycle Management (PLM) market remains a dynamic and competitive landscape. Leading vendors continue to innovate (and acquire) to expand their offerings to meet the evolving needs of the industry. Newcomers are becoming stronger and developing various niches of the market. And customers are continue to struggle. Check my article about 5 Critical Problems in Engineering and Manufacturing, exploring a shocking data point about PLM adoption shared by CIMdata. If you’re researching PLM software, I’d recommend you a few sources. Here they are CIMdata Industry and Market report – this is an analyst perspective, G2 PLM reviews (G2 collects customer reviews, so it will be users’ perspective). For a comprehensive view of the competitive landscape in engineering software, refer to Blake Courter 's Engineering Software Moat Map, which I found as an interesting source of information about startups. This article provides a mid-year check on some of the most prominent PLM vendors as well as startup and growing businesses. You can also find useful links you can navigate later to dig deeper. Check the article [ link below ] Andrew Anagnost Neil Barua Joe Bohman Tony Hemmelgarn John Kelley Jon Hirschtick Igal Kaptsan Roque Martin Rob McAveney Stephen Hooper Brenda Discher Michael Corr Ray Hein Ross Meyercord Pascal Daloz Gian Paolo Bassi https://lnkd.in/eWkgTTfA

✨ PLM is fundamentally changing. There's a whole new dynamic within the community. I experience this in numerous customer discussions. 🗣️💼   I believe it's the changes in the Supply Chain that are setting completely new requirements for PLM, or what we understand by PLM. We at STZ-RIM Reshape Information Management are trying to capture this dynamic and topics, to underpin them methodically, and to make them discussable. 🔧📊   This new knowledge then flows directly into our coaching program, "Methodical Essentials for PLM Experts". 📚🎓   Yesterday was such a day again: We had a team of BDF EXPERTS with us. BDF-Experts are top specialists for challenging PLM topics. We were very pleased that you were with us. Maximilian Böttge Sebastian Fuchs Tom Tetzlaff Anton Gaus🤝🌟   In the course of the discussion, we also discussed the paradigms for an ERP-near PLM. Why? Because both the guys from BDF-Experts and us notice in many customer situations that due to the dynamization, the fragility of the Supply Chains, and the control claim to these, completely new requirements and concepts for an ERP-near PLM emerge. 🔄🛠️   A central paradigm of yesterday's discussion on ERP-near PLM was "Generic Structure Instance Embedding". A working name for a concept that fundamentally rethinks the approach to generic product structure. 🤯💡   The classical approach to generic product structure assumes that the top structure of a product is purely generic, i.e., structuring. From a certain structural level, the product structure is then completed through positions/position variants by components/assembly instances. 📐🔩   However, if you want to implement a growing CTO+ Modular Kit, this approach needs to be rethought. This is done by extending the Generic Structure into the deeper levels of the product structure. The boundary between structuring and instantiation disappears. The instantiation is no longer horizontal but vertical to the structure, and a "double structure" emerges that contains both the instances and the generic structure. This makes automated instantiation that can also include the CTO+ portion possible down to the lower levels of the structure! 🔄✨   An exciting approach that enables a growing Modular Kit with maximum automation and CTO+.   Sounds complicated? It is – but only when building it for the first time. Once the concept is established, it enables offering high-variant products at the prices and delivery times of standard products on the market! 🏭💼   What do you think? Now, if you want to know more about it, feel free to book our "Methodical Essentials for PLM Experts" workshop at the RIM Academy (https://lnkd.in/egrBZE2x). 📅🎟️

