PDM System Implementation in Manufacturing – A 5 Part Guide


A Comprehensive Planning Guide for Manufacturers - Data Management Implementation

Implementing a data management solution can be a game-changer for your organization, but it requires careful planning. In this blog, we will break down the essential steps involved in planning your data management implementation. We’ll explore the benefits, goals, risks, and success factors associated with this process. Additionally, we’ll discuss the importance of understanding your organization’s current state, identifying the ideal state, and focusing on the human element of change management. By the end of this guide, you’ll have a clear roadmap for a successful data management implementation.

Benefits of Data Management:

Before diving into the planning process, it’s crucial to understand why you need a data management solution. Data management offers several benefits, including streamlining processes, reducing errors and rework, faster data access, and improved data fidelity. Moreover, it provides a foundation for embracing emerging technologies like AI. By implementing a data management solution, you can optimize your operations and stay competitive in today’s tech-driven world.

Setting Goals:

To plan effectively, you must define your goals. Consider why you need a data management solution and what problems you aim to solve. Common goals include reducing errors, improving data access, and enhancing data accuracy. Identify specific pain points within your organization, such as manual data handling, and set clear objectives for addressing them. Additionally, aim to streamline workflows and improve data synchronization across various departments.

Assessing Risks:

Understanding the risks associated with data management implementation is crucial. Risks may include resistance to change, potential disruptions during the transition, and technology expenditures. Evaluate how these risks may impact your organization and develop mitigation strategies. Ensure that you have a contingency plan in place to address unforeseen challenges.

Identifying Success Factors:

Success factors are key metrics and indicators that help you measure the effectiveness of your data management implementation. These factors should align with your goals and address pain points within your organization. Consider factors like collaboration improvements, data synchronization, and access points. Document these factors to track progress and ensure that your implementation achieves the desired outcomes.

People-Centric Approach:

While technology is essential, it’s crucial not to overlook the human element of change management. The ADKAR methodology (Awareness, Desire, Knowledge, Ability, Reinforcement) can help your organization navigate the challenges of implementing change. Prioritize people’s needs and ensure they are aware of and invested in the implementation process. Empower your team with the knowledge and skills needed to adapt to the changes, and reinforce the benefits of the new system.

Current State Analysis:

To move forward, you need a clear picture of your organization’s current state. Analyze your folder structure, file organization, the volume of data, duplicates, file associations, metadata needs, system dependencies, permissions, points of access, and data flow. This analysis will provide insights into where your organization stands today and what needs improvement.

Defining the Ideal State:

Based on your analysis, define your organization’s ideal state for data management. Determine what isn’t working in your current state and how changes can improve efficiency. Consider the necessary technology, workflow modifications, and training requirements to achieve the ideal state. Document workflows clearly to guide your implementation strategy.


Planning your data management implementation is a crucial step towards harnessing the benefits of streamlined processes, reduced errors, and improved data access. By setting clear goals, identifying risks, and understanding success factors, you’ll be well-prepared to navigate the challenges ahead. Additionally, a thorough analysis of your current state and a well-defined ideal state will guide your implementation strategy effectively. With the right plan in place, your organization can successfully implement a data management solution and reap the rewards it offers.

Optimizing Data Preparation for Data Management Implementation

In the last section, we’ve covered how to plan for your data management implementation. In this post, we will delve into the crucial process of optimizing your data in preparation for a successful data management implementation. This is part of our Data Management Implementation series, and we’ll be focusing on the vital steps you need to take to ensure a smooth transition.

Understanding the Context

Before we dive into the preparation process, let’s recap some essential points from our previous episode. At KETIV, we emphasize the significance of data management across various business domains, from sales engineering to manufacturing. Central to this is the protection and utilization of intellectual property through a robust data management application.

Assessing Technology Maturity

Another critical aspect to consider is your organization’s technology maturity. This evaluation helps you determine where you stand in the technology landscape and what steps are needed to optimize your environment. The digital pipeline diagram illustrates how data flows through various departments, emphasizing the role of a data management application in connecting these silos.

The Four Key Preparation Steps

Now, let’s explore the four key steps in preparing your data for a data management implementation:

1. File Analysis

Begin by thoroughly analyzing your existing data. Identify common file issues, such as broken links, duplicates, or inconsistencies. Tools like Vault Auto Loader can assist in scanning and assessing your data, providing valuable insights into its health.

