Nine months ago, I had a conversation with a company implementing a data management solution. They explained to me that managing file revisions using file names was “easy” and something they had always done. They also mentioned it worked well with their Excel reports because it allowed them to clearly see the revisions. It was a clear example of defending the status quo and resisting change.
Fast forward to last week—I received a letter from them, expressing how much they appreciate the push to adopt a better data management solution and how it has improved their processes and business outcomes.
Today, I’m reflecting on the importance of solving data management challenges and breaking the status quo to improve business processes.
In the world of engineering and product development, data management often follows the path of least resistance. Engineers, brilliant in their technical domains, frequently overlook the long-term implications of quick data management decisions. This oversight isn’t due to a lack of capability—quite the opposite. Engineers are smart, innovative problem-solvers who can make almost any tool work for their immediate needs. But therein lies the trap.
Quick Fix Is Easy
The typical approach to data management often starts innocently enough. A database? That’s for the IT team to worry about. Excel? Perfect—it can be endlessly customized, with macros and formulas showcasing technical prowess. It seems like a rational choice at first: quick to implement, familiar to use, and infinitely flexible.
However, what begins as a single spreadsheet rapidly multiplies. Soon, you’re juggling multiple Excel files, a task management system, GitHub repositories (because no self-respecting software team would work without version control), and CAD files scattered across various storage solutions. Each addition seems logical in isolation, but collectively, they create a tangled web of data silos.
The Real Problem Emerges
The real issue isn’t immediately apparent. It’s not that any single tool is inherently flawed—it’s that data becomes fragmented, inconsistent, and increasingly difficult to track. Changes happen in multiple places, versions conflict, and the source of truth becomes murky. What started as a simple solution transforms into a complex ecosystem of disconnected information.
Even more, it conflicts with digital transformation strategy and digital transformation initiatives. What can company do with all these spreadsheets.
Breaking the Cycle: A Strategic Approach
Guess what? It is not about buying an expensive database or ERP system to manage data. At least, this is not the first task I recommend to do.
To fix this problem, organizations need a clear plan for managing their data. The first step is to focus on the data itself. Before picking tools or setting up systems, figure out what kinds of data you need to manage. Decide who is responsible for each type of data, and write down what good data looks like and how to keep it that way.
The next step is to understand how your tools and apps work with your data. Make a list of all the tools you use to create, edit, or view data. Identify which tools are the main source of truth for different types of data, and think about whether each tool is really necessary.
It’s also important to look at how different pieces of data are connected. Write down how your data sets relate to one another and what depends on what. Then, set up rules to make sure these relationships stay accurate across all systems.
Finally, have a plan for handling data changes. Create simple steps for updating data, make rules for approving changes, and set up a way to track who changed what and when. Following this straightforward approach can help your organization move from messy, scattered data to a system that works smoothly and efficiently.
The Cost of Easy Choices
While taking the path of least resistance—using Excel for everything, emailing files back and forth, creating ad-hoc storage solutions—might seem efficient in the short term, it creates significant long-term costs:
- Reduced data reliability.
- Increased time spent searching for information.
- Higher risk of errors and inconsistencies.
- Difficulty in scaling operations.
- Challenges in maintaining data security.
However, the main one is to look at data holistically. From a single engineer perspective, sending a spreadsheet is an easy (and the right way). Any CAD exports Excel, attach it to the email, send and forget. What organization lose as a result of that is not the task engineer must be concerned about.
Therefore, digital transformation strategy and digital transformation leaders must think about how to analyze data, data sources, and think how modern digital technology including artificial intelligence can help to collect data, make data analytics to support company business strategies and contribute to digital transformation efforts.
What is my conclusion?
Organizational change management is hard. It includes analysis of key performance indicators, new business models, internal processes and make company to think about the entire organization and a single person. After all, it is also about company culture and potential value of new technologies.
The journey to better data management isn’t about finding the perfect tool or system. It’s about changing mindsets and establishing processes that prioritize long-term sustainability over short-term convenience.
This might mean:
- Investing time in proper data modeling.
- Implementing structured data management systems.
- Training teams on data management best practices.
- Conducting regular audits and updates of data management procedures.
Using Excels is tempting – it is what everyone is familiar with, organizations must recognize that better data management, though initially more challenging, provides significant returns in efficiency, reliability, and scalability. The key is to start viewing data management not as a necessary evil but as a strategic advantage that deserves careful consideration and investment.
A note to business leaders – better is harder than easy, but it’s worth the effort.
Just my thoughts…
Best, Oleg
I am the co-founder and CEO of OpenBOM, a digital-thread platform that offers cloud-native collaborative services, including PDM, PLM, and ERP capabilities. With extensive experience in federated CAD-PDM and PLM architecture, I advocate for agile approaches, open product models, and the adoption of cloud technologies in manufacturing. Please note that my opinions may reflect my work at OpenBOM and could be unintentionally biased.
