For decades, automotive innovation was driven primarily by hardware. Engineers designed vehicles, manufacturers built them, and once they left the factory, their capabilities were largely fixed. Today, that model is rapidly changing.

Software is becoming the primary driver of vehicle functionality, customer experience, performance improvements, and even new revenue opportunities. Features can be added after purchase, safety systems can be enhanced remotely, and entire vehicle platforms can evolve throughout their lifecycle through software updates.

This shift has given rise to the Software-Defined Vehicle (SDV), a transformation that is reshaping not only the vehicles themselves but also how automotive products are designed, developed, tested, and maintained.

For OEMs and suppliers alike, understanding what software-defined vehicles mean for engineering operations is becoming increasingly important.

What Is a Software-Defined Vehicle?

A software-defined vehicle is a vehicle whose functionality is increasingly controlled, enhanced, and updated through software rather than being permanently tied to hardware components. Traditionally, adding new vehicle capabilities often required redesigning or replacing physical components. In an SDV environment, many of those improvements can be delivered through software updates instead.

Think of how smartphones receive regular operating system updates that introduce new features and improve performance. Software-defined vehicles follow a similar concept, allowing manufacturers to continuously improve vehicle functionality long after it leaves the production line.

Common characteristics of software-defined vehicles include:

The result is a vehicle that can evolve over time rather than remaining static throughout its lifecycle.

Why the Automotive Industry Is Moving Toward SDVs

The transition to software-defined vehicles is being driven by both market demand and competitive pressure. Consumers increasingly expect their vehicles to behave more like connected devices. They want improved user experiences, new features, seamless connectivity, and ongoing innovation after purchase.

At the same time, automotive manufacturers face growing pressure to differentiate products in an increasingly competitive market.

Software provides new opportunities to:

As a result, software is becoming a strategic differentiator rather than simply a supporting component of vehicle development.

The Technology Behind Software-Defined Vehicles

The rise of software-defined vehicles is also driving significant changes in vehicle architecture. Traditional vehicles often rely on dozens, or even hundreds, of electronic control units (ECUs) operating independently throughout the vehicle. While effective for many years, these architectures can make software updates and system integration increasingly complex.

Modern SDV architectures are moving toward more centralized computing models. Rather than distributing functionality across numerous isolated systems, centralized platforms enable greater coordination between vehicle functions and simplify software deployment.

This architectural evolution helps manufacturers:

However, while the technology is important, the bigger challenge often lies elsewhere.

The Real Challenge: Engineering Complexity

Many discussions about software-defined vehicles focus on technology. In reality, one of the biggest challenges is managing the engineering complexity that accompanies software-driven development.

As software content grows, engineering teams must coordinate increasingly complex relationships between:

Historically, many organizations managed these disciplines through separate teams and disconnected systems. That approach becomes increasingly difficult as software and hardware become more tightly intertwined.

When engineering data is fragmented across multiple tools and processes, organizations often experience:

The challenge is no longer simply developing great software. It is ensuring software, hardware, and product data remain aligned throughout the entire lifecycle.

Why Automotive Suppliers Should Pay Attention

While much of the conversation around software-defined vehicles focuses on OEMs, suppliers are increasingly affected by the same trends. OEM expectations around software quality, traceability, collaboration, and lifecycle visibility continue to move deeper into the supply chain.

Tier 1, Tier 2, and Tier 3 suppliers are being asked to provide greater transparency into development processes, requirements management, testing activities, and engineering changes. Even suppliers that do not directly develop vehicle software are often impacted by these evolving expectations.

Organizations that rely on disconnected engineering systems may find it increasingly difficult to support:

As software-defined vehicles become more prevalent, suppliers must be prepared to operate within increasingly connected engineering ecosystems.

Why the Digital Thread Matters More Than Ever

Successfully supporting software-defined vehicle development requires more than new tools. It requires better connectivity across engineering information. This is where the concept of the digital thread becomes critical.

A digital thread connects data across the product lifecycle, providing visibility between requirements, software development, product design, testing, manufacturing, and service operations.