2. Categorizing Files

Categorize your files based on their usage and characteristics. This categorization helps you organize data efficiently and sets the stage for proper storage and retrieval. Consider patterns and relationships that emerge during this process.

3. Reorganizing Files and Folders

Your current folder architecture may not align with your data management application’s strengths. Understand the capabilities of your chosen application, such as Autodesk Vault, and adapt your folder structure accordingly. Consider reducing complexity where possible, as this can enhance user experience and performance.

4. Meeting Departmental Needs

Different departments within your organization may have unique data requirements. Engage with these departments to understand their specific needs and metadata preferences. Tailor your data organization strategy to accommodate these varying demands.

Static vs. Dynamic Files

Distinguish between static and dynamic files within your data. Static files, like images or 2D documents, typically require straightforward storage. Dynamic files, which may include parametric models, require more nuanced handling due to their changing nature.

Design Reusability

Separate information that is subject to design reusability, such as vendor-provided components, from customer or project-specific data. Create a distinct structure for reusable content to streamline access.

Installation and Testing

After thorough preparation, it’s time to move on to installation and testing. Here are some key considerations:

Hardware and Software Acquisition

Acquire the necessary hardware and software components based on your system requirements. Consult the official documentation for your data management application for detailed specifications.

Licensing and Dependencies

Ensure proper licensing for all software components. Identify any system dependencies, such as connections to ERP systems or cloud repositories, and address them during the installation process.


Create a dedicated test environment to validate your installation. Test local and remote connectivity, administrative functions, and file check-in/check-out procedures. Implement disaster recovery strategies and fine-tune your system to optimize performance.

Configuration and Maintenance

Lastly, maintain your data management system by configuring it to suit your organization’s needs. Leverage advanced configuration guides provided by your software vendor to fine-tune settings for optimal performance. Regularly monitor and maintain your database to ensure efficiency.


In conclusion, preparing for a data management implementation is a comprehensive process that involves careful analysis, strategic planning, and meticulous testing. Remember to seek expert guidance if needed, set realistic expectations, and consider your long-term goals. By following these steps and understanding the nuances of your data, you can lay a strong foundation for a successful data management implementation that will benefit your organization for years to come.

A Guide to Data Management Implementation Configuration

In previous blog posts, we’ve covered various aspects of data management implementation, including planning and environment preparation. Now, in this third installment of our series, we will delve into the crucial step of populating your data management system. In this post, we’ll delve into the crucial aspects of configuring your data management system to maximize its effectiveness. Proper configuration ensures that your organization can efficiently utilize and protect its valuable data. We’ll explore various elements, including categorization, naming conventions, properties, life cycles, revision management, and the security model. This guide will give you a solid understanding of how to configure your data management system for success.

Configuring Excellence – Data Management Implementation:

Data management implementation is a critical aspect of any organization’s operations. Configuring your data management system effectively is essential to harness the full potential of your data resources. In this blog, we will break down the key steps and considerations for achieving excellence in data management configuration.

Understanding Your Needs:

Before diving into the configuration process, it’s crucial to understand your organization’s specific needs and goals. Take the time to plan and document your data management strategy comprehensively. Gather input from different roles within your organization, including administrators, power users, general users, non-engineering personnel, and external users. By considering the unique requirements of each group, you can tailor your data management system to cater to their needs effectively.

Starting Simple:

Begin your data management configuration journey with simplicity in mind. Many organizations find success by initially using out-of-the-box configurations. This simplified approach helps you become familiar with your chosen PDM software while avoiding unnecessary complexity. As your needs evolve and become clearer, you can gradually introduce more advanced features and customizations to enhance your data management capabilities.

Documentation and Visualization:

Documentation is your ally in this process. Document your data management configuration plan, naming conventions, properties, categories, life cycles, and security model. Visualization tools can help you create diagrams and illustrations that provide a clear picture of your configured environment. Having comprehensive documentation and visuals ensures that you and your team can easily refer to and understand your data management configuration.

Setting Realistic Expectations:

Implementing data management configuration is a substantial endeavor that requires time and resources. It’s crucial to set realistic expectations and communicate them clearly within your organization. Understand the potential challenges, costs, and timeframes involved in the process. By managing expectations effectively, you can minimize surprises and ensure a smoother implementation journey.


