Manufacturing companies are facing a digital transformation. They are looking to modernize their business processes and improve their operations. But things are not so simple. Engineering teams and manufacturing companies are struggling with a large number of problems. Some of these problems are technical and “old habits” of using CAD files, Excels, Emails attachments, and legacy and homegrown systems. Other issues are conceptual and educational. Companies are looking for simple answers to solve problems that are not simple.
One area that is receiving a lot of attention is product lifecycle management (PLM). PLM can play a critical role in helping companies achieve their goals, but there is no clear answer as to whether or not all manufacturers should adopt it. In this blog post, we will explore the benefits of PLM and help you decide if it is right for your business.
Why Can Excel not Be A Simple Solution?
If the only tool you have is a hammer, you tend to see every problem as a nail. If you’re looking to solve all data management problems using Excel, everything you do will have the limitations of spreadsheets. And manage a product development and manufacturing process is complex. It doesn’t fit the Excel paradigm, and it hurts. Here is why you cannot use a simple solution to complex problems.
Simple solutions for complex problems usually fail because the situation demands you to acknowledge that complexity exists. Many engineers and organizations I talked to refuse to accept such complexity and keep trying to solve the problem by applying “it is just Excel export” to get it done. Many organizations lack a conscious management understanding that product development requires technical and IT skills, knowledge, and tools. They want to improve the production and process with no cost, software, computers, and human resources.
The best way to face a complex problem is not to break it down into smaller manageable pieces (e.g., let’s export a part list from the CAD system to Excel and then decide what to do next). Doing so will ignore and lose the critical interconnections between parts of the systems and how to manage them. You will lose how and when those connections create their impact on the entire system (eg. Sending an Excel file to the procurement department solves the answer to what to order at this moment but completely misses the change process and updates, which will become a mess later down in the process).
Taking a complex system apart until you find a single problem you can solve (e.g., create an excel with a BOM) means that only that piece will ever be addressed. However, the unintended consequences that come from only solving part of the problem will negate any progress anyway (in the case of product lifecycle management, it is an entire data and process management to support your manufacturing organization).
Instead of addressing a small problem, you should start by considering the system as a whole. It would help if you described how all parts of the system work together, how parts of the system are connected to each other, and what impact changes.
Is there a straight answer to how to solve the problem?
I’ve got a comment from one of my readers saying that they are concerned about how to manage information between engineering, standard parts ordering, and the custom parts manufacturing process. They have all the data stored in multiple places – drawing BOMs, Excel files, and even an ERP system used for standard parts procurement. However, they are looking at how to make a single list to get everything together. The reader commented that PLM does provide a straight answer on how to make it work.
I can see a typical problem in many companies and engineering organizations. What these companies do is that they look at the complex processes (design, production planning, manufacturing planning, procurement, etc.) and try to bring them all together in a single list (preferable in Excel, because then the solution comes “for free”). The thing that all these companies are ignoring is the complexity of data and processes. You can get the data in a single Excel, but it will break in the next moment because people in various parts of the company will be making changes to this data.
How can PLM help to solve the digital transformation problem?
The straight answer is to acknowledge the complexity of the problem. Let’s start with the complexity of the data and its dependencies. Every company has design data, CAD documents, product information, product structure, manufacturing planning, orders, inventory, and many others.
The goal of digital transformation is to organize a single source of truth and integrated information flow that fits your company’s needs. It might be a single PLM platform, but it is better to follow modern digital web services to manage information and its dependencies. Every company has its way, and the goal must be to figure out the setup and the process that must be applied. It is easier for startups and new businesses, but it is never an out-of-the-box process for complex manufacturing companies with existing processes and dependencies.
The way to solve these problems is to focus on organizing a process to model your company’s needs, finding modern digital tools to manage information, and eliminating data siloes by enabling data sharing and process management to support multiple teams and organizations (internal and external).
What is my conclusion?
Don’t try to solve complex problems by breaking them into simple pieces. You will lose the situation, and your solution won’t be accepted in the best-case scenario. In the worst-case scenario, you will create a new (sometimes bigger problem) that will require more effort and cost to solve.
By bringing “Excel lists” to solve the data and process management problem, you ignore some fundamental rules and dependencies – data is complex, and the changes continue and involve multiple people and organizations. What seems like a “simple export” will result in the massive cost of mistakes, missed delivery time, increased cost, and frustration.
Start your digital transformation from the ground up by analyzing data silos and processes and how to combine them to create a single product lifecycle management process to support all stages of the product development process.
Just my thoughts