Rather than maintaining separate versions of engineering information across multiple systems, organizations create a connected flow of information that improves collaboration and decision-making.

For automotive manufacturers and suppliers, this can help:

As SDV programs become more sophisticated, the ability to connect software and hardware development through a unified engineering environment becomes increasingly valuable.

Common Barriers to SDV Readiness

While most organizations recognize the importance of modernization, several challenges frequently slow progress.

Siloed Engineering Systems: Many organizations still manage requirements, software development, product data, and testing activities in separate systems with limited integration.

Limited Traceability: Disconnected processes can make it difficult to demonstrate relationships between requirements, design decisions, testing results, and final products.

Growing Software Complexity: Software content continues to increase across vehicle platforms, creating additional dependencies and coordination challenges.

Organizational Change: Technology alone does not solve engineering challenges. Teams must also adapt processes, workflows, and collaboration models to support software-driven development.

Recognizing these barriers is often the first step toward building a more connected engineering environment.

What Automotive Leaders Are Doing Differently

Leading automotive organizations are approaching software-defined vehicle development as both a technology initiative and an operational transformation effort.

Many are investing in:

These investments help organizations reduce engineering friction while creating a more scalable foundation for future innovation.

Preparing for the Software-Defined Future

Software-defined vehicles represent one of the most significant shifts the automotive industry has experienced in decades. The transformation extends far beyond vehicle technology. It is changing how products are designed, developed, validated, manufactured, and maintained throughout their lifecycle.

Organizations that succeed in this environment will be those that modernize both their technology platforms and the engineering processes that support them.

For automotive suppliers, the question is no longer whether software-defined vehicles will influence the industry. The real question is how quickly engineering operations can evolve to support the future of connected, software-driven product development.

Continue Exploring Automotive Engineering Modernization

As software-defined vehicle complexity continues to grow, manufacturers need strategies that improve traceability, align software and hardware development, and create more connected engineering environments.

Explore additional resources and insights designed to help automotive teams modernize product development and prepare for the future of engineering.

MedTech manufacturers have never faced more pressure to innovate faster while simultaneously controlling costs, maintaining quality standards, and navigating increasing regulatory scrutiny. Supply chain instability, inflationary pressure, labor shortages, and evolving compliance requirements are all contributing to rising operational costs across the industry. But for many organizations, the biggest challenge is not any single external pressure.

It is the growing operational complexity created by disconnected systems, fragmented engineering data, and manual processes that slow responsiveness across the enterprise. As medical devices become increasingly software-driven and regulatory expectations continue to evolve, many MedTech organizations are recognizing that traditional operational models are no longer sufficient to support long-term scalability and competitiveness.

The manufacturers best positioned for the future are not simply reducing costs. They are modernizing how engineering, quality, regulatory, and operational teams work together through connected lifecycle strategies that improve visibility, traceability, and organizational agility.

Regulatory Complexity Is Accelerating Faster Than Legacy Processes Can Support

Regulatory oversight in MedTech continues to expand globally. From FDA requirements and EU MDR updates to cybersecurity standards and emerging AI governance expectations, manufacturers are being asked to manage increasing levels of complexity throughout the product lifecycle.

For many organizations, compliance preparation still relies heavily on spreadsheets, disconnected documentation systems, manual approvals, and siloed engineering records. These approaches may have worked when products were simpler and development cycles were slower, but they increasingly create bottlenecks in modern MedTech environments.

The challenge is not simply staying compliant. The challenge is maintaining engineering velocity and operational responsiveness while managing compliance requirements at scale.

Disconnected systems often make it difficult to trace requirements, manage engineering changes, coordinate software and hardware development, or prepare for audits efficiently. Teams spend valuable time searching for information, validating records, and manually reconciling lifecycle data across systems.

As product complexity increases, those inefficiencies compound. Organizations that continue relying on fragmented operational environments often struggle to adapt quickly when new regulatory requirements emerge or engineering priorities shift. This is one reason many MedTech leaders are reevaluating how lifecycle data is managed across engineering, quality, manufacturing, and service operations.