Configuring your data management system is a critical step toward efficient data utilization and protection. By understanding your organization’s needs, starting with simplicity, documenting your plan, and setting realistic expectations, you can achieve excellence in data management implementation configuration. This comprehensive guide has provided you with valuable insights to embark on this journey successfully.

4 Strategies for Seamless Data Population in Data Management Implementation

In the last section, we’ve covered various aspects of data management implementation, including planning, environment preparation, and configuration. Now, in this fourth installment of our series, we will delve into the crucial step of populating your data management system. Data population is where your data management solution truly becomes a usable entity within your organization. So, let’s explore four key strategies for achieving a seamless data population.

Leverage Auto Loader for Vault

Auto Loader for Vault is a powerful utility that comes bundled with Autodesk Vault, making it an attractive choice for data population. Here are some key points to consider:

  • Cost: Auto Loader is a free tool that is readily available to anyone who has purchased a Vault license.
  • Validation: Besides data loading, Auto Loader can provide valuable feedback about your data during the preparation phase, helping you identify and address potential issues.
  • Compatibility: Auto Loader is Microsoft-friendly, allowing you to work with various Microsoft file formats, not limited to CAD data.
  • Bulk Upload: It works seamlessly with both folders and individual files, making bulk uploading a breeze.
  • Visualization: Auto Loader can automatically generate DWF (Design Web Format) visualization files, enhancing the accessibility of your 3D models within Vault.
  • Multi-User Functionality: Multiple users can simultaneously analyze and load data, improving efficiency.

Utilize Inventor Task Scheduler

If your organization uses Autodesk Inventor in conjunction with Vault, the Inventor Task Scheduler can be a valuable tool for bulk data loading. It is particularly suitable for handling Inventor-related files and assemblies. Keep in mind that this method is more suitable for non-associated files.

Drag and Drop Capability

While it’s generally recommended to use dedicated tools like Auto Loader or Inventor Task Scheduler for data population, Vault offers a drag-and-drop capability within Windows Explorer. This method is suitable for non-associated files and can be handy for small-scale data additions. However, be cautious when using it with complex files with extensive relationships, as Vault may not recognize these connections.

Seek Consultancy Services

Consultancy services, such as those we offer at KETIV, offer several advantages:

  • Expertise: Consultancy firms have extensive experience working with various companies, industries, and data management systems. They can provide insights, best practices, and customized solutions.
  • Streamlined Processes: Consultants often follow well-defined processes to streamline data population, ensuring efficient and error-free implementations.
  • Support Contracts: You can opt for support contracts to receive assistance during and after the implementation phase, ensuring that you have help when needed.
  • Specialized Tools: Consultancy services may have access to specialized utilities and tools, such as data transfer utilities, to facilitate data population more effectively.

On-Demand Loading and Testing

Finally, when populating your data management system, consider two additional factors: on-demand loading and testing.

On-Demand Loading: Explore different methods of on-demand loading based on your business needs. These include pulling data from the Vault client, pushing data from the authoring tool, or using drag-and-drop functionality. Select the method that best suits your specific requirements and file associations.

Testing: Before fully populating your system, conduct thorough testing. Start with a small subset of data and assess how well your workflows function. Ensure that your data behaves as expected, security measures are in place, and life cycle stages are correctly defined. Document the results, issues, and solutions to refine your data population strategy.


Seamless data population is a critical phase in data management implementation. By following these four strategies and considering on-demand loading and testing, you can ensure that your data management system is populated effectively, setting the stage for efficient and productive data management within your organization. Remember, good data in means good data out, so always prioritize data quality and organization.

Going Live with Your Data Management Solution

This is part five of our series on data management implementation. In the previous episodes, we’ve covered the crucial steps of planning, preparation, configuration, and data population. Now, we’re diving into the final phase: going live with your data management solution. In this blog post, we’ll discuss what you need to consider as you prepare to introduce your system into your production environment.

Understanding Your Company’s Unique Needs

Every company is unique, and your data management requirements are no exception. What works for one organization may not work for another, even within the same industry. At KETIV, we understand the importance of tailoring data management solutions to your specific needs. Whether you’re working with sales engineers, estimators, designers, or engineers, we recognize that data management is the common thread weaving through all these areas.

