Making the value of technology clear
State of Product Development
Product development continues to face an era defined by growing complexity, shrinking margins for error, and accelerating market demands. This is exacerbated as companies are under increasingly pressure not only from traditional competitors, but also from nimble startups, vertically integrated disruptors, and offshore manufacturers. At the same time, they must manage ongoing supply chain volatility, shifting customer expectations, and a growing need for smarter, more connected products.
To remain competitive, companies must design faster, adapt to change more easily, and eliminate costly inefficiencies. Yet many are still burdened by manual tasks, disconnected tools, and poor collaboration, especially between engineering and manufacturing. These challenges are not just frustrating for employees; they lead to missed deadlines, higher costs, and compromised quality. In fact, 78% of respondents report increased manufacturing and development costs due to product development challenges.
Key Findings
Top Performers, companies that consistently meet or exceed product development goals, are leading the way. Compared to Others, they are:
Expand simulation usage: Use simulation earlier and across more roles to cut physical prototyping, identify issues sooner, and improve design quality. Seventy-four percent of Top Performers use simulation to optimize performance.
How can MedTech companies accelerate digital transformation?
On Thursday, October 23 at 10:00 am EDT, please join Tech-Clarity’s Michelle Boucher for an interactive discussion with Christian Vogelei of Fresenius Medical Care and René Zoelfl of PTC as they discuss this.
They will explore topics like:
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can companies managing capital-intensive projects, such as factories, nuclear facilities, offshore platforms, rail infrastructure, and data centers, avoid delays and cost overruns? What leads to successful projects?
Significant growth is expected in the number of capital-intensive projects over the next few years. However, many of these projects will face delays, cost overruns, and execution inefficiencies. In today's climate of economic volatility, labor shortages, and complex regulations, the pressure to complete projects on time and within budget has never been higher. Still, some companies consistently outperform their competitors. What are they doing differently?
This research study explores project management strategies using a survey of 201 professionals working on capital-intensive projects. The study identifies the primary challenges companies face when managing these projects, including the underlying causes of delays and cost overruns. The findings highlight three key strategies that Top Performers use to manage risk, enhance predictability, and achieve better outcomes in today’s most complex and high-stakes projects.
Please enjoy the summary* below. For the full research, please visit our sponsor, Dassault Systèmes (registration required).
Capital-Intensive Project Challenges
Capital-intensive projects represent some of the most complex and costly initiatives a business can undertake. As global economic volatility, supply chain disruption, skilled labor shortages, and other uncertainties continue to intensify, organizations must figure out how to deliver these on time, more predictably, and with greater financial control.
The research reveals that while there is a strong need for these capital-intensive projects, their execution continues to be hindered by outdated processes, fragmented tools, and collaboration breakdowns. An overwhelming 75% of respondents report that siloed information and miscommunication have a major or significant negative impact on project success.
Overcoming Challenges
To overcome these challenges, skilled labor shortages, and financial risk, companies are investing in capabilities to improve project predictability, increase on-time completion, strengthen regulatory compliance, and become more agile in response to market shifts.
Best Practices
The research revealed three strategies that Top Performers, the most successful companies, implement to manage capital-intensive projects more effectively:
Regulatory Compliance
Evolving regulations, especially in energy, infrastructure, and life sciences, often cause delays and rework. Teams must monitor changes, document compliance, and respond to audits. Yet fragmented tools and siloed data make this a time-consuming, manual task.
Without accurate, traceable data, it’s difficult to:
Too Many Disconnected Tools
Establishing a single source of truth is the most common strategy among Top Performers for improving capital-intensive project performance. This creates a centralized repository of project data accessible to all stakeholders. While most companies recognize the value of this approach, many struggle to implement it. Respondents report widespread reliance on multiple disconnected tools, creating fragmented data environments that hinder coordination, transparency, and decision making.
On average, respondents use 7.5 standalone tools to manage project data, with 46% relying on more than eight. These include spreadsheets and general tools for managing projects, collaboration, scheduling, supply chains, risk, costing, and more.
While each tool may be well-suited for its task, many disconnected solutions make it extremely difficult to get a consolidated view of project information. Respondents report spending an average of 4.8 hours preparing for a single status meeting, while 33% say it takes six or more hours just to gather needed information.
Another issue is that data stored in multiple locations can easily become outdated or conflicting, eroding trust in its accuracy. Team members then waste time searching for and validating data.
An Integrated Platform
These challenges are driving a strong preference for integrated solutions over many disconnected, best-of-breed tools. An overwhelming 85% realize significant benefits with an integrated platform. By consolidating data and workflows, companies can reduce the risk of errors, rework, and delays while increasing transparency for executives and stakeholders. This leads to improved data accuracy, faster decision making, clear audit trails, and more optimized resource allocation. Together, these advantages translate into measurable business value (see graphic).
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full research, please visit our sponsor, Dassault Systèmes.
If you have difficulty obtaining a copy of the research, please contact us.
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What will help MedTech companies stay competitive in an era marked by rapid innovation, rising regulatory complexity, and global disruption?
As the industry moves toward smarter, more personalized, and increasingly connected healthcare, MedTech manufacturers face mounting pressure to reduce time to market, improve patient outcomes, control costs, and ensure compliance without sacrificing quality or patient safety. Achieving success in this environment requires digital transformation. With it, MedTech companies can realize greater efficiencies while developing, building, and servicing products and devices across their lifecycle. What should companies consider to successfully select the right solution?
This buyer's guide outlines key buying criteria across four critical areas: software functionality, implementation support, vendor capabilities, and company-specific needs. Based on expert interviews and market research, it's designed to help MedTech leaders evaluate and invest in the tools that will drive innovation, efficiency, and compliance in the years ahead.
Please enjoy the summary* below. For the full research, please visit our sponsor, PTC (registration required).
Operational Resilience
As regulations tighten and risks rise, full traceability has become critical. MedTech companies must demonstrate how decisions are made, how changes affect safety and performance, and maintain compliance from design to post-market support. Legacy systems cannot maintain this end-to-end visibility. A digital thread, enabled by an integrated solution, supports traceability, audit readiness, and proactive quality management.
Overcome Silos
A digital thread links requirements, design, engineering, manufacturing, quality, and service, making every decision traceable, every change visible, and every team aligned. Traceability accelerates root cause analysis, simplifies compliance, and improves first-time-right development. When requirements are linked to test results, quality and regulatory assurance become built-in.
By integrating Application Lifecycle Management (ALM), Product Lifecycle Management (PLM), Quality Management Systems (QMS), ERP, Manufacturing Execution Systems (MES), and Service Lifecycle Management (SLM), companies improve collaboration, manage requirements, plan for manufacturing, and leverage real-world service data in a shared digital environment. This integration yields numerous business benefits (see graphic).10
Prepare for the Future
This approach enables MedTech companies to transition from document-based processes to data-driven development, integrated quality systems, and connected service operations. It provides the agility needed to thrive in today's disruptive environment. The right solution will also support next-generation capabilities like AI, digital twins, and open interoperability.
How can machine builders improve engineering productivity?
Industrial machinery has become increasingly complex, with even more mechanical components, electronics, and software. Customer needs for improved maintainability, increased automation, and better efficiency have driven this complexity further. Engineers are critical to successfully meet these requirements. Yet, engineers regularly lose productivity to non-value-add tasks that not only rob them of their ability to innovate, but also threaten their company’s ability to compete, differentiate, and grow. Imagine the potential of identifying and removing the most common non-value-add activities engineers face and empowering them to focus on designing better machines.
This research examines how engineers spend their time, where they lose productivity, and the impact on the business. It then identifies solutions and approaches to reduce time wasters. Based on a survey of 228 manufacturers across industries, this report shares the results of the industrial equipment industry and looks at their challenges and opportunities from the perspective of industrial machinery companies.
Please enjoy the summary* below. For the full research, please visit our sponsor, Siemens (registration required).
This report is based off the research published in The Business Value of Reducing Engineering Time Wasters which takes a look across all industries.