Rising Costs Are Exposing Operational Inefficiencies

External cost pressure continues to affect nearly every aspect of MedTech operations. Material costs remain volatile. Supply chains continue to experience disruption. Labor shortages persist across engineering and manufacturing roles. At the same time, organizations are managing growing software complexity, increasing documentation requirements, and heightened pressure to accelerate product delivery timelines.

While these external pressures are difficult to control, many organizations are discovering that internal inefficiencies are magnifying their impact. Disconnected workflows, duplicate data entry, fragmented approval processes, and limited visibility across engineering systems often create hidden operational costs that reduce responsiveness and increase rework.

Engineering teams frequently spend significant time managing documentation and administrative coordination instead of focusing on product development and innovation. Quality and regulatory teams may struggle to maintain real-time visibility into design changes or testing activities. Manufacturing teams may lack timely access to updated lifecycle information.

When systems do not communicate effectively, organizations often compensate with manual processes. The result is slower decision-making, delayed approvals, inefficient change management, and increased operational friction across the enterprise. In today’s environment, operational inefficiency is no longer simply an inconvenience. It has become a direct business risk.

Why Connected Lifecycle Management Is Becoming a Strategic Priority

To address these challenges, many MedTech manufacturers are shifting away from siloed operational models and toward connected lifecycle management strategies. This approach is often described as a “digital thread”: a connected framework that links engineering, quality, regulatory, manufacturing, and service data across the entire product lifecycle.

Rather than managing disconnected systems independently, organizations create a unified operational environment where lifecycle information can move more efficiently between teams and processes. For MedTech manufacturers, this shift can create significant operational advantages.

Connected lifecycle strategies help organizations improve traceability between requirements, risk, testing, validation, design controls, and engineering changes. Teams gain greater visibility into product development activities and can respond more efficiently when issues arise.

The benefits extend beyond compliance. Organizations with connected lifecycle environments are often better positioned to:

The contrast between traditional operational models and connected lifecycle environments is becoming increasingly clear.

As device complexity continues to grow, connected lifecycle management is evolving from a technology initiative into a broader operational strategy.

Operational Resilience Is Becoming a Competitive Advantage

Historically, digital transformation discussions in MedTech often focused on innovation enablement or technology modernization. Today, the conversation is broader. Organizations are increasingly focused on operational resilience: the ability to adapt quickly to regulatory changes, engineering complexity, market volatility, and evolving customer expectations without disrupting business performance.

This shift is changing how MedTech leaders think about operational investment. Modernization is no longer only about increasing efficiency. It is about creating operational environments capable of supporting continuous change.

Manufacturers investing in connected lifecycle strategies are often better positioned to:

In many cases, operational resilience becomes a competitive differentiator. Organizations with greater lifecycle visibility and stronger engineering continuity can often bring products to market more efficiently while maintaining the quality and traceability expectations required in regulated environments.

As a result, operational modernization is increasingly being viewed as a long-term business strategy rather than a standalone IT initiative.

What MedTech Leaders Should Prioritize Next

For organizations evaluating how to improve operational efficiency and lifecycle visibility, modernization does not need to happen all at once.

Many successful transformation initiatives begin by focusing on a few foundational priorities.

1. Evaluate Lifecycle Visibility

Can teams efficiently trace requirements, risks, changes, and validation activities across the product lifecycle?

Limited visibility often creates bottlenecks that affect both engineering speed and compliance readiness.

2. Identify Manual Workflow Dependencies

Where are teams relying on spreadsheets, disconnected approvals, or duplicate data entry?

Manual coordination processes often become major scalability constraints over time.

3. Connect Engineering and Quality Data

Improving continuity between ALM, PLM, quality, and regulatory systems can significantly improve collaboration and operational responsiveness.

4. Modernize Incrementally

Transformation initiatives should support existing validated environments rather than disrupt them.

