A blog by Oleg Shilovitsky
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PLM vs. Excel Dilemma: Effective Data Governance and Spreadsheet Replacement for Engineers

PLM vs. Excel Dilemma: Effective Data Governance and Spreadsheet Replacement for Engineers
Oleg
Oleg
9 March, 2024 | 5 min for reading

The discussion about PLM vs Excel is one of the long standing topics in PLM industry. I touched this topic many times. The ubiquitous capabilities of spreadsheets, combined with simplicity and availability (free), make it an easy way to be a universal data management and collaboration tool. It served engineering community for a long time. The debates about brining PDM or PLM was always about how to introduce a government and reduce the freedom.

In one of my recent articles I shared thoughts why Excel remains so popular for engineers. At the same article I explained that introducing of product lifecycle management (PLM) and product data management (PDM) for engineers will be always considered as a way to bring a government and to build a system of rules and restriction using PLM system.

Rob Ferrone of Quick Release (who calls himself data PLuMber who fixes PDM leaks) brought this nice picture and comment in the LinkedIn post

No alt text provided for this image

I realised that the majority of an organisation, even when they are directly impacted by PLM/ERP/MES… systems, care about PLM as much as they might a government office. It’s a means to an end, and usually a painful one. I think the only ones genuinely excited about PLM systems are the vendors and system integrators. If you want to be successful using technology to enhance business value, look at how the team are working and how they’d like to be working more efficiently and use that insight to create the tech transformation plans. The people-centric, bottom up approach is one of the reasons why start-ups go faster. IT can build the layer/graph that enables holistic information flow. The connections and enterprise architecture should be invisible to the user, whilst data is visible to the whole organisation and empowers decision making. In summary: make the question “How can I make it easier for you to provide your unique value?”

The comment and the question made me think about what modern PLM software and tech can do different and what tools to offer to engineers, so they will abandon their spreadsheets.

Addressing the PLM vs. Excel Dilemma

In the world of engineering and PLM there exists a longstanding conflict between the perceived necessity of PLM governance and the comfort of using Excel. On one hand, PLM is hailed as a governance tool, but one that many engineers loathe due to its complexity and rigidity. On the other hand, the strategy of relying solely on Excel, while convenient, often leads to chaos and a lack of structured processes.

The debate between PLM governance and Excel usage underscores a fundamental tension within engineering organizations. PLM is seen as a necessary evil, imposing rigid processes and structures, while Excel offers familiarity and flexibility. However, relying solely on Excel leads to fragmented data and inefficient collaboration. It’s essential to find a middle ground that combines the strengths of PLM governance with the flexibility of Excel-like tools.

Separating Functions for Data Management and Collaboration

So, what is the way to solve the problem and remove the tension between engineers preferring to use Excel and setting up data management governance? How to bridge the gap between value of organized data and processes and ease of Excel usage. Here is the idea that in my view, can work. Introducing of modern cloud-based architectures can help to layer and separate data functions into two groups – data management and collaboration.

Data Management Foundation: Establishing a robust data management infrastructure is essential for ensuring data integrity and accessibility. This involves centralizing data storage, establishing standardized processes, and implementing version control mechanisms. Modern data management tools can provide a advanced and flexible data modeling capabilities.

Seamless Integration & Collaboration: While Excel may offer a familiar interface for data manipulation, it falls short when it comes to collaborative workflows. PLM solutions should focus on providing easy and seamless ways for teams to integrate with engineering tools (eg. CAD), collaborate, share data, and track changes in real-time. The level of seamless user experience should help to engineers to disconnect from Excel.

Prioritizing Data Management and Collection

A crucial aspect of effective PLM governance is prioritizing data management and collection. The more comprehensive the data collected, the better equipped organizations are to make informed decisions and drive innovation. This involves capturing data at every stage of the product lifecycle and ensuring interoperability between different systems and tools.

Focusing on Collaborative Services and Integrations

Moving away from traditional file-based workflows, organizations should focus on adopting service-oriented architectures and integrations. This entails shifting from a “file/email” mode of operation to a connected ecosystem where data is readily accessible and shared seamlessly between applications. Integrating AI tools can further enhance data analysis and decision-making capabilities, closing the loop between engineering and manufacturing processes.

Harnessing the Power of AI

Integrating AI into PLM solutions can revolutionize the way organizations manage and utilize data. AI tools can analyze massive amounts of data to identify patterns, detect errors, and mitigate risks. By leveraging AI-driven insights, organizations can optimize processes, improve product quality, and drive innovation.

What is my conclusion?

How companies can embrace a new vision of PLM governance and keep efficient collaboration? The key to navigating the PLM vs. Excel dilemma lies in embracing a layered and integrated data services approach. Rather than imposing a vertically integrated platform, organizations should adopt a more granular, open, and efficient approach. This involves leveraging interconnected services that collect and reuse data, provide focused and seamless user experiences, and empower organizations to harness the full potential of their data for creative and analytical tasks. Collaborative services can provide a layer to communicate efficiently. By striking the right balance between governance and flexibility, organizations can unlock new opportunities for growth and innovation in the digital age. Just my thoughts…

Best, Oleg

Disclaimer: I’m co-founder and CEO of OpenBOM developing a digital-thread platform with cloud-native PDM & PLM capabilities to manage product data lifecycle and connect manufacturers, construction companies, and their supply chain networks. My opinion can be unintentionally biased.

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