Breaking Free from Excel: Your 5-Step Plan to Solve Data Organization Challenges in Engineering and Manufacturing

Oleg Shilovitsky
Oleg Shilovitsky
22 June, 2024 | 3 min for reading
Breaking Free from Excel: Your 5-Step Plan to Solve Data Organization Challenges in Engineering and Manufacturing

In the rapidly evolving landscape of manufacturing, data is the new gold. Yet, many organizations find themselves entangled in outdated practices that hinder their potential. Chronic short-termism and a refusal to look beyond Microsoft Excel and/or whatever software your company’s been running for the last 20+ years is not good for engineering output, organizational effectiveness, engineer satisfaction, or basically anything else that matters.

Last year I published my article – The Data Dilemma: Why Engineers and Manufacturing Companies Struggle to Find Time for Data Management. The topic resonated with many engineering minds sending me their examples about how they struggled to organize their data and set up reliable, robust, and, at the same time, simple data management systems. Here is my short conclusion after speaking to many engineers: 

Chronic short-term thinking and ignorance to look beyond Microsoft Excel and/or whatever spreadsheet software companies have been running for the last decades are not good for engineering output and manufacturing processes. It impacts organizational effectiveness, engineering satisfaction, and basically anything else that a manufacturing company is focusing on. The engineering ideas to preserve the simplicity of Excel to bad outcomes all the way down. 

In my article today, I want to speak about why it is happening and give you a plan on how to break from Excel.

The Excel Dependency

Excel, while versatile and familiar, has become a crutch for many manufacturing firms. Its simplicity and ease of use have made it a staple in data management. However, its limitations in handling complex, interconnected data sets are becoming increasingly apparent.

The Real Cost of Outdated Systems

Sticking to what’s familiar may seem like a safe bet, but it often leads to significant inefficiencies. Data silos, version control issues, and a lack of real-time collaboration are just a few of the challenges that can arise. These inefficiencies can delay projects, increase costs, and lead to suboptimal engineering outcomes.

Engineering Output and Organizational Effectiveness

For engineers, the frustration of working with outdated systems can’t be overstated. In an age where digital transformation is key to staying competitive, relying on tools designed decades ago can stifle creativity and innovation. Modern PLM (Product Lifecycle Management) systems offer a way to integrate and streamline processes, providing a single source of truth that enhances both engineering output and organizational effectiveness.

The Path Forward: Embracing Digital Transformation

The solution lies in embracing digital transformation. Moving to cloud-native PDM (Product Data Management) and PLM solutions can revolutionize how data is managed and utilized. These systems offer real-time collaboration, robust data security, and scalable solutions that grow with your business.

5 Steps to Organize Data When You Have No Time

  1. Focus on Key Data and Identify Existing Systems: Determine the most critical data to organize and identify existing systems that need to be preserved and integrated. This helps prioritize efforts and ensure continuity.
  2. Decide on a Central Repository for Product Data: Select a service to act as the central repository for product data, establishing a single source of truth. This centralization is crucial for maintaining consistency and reliability.
  3. Define Integration with Existing Systems: Plan how to integrate the new repository with existing systems across engineering, finance, production, and customer relations. Seamless integration minimizes disruptions and maximizes efficiency.
  4. Set Up NPD and ECO Processes: Establish New Product Development (NPD) and Engineering Change Order (ECO) processes. These structured workflows ensure that data is managed systematically and changes are tracked accurately.
  5. Import Legacy Data from Existing Spreadsheets: Migrate legacy data from current spreadsheets into the new system. This step ensures that historical information is preserved and accessible within the new framework.

Conclusion

It’s time for manufacturing organizations to look beyond Excel and legacy systems. By adopting modern data management solutions and implementing quick, effective strategies for data organization, companies can improve efficiency, foster innovation, and enhance overall satisfaction among engineers and stakeholders. Breaking free from the constraints of outdated systems is not just an option; it’s a necessity for future success.

REGISTER FOR FREE and check how OpenBOM can help you. 

Best, Oleg

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