Organizations often achieve better long-term adoption when modernization is phased strategically.

5. Align Technology to Operational Outcomes

The goal is not simply implementing new tools.

The goal is improving traceability, visibility, efficiency, and organizational agility across the enterprise.

The Future of MedTech Operations Will Be Defined by Adaptability

The MedTech organizations best positioned for long-term success will not necessarily be the ones investing most aggressively in technology. They will be the organizations creating operational environments capable of adapting to constant change.

As regulatory complexity, software integration, and operational pressure continue to increase, connected lifecycle strategies are becoming essential for maintaining both innovation speed and operational resilience. Digital transformation is no longer just about modernization.

It is increasingly about creating the visibility, continuity, and agility required to compete in a rapidly evolving MedTech landscape.

Ready to Build a More Resilient MedTech Operation? Rising costs, regulatory complexity, and growing product demands are reshaping how MedTech organizations approach product development. Explore strategies for improving traceability, strengthening collaboration, and creating a connected digital foundation that supports long-term growth.

Most organizations today have at least a high-level understanding of Product Lifecycle Management (PLM). They know it’s meant to connect product data, streamline processes, and improve collaboration across teams. But that definition feels abstract. Engineering leaders aren’t waking up thinking, “We need lifecycle management.” They’re dealing with very real, very specific challenges: disconnected systems, version confusion, slow change processes, and increasing product complexity. That’s where the real value of PLM comes into focus.

PLM isn’t just a concept. It’s a solution to the operational issues that slow teams down, introduce risk, and make scaling difficult. Let’s break down the most common challenges engineering organizations face today, and how PLM addresses them.

Disconnected Engineering Data

One of the most persistent challenges across engineering teams is fragmented data. CAD files may live in one system, BOMs in another, and supporting documentation in shared drives or spreadsheets. In many cases, teams are still relying on email or manual processes to share critical product information.

The result is a lack of visibility and consistency. Engineers spend time searching for the right files, verifying accuracy, or recreating work that already exists elsewhere. PLM addresses this by creating a centralized backbone for product data. Instead of multiple disconnected systems, teams operate from a single source of truth. Everyone (from engineering to manufacturing) can access the same, up-to-date information in a controlled environment. This shift alone can significantly reduce wasted time and improve overall data confidence.

Version Control and Change Chaos

As products evolve, managing versions and changes becomes increasingly complex. Without a structured system in place, it’s easy for teams to work from outdated files or lose track of revisions. Change processes are often handled manually, making it difficult to maintain consistency or trace decisions over time. These issues don’t just create confusion. They introduce real risk. Errors caused by incorrect versions can lead to rework, delays, or even costly mistakes in production.

PLM brings structure to this process through automated version control and formalized change management workflows. Every revision is tracked, every change is documented, and teams always know they’re working from the latest approved data. With full traceability, organizations gain both control and accountability, two things that are difficult to achieve with manual processes.

Poor Cross-Functional Collaboration

Product development doesn’t happen in a vacuum. Engineering, manufacturing, quality, and supply chain teams all need to work from the same information, but too often, they don’t. When systems are disconnected, each team operates within its own silo. Engineering may release a design without full visibility into manufacturing constraints, or downstream teams may be working from outdated data.

This misalignment leads to miscommunication, late-stage design changes, and delays that ripple across the organization. PLM helps break down these silos by providing shared access to product data across departments. With role-based visibility, each team can access the information they need, without compromising control or security.

The result is better alignment, fewer surprises, and a more collaborative product development process.

Inefficient Product Development Processes

Many organizations rely on manual workflows for approvals, reviews, and change processes. These workflows are often inconsistent, difficult to track, and prone to bottlenecks. As products become more complex, these inefficiencies become more pronounced. Teams struggle to keep projects moving, and delays in one area can impact the entire timeline.

PLM introduces structure and automation into these processes. Workflows can be standardized, approvals can be routed automatically, and progress can be tracked in real time. This not only improves efficiency. It also creates consistency across the organization. Teams can move faster, with greater confidence that processes are being followed correctly.

