I’ve had this conversation countless times—sometimes with a frustrated client, often with a colleague, and occasionally with my own reflection.

What’s truly holding your discrete manufacturing shop back from reaching its full potential? It’s often not the commonly cited culprits like labor shortages, razor-thin margins, or fierce competition. It’s more often paper: the unseen, insidious enemy.

The conversation about generative AI (gen AI) is unavoidable in today’s business land

In this article I’m looking at a question that’s rarely asked in management: What if the most responsible course of action isn’t to maximize benefit, but to minimize harm? In decision theory, this is expressed as the minimax principle.

Even the smallest manufacturer would never consider using a typewriter to develop an invoice, or manage a sales prospect list from a Rolodex.

Amidst uncertainty in manufacturing, AI adoption, labor market fluctuations, and salary disparities across industries and geographic regions, quality professional compensation can be difficult to navigate.

One of the principles for understanding data is that while some data contain signals, all data contain noise. Therefore, before you can detect the signals you’ll have to filter out the noise. This act of filtration is the essence of all data analysis techniques.

Staff meetings can be incredibly productive. Or unproductive—and more often the latter. If your staff meetings are terrible, it’s your fault because you’re not structuring them well.

From manufacturing and mining to hospitality and healthcare, computerized maintenance management systems (CMMS) have become all but essential.

In this article, I want to explore an idea that often is framed in moral terms but is actually a cybernetic imperative: the necessity of diversity for viable systems.