For other industry-specific related research, read:
Product Development Is Critical to Business Strategies
Machine designers also waste efforts redoing work. They waste time recreating what they can’t find or fixing errors due to outdated or conflicting information. Better methods to centralize access to data would help get that time back.
Given how fast technology and markets are changing, how can manufacturers of intelligent products ensure they are ready for what’s next? Future-ready manufacturing requires plant floor systems that go beyond traditional manufacturing execution systems (MES). With the full scope of manufacturing operations management (MOM), analytics, and artificial intelligence (AI), companies have a good opportunity to be agile enough to make the next pivot. This eBook explores all of that and more.
Please enjoy the summary* below. For the full research, please visit our sponsor iTAC Software (registration required).
Modern software should include an engine for machine learning and artificial intelligence (ML/AI). Look for models trained based on the MES provider’s expertise. The AI capability must span specific production environments that the engineers know, not just data scientists. The beauty of ML, as the name suggests, is that it learns from reality. In this case, the MES data reflects reality and teaches the model. Sometimes, the MOM offering also includes a toolbox of algorithms that can deliver automated insights.
At the Speed of Operations
What’s crucial is that the analytics, AI, or ML provide results fast enough for the operation to use them effectively. Event streaming can add speed and agility. For maximum effectiveness, the system will also deliver alarms and escalation when anomalies occur. Decision-makers often need to know right away.
Optimizing Analytics
While basic analytics are standard for MES, some special factors can optimize analytics. These include:
We are researching electrical design, including top challenges, identifying the most time consuming tasks, the impact of greater automation, and how poor collaboration between electrical and mechanical engineers affects the development process. We will also use the results to identify best practices. The survey takes about 10 to 15 minutes.
If you are familiar with the electrical design work at your company, either by doing the design work yourself, collaborating with those who do, or managing electrical design teams, please take the survey to share your thoughts. As a thank you, we will send you a copy of the report summarizing the findings.
In addition, respondents will be entered into a drawing for one of 20 $25 Amazon gift cards.*
Individual responses will be kept confidential. Please feel free to forward this survey to others you feel have an opinion to share.
Thank you for your support, please check out our Active Research page for additional Tech-Clarity survey opportunities.
*See survey for eligibility rules
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We’ve been researching make-to-order (MTO) and engineer-to-order (ETO) approaches for over two decades and we’ve witnessed continued growth in product customization. We’ve also watched configuration approaches and technologies evolve. Two things have been consistent over time:
What else has changed? We recently surveyed over 200 companies that manufacture to-order products to find out.
I recently had the opportunity to sit down with Rick Smith , Director of Engineer to Order Solutions at Siemens Digital Industries Software, to get his perspective on our survey and configuration and MTO (make-to-order) trends. I’ve worked with Rick on some of our research, including his participation as a contributing subject matter expert for our recent Making To-Order Product Configuration Profitable survey. I’m always excited to learn from his experience working with customers in the MTO and ETO (engineer-to-order) space.
Jim Brown
Hi Rick. Will you please introduce yourself and your company, and let us know your role with configurators and to-order products?
Rick Smith
I'm Rick Smith with Siemens Digital Industry Software. I'm a product manager for the Rulestream product line. Siemens has a very broad portfolio of engineering and manufacturing software, of which Rulestream is the solution for engineering automation. It works very closely with Teamcenter, our industry-leading PLM system. Rulestream interfaces directly through Teamcenter to a large number of the other solutions in the Siemens software portfolio, so it’s integrated to a complete set of design and CAE (Computer Aided Engineering, or simulation) tools.
Jim Brown
Rick, I always appreciate your enthusiasm as much as your expertise. What gets you jazzed about to-order manufacturing and configurators?
Rick Smith
The excitement goes back to the early 2000s when I discovered the profound impact an automation solution could have on the world of manufacturing complex products. I always suffered from the inefficiencies of the available tools and thought there had to be a better way to do it. In my early exposure to Rulestream (as a customer), I realized that it is a really different way of doing things, giving me the tools that I need to be more productive not only as an engineer but also across the whole business in terms of accuracy and efficiency.
Jim Brown
Thanks Rick. I’m excited to talk about the research with you. The survey looked into why companies configure products. The results show a variety of reasons. The top two, differentiation and higher prices, are about the ability to attract business and profit from it. For them, it’s about revenue and profitability. But sometimes companies don’t have a choice. In fact, our studies often show that providing to-order products is a “must have” for their industry.
Rick, you’ve been working in the space for a long time. Why is making products to order so compelling?
Rick Smith
I think there are several reasons, and it depends on the company and the industry. For one industry, it may just be the nature of the beast. If you're building a solar or a wind solution, you want to use every square inch or cubic inch of space to generate as much income as possible. That means that you want to put up as many solar panels or as many turbines of the right size to fit the space available. Or, if it's a hydro dam, you want to get more kilowatt hours or KVA from the same amount of water. Can we get a more efficient turbine? Can we get more efficient distribution? All of those things require engineering to customize the solution to the unique requirements of the request. By choosing to be in this industry, you chose MTO.
Jim Brown
The next most common response is to sell standard products. In this case, selling customized products is a necessity for commercial rather than technical reasons. What creates this scenario?
Rick Smith
One way this happens is in industries that are commoditized or commoditizing. If customers are consolidating their spend and a manufacturer can offer customized products alongside their standard ones, they choose the company that can offer related products that are configurable, allowing that company to sell more standard products and become the supplier of choice.Making To-Order Product Configuration Profitable, Tech-ClarityMaking To-Order Product Configuration Profitable, Tech-Clarity
Or, they're in a commodity business and they recognized that if they can offer a customized solution at the same cost and lead time as their competitors are offering standard solutions they can take over the market. We had just one such company do that with a commercial air handler, a very competitive business, and they became the number one supplier of that product in the world.
Jim Brown
Configured products are compelling and companies don’t seem to be able to get enough of them. Our research from five years ago showed that the majority of companies were increasing the amount of configuration in their products, and it jumped again during our latest study with 94% saying it will grow over the next five years.
Why do you think customization continues to grow?
Rick Smith
It's all the reasons that we just talked about that drive the desire to do it. Everybody wants a product that is tailored to their unique needs, right? But
I think more companies are moving towards it because their competitors are and they want to either lead or catch up. Just the HVAC example that we talked about, right? They killed their competitors because they offered a custom product.
I also think it’s because automation makes it more cost-effective. Engineering software can do more for to-order manufacturers than ever. It now takes them less effort to support customization across their business because the technology can accomplish more for them and is more integrated into other engineering and manufacturing applications.
Jim Brown
One of the things we looked at in the survey was best practices to increase profits from to-order products across different aspects of their business, including engineering. I know you and I are both engineers, and we found best practices there, but let’s focus on sales. We analyzed what top performing companies do differently in the selling process.
One of the things that we saw was moving configuration closer to the customer, or “shifting left. About one-half of all respondents have taken steps to shift configuration left, such as from sales engineers to salespeople or from distributors to customer self-service. Almost all, a full 90% of responding companies, have, or would like to, shift configuration closer to the customer. Why do you think that the manufacturers are moving detailed configure order entry towards the customer?
Rick Smith
Making To-Order Configuration Profitabile, Tech-ClarityPart of it I believe is due to demographics of the people who are buying. I was a chalkboard and slate guy. There are people today that were born with technology in their hands that expect the ability to chat to their friends at any point in time. So their expectation is I want to do whatever I want to do when I want to do it. They want self-service.
I think part of it is to be easier to buy from. So, we always talk about the sales process. I want to talk about the buying process, which is the more important part. Customers are going to buy from whoever they can buy from the easiest, so long as it is a good solution at a competitive price. It doesn't even have to be the lowest price necessarily, but they're the easiest to buy from. The same is even more true for distributors that may carry different product lines. They don’t necessarily care which line they sell, so they are motivated to sell the one that is easiest to order.
Another proof point that the shift left is happening because is that the survey says companies need mobile device support. Ten years ago, you were not going to buy anything on your phone. Now, it's required because people expect to be able to configure and order things from their mobile device.
Jim Brown
Great insights. Well, we know it’s valuable because Top Performers are 74% more likely to have significantly shifted configuration left than poorer performing companies. As I mentioned, we also identified best practices for engineering techniques, but we’ll have to save that for another interview.
