Standards, security, and AI: The role of PDM systems in the digital industry

A new order from the OEM comes in. But no one knows exactly which drawing in the PDM system is currently valid. Product development wants to introduce an AI application, but the required data is neither complete nor consistent. During the audit, proof of a change is missing, even though the measure was implemented weeks ago.

Situations like these are an everyday reality in many small and mid-sized enterprises. Often, these are merely symptoms whose cause lies deeper: in product data management (PDM). The importance of PDM systems for digital transformation is frequently underestimated, even though they form the foundation for many technologies and processes. This becomes clear when looking at three key goals of digitalization:

1. Competitive advantages through artificial intelligence

AI applications already support engineering today across all phases of the product lifecycle – whether in design, variant management, or manufacturing. Companies can automate processes across disciplines and departments and make decisions based on data-driven insights. However, implementing industrial AI solutions requires a database and structure on which AI algorithms can be trained.

For the use of AI, powerful and scalable PDM solutions are essential. They centralize and version large volumes of product data, such as CAD models, specifications, manufacturing information, and change documentation. This data is structured, prepared, and enriched with metadata in the PDM system. That creates the necessary quality of training data for AI models. Building on this, AI functions can be integrated as needed – for example, for design optimizations, predictive quality assurance, energy management, or variant configuration.

In the field of AI, the demands on PDM are particularly high. Without a powerful system, it is impossible to ensure the quality, consistency, and accessibility of data for AI. Problems such as inconsistencies, missing or unstructured metadata, and inadequate validation mechanisms result in a flawed and unreliable database for AI algorithms. Under such conditions, investments in AI applications fail to deliver results.

2. Meeting external standards

Transparency, consistency, and data integrity are three prerequisites for implementing quality and industry standards. To meet reporting obligations and process requirements, companies must manage all product-related information centrally, versioned, and traceable. This is done in the PDM system, which serves as a single source of truth and provides current, reliable data across organizational boundaries.

How important PDM software is for meeting external requirements is demonstrated by the example of Automotive SPICE (A-SPICE). This internationally recognized standard aims to ensure the quality and safety of electronics and software in vehicles. A-SPICE is designed to enable suppliers to develop safe, error-free software that can be integrated into other vehicle systems. At its core, it is about qualifying suppliers and avoiding risks during development.

The requirements of A-SPICE are particularly challenging for SMEs. Here again, effective product data management is crucial. PDM systems provide a framework that ensures the structure, control, and quality of work results required by A-SPICE throughout the entire development lifecycle. This is supported by functions for centralized data storage and availability, as well as version, change, and configuration management.

Currently, A-SPICE is not mandatory. Nevertheless, many automotive manufacturers use the framework to assess the process competence of their suppliers. Companies that fail to meet the standard risk losing customers.

It is foreseeable that A-SPICE will become a knockout criterion for OEMs. Companies that do not meet the standard will be excluded from the supply chain. This risk also exists with other regulations if product data management is inadequate. Therefore, companies must invest in their PDM.

3. Ensuring IT security

PDM is primarily seen as an administrative task. In product development, however, it is also a key focus of IT security. PDM systems are responsible for managing critical intellectual property – the product data itself. Protecting this sensitive information (CAD models, bills of materials, technical specifications, test results, customer information, etc.) is directly linked to the functions of the PDM system.

Unauthorized access, theft, manipulation, or data loss can be effectively prevented with PDM systems based on highly available architectures. Important modern features include:

  • Access control and authorization (roles and rights),
  • Robust encryption,
  • Multi-factor authentication,
  • Version control and change management,
  • Implementation of backup and recovery strategies, for example in the event of a cyberattack,
  • Audit trails and histories of data access and changes (for traceability in the event of security incidents), and
  • Risk management and compliance.

PDM systems should have no gaps in these areas. Otherwise, they become a security risk. A warning sign is when the software is based on outdated architectures or the vendor discontinues security updates and support. In such cases, companies are forced to isolate the tool in operation, which inevitably creates IT risks and inefficiencies.

Responsibility for data protection and cybersecurity is increasing in almost all industries. While some requirements primarily affect OEMs and tier-1 suppliers, these companies pass verification obligations and security requirements on to their suppliers and partners. As a result, smaller companies must also be able to collect, consolidate, and protect data using appropriate IT solutions.

More about PDM systems

Managing product data is a key focus point in digitalization. Whether standards are met, information is protected, and technologies such as AI have a chance depends on the performance of the PDM solution.

As of today, however, PDM software in many companies is a hidden cost driver. Older, slow, functionally limited systems are often in use, and they offer neither web nor cloud services. Such tools hinder coordination between departments and are a source of errors that can jeopardize entire projects.

Read how to solve this problem in our guide “When the PDM System Becomes a Risk.”

