4,000 Reasons Supply Chain Design Tools Fall Short — And 1,500 Why They Don't Have To

I didn’t know off the top of my head — but thanks to WhatsApp and our lead programmer, a few minutes later I had the answer: about 1,500.

It was the first time I’d seen that figure, and I thought it was impressive. He did not. In fact, he told me that in his experience, anything below 4,000–5,000 fields “wasn’t robust enough.”

Each layer of detail and each additional field may add value — but it also adds complexity, more data to maintain, and more time spent wrestling the tool into giving results. At some point the extra “robustness” undermines the very goal of the tool: timely, useful decisions.

And if time runs out, no model matters. That was true 30 years ago — and it’s true today.

Time has been a critical resource pretty much since day one.

A few years after Jobs and Wozniak began tinkering in that now-famous garage, PCs were fundamentally transforming business decision-making. Managers suddenly had access to menu-driven, visual applications they could interact with in real time.

This shift from batch-oriented, IT-mediated computing to interactive, user-controlled applications democratized decision support — empowering individuals to make choices on the spot instead of waiting for static reports that were often outdated by the time they arrived.

For those of us working on planning and optimization solutions in the supply chain space, these were exciting times. We could finally begin linking Operations Research (OR) models with the new world of interactive, menu-driven applications.

With the arrival of commercial solvers, we started developing visual network design and tactical planning tools that managers could use directly. But time quickly became a major bottleneck — not just the time to prepare scenarios and interpret results, but above all the processing power needed to run them.

Computing speed, more than anything else, set the practical limits of what was possible.

To deliver affordable solutions with a reasonable chance of success, we had no choice but to design — or more accurately, match — models to the machines we had. Optimality in the textbook sense was usually not an option.

To this day, the goal remains the same: solutions that can consistently generate good-quality results in a reasonable amount of time, at an affordable cost. 

The fact that many of these solutions have lasted far longer than industry norms — one of the earliest supply chain planning systems recently turned 32 — is a solid indication that this approach works: right-scope the model, aim for good results, and don’t overcomplicate things.

So when that expert suggested that the size of our database wasn’t big enough for a robust solution, I understood his perspective — but I’m not changing my mind.

Some supply chain modeling apps aim to handle more complex problems. To do that, they pack in the features and functionality to support this complexity — which inevitably comes at the cost of usability, speed, and adoption.

At Factible Tools, we’ve chosen a different path: to build a supply chain network design and tactical planning tool that delivers what the vast majority of organizations actually need.

We add complexity only where it benefits the broader community of users. Our solution won’t be the right fit in every case, and that’s fine. But for the many who want good answers quickly, without wading through endless configuration screens, “less” isn’t just more — it’s just right.

After 30+ years of watching simpler solutions outlast more sophisticated ones, I’ll keep chasing the metric that matters most: do people actually use what we build to make better decisions?

Because in the end, that’s the clearest sign we’ve been on the right track — and still are.