Jim Brown
There are a variety of technologies available to help companies reduce (or perhaps embrace) the complexity of configuration. Sales configurators, engineering configurators, and simpler CPQ solutions. Top Performers are more likely to use configurators in general. But what really stood out is that they’re also more likely to use advanced configuration functions like of drawing creation, CAE automation, 3D visualization, and engineering calculations.
Rick, this reminds me of the automation you spoke about earlier. In the survey report, we interviewed a customer who says they reduced engineering hours from CAD automation that works hand-in-hand with their PLM. The Top Performers also say it helps them grow revenue and profitability.
Why do you think these capabilities are correlated with improving operational and business performance of their to-order products?
Rick Smith
I think there's two things. It allows them to create a better quality design and a better quality bid package. That’s a start. But the types of products that our customers sell are not simple products, right? There are calculations that need to take place. There are a lot of very good CPQ systems with good configurators built into them, but those are not really built for technically complex products. The industries targeted in the survey included heavy equipment, industrial machinery, agriculture, and energy equipment. Those products require more industrial strength, if you will, configuration technologies.
They need better tools to get the value they want. For example, the survey showed the leaders use substantially fewer engineers in the bid process. It's because those companies use the more sophisticated tools that are capable of doing more of what an engineer does as part of the sales process. The market leaders have figured out how to get the engineers to invest their brains into the configurator so they can go off and build new, exciting things and they don't need to be a part of creating the bid package.
Jim Brown
So not only are the Top Performers able to create better-configured order designs and design deliverables, but they are also doing it more efficiently, responding more quickly and freeing up engineering resources at the same time?
Rick Smith
Exactly!
Jim Brown
Let’s drill down on technology. Our research shows that companies are getting significant value from AI, and we’ve even seen that AI is providing benefits faster than other technologies. We haven’t studied the use of AI for configuration, although it seems like there could be significant value. I have to imagine you have looked into the value of AI for product configuration. Is there real value, or are we just in a period of hype?
Rick Smith
There is a ton of excitement. I think you’re right that it is a little bit early, and I think some of it is misunderstood. One of the areas where we can see direct applicability of AI is getting specifications right. A customer may provide a spec document and drawings. Then, a sales engineer opens it up with a yellow highlighter (or virtual yellow highlighter) and reads through those requirements and the drawings and creates takeoffs. That’s a perfect application for AI, and there are solutions available to help with that today. That directly replaces manual effort.
Another area that's very interesting is being able to get more information out of your configuration knowledge. Configuration rules have typically been expressed in a form that a solver can use, whether it's declarative, closed form, constraints, or whatever. You could use AI to interpret it and give you back that knowledge in a format that people can understand, validate, and reuse.
Jim Brown
That’s very interesting. Will AI replace traditional configuration techniques?
Rick Smith
I don't think they're going to replace the automation or configuration solutions. And here's why. You need to train AI. But how many designs do most companies have that actually follow their design best practices? The designs may include changes to address a supply chain event or may be prior to a cost engineering event. Do they have enough designs to cover the full range of product variability in the way they design today? Automating outdated rules does you no good. And even if AI got you 80% of the way there, well-formed automation or well-formed configurators give you the right answer 100% of the time.
In the next several years, I do think AI can be used to help feed configurators the rules. That’s something that's done by hand today and can be assisted by a co-pilot.
Jim Brown
The last question I would ask you is if you were working for a manufacturer and trying to figure out what you were going to do around configuration, what advice would you give yourself?
Rick Smith
I did not have an answer thought through on this one. I think there are three things I would say:
First is to understand your product space, your competitive landscape, your market, and the trends for the future. Don't just try to solve today's problem.
The second thing is be careful. You need to leverage the experts and ask them counter questions. We’ve seen examples where consultants have recommended an approach like shifting from ETO to MTO that was fundamentally unachievable. That company wasted a lot of time and money, and ended up losing significant market share. Work with people who understand configuration.
Finally, look at a platform. You want to have a platform that's going to be around because you're going to be investing in it. Look at companies that have proven track records, are continuing to invest in their solutions, and are investing in the integration of solutions. Point automation can be helpful, but optimizing for an entire business process is even more powerful. Configuration is not trying to automate one little thing, it's trying to optimize an overall digital thread, a business process for to-order products.
Jim Brown
That makes sense. Configuration doesn’t only touch Engineering, it impacts across the enterprise and the supply chain.
Thank you Rick. That’s all we have time for. As we concluded in the report, we believe that the use of product configurators is a basic necessity for designing, selling, and delivering to-order products, but that companies who adopt proven best practice engineering, order, quote, and technical enabler gain significant advantages that translate directly to improved revenue and profitability.
There is more information available in the underlying survey report, including interviews with Schumacher Elevator Company and Ingersoll Rand. You can view a summary of the research on our site or download the full survey report courtesy of Siemens.
Thank you for the conversation Rick, I always learn something new when we talk!
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Hexagon AB invited Tech-Clarity to the recently concluded HxGN LIVE Global 2025 event in Las Vegas and our analyst, Arvind Krishnan covered this event. In this article, we want to discuss three announcements that stood out: Octave, Proplan AI/Autonomous Metrology Suite, and Aeon.
What is Octave, and why did Hexagon create this new company?
Not too long ago, Hexagon announced it would spin off its Asset Lifecycle Intelligence (ALI) division. Now, we know the name of the new company - Octave. In addition to ALI, Octave will include the Safety, Infrastructure, and Geospatial (SIG), ETQ, and Bricsys divisions. Hexagon also announced Mattias Stenberg as Octave's CEO. Hexagon expects Octave to become a publicly listed company sometime in 2026 (subject to the approval of the Board and shareholders). So, what was the need to create Octave? The answer is FOCUS, in our opinion. If you attended HxGN LIVE Global 2025, it was clear that Hexagon's core business wants to focus on metrology and other hardware-related verticals. Another reason could be that it intends to separate its software/SaaS businesses from its hardware businesses and unlock value in both divisions. If you believe that the growth potential of the SaaS business is higher than that of the traditional hardware business, Hexagon's shareholders can realize this superior growth from Octave. We wish Octave the very best in its new journey.
The theme for Manufacturing Intelligence was quality. Andreas Renault, the President of MI, talked about quality for life. Many of today's products touch people's lives and quality products are about delivering a great experience. Good quality products turn functionalities into great experiences for customers. And Hexagon believes that quality is the #1 driver for innovation. Andreas shared some eye-popping data (85% of manufacturers struggle to solve the underlying causes of quality issues), where solving quality problems is a significant business challenge. Many new products (scanners, CMM machines, and software) that Hexagon unveiled at the event directly address quality. A couple of solutions that I want to discuss are Proplan AI and the Autonomous Metrology Suite.
Proplan AI is an advanced AI-driven CNC process planning solution integrated with Hexagon's ESPRIT EDGE CAM suite. Proplan AI helps new operators quickly become proficient in programming CNC machines, enables companies to cope with the skills gap, and improves productivity by reducing manual processing time. Since Proplan AI learns from past CAM files generated by experienced programmers in the company, it embeds corporate know-how (preferred speeds, feeds, tools) to ensure consistency and guarantee quality. Ultimately, Proplan AI empowers organizations to retain institutional knowledge, defer routine engineering work to AI, and accelerate time‑to‑market with consistent quality and lower resource overhead. Proplan AI uses the Nexus platform and also Nexus SaaS user interface. According to Hexagon. this platform and user interface approach to Proplan AI would accelerate the adoption of cloud technology for traditional desktop users.
Hexagon also announced the Autonomous Metrology Suite, an innovative software solution designed to streamline quality control in manufacturing by eliminating coding from coordinate measuring machine (CMM) workflows. By Automating and simplifying measurement processes the Autonomous Metrology Suite drastically reduces programming time from days to hours, making it easier for manufacturers to maintain high accuracy amid growing pressures like shorter product lifecycles and a shortage of skilled CMM programmers. Based on the Nexus platform, the solution features a user-friendly interface, enabling even novice users to create compliant inspection programs while ensuring consistent measurement standards across operations. solution's real-time data analytics and monitoring capabilities empower manufacturers to make data-driven decisions, ultimately enhancing productivity and efficiency on the shop floor.