Lack of Traceability and Compliance Risk

For organizations in regulated industries, traceability isn’t optional. It’s essential. But even outside of strict regulatory environments, the ability to track requirements, changes, and decisions over time is critical. Without it, organizations face increased risk, whether in the form of audit challenges, quality issues, or difficulty identifying the root cause of problems.

PLM provides end-to-end traceability across the product lifecycle. From initial requirements through design, change, and release, every action is recorded and accessible. This creates a clear audit trail and supports compliance efforts, while also improving internal visibility and decision-making.

Challenges with Scaling

What works for a small team doesn’t always work at scale. As organizations grow, product complexity increases, teams expand, and processes become more difficult to manage. Systems that once felt sufficient begin to show their limitations. Manual processes break down. Data becomes harder to manage. Collaboration becomes more complex.

PLM is designed to scale with the organization. It provides a structured framework for managing product data and processes, regardless of team size or product complexity. Whether supporting global teams or highly engineered products, PLM enables organizations to grow without sacrificing control or efficiency.

From Challenges to Business Outcomes

When these challenges are addressed collectively, the impact goes beyond operational improvements. Organizations move from reactive to proactive. Instead of responding to issues after they occur, they build processes that prevent them in the first place.

With PLM in place, teams can:

Ultimately, this leads to faster time-to-market, improved product quality, and better overall business performance.

Where Windchill Fits In

While PLM as a concept addresses these challenges, the platform you choose plays a critical role in how effectively they are solved. PTC Windchill is designed specifically to support complex product development environments. It provides a robust foundation for managing product data, enabling collaboration, and connecting processes across the organization.

With capabilities that support the digital thread, integration with CAD tools like Creo, and scalability for enterprise use, Windchill helps organizations move beyond disconnected systems and manual processes. It’s not just about managing data. It’s about enabling a more connected, efficient approach to product development.

PLM Is a Business Solution, Not Just a System

At the end of the day, organizations don’t invest in PLM for the sake of implementing new software. They invest in it to solve problems. If your team is struggling with disconnected data, version control issues, inefficient processes, or challenges scaling, PLM may be the next step toward improving how you develop and deliver products.

Understanding what PLM actually solves is the first step in evaluating whether it’s the right fit for your organization, and how to move forward with confidence.

If your organization is using Windchill today, you cannot ignore the shift to Windchill ePLM licensing. PTC’s move to ePLM represents a fundamental change in how companies license, scale, and operate their PLM environments. And while it may appear to be a licensing update on the surface, the reality is much bigger. It’s a shift toward aligning PLM systems with how teams actually work.

For many organizations, this transition will expose inefficiencies, gaps, and opportunities that have existed for years.

What Is Windchill ePLM?

Windchill ePLM (Enterprise PLM) is PTC’s new role-based licensing model that replaces traditional bundled licensing structures.

Historically, Windchill licenses were packaged into tiers like:

These bundles often resulted in users having more access than they needed, others lacking critical functionality, and complex and difficult-to-manage license structures.

With ePLM, licensing is restructured around three main things. The first is Role-Based Access. Users are assigned licenses based on what they actually do, not what bundle they were placed into years ago. The second is Modular Capabilities. Capabilities are aligned to job function, allowing more precise control over access. Finally, Scalable Licensing. As teams grow or roles evolve, licensing can adapt more easily.

Why PTC Is Moving to ePLM

The transition to Windchill ePLM licensing is driven by a few key realities. First, legacy licensing doesn’t reflect modern teams. Today’s product development environments are more collaborative, more cross-functional, and more data-driven.Unfortunately, legacy licensing wasn’t designed for distributed teams and integrated systems.

Second, over-licensing and underutilization. Many organizations are paying for capabilities users don’t need andmissing capabilities other users do need.This creates both cost inefficiency and workflow friction.

Third is increasing complexity in PLM environments. As organizations scale, Windchill environments often become harder to manage, harder to govern, and harder to optimize. Windchill ePLM is designed to simplify and modernize this.