I've dealt with many misconceptions of PLM for manufacturing. Here are the top major misconceptions of PLM and how to overcome them. PLM is just software: While software solutions are often a central component of PLM, it's more than just a technology platform. PLM encompasses people, processes, and data, and successful implementation requires alignment across all these aspects within an organization. PLM is only for large enterprises: While PLM systems have traditionally been associated with large corporations due to their complexity and cost, there are now PLM solutions available that are tailored for small and medium-sized enterprises (SMEs). These solutions offer scaled-down features and pricing to meet the needs of smaller businesses. PLM is only for product design: While PLM systems do support product design, they also manage data and processes across the entire product lifecycle, including manufacturing, supply chain management, quality assurance, and maintenance. PLM facilitates collaboration and information sharing among different departments and stakeholders involved in the product lifecycle. PLM is only for physical products: PLM systems are often associated with managing the lifecycle of physical products, such as automobiles or consumer electronics. However, PLM concepts and methodologies can also be applied to manage the lifecycle of digital products, software applications, and other intangible assets. PLM is a one-size-fits-all solution: Every organization has unique processes, requirements, and challenges, so there's no one-size-fits-all approach to PLM. Successful implementation requires customization and configuration to align with the specific needs and workflows of the organization. PLM is primarily a cost-cutting tool: While PLM can lead to cost savings by streamlining processes, reducing errors, and improving collaboration, its primary goal is to drive innovation and improve product quality. By providing a centralized platform for managing product data and processes, PLM enables organizations to bring high-quality products to market faster and more efficiently. PLM implementation is quick and easy: Implementing a PLM system is a complex undertaking that requires careful planning, stakeholder engagement, and change management. It involves integrating with existing systems, migrating data, configuring workflows, and training users. Successful implementation requires a long-term commitment from the organization and its leadership. PLM is Just a Document Management System: PLM goes beyond document management. It manages data related to product structures, requirements, configurations, and change processes, ensuring data consistency and traceability. PLM is Only About Compliance: While compliance with industry regulations is an important aspect of PLM, its benefits extend beyond compliance. It enhances innovation, reduces time-to-market, and improves product quality. #plm #engineering #manufacturingsolutions

Hi, PLM, ERP and MES gurus in my network, I am inviting you to join below discussion initiated by Niels Erik Andersen on MBE. This is one of the biggest opportunity and a lot of challenge in discrete manufacturing industry. Several cents from my side: 1) MBE is gaining momentum in A&D, and auto, industrial machinery and medical devices. The scope is across the product lifecycle (design, manufacturing, service) but also across the business network (supplier collaboration, procurement). 2) PLM is more than product definition system, instead, it has been evolving into an enterprise collaboration platform, someone called it enterprise PLM and Gartner called it something like PLM 360 at sometime if I recall correctly. More and more manufacturers are expanding PLM to manage manufacturing engineering, parts management/supply chain collaboration and closed loop quality management. The major business driver is to improve velocity, quality and efficiency. All in all, 70% of product cost and 80% of the product carbon footprint is most influenced in design stage. 3) MBE is not only about the data flow across lifecycle but also managing the changes across business functions. While manufacturer are shifting more and more from Make to Order, Engineering to Order and Config to Order, and the products get more complex (not only hardware but also software), it is mission impossible to manage the changes without an enterprise collodabraiton platform. 4) Completely agreed with Niels that there is no single system owns the MBE data across digital thread, there are as-design, as-planned, as-built, as-purchsed, as-used, as-maintained, etc. No single system of record could have all of them. 5) An open architecture should be embraced by the tech vendors and it is the best interest of the customers (IMHO, some Unified Namespace framework would be ideal and data can be shared in common structure and pub/sub). 6) There is still a big challenge with legacy applications especially in shop floor. Every plant will need MBE, but only a few need or have a MES. Some composable, role based Connected Worker applications that is integrated with PLM/MPM would be ideal to democratize the power of MBE in factory. 7) MBE could create a valuable feedback loop from downstream of product lifecycle back design stage. The industry has been talking of design for X for decades, great concept, but few have capitalize on it. The model-based digital thread is the tech enabler to make it happen at scale.