Technology Maturity Assessment

Before proceeding with the go-live phase, it’s crucial to assess your organization’s technology maturity. By evaluating your current technology landscape, you can determine your starting point and the steps needed to reach a higher level of proficiency and productivity. We’ve identified four levels of technology maturity to help guide your assessment:

  1. Manual Processes: You rely heavily on manual processes with limited system integration.
  2. Basic Automation: You have several systems that are interconnected, enabling basic automation.
  3. Proficient Automation: Your systems are well-integrated, and you leverage automation effectively.
  4. Optimized Automation: You aim to achieve the highest level of automation for efficiency and productivity.

Understanding your current maturity level will assist you in planning your data management implementation more effectively.

The Role of Data Management in Your Organization

Data management is the linchpin connecting different areas of your manufacturing business, including sales, engineering, and manufacturing. Autodesk Vault, as a data management solution, plays a critical role in tying these areas together. It ensures that your data flows seamlessly and accurately through your organization, ultimately contributing to your overall success.

Let’s focus on key aspects of going live with your data management solution, including:

  • Assessing Your Environment Status
  • Training and Upskilling Your Users
  • Effective Notification Strategies
  • Providing Ongoing Support

Assessing Your Environment Status

Before making the transition, you must thoroughly assess your environment status. This involves rigorous testing of your data management solution within both your test and production environments. By carefully reviewing the results of your testing efforts, you can identify any issues or adjustments that need to be made before going live. Additionally, consider the challenges posed by the time lag between turning off one system and introducing another, and have a strategy in place to address any data discrepancies that may arise during this transition.

Preparing for the Unexpected

Remember that no implementation is without its hiccups. You may miss certain details or encounter unforeseen issues. The key takeaway here is that you have the flexibility to make changes and adjustments. Don’t hesitate to seek guidance from experts like KETIV when facing unexpected challenges. We’ve encountered various situations and can provide valuable assistance to help you overcome any obstacles.

Training and Upskilling Your Users

One of the most critical aspects of going live with your data management solution is ensuring that your users are well-prepared. Adequate training is essential to empower your team to contribute effectively to your company’s success. Here are some training considerations:

  • Focus on Administrators: Identify key individuals to act as administrators early in the process. They should be involved in the implementation and receive in-depth training to ensure they have a deep understanding of the system.
  • Include Internal and External Users: Provide training for both internal and external users. While internal users may have more accessible training options, consider creating specialized training modules for external users who access your system.
  • Accommodate Non-Engineering Roles: Recognize that not all users are engineers. Tailor training to non-engineering individuals, such as those in sales, manufacturing, procurement, and inventory, to ensure they can interact with the system effectively.
  • Educate IT: Ensure that your IT team is well-informed about your data management system. They should be aware of system changes, requirements, and how to troubleshoot issues.

Effective Notification Strategies

Proper communication is vital when introducing new systems or processes. To notify your team effectively, use various communication channels:

  • Email Notifications: Send out emails with clear information about the go-live date and any relevant details.
  • Instant Messaging Services: Leverage platforms like Slack or Teams to send instant messages and updates.
  • Internal Website Announcements: Display banners or notices on your internal website to keep everyone informed.
  • Physical Bulletin Boards: Use physical bulletin boards in common areas to post important updates.

Remember, over notification is better than under notification. Ensuring everyone is well-informed helps minimize confusion during the transition.

Providing Ongoing Support

Anticipate that issues may arise after going live, and have a support plan in place. Consider the following support strategies:

  • Training Curriculum: Develop a training curriculum that is accessible online, allowing users to access resources and videos to address common issues.
  • Office Hours: Schedule regular office hours with subject matter experts or administrators who can provide real-time support to users.
  • IT Support: Ensure your IT team is available to address technical issues promptly.
  • Consultancy Support: If you’re working with a service provider like KETIV, establish a support contract or mentoring arrangement to access expert assistance when needed.


As you prepare to go live with your data management solution, remember that empowering your users with information, offering comprehensive training, effective notification strategies, and ongoing support are key to ensuring a smooth transition. Going live is an exciting step toward accessing data more efficiently, reducing manual processes, and achieving a single source of truth for your organization. Embrace the change and rely on experts like KETIV to guide you through any challenges along the way. Your success is our priority.