Key Deadline: What You Need to Know

PTC has made it clear: Legacy Windchill licensing models will no longer be renewable after September 30, 2026.

That does that mean for you? Every organization running Windchill will need to evaluate their current licensing, map to ePLM roles, and plan and execute a transition.

Want a quick breakdown of what’s changing? The webinar replay below shares just that.

What the Windchill ePLM Transition Actually Involves

The transition to ePLM is not just a contract change. It’s an operational change. Let’s have a look at how it typically goes.

The first step is license mapping. It’s vital to map existing users to new ePLM roles and identify gaps and overlaps. Next comes user segmentation. Companies must define user groups based on real workflows and align capabilities with responsibilities. The third step is system validation. Ensure users retain required access and test workflows across teams.

The fourth step is the cleanup of legacy complexity: remove unused licenses, simplify license structures, and optimize cost and usage. Finally is the transition execution. Here companies must implement the new license model, train users if needed, and monitor adoption and performance.

Common Challenges with Windchill ePLM

All written out, it’s easy to feel overwhelmed. This transition carries a level of complexity companies generally aren’t equipped to handle themselves. Unfortunately, organizations can underestimate the transition. When they do, they often run into issues like the following.

Some treat it as a procurement exercise. They focus only on pricing and license counts, instead of system performance and workflow alignment. Or there’s a lack of visibility into current usage. Many teams don’t have a clear view of how licenses are used and what users actually need. There may also be misalignment between roles and access. Without proper planning, users lose accessor gain unnecessary access. Both create friction.

The Bigger Opportunity: Fix What’s Broken

The reality is this: the Windchill ePLM transition is a forcing function. It forces organizations to look at how their system is structured, how their teams actually work, and where inefficiencies exist.

The companies that get the most value from ePLM are the ones that use it to improve system alignment, matching PLM to real workflows. They’ll also see increased user adoption, by giving users the tools they actually need. Organizations benefit additionally from reduced complexity, with ePLM simplifying the licensing and system structure. Further, they enable an intelligent product lifecycle, connecting data around the product from first design to the manufactured version and beyond.

How Windchill ePLM Supports the Intelligent Product Lifecycle

One of the biggest advantages of ePLM is how it supports broader digital engineering initiatives. By aligning access and capabilities to roles, organizations improve data flow across teams, reduce bottlenecks, enable better collaboration, and support end-to-end traceability. This is critical for complex manufacturing, regulated industries, and digital transformation initiatives.

Where to Start with Windchill ePLM

If you’re early in the process, start with understanding your current state. Who is using Windchill? What capabilities are actually used? Where are the gaps? From there, you can begin identifying misalignment: over-licensed users, under-supported roles, and inefficient workflows. Then, define your future state. You should be able to determine what your system should support and how your teams should interact with it. The last step is building a transition plan, including timeline, role mapping, and risk mitigation.

Let’s Help You Navigate the ePLM Transition

Most organizations don’t need more tools. They need clarity.

If you’re evaluating the Windchill ePLM transition, we can help you:

Start the conversation with our team.

Final Thoughts: This Is Bigger Than Licensing

Windchill ePLM is not just a change in how you license software. It’s a shift in how your PLM system supports your organization. The question isn’t: “How do we switch to ePLM?”

It’s: “How do we make our system actually work?”

Because for most organizations, the transition will surface challenges that have been building for years: misaligned processes, disconnected systems, and workarounds that quietly slow everything down. Teams that approach this as an opportunity, not just a requirement, will come out with stronger systems, better alignment, and more confidence in how they operate.

The Department of Defense has made it clear: digital engineering is no longer optional. With the release of DoDI 5000.97, the DoD is formalizing expectations for how acquisition programs plan, execute, and sustain complex systems using digital, model-based approaches.

For aerospace and defense contractors, the directive is both challenge and opportunity. Many organizations have invested in digital tools: MBSE platforms, CAD, simulation, and analytics. A much smaller number have established the data foundation required to scale digital engineering across programs and lifecycle phases. That foundation is Product Lifecycle Management (PLM).