Insightful. A pathway towards singleinsight.io

I agree with both James Zhang and Niels Erik Andersen - MBE is not new, not limited to PLM, nor even product definition. No single system exclusively owns MBE; many systems contain dependent information that provides context to the product as it is defined, built, used, or even disposed of. I too am seeing MBE gaining maturity in A&D, and momentum in the auto, industrial machinery, and medical devices sectors. But I am also seeing false flag battles that focus on where the data is stored or allowed to flow, which has only served to slow down adoption. There are many forms of models in various business systems that have value to their specific users. I marvel at just how accurate George Box's famous line, “All models are wrong, some are useful,” really is. We should focus on managing the model as valuable assets rather than debating if the answers they provide are correct in all cases or questioning if they are valuable enough to manage. If there is a perception that MBE should only be owned by the PLM system, as the product definition manager, I would argue that this viewpoint is simply too limiting. PLM certainly has a role in managing product definition, and it also has a role in managing the definition of the process by which said product is intended to be manufactured, as well as the definition of the equipment used to manufacture the product. PLM doesn’t need to know much about how specific instances of the product were produced, used, and maintained. In contrast, PLM should know, in aggregation, from other systems. It should know if the production of the product was performed efficiently and at a given moment the product is being produced in compliance with the intended manufacturing processes and design intent. For example: •  Were the dimensions assigned in the product definition properly aligned to the product requirements? Were those modeled requirements traceable to the customer's needs? •  Did we leverage the right level of product definition abstraction to simulate the product behavior in intended or unintended use? •  Did we model and simulate the manufacturing and quality assurance processes used to make the product well enough to virtually commission the driving control code? •  If a supplier asks to relieve a flowed-down derived tolerance for their component in our product, would we know if any of these models and simulations were impacted? As product and process data evolves and flows between PLM, through Manufacturing MES, through operations, and beyond, these systems must be aware of relevant assumptions, context, and intent managed within these adjacent systems. Every manufacturer regardless of size, is becoming a model-based enterprise, and they need to act as an MBE with PLM and Manufacturing Execution Systems. It is needed to accelerate the feedback loop from downstream back to design. We all need to work to manage models and simulations while making MBE leading practices more accessible at all levels of the supply chain.

Redefining PLM implementation approach with data and AI Yesterday, I initiated a discussion on PLM (Product Lifecycle Management) implementation, starting with a crucial question that often sparks debate: Should process refinement precede PLM implementation, or vice versa? Drawing from my experience with OpenBOM implementations and lessons learned over the last few years working with engineering and manufacturing organizations, I shared my insights. Check this out - https://lnkd.in/gyBjyAyx In my today's Beyond PLM article, I want to dig deeper into PLM implementation strategies and discuss how emerging technologies like cloud computing, SaaS and AI are set to change PLM implementations in the future. In this era of digital transformation, PLM implementations have become pivotal for manufacturing and engineering firms eager to innovate and enhance efficiency. Traditionally, the belief that adopting a PLM system requires an extensive overhaul of business processes has created a paradox. Companies are caught in a standstill, hindered by entrenched process inefficiencies and often resorting to basic tools like Excel, PowerPoint, and emails for data management and collaboration. The landscape is now shifting as modern PLM-oriented SaaS services and tools proliferate, transforming implementation methodologies. Here is my perspective into how future PLM implementations will evolve: 1- The swift adoption of SaaS services and tools will focus on aiding companies in addressing fundamentally flawed tasks in new product development, data management, and collaboration. These areas are deeply broken, with companies traditionally relying on Excel, PowerPoint, and emails for management. 2- The immediate availability of SaaS PLM tools will enable companies to initiate small, agile pilot projects. These pilots will facilitate a deeper understanding of existing data and processes, helping identify the most effective approach to PLM implementation. This will be made possible through the availability of SaaS tools, a flexible data model, and adaptive learning processes. 3- Advanced data management, analytics, and AI tools will assist companies in navigating PLM implementation, identifying discrepancies in data and processes, and optimizing these elements throughout the adoption phase. Refer to my initial article on the redefinition of PLM implementations, emphasizing modern SaaS PLM services. Discover more in the article and stay tuned for the next piece discussing the role of data and AI in future PLM implementations. I discussed this dilemma of PLM implementation with PLM minded people over the past few years. Curious what you think - Stan Przybylinski Allan Behrens Monica Schnitger Jim Brown Chad Jackson Christine Longwell Marc Halpern Peter Bilello Jos Voskuil Helena Gutierrez Bjørn Arvid Fidjeland Christoph Golinski (sorry I cannot put all people I want here)  #PLM #SaaS #Implementations