The Data Dilemma: Why Engineers and Manufacturing Companies Struggle to Find Time for Data Management

In today’s data-driven world, managing data efficiently is critical for the success of any business, including engineering and manufacturing companies. However, these sectors often find themselves grappling with a common problem – the inability to find time for proper data management. In this blog, we will explore the reasons behind this challenge and the potential consequences it can have on these industries

The image above surfaced on the internet a few years ago and very nicely illustrates the situation I often observe in many engineering teams and manufacturing companies. Engineers find ourselves consumed with the task of manually extracting data, tallying parts, and generating reports. Furthermore, I frequently encounter situations where supply chain managers inadvertently send the wrong file with incorrect revisions to contractors, resulting in substantial financial losses and delayed product deliveries. Additionally, it is not an unusual to see how managers spend an excessive amount of time in Excel, calculating product costs. 

So, what is behind this “busy behavior”? Why are engineers and manufacturing companies keep the inefficient processes and refuse to make a change? 

A few days ago, a former OpenBOM customer reached out to me and shared his insight about working in different companies and why companies don’t move to optimize their working processes. Company inertia plays a big role in the decisions engineering teams and manufacturing companies. As a result, companies decide not to improve systems and processes. This point made me think in a more structured way about what makes engineers struggle to find time to optimize the way they manage data and processes. 

5 Reasons Why Old Habits Die Hard 

In my 20+ years of experience in PDM and PLM business, I found that everyone in the company needs data, but no one is interested in dealing with data management. Historically, engineering teams and manufacturing companies were using desktop CAD systems, pushed data to Excel, and moved on by giving other people in an organization to deal with this information. It was called to through it over the wall of manufacturing. For large companies, the ERP / MRP system took care of the business. For smaller companies, people responsible for running procurement or production planning were taking these spreadsheets and other files to deal with them. While it sounds like an obvious thing to improve, many companies struggle to make this change happen. The main reason is ownership. You need someone to take responsibility for the entire process. Otherwise, every person feels good to postpone, to blame others and keep the current bad habits.

Legacy Systems and Processes

We always did it this way. You probably heard this statement many times. Many engineering and manufacturing companies rely on legacy systems and processes that were designed before the era of computing systems, cloud services, and online data storage. These outdated systems often lack the capabilities that can simplify the work and optimize data process and communication.  Migrating to newer systems can be time-consuming and costly, deterring companies from making the necessary upgrades.

Overwhelming Workloads 

Another reason why engineers and manufacturing companies struggle with data management is their overwhelming workloads. Engineers are tasked with designing, testing, and optimizing products while manufacturing companies are focused on producing goods at scale. These tasks are inherently time-consuming, leaving little room for data management efforts. Engineers are busy “pushing data out of their hands”, and manufacturing and supply chains are focusing on how to procure and build stuff. There are very few people in a traditional manufacturing company who are thinking holistically to find how to focus on information flows in a company. Engineers are focusing on building products and they are not accountable for business process management, data management and communication.

Lack of Data Expertise

While engineers are super smart people and always look at how to innovate, when it comes to data management, I can see typical disengagement and lack of interest. Data management sounds like a boring topic and engineers feel they are “not up to this job”. Data management requires a certain level of expertise, including data collection, storage, analysis, and security. Engineers and manufacturing professionals are experts in their respective fields, but they may not have the necessary skills or knowledge to effectively manage data. Especially when things are going what I call “beyond Excel”. This lack of expertise can lead to inefficiencies and data-related challenges.

Short-Term Focus

In many cases, when it comes to data management, engineers and manufacturing companies are driven by short-term goals and deadlines. This short-term focus can lead to a neglect of long-term data management strategies. Companies may prioritize meeting immediate production targets over investing time and resources in data organization and analysis.

Resource Constraints

Resource constraints, both in terms of personnel and finances, can hinder data management efforts. Hiring dedicated data professionals or implementing robust data management systems requires a financial commitment that some companies may find challenging, especially when they are already stretched thin.

Consequences of Neglecting Data Management

Now, let me focus on what can happen if a company continues to ignore data management and let things flow in a natural way. The failure to prioritize data management can have several critical consequences for engineers and manufacturing companies:

1. Inefficient Operations: Inaccurate or inaccessible data can lead to inefficiencies in product development, manufacturing processes, and supply chain management.
2. Missed Opportunities: Without effective data analysis, companies may miss opportunities for cost savings, quality improvements, and innovation.
3. Compliance Risks: Neglecting data management can result in non-compliance with data privacy regulations, leading to legal and financial penalties.
4. Competitive Disadvantage: Companies that do not leverage data effectively may lose their competitive edge to more data-savvy competitors.

To sum up, ignoring data management can impact your manufacturing business in a substantial way. Your company will take longer to develop products, the cost will increase and you expose your company to a potentially large number of compliance, regulation, supply chain and security risks.  

Conclusion

Data management is a critical aspect of modern business operations. Engineering and manufacturing companies are not an exception from this rule. While engineers and manufacturing companies face unique challenges, such as resource constraints and complex legacy systems, it is dangerous to neglect data management. 

To find a balance between day-to-day tasks and long-term data management strategies is essential for staying competitive and ensuring sustained growth in the data-driven world. Investing in data expertise, modernizing systems, and adopting a proactive approach to data management can help these industries overcome their data dilemmas and thrive in an increasingly data-centric environment.

At OpenBOM, we provide an easy yet powerful way to balance all data management activities and jumpstart your business in the future of digital transformation. 

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Best, Oleg