In this blog we’ll walk through what DoDI 5000.97 is, why it matters to aerospace and defense contractors, and how PLM is a foundational to any initiative.

What Is DoDI 5000.97?

DoDI 5000.97 institutionalizes digital engineering as a core element of the DoD acquisition lifecycle. Its intent is to move programs away from document-centric processes toward data-driven, model-based decision making, from concept through sustainment.

At a high level, the directive emphasizes:

In short, DoDI 5000.97 mandates that digital artifacts, not static documents, become the authoritative source for engineering and program execution.

The Reality for Many A&D Contractors

Despite years of discussion, many organizations still struggle to operationalize digital engineering. Common challenges include:

These challenges are not caused by a lack of engineering capability. They come from the absence of a central system of record that connects people, processes, and product data across the lifecycle.

Why PLM Is the Foundation of Digital Engineering

Deploying a single tool doesn’t mean a company has achieved digital engineering. It requires an enterprise backbone that manages product data, controls change, and enables traceability. PLM provides that backbone.

A Single Source of Truth

PLM establishes a controlled, authoritative environment for product data, including: requirements, configurations, designs, changes, and approvals. This ensures that all stakeholders are working from consistent, current information.

Enabling the Intelligent Product Lifecycle

A core objective of DoDI 5000.97 is lifecycle traceability. PLM enables the intelligent product lifecycle by linking requirements, system models, CAD, manufacturing plans, and verification artifacts. This creates end-to-end visibility across disciplines.

Connecting MBSE to the Enterprise

MBSE is a critical component of digital engineering, but it cannot operate in isolation. PLM integrates system models with downstream engineering and manufacturing data, ensuring system intent is carried through design, production, and sustainment.

Supporting Governance and Compliance

PLM provides built-in version control, configuration management, and auditability. These capabilities are essential for meeting DoD oversight, reporting, and certification expectations.

Mapping DoDI 5000.97 Objectives to PLM Capabilities

While DoDI 5000.97 defines what the DoD expects from digital engineering, it leaves the how up to contractors. Many organizations struggle with translating policy language into executable engineering and program processes. PLM provides the operational capabilities that allow companies to implement DoDI 5000.97 objectives consistently and at scale.

Digital Engineering Implementation

PLM acts as the enterprise system of record for digital artifacts, ensuring that models, requirements, configurations, and engineering decisions are managed as authoritative data, not disconnected files. This enables teams to operationalize digital engineering across programs rather than treating it as a pilot or standalone initiative.

Digital Thread Enablement

A core expectation of DoDI 5000.97 is end-to-end traceability. PLM enables the intelligent lifecycle by linking requirements to system models, designs, manufacturing plans, and verification results. This provides continuous visibility across the lifecycle and supporting faster, more informed decision-making.

Model-Based Systems Engineering Integration

PLM connects MBSE outputs to downstream engineering and manufacturing data, ensuring system intent is preserved throughout execution. This integration allows changes at the system level to propagate accurately, reducing rework and misalignment across disciplines.

Lifecycle Data Management & Governance

Defense programs often span decades. PLM provides long-term data governance, configuration control, and version management. These capabilities are essential for sustaining digital continuity across development, production, and sustainment phases.

What This Looks Like in Practice

When PLM is positioned as the foundation of digital engineering, the impact extends well beyond engineering efficiency. Programs gain greater confidence in data integrity, leadership gains clearer insight into program health, and compliance becomes an outcome of daily work rather than a last-minute exercise.

In practice, a PLM-enabled digital engineering environment enables:

Rather than chasing data across tools, teams work within a connected ecosystem where digital artifacts remain synchronized throughout the lifecycle.

Getting Started: Building a PLM-Centered Digital Engineering Strategy

Adopting digital engineering under DoDI 5000.97 does not require a wholesale transformation overnight. Successful organizations take a phased, pragmatic approach, grounded in business priorities and program realities. PLM provides the structure needed to scale these efforts deliberately and sustainably.