Hexagon’s Robotics Division introduced Aeon, a versatile, humanoid robotic system blending advanced mobility, sensor fusion, and AI-powered spatial awareness to execute tasks in human-centric industrial environments autonomously. Hexagon Robotics designed Aeon for manufacturing applications. Three use cases that Hexagon highlighted stood out for us.
Many of the new solutions we learned about in this event directly support Tech-Clarity's research findings. Quality is indispensable to manufacturers, and they are investing in technologies that can help them improve the quality of their products and services. At the same time, finding a skilled workforce in manufacturing is challenging. Manufacturers in every region echo this challenge. So, solutions like Proplan AI, Autonomous Metrology Suite, and Aeon, which address quality and skill deficiency issues, are likely to be widely adopted by manufacturers.
Many of Hexagon's existing software solutions in Design and Engineering also help manufacturers find and address the root cause of quality problems in manufacturing. The users of these solutions could also benefit from AI. Unfortunately, Hexagon did not share much about its AI strategy for existing products. It is possible to see Copilot-like features for many of Hexagon's software solutions. And this enhancement could be a game-changer for Hexagon’s customers.
Thank you, Robin Wolstenholme and Mandy Wardman, for giving us analysts a wonderful experience at the 2025 event.
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How do Top Performing automotive companies balance quality, cost, and sustainability to gain a competitive edge?
Early design decisions significantly shape a vehicle’s total cost and environmental impact. Yet, for many OEMs and suppliers, critical cost and carbon footprint data is scattered across systems, making it hard to evaluate trade-offs when it matters most.
How can automotive companies empower teams to make informed decisions to optimize trade-offs?
Based on a survey of 178 automotive companies, including OEMs and suppliers, this research study examines best practices for managing cost while considering the implications of quality and carbon footprint. The research also reveals how automotive companies can empower teams, including sales, design, procurement, and sustainability, to make more informed decisions to increase profitability.
Please enjoy the summary* below. For the full research, please visit our sponsor, Siemens (registration required).
Balancing Profitability Drivers
Standing out in the competitive automotive market requires early strategic decisions. Survey respondents report cost, quality and product carbon footprint among the most important differentiators. Research estimates that 70%-80% of a product's lifecycle costs1 and 80% of a product’s environmental impact2 are determined by decisions made early in the product lifecycle. Multiple roles including sales, design, procurement, and sustainability would benefit from accurate, consolidated insights to make more informed decisions around this criterial criteria. However, data is unavailable or scattered, making it hard to assess trade-offs. With competing priorities, teams struggle to gather needed information. If they could, it would drive significant advantages. This report explores those benefits.
Win More Bids
Competitive pricing and delivery timelines are key to winning bids. Consequently, understanding cost is critical to keeping prices reasonable without compromising profit margins. Beyond that, when everything else is equal, lowering the carbon footprint can be a deciding factor.
Early Assessments
Early product cost and carbon footprint estimates enable better decisions when they have the most impact. Access to comprehensive data helps automotive companies reduce costs without compromising quality.
Digital Thread
While early access helps, decisions based on outdated information offer little value. Teams need a comprehensive view of current data as designs evolve and supplier data changes. Traceability will enable a better understanding of a decision's full impact.
Use the Right Software Tools
A tool that consolidates data sources, such as from PLM, CAD, ERP, and supply chain solutions, provides a comprehensive view of design details, material information, and supplier data to support more informed decisions.
This report explores this approach and the benefits Top Performing automotive companies achieve.
How Top Performers Were Defined
To define Top Performers, Tech-Clarity identified the top 25% of companies that outperform their competitors in metrics that indicate business success. These metrics were:
Recommendations and Next Steps
We are pleased to announce that Howie Markson joins Tech-Clarity as Director of Research for Digital Innovation. This strategic hire strengthens Tech-Clarity’s ability to help educate manufacturers on how to navigate complex technology decisions to improve business performance. Howie’s focus areas include product design, simulation, PLM, PDM, SLM, IoT, AI, and other product development solutions for manufacturing companies. Howie has a degree in mechanical engineering and 25+ experience across product design, product management, application engineering, and product marketing covering a wide range of companies, industries, and technologies.
Please visit Howie’s bio page for more details on his background.
“Howie brings deep PLM knowledge and experience to Tech-Clarity. This enables our analyst team to expand coverage of digital transformation across the enterprise, including service and supply solutions,” notes Jim Brown, President and Founder of Tech-Clarity. “At Tech-Clarity our goal is to provide manufacturers valuable insights on industry trends and new technologies, such as AI, throughout the product digital thread from inception to service. Howie’s extensive industry background and keen understanding of technology and its business value helps us further our mission.”
Today, manufacturers are challenged by product complexity, regulations, cost pressures, and changing market dynamics across many traditional sectors. Consumer expectations have reached new heights with the desire for sustainability, personalization, affordability, and advanced features. This puts enormous pressure on a company’s product development process. Fortunately, unprecedented access to mature product development applications and powerful digital technologies makes it possible for manufacturers to improve their product innovation and business performance.
To take advantage of these opportunities, manufacturers are digitally transforming and seeking the latest technologies and best-in-class solutions for their product development needs. Their goal is to find solutions that deliver powerful new capabilities (such as Artificial Intelligence) and support key transformative goals (such as Digital Twin, Digital Thread) that bring tangible business benefits.
However, in a software industry full of acronyms, rapidly evolving product capabilities, and fast-changing technology it is difficult for manufacturers to navigate through the myriads of software providers and product offerings. Howie‘s experience across a wide range of industry products and technologies brings a needed perspective to manufacturers looking for clarity on the capabilities and value of the various offerings.
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Tech-Clarity President and Founder Jim Brown had the opportunity to join Siemens Vice President of Industry Strategy Dale Tutt on his podcast, The Industry Forward. Host Conor Pieck leads a lively conversation between Dale and Jim where Jim shares insights from Tech-Clarity’s research and Dale offers perspectives from his rich experience in the manufacturing and software industries.
Conor leads them in a discussion about what leading companies are doing differently in pursuing the digital enterprise and how they use digital transformation to drive agility and overcome disruption. Jim shares statistics showing that companies with more digital data and processes achieve better business performance. Dale and Jim discuss how becoming more digital helps companies in a variety of ways, including getting to market faster and improving engineering efficiency. Listen to this episode for the first of three parts of the rich conversation between the two seasoned professionals.
About The Industry Forward Podcast:
Welcome to the Industry Forward Podcast with Dale Tutt! Join Dale Tutt, Vice President of Industry Strategy at Siemens Digital Industries Software, and host Conor Peick to learn more about the trends, technologies, and opportunities affecting some of the largest and most important industries in the world. In each episode we will be joined by a seasoned expert to dive into the dynamic challenges and creative solutions being developed in a variety of industries to learn how companies are transforming for the future. These experts will tell us about everything from medical devices to heavy equipment and more and explain how each of these industries is approaching digitalization and the digital twin to overcome the hurdles they are facing.
[post_title] => Jim Brown Talks Digital Transformation on The Industry Forward Podcast
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Can manufacturers maximize plant human resources as effectively as inventory and equipment? Covalent would say yes. That is what their workforce operations platform is designed to do: continuously maximize labor effectiveness. They continue to build out in multiple directions: functionally, beyond tracking training and job experience to creating an interactive skills matrix, optimizing work allocation, and last-mile line staffing. They have also gained new customers beyond A&D and automotive in chemicals and CPG.
How can individuals be more effective and efficient through improved collaboration? How can companies get the most out of their people, processes, projects, and portfolios? We'll explore how improved collaboration, both structured and unstructured, helps companies grow, scale their business, and become more resilient to achieve long-term, sustainable business success. We'll also share how to improve collaboration in five dimensions: people, process, project, portfolio, and technology.
You can download the full eBook here here and learn more about business collaboration from our sponsor, Dassault Systèmes.
