When ''That's Just How it's Done'' Becomes The Real Problem

For most electronics engineers, the situation is familiar. 

You’ve selected the component you want to use, opened your CAD tool, and discovered that the symbol, footprint, or 3D model either doesn’t exist, doesn’t match the datasheet, or can’t be trusted. What happens next is rarely discussed. The engineer quietly builds or fixes the model themselves, checks it, and moves on. 

For decades, this work was accepted as part of the job. That quiet acceptance is exactly why the problem persisted for so long and created an opportunity for us to help the industry. 

Why The Problem Was Normalised

The electronics industry didn’t ignore CAD model creation out of negligence. It persisted because responsibility was fragmented. 

EDA vendors focused on tools and features. Component manufacturers focused on silicon and datasheets. Distributors treated CAD data as supplementary collateral. 

Engineers were left to bridge the gap. Because each engineer solved the problem locally — building libraries one part at a time — the cost was never visible at a system level. It didn’t appear in project plans or budgets. It lived in evenings, workarounds, and quiet rework. When everyone carries a small burden individually, the industry never feels the weight collectively.

The Real Cost Was Not Just Time

It’s tempting to describe the issue as wasted hours, but that understates the impact. Manually created models introduce inconsistency across teams. They increase risk under schedule pressure. They surface errors late, when changes are expensive. 

In complex design environments, small inaccuracies compound. A footprint error discovered after layout can ripple into procurement delays, manufacturing issues, or late-stage redesigns. The downstream cost far exceeds the original effort of “just building the model.” The most damaging consequence was not inefficiency, but unpredictability. 

Seeing The Problem From The Inside

For many engineers, including myself earlier in my career as a PCB designer, building CAD libraries was routine. Symbols and footprints were created manually, dimensions were checked repeatedly, and there was always the lingering concern that something subtle might have been missed. 

The frustration was not that the work was difficult. It was that it was repetitive, unscalable, and disconnected from the value engineers are employed to deliver. 

At the time, this felt unavoidable. It was simply how things were done. 

When a Workaround Stops Being An Edge Case

Later, working closely with engineering teams across many different organisations, a pattern became impossible to ignore. 

• Different companies. 
• Different CAD tools. 
• Different products. 

The same workaround appeared everywhere. Once the same behaviour repeats across dozens of teams, it stops being an isolated inconvenience. It becomes a structural issue. This was not a tooling gap. It was a data problem embedded deep within the workflow. 

Why Early Attempts Didn't Go Far Enough

There were attempts to address parts of the problem. Some were well funded and technically competent. But most approaches treated CAD models as static files to be catalogued rather than as living, verified data inside engineering workflows. 

Engineers don’t want files.   
They want accuracy. 
They want speed. 
They want trust.

Without automation, standardisation, and quality control at scale, the same friction simply reappears in a different form. 

What Changed

The shift only became possible when the problem was broken down to first principles. What does an engineer actually need at the moment a part is placed? 

• Correct geometry.
• Verified data.
• Immediate availability. 
• Native compatibility with their CAD environment.

Anything less reintroduces risk. Over time, the industry has moved toward treating CAD models as structured, managed data rather than one-off artifacts. Instead of being built repeatedly from scratch, models are now increasingly generated, verified, and delivered directly inside design workflows, aligned with manufacturer intent and maintained at scale. 

Platforms such as SamacSys helped drive this shift by treating CAD models as a first-class part of the engineering data ecosystem rather than an afterthought. 

The Broader Lesson 

Many industries carry long-standing inefficiencies simply because ownership is unclear and workarounds become normalised. The most valuable problems are often the ones people stop questioning, not because they are unsolvable, but because they are familiar. 

Progress rarely begins with better tools alone. It begins when someone decides that a long-accepted frustration deserves to be taken seriously. 

This pattern is not unique to electronics. 

Every large organisation has its own version of the thing everyone just deals with. It might be a spreadsheet no one fully trusts, a manual approval step that exists only because it always has, or a process so fragile that only one person knows how it actually works — and everyone is quietly relieved when they are not on holiday. 

These issues survive not because they are difficult to solve, but because they are rarely visible at the right level. By the time leadership hears about them, they have already been normalised. 

My advice is simple. 

Pay close attention to the phrases people use when describing friction. Everyone does it this way. Its quicker if I just fix it myself. Its not ideal, but it works. Those sentences are early warning signs. 

They usually indicate hidden cost, unowned responsibility, and a system that relies on goodwill rather than design. Left unchallenged, they scale remarkably well — just not in a way you would ever choose if you were starting again. 

And a note of caution. If a problem has been around for ten or twenty years, it does not automatically mean it is hard. Sometimes it just means it has never been important enough to the right person at the right time. 

If you ever want a reliable source of valuable opportunities, start by asking your most capable people what they spend time on that they believe should not be their job. You will not hear about innovation or strategy. You will hear about workarounds. That is usually where the real leverage is hiding. 

Final Thought

The real cost of “just building the CAD model” was never the time spent creating it. It was the decades spent assuming the problem couldn’t be solved. 

Sometimes the most meaningful improvements come not from working harder, but from finally challenging the assumptions everyone else has learned to live with.