Key steps include:

Common Pitfalls to Avoid

Many digital engineering initiatives stall not because of technology limitations, but due to strategic missteps. Understanding these pitfalls can help organizations avoid costly rework and unrealized value.

Common challenges include:

Avoiding these pitfalls requires viewing PLM as a strategic capability, one that supports compliance, execution, and long-term program success under DoDI 5000.97.

PLM Is Non-Negotiable Under DoDI 5000.97

DoDI 5000.97 makes one thing clear: digital engineering is a strategic imperative for defense acquisition programs. For aerospace and defense contractors, success depends not just on adopting digital tools, but on establishing PLM as the foundation that connects them.

Organizations that treat PLM as an enterprise capability, not simply an engineering system, will be best positioned to meet DoD expectations, reduce risk, and deliver complex systems with greater speed and confidence.

Interested in learning more about the importance of PLM? Explore how foundational PLM is in our guide: Digital Transformation Starts with PLM.

For years, Oracle Agile PLM has been a foundational system for manufacturers managing complex products, changes, and compliance requirements. Many organizations built their product development processes around Agile, relying on its stability and structure to support regulated, multi-discipline environments.

That era is now coming to a close. With Oracle Agile reaching end of life this December, companies using the platform face an important inflection point. The question is no longer if a change is required, but how to approach it in a way that sets the organization up for long-term success.

What Is Oracle Agile?

Oracle Agile PLM has long served as an enterprise solution for managing product data and lifecycle processes. It is best known for its strengths in:

Agile gained widespread adoption in industries with strict regulatory requirements and complex product configurations, including medical devices, aerospace, industrial equipment, and high-tech manufacturing. For many organizations, it became the system of record for product decisions and approvals.

What’s Happening to Oracle Agile

Oracle has announced that Agile PLM will reach end of life in December. While end of life does not necessarily mean systems stop working overnight, it does have serious implications:

Over time, staying on an unsupported PLM platform becomes increasingly expensive and risky. What once felt stable can quickly turn into a liability.

The Risks of Staying on an End-of-Life PLM System

Some organizations may be tempted to delay action and “keep Agile running as long as possible.” However, the risks compound quickly:

At a certain point, the cost of staying exceeds the cost of moving forward.

What Companies Using Oracle Agile Should Do Now

This transition moment shouldn’t be treated as a forced, last-minute replacement. Instead, it’s an opportunity to step back and reassess.

Before choosing a new platform, organizations should consider:

The most successful transitions are those that plan first, migrate second. Use this moment to modernize processes, not just swap tools.

Why Many Agile Users Are Evaluating Windchill PLM

As organizations explore alternatives, Windchill PLM is frequently shortlisted by former Agile users. The reasons are all in what Windchill offers:

Rather than serving as a static repository, Windchill acts as a dynamic backbone for product development across engineering, manufacturing, quality, and service.

The Benefits of Transitioning from Agile to Windchill

Moving from Agile to Windchill is more than a technical upgrade. It’s a strategic reset.

Key benefits include:

For many organizations, Windchill doesn’t just replace Agile. It enables capabilities Agile was never designed to support.

Key Considerations for an Agile-to-Windchill Transition

A successful transition requires careful planning. Common considerations include:

Organizations that approach migration as a structured program (not a technical event) see better outcomes.

End of Life? Or Beginning of Opportunity?

Oracle Agile’s end of life is undeniably disruptive, but it’s also a strategic opportunity. Rather than rushing to preserve the past, organizations can use this moment to modernize how product data, decisions, and processes are managed.

The right PLM platform lays the foundation for the next decade of product development, not just the next release cycle.

Don’t wait until support runs out. Ready to explore how Windchill PLM can help replace Oracle Agile while positioning your organization for scalable, compliant, and future-ready product development? Check out our guide Top 5 Reasons Manufacturers Choose Windchill Over Other PLM Tools.