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Overcoming On-Prem to Cloud Migration Challenges in PLM Software

Solving Cloud Migration Challenges in PLM with eQube®-GMP

Migrating Product Lifecycle Management (PLM) software from on-premises infrastructure to the cloud is a strategic move for many companies aiming to leverage the scalability, accessibility, and cost benefits of cloud computing. However, this transition is not without its challenges. Let us delve into some of the key obstacles and explore how eQ Technologic’s eQube®-GMP (Generic Migration Process) software can facilitate this process with zero KB migrations. 

What drives a company to migrate or adopt Cloud PLM solution.

We could list the same reasons that any AI engine will most likely state. They are -  

  • Cost Efficiency 

  • Scalability and Flexibility 

  • Accessibility and Collaboration 

  • Data Security and Compliance 

  • Improved Efficiency and Innovation 

  • Data Centralization and Consistency 

  • Faster Implementation and Time-to-Value 

  • Environmental Sustainability 

  • Disaster Recovery and Business Continuity 

However, out of all the above-mentioned reasons, we are only going to focus on those that drive specific impacts to the adoption of cloud as many of the benefits of cloud are well understood. It is the following benefits that carry the hidden complexity when it comes to migration. Understanding the problems can unlock more savings or mitigate costs. 

Data Centralization and Consistency: Having all your information in a single repository can help maximise reuse, reduce data inconsistency, and make effective decisions.  

Major companies such as Boeing and Toyota reported huge savings related to reuse across product lines, estimating 60-70% commonality across products. Having huge increases in reliability, massive reductions in cost and decrease in time to market as a result. 

Improved Efficiency and Innovation – This includes automated updates making sure Cloud PLM solutions are automatically updated with the latest features and improvements, ensuring users always have access to the most current tools without the need for manual intervention. 

It also includes Innovation and Integration; how does PLM easily integrate with other cloud-based applications and emerging technologies (e.g., IoT, AI, machine learning), fostering innovation and enhancing product development processes. 

 
Here are some key challenges of adopting or migrating a Cloud PLM system  

  1. Data Integrity and Security: Ensuring that sensitive PLM data remains intact and secure during migration is paramount. Any data loss or breach can have serious repercussions. As human beings, our tendency is to focus on new methods and usage of technology while trying to find more optimal ways of working. We sometimes tend to overlook decades of information that got the company where it is and forget the integrity of this information and the importance of it to the business. 

    Loss of the audit trail, digital thread of product data can result in insurance and liability risks, increased insurance costs, loss of product certification and finally impact revenue or market share. As an example of the impact of Data Security; a major European semiconductor company recently announced a data loss around its proprietary technology with a yet to be determined impact on reputation, revenue, or loss of competitive advantage. Cloud PLM projects are highly sensitive for exactly these reasons and must be the primary consideration for companies migrating to cloud. This is the reason the PLM domain remains measurably behind other IT systems in the adoption of cloud.  
     

  2. Downtime and Business Continuity: Migration can lead to system downtime, affecting business operations. Minimizing this downtime is crucial to maintaining productivity. Migration is often a lower priority in project plans for new system implementations. We build the new system and a single bar at the bottom of the plan says data migration. Why? Solution Integrators cannot accurately quantify the effort, data is owned by the business and assumptions on its quality are estimated. Until you begin the extraction and understand the transformation effort, it is incredibly difficult to accurately predict effort.  

    Data Migration then becomes the bottleneck that delays the project, and impacts business continuity. Data may be missing, inaccessible or in a new format that does not support downstream process or simply migration processes have not completed. 

    While adjustments to your migration approach can mitigate issues, the numerous unknowns require a more analytical strategy to fully prevent impacts.  
     

  3. Compatibility Issues: The existing PLM system may have custom configurations or integrations with other enterprise systems that may not be easily replicated in a cloud environment. Like ERP tools most PLM solutions have been configured to optimize company specific processes. Whilst strict adherence to configuration vs customisation has been the PLM product mantra for decades it is not always possible to deliver without architectural debt. Those little bits of code are written to make things easier.  

    The other area of significant investment around PLM systems is integration. Product data is critical to all downstream processes. Integration is often numerous to the point where home grown applications using product data may not even be fully understood by organisations. Shadow IT projects are plentiful.  
     

  4. Performance Concerns: Achieving comparable performance in the cloud as experienced on-premises can be challenging, particularly for data-intensive PLM applications. PLM evolved from Product Data Management (PDM) which focuses on controlling CAD related information. Consequently, the vast majority of PLM system still control huge volumes of CAD data. Large file sizes, high volume of file, network/ bandwidths and frequency of change are all factors which can impact decisions on Cloud adoption. Many companies see cloud as a way to optimise global design team processes, increasing collaboration, and reuse to drive down costs. There are still a number of limiting factors. 
     

  5. Change Management: Employees need to adapt to the new system, which involves training and adjustments in workflows. 

    One of the biggest value drivers for Cloud PLM adoption is in the ability to innovate using technology. How can your company exploit new tools to design product quicker, use less materials, reduce waste, additive, subtractive and now that we have generative AI? Companies will only be able to leverage the advantages of technology exploitation if their enterprise will embrace the changes. On-premises solution undoubtedly limit adoption of technology but no more than a company's ability to change.  

Conclusion 

Migrating PLM software from on-premises to the cloud presents several challenges. It also provides enormous potential benefits to a company's ability to leverage its most valuable asset - its product information. 

The problems highlighted can be mitigated effectively by recognising them early and taking steps to understand the implications of them - how clean is our core data model, what volume of data inconsistency do we have? What rules should we apply to cleanse the data? All of this can be defined, built into your migration process. 

There are technology solutions designed specifically to support cloud PLM migrations. eQ Technologic’s - eQube®-GMP solution ensures data integrity, minimizes downtime, addresses compatibility issues, optimizes performance, and facilitates change management, all delivered with zero operational downtime. 

If you want to know more about how our technology has migrated 10’s of millions of data objects in a weekend, reduced the migration effort on project by 50-60% through automation, or simply want to know how we reduced the cost of migration by 80% compared to industry benchmarks then please have a look at the following case studies on the www.1eq.com website for more information.  

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