Let's look at operationalizing collaboration from a people perspective to maximize their collective insights, innovation, and knowledge. As companies grow, it's essential to move beyond more naturally occurring ad-hoc collaboration common to smaller teams and organizations. Larger teams and companies must be more intentional to create a virtual environment that encourages people to share their unique ideas, perspectives, and expertise. Even smaller companies typically have significant room for improvement.
Beyond simply submitting ideas, contributors have to be able to expand on ideas and provide feedback in a social, community setting. They have to create an environment where ideas can mature, grow, and spawn new idea threads. Community-centered collaboration helps empower individuals to effectively contribute based on their unique skills, training, and experience. It allows the company to leverage the tacit knowledge in their employees’ heads in addition to structured documentation.
A Case in Point
Let's look at a scenario where people work together and combine their expertise to resolve a customer complaint about a product damaged in delivery. In this case, the problem – and the solution – may lie across a variety of company domains, including product engineering, packaging design, distribution, the supply chain, and customer service. Bringing a cross-functional team together to brainstorm and problem-solve in a virtual workspace with a virtual whiteboard allows employees to contribute to a more holistic solution. They can work toward a common goal instead of placing blame across departments. In this way, the company leverages its know-how to develop an optimal solution and simultaneously capture the interaction to increase company knowledge.
Create Repeatable Collaboration
Next, let's look at operationalizing collaboration from a process perspective. There is no value in recreating the wheel for every collaboration effort. Companies should coordinate work and workflows to move from ad-hoc to repeatable, managed approaches. By focusing efforts around tasks and workflows, teams can leverage best practices and continuously improve the way they work together on specific scenarios. Leveraging workflows to manage collaborative processes helps people stay on task and track progress.
These workflows should also be associated with their context, the underlying data people need to play their roles. Associating the process with the appropriate information improves efficiency because team members can efficiently work in a common environment on the same data. Then, they can add their own information to extend knowledge. It also helps create traceability and develop a digital thread of information related to the process.
A Case in Point
Let's take an example of bidding for a new program or contract. Capturing new business requires input and tradeoffs between legal, financial, pricing, strategy, compliance, technical, and other perspectives. Allowing participants to track progress centrally by creating a collaborative process that leverages common data streamlines their work. Enabling them to make new information visible across roles in real-time so they don't have to wait for another department to finalize their input before providing feedback or adding their own perspective saves time. By leveraging a standard workflow, or at least starting from a common template, the team can ensure they cover all aspects and take advantage of automation, such as routing logic to improve the efficiency of input, reviews, and signoffs.
Organize Activities and Actions
Let's examine operationalizing collaboration at a broader level to improve project performance. Larger initiatives require greater coordination but bigger team sizes can hamper collaboration. It's essential to ensure project basics, including tasks, schedules, staffing, and budgets, are in place and people are working against a single plan. But to get the most from everyone, companies have to move beyond spreadsheets and disconnected project planning tools. Instead, they need a shared project environment so the entire team can access shared, measurable, and highly visible objectives that create a sense of team mission.
A collaborative project approach gives teams central visibility to track and manage tasks, progress, KPIs, and risks so everyone has visibility to the broader initiative, not just their individual activities. Connecting project management with underlying people, processes, and data makes project management integral and not standalone. This is important for traditional project management approaches but even more critical for increasingly common agile project approaches.
A Case in Point
Let's consider a company planning and executing a decarbonization initiative. People need to know their roles and tasks and should be able to raise issues so they can be addressed quickly, for example by using lean techniques like Kanban. Taking an integrated approach associates data and tools so the team can work together in real time, such as using data science tools to gather supplier data, product information, and additional details to calculate, optimize, and report on carbon content. An integrated approach also allows dashboarding, for example connecting sustainability goals with actions, giving the team more ownership of – and pride in – the results of their work.
Develop Profitable Portfolios
Stepping up to an even broader perspective, let's discuss how operationalizing collaboration helps improve the ability to turn innovation portfolios into profits. Defining a winning portfolio is inherently a data-driven activity and companies have to move beyond disconnected tools and spreadsheets. Instead, they must be able access internal and external content from enterprise systems, the cloud, managed content, broader data repositories, and data lakes in real time to optimize decisions through simulation and what-if scenarios to act on facts instead of opinions.
Optimizing portfolios, however, requires effective collaboration. Portfolio management and new product development are inherently team-oriented activities, requiring input and analysis from across the organization. Team members must be able to share internal knowledge and prior experience to analyze and validate opportunities. They have to be able to work together across departmental boundaries to test assumptions, find issues early, and make difficult tradeoffs required to optimize the innovation strategy. Doing this in a collaborative environment allows them to trace decisions so they can leverage prior analysis as market or technical considerations change over time.
A Case in Point
Let's look at an example of setting the product innovation roadmap. Companies need to optimize their R&D investments to drive market share and profitability. Analysts need to be able to rapidly gather market data, insights, and analysis through data analytics and incorporate internal data like customer experience, sales, complaints, and requests. They need to be able to bring perspectives from across the enterprise to identify risks and validate plans to optimize the portfolio and gain executive buy-in before communicating and executing the portfolio strategy. Beyond the data, they must incorporate the organization's collective experience through collaborative decision-making on centralized data.
Adopt a Collaborative Platform
The fifth dimension supports the first four. Companies need the right digital infrastructure to operationalize collaboration across people, process, project, and portfolio perspectives. As the examples show, moving from ad-hoc and unstructured collaboration demands new ways of working. These methods require new technology, such as virtual workspaces for people, processes, projects, and portfolios that connect data, decisions, and workflows with the people who have the right information and ability to take action.
Traditional, ad-hoc tools are insufficient to support innovation, agility, and resilience. Today's status quo, including spreadsheets, presentations, emails, texts, online meetings, and phone calls, are all disconnected forms of collaboration. These result in people acting on partial information and not getting the benefits of company-wide experience and knowledge. Informal, disconnected tools don’t support even very small companies well, and certainly won’t allow them to scale collaboration as they grow.
What to Look For
It's critical to adopt the right collaboration platform. Standalone collaboration tools that provide communication and threaded discussions are valuable but don't create a single source of truth. Further, they don't provide the tools needed to make and execute optimal decisions without having to open yet another set of applications. On the other hand, the right collaboration platform can create more harmonized collaboration and communication by capturing all activity and information in a central location, integrating it, and putting it in the context of data, tasks, projects, and decisions.
It's essential to adopt socially-oriented collaboration, for example through cloud-based wikis, discussions, and communities to encourage broad participation. However, the solution should also provide integrated status, processes, and contextual data.
It should offer the right analytic, simulation, and visual communication tools to gather the right information, frame the decision, provide direction, and allow people to collaborate and communicate an optimal plan.
Go Beyond Generic Tools
Beyond generalized collaboration tools, it's prudent to explore collaboration platforms that to provide tools to get the job done in addition to enhancing communication. Companies should look for a platform that adds direct value to their business, such as functionality to support product development or engineering work. The ideal collaboration environment provides a common area for collaboration, decision-making, and traceability. That platform, however, should also incorporate modeling, digital twins, simulation, and analytics surrounding common data to support the task at hand from people, process, project, and portfolio perspectives to drive future innovation and continuous improvement.
It’s Time to Act on Collaboration
Collaboration is more than a buzzword, it’s a means of competition that drives countless business benefits ranging from individual productivity to enterprise-level profitability. Companies that optimize how they collaborate are better poised for profitable growth as they compete in today’s environment characterized by increased business risk from disruption and increased opportunity from digital transformation. It’s time to focus on collaboration as an operational discipline that can be enabled and continuously improved over time.
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What makes a digital thread that weaves through manufacturing possible? The answer is: operational data management, which includes a host of capabilities to connect, collect, contextualize, and make data flow across offices, plants, and the field. ThingWorx, a PTC Technology, has been doing that for years, and we recently had an update briefing on version 10.0. Working with customers, PTC continues to improve, evolve, and expand the platform.
