CONTACT Software Blog

Cost comparison: Cloud PLM vs. On-Premises PLM

When deciding whether to upgrade your Product Lifecycle Management (PLM) system or implement one for the first time, the benefits are clear: more efficient processes, faster time-to-market, and improved collaboration. However, once you discuss features and use cases, another critical question arises: what does it actually cost, and which option is more cost-effective in the long run?

Choosing between Cloud PLM and traditional On-Premises PLM is often a balancing act between initial investment and ongoing operational costs. This article examines the costs of Cloud PLM vs. On-Premises PLM.

The traditional approach: On-Premises PLM

On-Premises PLM refers to purchasing and running the software on your own IT infrastructure. While it requires a high upfront investment, it gives you complete control over your system.

Upfront costs:

Software licenses: Typically, the highest cost. You buy perpetual licenses granting unlimited use. Prices vary depending on vendor, functionality, and number of users.
Hardware infrastructure: Powerful servers, storage, network components, and backup systems are necessary and must scale for future growth.
Facility costs: Server rooms with proper cooling, power supply, and security systems are essential.
Implementation and customization: Installation, configuration, data migration, and process customization often require external consultants and internal resources.
Training: Comprehensive training for administrators and end-users is essential to maximize system efficiency.

Ongoing Costs:

Maintenance and support contracts: Annual fees for updates, patches, and technical support typically amount to 15–25% of the original license cost.
IT staff: Dedicated IT personnel are needed for maintenance, troubleshooting, security, backups, and performance optimization.
Hardware maintenance and replacement: Servers and storage must be regularly maintained and replaced.
Energy costs: Running servers and cooling systems generates ongoing electricity costs.
Security measures: Antivirus, firewalls, and regular penetration testing are required for data protection.
Upgrades: Major version upgrades can be as complex as re-implementation, often involving adjustments, intensive testing, and retraining.

The flexible option: Cloud PLM

Cloud PLM (often offered as Software-as-a-Service, SaaS) provides the software and infrastructure via a third-party provider, usually requiring lower upfront costs.

Upfront costs:

Setup fees (optional): Some providers charge a one-time fee for account setup or initial configuration.
Implementation and customization: Configuration, data migration, and process-specific adjustments are necessary but often less extensive than On-Premises due to prebuilt infrastructure and standardized workflows.
Integrations: Connecting to existing On-Premises systems may require integration projects with associated costs.
Training: Training is still needed, but intuitive interfaces and online resources can reduce effort.

Ongoing costs:

Subscription fees: The primary cost. Monthly or yearly fees per user usually include software, infrastructure, updates, and basic support.
Scalability: Adding or removing users or storage is flexible and reflected in subscription fees.
Premium support/add-ons: Extra charges may apply for advanced support, additional features, or storage.
Customizations/integrations: Ongoing adjustments or new integrations may incur service fees.
Internet access: Reliable, high-speed internet is essential and should be factored in, even if already available.

Direct Cost Comparison

Evaluating total costs over 5–10 years is crucial for an informed decision.

Conclusion

The optimal solution depends on your company’s specific needs:

Small and medium-sized businesses (SMBs): Cloud PLM is often more cost-effective, offering low upfront costs, predictable monthly fees, and reduced IT workload. Tools like CONTACT Software’s Cloud PLM system provide scalable, flexible solutions and even free trials to experience cloud-based PLM firsthand.
Large enterprises or companies with complex requirements: On-Premises PLM may remain preferable, offering maximum control over data and systems if sufficient IT resources are available. High upfront costs can be justified over long-term usage.

Speeding up Product Carbon Footprint calculation with data ecosystems

Companies face the challenge of designing sustainable products and processes and reducing emissions across their entire lifecycle. The Product Carbon Footprint (PCF) captures all greenhouse gas emissions generated throughout a product’s lifecycle. While internal emissions data is often available, companies need to track and consolidate data across a product’s entire supply chain to determine the PCF. Requesting and collecting this information individually from every single supplier is hardly feasible. This is where sovereign data ecosystems like Catena-X and Manufacturing-X come into play. They enable easier, more controlled data exchange across company boundaries.

External data in PCF calculation

Product Lifecycle Management (PLM) systems already manage much of the data needed to determine the PCF. They contain information on products, variants, and bills of materials. However, many emissions originate earlier in the upstream value chain, for instance, during raw material extraction or through production and transportation processes. Requesting and maintaining this data is complex and is currently done using document-based templates, Excel spreadsheets, or specialized web portals. Data is shared on demand.

For suppliers, the approach with customer-specific portals and templates simply doesn’t scale. Requested data fields lack standardization, while input data, formats, and calculation methods often don’t align. This creates immense overhead for everyone involved: data is manually compiled, entered, and verified, increasing the risk of transfer errors.

Data ecosystems as an alternative

Data ecosystems such as Gaia-X and Catena-X counteract these data silos and simplify sharing across the entire supply chain. Instead of individually requesting necessary data and uploading it to various platforms for each customer, companies provide it in standardized data formats. If a participant in the ecosystem needs this data, they simply access it through defined protocols. Control remains with the data provider. Each participant decides for themselves which data they make available, with whom they share it, and for what purposes it can be used.

The foundation is a connector based on Eclipse Dataspace Components (EDC). Each participant uses their EDC connector to manage the data and conditions under which they wish to participate in the ecosystem. The connector compiles these into a searchable catalog. If another company wants to access the data, the two EDCs automatically negotiate the terms and conditions governing the data exchange. Only with such a legally binding agreement does the other participant gain access to the data. This way, every participant retains full control over their data.

PCF calculation within data ecosystems

PLM systems are the ideal starting point for PCF calculations. Bills of materials and work plans form the basis for capturing internal emissions. Data ecosystems now enable companies to integrate data from external partners and suppliers into their calculation. For purchased parts, not only suppliers but also their digital identities are managed within the data space. This makes it possible to search for and import PCF values for external items directly from the supplier’s EDC.

Once a product’s PCF calculation is complete, the results can be made available within the data ecosystem for further use along the value chain. Each company thus individually determines with whom and under what conditions it shares the data. The relevant data set is then available in its own EDC catalog, without the need for Excel spreadsheets and web portals.

Why PLM systems are the natural integration point

This entire workflow must take place where product data is already managed: PLM systems manage bills of materials, supplier relationships, and engineering workflows. They are the single source of truth for product information throughout the lifecycle.

PLM systems like CIM Database PLM are the ideal starting point for PCF calculations, as this is where products, bills of materials, and materials are managed.

CIM Database PLM manages all relevant data needed to exchange meaningful PCF values, including calculation methods and data quality statements.

Existing data is easily made available within the data space. The provider individually controls who can access the data and for what purposes.

Fully exploiting the potential of data ecosystems requires PLM systems with open standard interfaces. Engineering workflows now also govern how internal and external PCF data is integrated. The supplier database now includes identities within the data space, and audit trails capture external data exchanges in addition to internal changes.

Today, value creation largely stems from the ability to quickly and reliably exchange product data across the supply chain. Only deep integration between internal PLM systems and external data ecosystems can generate the necessary efficiency and build trust, both internally and externally.

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.