Digital transformations & organizational change management

What do climate change, pandemic developments, and statistical risks have in common with the impact of digital transformation on an organization’s people? Short answer: There’s a well-documented human tendency to ignore or underestimate complex or abstract risks. And what does that have to do with organizational change management? I’ll explain it all in this blog post.

A classic example of statistical risks involves the impact of a lack of exercise, nicotine, or alcohol on the increasing risk of cardiovascular diseases. When organizations embark on a digital transformation, they face a staggering 70% risk of failure. So, where’s the connection?

In both scenarios, there are recognized and effective solutions to minimize these statistical risks. When it comes to digital transformation, that solution is the consistent application of organizational change management. It’s not enough to be perfectly set up technically and methodologically. The human factor – the people who are the target of the change – must also be a central focus.

What is organizational change management?

Organizational change management is a systematic approach. It actively manages the human side of change in an organization. This includes a range of processes, technologies, or strategies to support people through change and thus achieve the desired outcome.

“Managers assess that 69% of transformations fail due to insufficient change management.”

– Change Management Compass 2023, Porsche Consulting

Sounds familiar?

In my consulting practice, I often find that anecdotal or psycho-educational examples help people tap into their own experiences, sparking memories of similar situations. I often hear reactions like, “That’s exactly how it is for us too,” or “I can totally relate to a project like that.” That’s the exciting moment when things suddenly click, and connections are seen in a whole new light. Let me give you two examples:

1. Unclear direction

In one instance, the stated vision for a change program was simply: An 8% EBITA increase. However, employees in their day-to-day work couldn’t grasp how their efforts, directly or indirectly, contributed to this vision, which, let’s be honest, was more of a metric target.

They had no idea when or how this would be measured, what would happen next, or what it meant for them personally. They also didn’t know the consequences of either falling short or exceeding the target. Ultimately, this vision was a pretty ineffective way to provide direction.

It’s rarely just one missing piece. More often, it’s a combination of several underestimated or misunderstood situations and actions that, together, negatively impact the outcome far more significantly than any single one would appear to do.

2. Lack of Sponsorship

Understanding is fundamental to the willingness to support a change project. Employees must recognize that this change is important and urgent and that the consequences of ignoring this fact really must be avoided.

Part of this understanding is that the situation naturally commands adequate management attention. Someone needs to be at the helm, actively and with clear commitment, steering the ship around these critical shoals.

Here are the three most common misunderstandings about sponsorship I’ve encountered in projects:

  1. Top management views its sponsor role as something done exclusively behind closed doors, in steering committee meetings. Result: No one sees anyone actually steering.
  2. Responsibility for the change is delegated to a management level that lacks the necessary decision-making authority. Result: Someone is handed a tiny paddle and told to steer a supertanker.
  3. The entire topic of sponsorship simply hasn’t been formally clarified. Result: The steering wheel just spins wildly on its own.

Unclear visions and a lack of sponsorship are just two of the top drivers that can derail change initiatives.

Where skepticism and resistance brew

The human brain automatically fills in missing pieces. When intentions are opaque, information is scarce, and one’s own role in the changing landscape remains unclear, people instinctively fill those gaps with their own interpretations and explanations. These ideas spread like wildfire through the organization’s fastest communication channel – the rumor mill – where they’re vetted for plausibility. This includes things like ideas for better solutions, anxiety about no longer being seen as an expert, fear of losing the security that comes with familiar processes and tools, or the firm belief that “we can just keep doing things the way we always have.” Prominent themes are also appreciation, future prospects, and the fear of job loss.

To cut to the chase: we humans generally don’t like change. In fact, we often go to great lengths to preserve the status quo, or even to restore it if it’s been disrupted.

What role plays organizational change management?

At its core, organizational change management has three main goals:

  1. Accelerating adoption by boosting user acceptance and reducing resistance to new solutions or ways of working.
  2. Maximizing utilization by ensuring people consistently and effectively use new tools, processes, or systems, rather than reverting to old habits.
  3. Optimizing efficiency by empowering users to work productively with new solutions and unlock the full potential of the transformation.

Organizational change management: your path to success

Humans are a critical component of any digital transformation. Organizational Change Management is a critical success factor for any change project, ensuring that technological investments actually deliver their intended value.

And as I’m sure you’ll agree, there are indeed parallels between climate change, pandemic developments, and statistical risks, and the impact of digital transformation on an organization’s people: The more abstract and complex a danger or risk is, the more likely people are to underestimate or even ignore it. To minimize the significant risks posed by human factors in digital transformation, the consistent integration of organizational change management isn’t just helpful – it’s absolutely essential.

Pontus-X: The backbone of the Gaia-X ecosystem

Pontus-X is a core ecosystem within Gaia-X. It was one of the first publicly available Gaia-X ecosystems with a large number of participating projects and companies from multiple countries. This has made it a crucial catalyst for the development and deployment of Gaia-X technologies. By connecting CONTACT Elements to Pontus-X, we enable federated data exchange that boosts operational efficiency and improves data governance. In this article, learn how companies can operate confidently in a world of distributed data.