ThingWorx is an established and widely used industrial Internet of Things (IIoT) platform. PTC claims over 2800 customers trust it, including over half of the Fortune 500. It also has an impressive ecosystem of partners with thousands of developers. It is widely used in industrial equipment, automotive, aerospace and defense, and medical technology companies.
Our research shows that having data available and ready to use is the most common challenge for AI projects. Together with Kepware connectors, ThingWorx can bridge to nearly any on-prem, edge, and cloud data to enable an industrial digital thread. Beyond connectivity, the ThingModel ensures the data is in context. Other keys to gaining value are the ability to build mash-up solutions and dashboards or other visualizations. These can help the manufacturers’ teams solve specific issues and analyze the complex data sets that the platform puts into context. 
On top of the platform, PTC has built a set of interesting solutions. These leverage the ThingWorx platform for data management, but go well beyond. These pre-built solutions deliver specific, targeted capabilities.
During the MLC Rethink conference, PTC released ThingWorx Version 10. We were particularly impressed with IoT Streams, which deliver fast access to time-series industrial data from anywhere in the company. To do this, ThingWorx 10.0 aligns with Kafka and soon, MQTT, for data flows, contextualizes the data. Upcoming releases enable it to feed into a data lake or AI model. PTC is partnering with Databricks and Microsoft Fabric on this. We see this as a crucial improvement for industrial DataOps.
Performance enhancements include better caching, better server scalability, and reduced response times. Security upgrades to TLS, Tomcat, and Java are designed to meet the needs of regulated industries such as federal contractors and medical devices. The 10.0 version also updates analytics and integration with genAI tools[AT1] [AT2] , and includes a native debugger to boost development productivity.
ThingWorx has many fascinating customer examples of business value.
Clearly, the original scope of ThingWorx as an IIoT Platform is central, but it keeps growing. Solutions and accelerators are becoming more robust and scalable with users’ input. As most software providers today, AI is a significant focus for the roadmap.
Our key takeaway is that ThingWorx with Kepware for industrial connectivity has grown to be more capable as an industrial data management and data operations platform than we’d realized. All the essentials are there and being improved regularly. This makes ThingWorx a capable platform for AI and applications using an array of industrial and enterprise data.
Thank you, Ayush Tiwari, for taking the time to brief Julie Fraser and Rick Franzosa on the latest for ThingWorx. We look forward to following your continued progress in the market.
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Should emerging companies implement factory software before product lifecycle software? Sometimes. Julie Fraser’s blog post for the First Resonance site explores the strengths of modern MES and when it might be the priority application to implement, even when PLM is not yet in place.
Can a highly regulated pharmaceutical or biotech company trust AI in their GXP manufacturing operations? Apprentice says yes. In the past year, they have added GenAI for intelligent context-awareness to the Tempo MES / LES / Automation solution. Now, they have added agentic AI to automate production and lab processes further. It might sound like auditors would balk, but Apprentice has built ways to control the agents’ capabilities and validate the system.
Apprentice started in 2014 with cloud-native training, and shook the market in 2020 with its GXP-focused Tempo MES being no-code, cloud-native, and available on mobile. Pharmaceutical, biotech, and vaccine companies started to adopt it with good results. These customers pushed for a broader footprint, including the lab execution (LES) and automation elements. Apprentice also added multi-site and multi-enterprise capable versions to serve its major pharma customers. Now AI is the news, and Apprentice has it, with additions that support all of the functionality and users in new, intuitive ways.
Last year, the product gained generative AI capabilities. In Ask Apprentice, operators can ask questions about their tasks and get guidance on the spot. Supervisors can also see status and get production updates from this portion of the software. This is classic copilot capability for Tempo.
Other GenAI capabilities include a procedure author that can start with a prompt, an existing PDF procedure document, or the procedure from an MES and uses natural language for editing. It could also recommend procedures that the user could accept or reject. The AI Run Simulate capability could simulate and test procedures to ensure they behave as expected before deploying them to the operation.
Apprentice is adding agents for authoring, quality, and a limited release for process in the September release. These take GenAI capabilities to the next level, with autonomous agents to execute tasks that still have a human in the loop. They have chain-of-thought reasoning and test their work. Authoring, for example, will check itself, quality will focus on things such as review by exception and batching for bulk approval. There is also a second agent checking the work and recommending edits to the procedures. These agents can test what executed values of a recipe would be using that procedure, and can iterate until satisfied with the output. The end-of-2025 release will include additional agents for scheduling and continuous improvement. All five agents were in beta testing when we met with them in August.
These agents are built on top of everything already in the Tempo system, which our research shows is what manufacturers want. The vision Apprentice has is that instead of scaling out teams with people, their customers will use these agents for tasks no one wants to do or that are time-consuming. The agents are intended to free the people for deep thinking tasks. In this way, the company believes they will make it easier to see the financial payback of MES by increasing throughput and decreasing the cost of goods sold (COGS).
Privacy: In the regulated environments Apprentice serves, questions abound. We asked about privacy and protecting the customers’ IP in these agents. Apprentice does not train the agents on customers’ data, but rather on internally generated golden run data sets.
Guardrails: Customers are in control of what agents can do. They can set per-agent parameters either globally or for each process. They also decide who can use which agentic and GenAI capabilities. This goes beyond existing Tempo roles and access controls.
Validation: Apprentice has, for years, followed FDA guidance for risk-based computer software assurance (CSA) validation, including documenting the validation. This reduces or eliminates the need for customers to do additional validation. With the agents, they are ensuring explainable decisioning, implementing data and concept drift, and stressing input conditions to see output accuracy, among other things. Apprentice product management and quality team members participate in the Biophorum AI validation work stream and the ISPE AI Guidance steering Committee to ensure they help drive and are up to date with the latest practices.
Apprentice manages over 7000 runs and 2000 exception approvals per month. Its customers have shared their successes at events such as Pharma MES USA.
Moderna used Tempo for a global facility expansion to improve preparation for a pandemic. Its greenfield plant went live in under a year, with 28 procedures created digitally in five months. The system is integrated with SAP and AVEVA OSI PI and operates as a fully validated GMP manufacturing facility.
A biologics CDMO used Tempo to digitize their labs and manufacturing operations. Batch records were a focus, and they did it without IT overhead or MES consultants. They had six sites go from kickoff to go-live in nine months. Their iterative approach achieved review by exception.
Apprentice expects to see enormous value for customers as the agents come online in full version releases later this year. It also has long lists of improvements in functionality, integration, analytics, and reporting or communications. Thank you, Emilee Cook and Justin Foreman, for explaining the product and company progress, and Kristen Kucks for setting up the briefing for Rick Franzosa and Julie Fraser. We look forward to our next update!
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Over the last seven years we’ve researched what companies are doing to drive long-term, sustainable business success. This year we extend our focus with a new look at business sovereignty and a deeper look into AI. What are the biggest disruptors companies face? What strategies are companies adopting? What priorities are they placing on the critical factors that drive success? What technologies are they employing? And how has the changed over the last year. Take a look at our survey results to find out.
Please enjoy the summary* below. For the full research, please visit our sponsor Dassault Systèmes (registration required).
ESG for Sustainable Business Success
As always, the study looks at ESG (environmental, sustainability, and governance) in the context of long-term success and profitability. The results show that the vast majority, 86%, say that environmental sustainability is critical or important to the long-term success of their company. The study also shows that ESG strategy drivers, including internal goals for net zero, customer demands, and increased calls for transparency like product passports, have increased.
Digital Transformation is Crucial to Success
As before, survey responses show the importance of digital transformation to long-term success. This year, we added a deeper line of inquiry into the adoption and strategic value of AI (artificial intelligence). Not surprisingly, companies have broad goals for AI, and it is delivering business value. Let’s dig into the details on how companies plan to focus on the essential pillars of long-term business sustainability to ensure business success.
Cybersecurity Threat is Significant
This year’s research began tracking the negative business impact of cybersecurity. This digital threat debuted as the second most commonly reported risk over the last year and was reported by almost two-thirds of respondents. Companies today can’t ignore online threats, and we expect this to continue as companies become increasingly digitalized.
