Category: Cloud

Organizational change management in the implementation of Cloud PLM software

The implementation of a Cloud PLM system is far more than a technical upgrade. It is a strategic transformation that significantly shapes your organizational culture. As our Fast Forward approach and customer success stories demonstrate, structured onboarding ensures rapid technical proficiency and efficient system usage.

However, the true lever for sustainable success does not lie in the software alone. Without organizational change management, even the most powerful system risks falling short of its full potential. The goal is not merely to provide a tool, but to actively shape processes and bring people along on the journey.

Integrating Cloud PLM: three key focus areas for change management

A Cloud PLM system centralizes data, standardizes processes, and enables cross-functional collaboration. This is an enormous opportunity, but also a challenge that is far beyond learning new software features.

A robust organizational change management strategy must address the following core aspects:

1. Rethinking and optimizing processes

Every organization has established ways of working. Many of these processes have evolved historically – often optimized within individual departments, but rarely considered holistically across the entire product lifecycle. The introduction of Cloud PLM software offers the ideal opportunity to rethink existing processes.

  • Identifying inefficiencies: Where do media breaks, duplicate data entry, or manual steps exist that the system could automate?
  • Standardization: Cloud PLM systems are typically based on best practices. Instead of merely mapping these technically, organizations should critically assess where internal processes can be aligned with system logic to fully benefit from these standards.
  • Cross-departmental alignment: PLM breaks down silos. This requires redefining responsibilities and interfaces, often involving stakeholders from engineering, procurement, manufacturing, sales, and service.

2. Establishing new ways of working

Adapting to the system involves much more than learning where to click. It requires a fundamental shift in how people work:

  • Data-centric thinking: Employees must understand that the Cloud PLM system is the single source of truth for product data. This means entering data consistently and responsibly rather than relying on local or informal solutions.
  • Transparency and collaboration: Cloud PLM software enables transparent workflows across the entire product lifecycle. This requires employees to take a holistic view of their work and be open to collaborating across departments.
  • Responsibility and ownership: Centralized data brings new responsibilities for data maintenance and quality. Change management helps define and assign these new roles clearly.

3. Cultural change, acceptance, and employee enablement

Every software implementation has a cultural dimension. Fear of the unknown, resistance to change, or skepticism about benefits can jeopardize system adoption. Effective organizational change management must address these factors:

  • Transparent communication: Why is the system being introduced? What benefits does it bring to individuals and the organization as a whole? These messages must be clear and communicated continuously from the start.
  • Active involvement: Employees – especially key users – should be actively involved early in the process. This turns them into ambassadors and multipliers for the new system.
  • Targeted enablement: Beyond technical training, employees need support in navigating the new process landscape and recognizing personal benefits. Creating early success experiences and providing ongoing support are critical.
  • Leadership as a driver: Management must lead by example, communicate the vision, and provide the necessary resources. Without leadership commitment, sustainable change is unlikely.

This blog post highlights the consequences of insufficient change management and outlines the phases employees typically go through during transformation processes.

Conclusion

The true foundation for organizational adaptation to Cloud PLM – rethinking legacy processes and aligning the organization culturally with the system – must be designed and actively driven by the company itself.

Successful Cloud PLM implementation combines technology with the necessary human adaptability. While our Customer Success Management team supports you throughout onboarding and the long-term operation of your Cloud PLM system, the key to lasting success lies in a well-designed and actively lived organizational change management approach.

Only organizations willing to transform their ways of working and their culture can unlock the full potential of cloud-based PLM.

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.”

Find out in our webcast when SaaS PLM systems are a viable alternative to PDM systems.

Introducing Cloud PLM Systems

How we support SaaS customers in Customer Success Management

Introducing Product Lifecycle Management (PLM) software is a significant step. The Cloud PLM system serves as a central hub for the development, management, and optimization of products throughout their entire lifecycle – from initial concept through production, service, and recycling. To ensure it yields results quickly, you need to set the right course from the outset. This is where our Customer Success Management comes in.

In this article, you will learn how Customer Success Management ensures a smooth and secure start with the CIM Database Cloud PLM system.

Onboarding in twelve weeks

To make your start with the Cloud PLM system as efficient as possible, we utilize our Fast Forward Approach. In a 12-week onboarding program, your key users will gradually learn all the essential functions of the system. Beyond the basic functions, we also provide you with industry best practices. This way, your team combines theoretical knowledge with practical expertise, enabling them to integrate the software into their daily workflow quickly.

The three pillars of the Fast Forward Approach

  • Structured Onboarding: PLM projects require a clear structure. From the initial steps to the extensive functionalities of CIM Database Cloud: We ensure that all employees confidently use the new system and enthusiastically embrace the possibilities of holistic product data management.
  • Active Support: During implementation, we stand closely by your side, answering questions and providing assistance to resolve potential obstacles in advance. Our support doesn’t end with the onboarding. We help you secure the long-term success of your Cloud PLM system.
  • Sustainable Success: Our primary goal is to enable you to work independently and efficiently with the Cloud PLM system after onboarding. We empower your teams to leverage the full potential of the software and create long-term value for your company.

This is how the Cloud PLM implementation process looks

In weekly onboarding sessions, we guide you intensively through the main modules of CIM Database Cloud. The focus is not only on the mere operation (how) but also on strategic understanding (why), to unlock the full potential of the software for your business processes and secure your long-term success.

Key users solidify their knowledge through a dedicated self-study phase. This ensures that they confidently master all relevant basic functions by the end of the onboarding. In this way your team is optimally prepared for daily work with the Cloud PLM system.

What our customers say about their onboarding process:

“Thanks to the excellent collaboration with the Customer Success Manager, we were able to quickly and efficiently map our processes within the CONTACT SaaS PLM system, CIM Database Cloud, and successfully bring it into production. The close contact greatly facilitated our understanding of the CONTACT SaaS PLM system’s methodology and helped us find the right settings for our needs.”
Lena Döhl, Head of Mechanical Design, SAS Softec GmbH

“At bulthaup, we see the use of CDB Cloud as a foundation for realizing our vision of the digital twin. The guided onboarding by a Customer Success Manager from CONTACT gives us the opportunity to quickly use a fully operational and productive system. The clearly structured onboarding process, led by the Customer Success Manager, allows our employees to work productively with minimal training time. A major advantage is also the direct exchange with the CSM when it comes to issues or questions regarding the methodology.”

Alexander Weyda, HEAD of IT, bulthaup GmbH & Co. KG, Authorized Signatory and Member of Executive Management

Conclusion

The introduction of a Cloud PLM system is more than just a technical innovation. It is a strategic transformation that significantly shapes your organizational culture. To ensure this transformation succeeds, our Customer Success Management team accompanies you from start to finish with our proven Fast Forward Approach. In just 12 weeks of onboarding, we guide you securely and purposefully through the implementation of CIM Database Cloud.

Discover all the features that CIM Database Cloud offers you now.