Technically, Pontus-X is built on Distributed Ledger Technology (DLT) for the decentralized and trustworthy management of data and services. A key element of Pontus-X is the Ocean Protocol by Ocean Protocol Foundation, which puts data control in the hands of data owners and service providers.

One of Pontus-X’s most relevant features for ensuring data sovereignty is Compute-to-Data.

Compute-to-Data – Data flow while maintaining data sovereignty (© deltaDAO)

With the help of Compute-to-Data, data never leaves its owner’s infrastructure, thus remaining more effectively under their control. Instead, it allows algorithms to be brought to the data, extracting valuable insights without revealing the data itself. One exemplary use case is Federated Learning, which involves training AI models with distributed data. In this process, users receive only the trained model but no direct access to the sensitive training data.

Through this combination of various technologies, Pontus-X provides a solid foundation for secure, transparent, and sovereign data exchange within the Gaia-X ecosystem.

CONTACT Elements: Your data in Gaia-X

CONTACT Elements enables companies to seamlessly integrate their data into the Gaia-X ecosystem. A practical example is our partner GMN, a leading manufacturer of high-tech motor spindles. GMN uses sensor data from its spindles to offer data-driven services.

We’ve integrated CONTACT Elements to link quality data from a spindle on the shopfloor with the results of an end-of-line test bench. This data allows GMN to offer its customers comprehensive data-driven services, such as verifying correct assembly or performing digital commissioning.

Example of the vibration velocity of a grinding spindle as part of quality inspection measurements at GMN

We realized this data offering through the Pontus-X ecosystem. CONTACT Elements collects the relevant data from the spindles, aggregates it, and publishes it in the Pontus-X ecosystem. This process is largely automated and uses the AAS integration module as well as the data space integration of the Elements platform.
Through this integration, we empower companies like GMN to securely, reliably, and sovereignly share their data in order to develop new business models and innovative services.

Federated data exchange: Added value for your business

Federated data exchange offers significant advantages to companies. Unlike centralized platforms, data remains at its original storage location. Each organization retains control over its own data and determines who can access which data.

Increased operational efficiency:

  • Faster data availability: Access to real-time data without long transfer times or complex integration projects accelerates decision-making processes and responses to market changes.
  • Improved collaboration: Secure and controlled data exchange supports cooperation with partners, suppliers, and customers. This leads to more efficient processes, shorter lead times, and higher quality.
  • Process automation: Automated data exchange between different systems and organizations reduces manual tasks and errors.

Improved data governance:

  • Transparent data origin: Understanding data provenance is particularly important for companies operating in regulated industries or those that need to meet strict compliance requirements.
  • Controlled data access: Companies retain control over who can access their data and how it is utilized. This enables them to protect sensitive data and adhere to data protection regulations.
  • Meeting compliance requirements: Federated data exchange supports companies in meeting compliance requirements by ensuring adherence to defined rules and guidelines for data exchange.

Specific use cases:

  • Supply chain management: Data exchange between suppliers, manufacturers, and logistics providers enables transparent and efficient supply chain management.
  • Engineering: The exchange of design data between various engineering departments or external partners accelerates the development process and improves product quality.
  • Production: Exchanging production data between different production sites enables more efficient resource utilization and optimizes production planning.

Our approach: “Bring your own connector”

Building and operating proprietary infrastructure can be complex. That’s why we support companies with our “bring your own connector” approach, which adheres to the Gaia-X principle of portability. This avoids vendor lock-in by giving companies the freedom to choose which connector they integrate into their existing or new infrastructure and where they operate it.

What CONTACT Elements offers:

  • Integration into existing infrastructures: CONTACT Elements focuses on seamless integration into existing or new infrastructures required for participation in Gaia-X.
  • Interfaces to various data spaces: Whether it’s Pontus-X or Eclipse Dataspace Components (EDC), CONTACT Elements provides interfaces to both technologies. This allows companies the flexibility to choose which data space best suits their needs.

With our “bring your own connector” approach, companies leverage the benefits of the Gaia-X ecosystem without compromising on flexibility, portability, or data sovereignty.

CONTACT Elements paves the way for sovereign data exchange in the Gaia-X ecosystem

The vision of Gaia-X to create an open, secure, and trustworthy data ecosystem is drawing closer. By connecting CONTACT Elements to Pontus-X and through the “bring your own connector” approach, we give companies the flexibility and portability they need.

Federated data exchange offers companies a multitude of benefits: from increasing operational efficiency and improving collaboration to unlocking new business models.

We are convinced that Gaia-X has the potential to fundamentally transform the European economy and drive innovation across all industries. With CONTACT Elements, companies are well equipped to seize these opportunities and actively shape the future of data exchange.