Other Factors Subsided
Risks come and go. For example, the impact of global health concerns dropped significantly this year. Workforce issues continue to plague companies, but have dropped slightly in prevalence after a significant increase last year. The impact of energy shortages also subsided somewhat, perhaps as companies learned to deal with issues and uncertainty decreased. Despite these reductions, of course, any of these could become significant issues in the coming year, demanding vigilance.
In addition to addressing time-sensitive disruptors, companies must maintain focus on the fundamentals of business to be successful over the long term. Additional pillars that companies report are critical to long-term success include product/service innovation and agility, environmental and social responsibility, and developing the workforce of the future.
ESG drivers remain steady, although the demand for transparency, including product passports, has increased. Even in these challenging times, when priorities may falter, companies this year are 26% more likely to include ESG as a critical long-term success driver, and more companies are incorporating ESG priorities into their corporate strategy and actions.
Focus on Resilience and Explore Sovereignty
Supply chain resilience continued to grow in importance to long-term success. One approach to accomplishing this is seeking supply chain sovereignty. We observed companies putting significant emphasis on supply chain independence and found that many are also pursuing sovereignty in other areas, including technology and data sovereignty.
Extend Digital Transformation Strategies with AI, Cybersecurity
Digital transformation is seen as the most common factor impacting long-term success. It’s the most common area companies are accelerating to combat short-term disruption. Technology is essential to long-term business success and adds direct value. Two areas getting significant attention are AI and cybersecurity.
Cybersecurity, as a new focus, is top of mind for executives, not just technologists. It showed up as both a significant driver of long-term success and a significant risk that creates negative impacts on companies. Company leaders are also focused on AI and have a wide variety of goals, are adopting a variety of approaches, and are gaining value despite facing both business and technical challenges. We see a trend toward companies looking to their solution providers to help with holistic, industry- and application-specific solutions built into their existing solution platform to speed up and ease adoption.
Remain Vigilant and Prepare for Disruption
This survey, as the previous ones, makes it clear that company success and profitability are under siege by a variety of challenging and changing factors. To survive, companies will need to continue to monitor and adapt to risk and disruption. We believe those that digitally transform will be better positioned to overcome short-term risk and disruption and improve the performance in the pillars that allow them to achieve long-term success.
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full report, please visit our sponsor Dassault Systèmes.
If you have difficulty obtaining a copy of the research, please contact us.
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How can shipbuilding companies improve engineering productivity?
Shipbuilding has become increasingly complex, with a growing number of owner and sustainability requirements, new technologies, suppliers, and co-makers. Engineers are critical to successfully meeting these requirements. Yet, engineers regularly lose productivity to non-value-add tasks that rob them of their ability to innovate and threaten their company's ability to compete, differentiate, and grow. Plus, this wasted time leaves little bandwidth to respond agilely to the fluctuating needs of the global economy. Also, wasted time increases the risk of late delivery penalties. Imagine the potential of identifying and removing the most common non-value-add activities engineers face and empowering them to focus on designing better ships.
This research examines how engineers spend their time, where they lose productivity, and the impact on the business. It then identifies solutions and approaches to reduce time wasters. Based on a survey of 228 manufacturers across industries, this report looks at the challenges and opportunities from the perspective of shipbuilding companies.
Please enjoy the summary* below. For the full research, please visit our sponsor, Siemens (registration required).
This report is based off the research published in The Business Value of Reducing Engineering Time Wasters which takes a look across all industries.
For other industry-specific related research, read:
The Time Wasters
Reclaiming Lost Time
Shipbuilders prioritize their future growth and sustained success with a market-leading product of superior quality, on time, and within budget. To support this, they can significantly boost their product development capabilities by eliminating time wasters that consume engineers' valuable time.
Companies developing complex products such as ships find that PLM can empower their engineers to innovate by significantly reducing engineers' time on non-value-added tasks. As a result, they can enjoy a competitive advantage. In addition, technological advances, such as cloud-based offerings, can reduce implementation time, cost, and difficulty, making PLM more accessible.
*This summary is an abbreviated version of the ebook and does not contain the full content. For the full report, please visit our sponsor Siemens.
If you have difficulty obtaining a copy of the research, please contact us.
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We’ve followed Tulip since the early days and were excited to catch up and see what they have accomplished over the past year. From their inception, Tulip Interfaces deliberately set themselves apart from existing industry acronyms like MES (Manufacturing Execution Systems) and MOM (Manufacturing Operations Management). This decision offered advantages and challenges, as many manufacturers seek solutions based on a clearly defined TLA (Three Letter Acronym). Instead, Tulip introduced itself as a Frontline Operations Platform. Early adopters of the solution/toolkit were drawn to Tulip’s platform for its intuitive application development and the potential for reusability—well before “composable enterprise” became an industry buzz phrase.
Critics and skeptics initially raised concerns about the absence of a unified data model, weak configuration management, minimal revision control, governance, and limited security. Over time, however, Tulip addressed these shortcomings. The platform matured, the library of available applications expanded, and critical features were refined.
Tulip’s reach grew from its roots in discrete manufacturing to include life sciences—encompassing pharmaceuticals, biotech, and medical devices—and now extends to aerospace and defense. Tulip has continued innovating in content and data management, edge and enterprise connectivity, and security and governance throughout this evolution.
Tulip is well-positioned as a data analytics and insights platform developer designed to transform factories and manage global operations digitally. Our research shows that manufacturers investing in Analytics and AI are gaining substantial benefits (see Making Manufacturing Analytics and AI Matter). The benefits matter, as they are in the areas that match their objectives: cost, efficiency/productivity, quality, and error-proofing, most commonly.
The strength of the Tulip platform has always been the ability to start with predefined functions and compose a solution that can be easily modified and/or extended to meet additional needs. To accelerate customers' abilities to create and extend these solutions, Tulip has provided a library of more than 170 predefined apps and more than 40 predefined app suites. If you are in an industry currently supported by Tulip, you will likely not be starting from scratch to build a solution for your production floor. Suppose your concern is the ability to connect to devices. In that case, Tulip supports the expected protocols for automated equipment (OPC UA, MQTT, Snowflake (UNS), etc.) and web-enabled no-code HMIs for Rockwell Automation, Inductive Automation, DMG Mori, and others. In addition, they have edge drivers for the more mundane devices that most MES vendors do not provide, label printers, scanners, torque tools, pH meters, thermocouples, cameras, scales – over two dozen device types from over thirty vendors. Coupled with drag-and-drop integration connections to ERP and SCM systems, they have created a composition platform that can be used to develop applications and connections for a production-ready system.
In 2024, Tulip added a workflow engine to the application creation suite. This capability is called “Automations”, as it is the ability to define workflows and automate them. Like other Tulip capabilities, their library has predefined automations for everyday tasks (more than fifteen at this writing) such as inventory update, part counts, Andon alerting, and production status. As the MES vendor community evaluates the uses of GenAI and LLMs in production, Tulip has built MCP server, their official implementation of the Model Context Protocol for the Tulip platform and is using existing connections and automations as a bridge to Agentic AI. The library already includes two: AI Automation – Defect Characterization and AI Automation – Defect Summarization.
While some skeptics felt it took Tulip way too long to add workflow capabilities, the Automations allowed them to leapfrog some of their competition, past traditional workflow to AI Agents.
To support Tulip’s continued growth across industries, it is essential to develop internal expertise in target markets and provide customers with tools and training for scaling from DIY pilots to enterprise production. Tulip is adapting functionality from apps designed for other industries to support new ones, hiring domain experts for those new target industries. This is a valid approach, admittedly time-consuming, especially where it relates to the support of domain-specific rules and regulations from CFR 21 Part 11 to FedRAMP.
The first part of full enterprise support has been achieved by building out their implementation service provider network, currently 90+ implementation partners in 25+ countries, which represents 50% growth year-over-year. However, expertise is something that is acquired over time, as other vendors have discovered. The growth rate of signing new partners does not translate to overnight success.
Some of the areas discussed by Tulip include:
Thank you to Madilynn Castillo and Natan Linder for the insightful briefing.
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Is your approach to product development helping you compete or holding you back?
Product development teams today face growing pressure to respond to market volatility, supply chain disruptions, and global competition. At the same time, they’re dealing with long-standing challenges like manual inefficiencies, poor collaboration, disconnected systems, and workforce shortages. These issues cause costly delays, especially during engineering-to-manufacturing hand-offs. In the past, these inefficiencies were tolerated. But today’s market demands more agility, and the tools to support it are finally available. Advances in digitalization, simulation, and AI are helping teams move faster and smarter. These issues are shaping product development.
The research identifies seven trends that are reshaping product development as companies confront this new reality. Top Performers are leading the way in adapting to these trends to gain a competitive edge. What are they doing differently, and what can others learn?
This study is based on a survey of 233 professionals involved in product development across design, engineering, and manufacturing roles. The findings reveal the biggest challenges teams face today, the trends driving change, and the strategic moves Top Performers are making to reduce risk, accelerate innovation, and deliver better products faster.
Please enjoy the summary* below. For the full research, please visit our sponsor Dassault Systèmes SOLIDWORKS (registration required).
State of Product Development
Product development continues to face an era defined by growing complexity, shrinking margins for error, and accelerating market demands. This is exacerbated as companies are under increasingly pressure not only from traditional competitors, but also from nimble startups, vertically integrated disruptors, and offshore manufacturers. At the same time, they must manage ongoing supply chain volatility, shifting customer expectations, and a growing need for smarter, more connected products.
To remain competitive, companies must design faster, adapt to change more easily, and eliminate costly inefficiencies. Yet many are still burdened by manual tasks, disconnected tools, and poor collaboration, especially between engineering and manufacturing. These challenges are not just frustrating for employees; they lead to missed deadlines, higher costs, and compromised quality. In fact, 78% of respondents report increased manufacturing and development costs due to product development challenges.
Key Findings
Top Performers, companies that consistently meet or exceed product development goals, are leading the way. Compared to Others, they are:
Expand simulation usage: Use simulation earlier and across more roles to cut physical prototyping, identify issues sooner, and improve design quality. Seventy-four percent of Top Performers use simulation to optimize performance.
Is your approach to product development helping you compete or holding you back? Product development teams today face growing pressure to respond to market volatility, supply chain disruptions, and global competition. At the same time, they’re dealing with long-standing challenges like manual inefficiencies, poor collaboration, disconnected systems, and workforce shortages. These issues cause costly delays,…
How can MedTech companies accelerate digital transformation? On Thursday, October 23 at 10:00 am EDT, please join Tech-Clarity’s Michelle Boucher for an interactive discussion with Christian Vogelei of Fresenius Medical Care and René Zoelfl of PTC as they discuss this. They will explore topics like: Why MedTech companies should consider digital transformation The benefit MedTech…
How can companies managing capital-intensive projects, such as factories, nuclear facilities, offshore platforms, rail infrastructure, and data centers, avoid delays and cost overruns? What leads to successful projects? Significant growth is expected in the number of capital-intensive projects over the next few years. However, many of these projects will face delays, cost overruns, and execution…
What will help MedTech companies stay competitive in an era marked by rapid innovation, rising regulatory complexity, and global disruption? As the industry moves toward smarter, more personalized, and increasingly connected healthcare, MedTech manufacturers face mounting pressure to reduce time to market, improve patient outcomes, control costs, and ensure compliance without sacrificing quality or patient…
How can machine builders improve engineering productivity? Industrial machinery has become increasingly complex, with even more mechanical components, electronics, and software. Customer needs for improved maintainability, increased automation, and better efficiency have driven this complexity further. Engineers are critical to successfully meet these requirements. Yet, engineers regularly lose productivity to non-value-add tasks that not only…
Given how fast technology and markets are changing, how can manufacturers of intelligent products ensure they are ready for what’s next? Future-ready manufacturing requires plant floor systems that go beyond traditional manufacturing execution systems (MES). With the full scope of manufacturing operations management (MOM), analytics, and artificial intelligence (AI), companies have a good opportunity to…
What are your biggest electrical design challenges? We are researching electrical design, including top challenges, identifying the most time consuming tasks, the impact of greater automation, and how poor collaboration between electrical and mechanical engineers affects the development process. We will also use the results to identify best practices. The survey takes about 10 to…
Introducing the Topic We’ve been researching make-to-order (MTO) and engineer-to-order (ETO) approaches for over two decades and we’ve witnessed continued growth in product customization. We’ve also watched configuration approaches and technologies evolve. Two things have been consistent over time: Configured products are compelling for customers Configuring and making products to order is challenging for manufacturers…
Hexagon AB invited Tech-Clarity to the recently concluded HxGN LIVE Global 2025 event in Las Vegas and our analyst, Arvind Krishnan covered this event. In this article, we want to discuss three announcements that stood out: Octave, Proplan AI/Autonomous Metrology Suite, and Aeon. Octave – The New Home for Asset Lifecycle Intelligence What is Octave,…
How do Top Performing automotive companies balance quality, cost, and sustainability to gain a competitive edge? Early design decisions significantly shape a vehicle’s total cost and environmental impact. Yet, for many OEMs and suppliers, critical cost and carbon footprint data is scattered across systems, making it hard to evaluate trade-offs when it matters most. How…
We are pleased to announce that Howie Markson joins Tech-Clarity as Director of Research for Digital Innovation. This strategic hire strengthens Tech-Clarity’s ability to help educate manufacturers on how to navigate complex technology decisions to improve business performance. Howie’s focus areas include product design, simulation, PLM, PDM, SLM, IoT, AI, and other product development solutions…
Tech-Clarity President and Founder Jim Brown had the opportunity to join Siemens Vice President of Industry Strategy Dale Tutt on his podcast, The Industry Forward. Host Conor Pieck leads a lively conversation between Dale and Jim where Jim shares insights from Tech-Clarity’s research and Dale offers perspectives from his rich experience in the manufacturing and…
Can manufacturers maximize plant human resources as effectively as inventory and equipment? Covalent would say yes. That is what their workforce operations platform is designed to do: continuously maximize labor effectiveness. They continue to build out in multiple directions: functionally, beyond tracking training and job experience to creating an interactive skills matrix, optimizing work allocation,…
How can individuals be more effective and efficient through improved collaboration? How can companies get the most out of their people, processes, projects, and portfolios? We’ll explore how improved collaboration, both structured and unstructured, helps companies grow, scale their business, and become more resilient to achieve long-term, sustainable business success. We’ll also share how to…
What makes a digital thread that weaves through manufacturing possible? The answer is: operational data management, which includes a host of capabilities to connect, collect, contextualize, and make data flow across offices, plants, and the field. ThingWorx, a PTC Technology, has been doing that for years, and we recently had an update briefing on version…
Should emerging companies implement factory software before product lifecycle software? Sometimes. Julie Fraser’s blog post for the First Resonance site explores the strengths of modern MES and when it might be the priority application to implement, even when PLM is not yet in place. Software for a Manufacturing Business Young companies, especially those with breakthrough…
Can a highly regulated pharmaceutical or biotech company trust AI in their GXP manufacturing operations? Apprentice says yes. In the past year, they have added GenAI for intelligent context-awareness to the Tempo MES / LES / Automation solution. Now, they have added agentic AI to automate production and lab processes further. It might sound like…
Over the last seven years we’ve researched what companies are doing to drive long-term, sustainable business success. This year we extend our focus with a new look at business sovereignty and a deeper look into AI. What are the biggest disruptors companies face? What strategies are companies adopting? What priorities are they placing on the…
How can shipbuilding companies improve engineering productivity? Shipbuilding has become increasingly complex, with a growing number of owner and sustainability requirements, new technologies, suppliers, and co-makers. Engineers are critical to successfully meeting these requirements. Yet, engineers regularly lose productivity to non-value-add tasks that rob them of their ability to innovate and threaten their company’s ability…
Reinventing MES/MOM and Operations We’ve followed Tulip since the early days and were excited to catch up and see what they have accomplished over the past year. From their inception, Tulip Interfaces deliberately set themselves apart from existing industry acronyms like MES (Manufacturing Execution Systems) and MOM (Manufacturing Operations Management). This decision offered advantages and…
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