As leaders, we say we want our people to be empowered to go out and make decisions. We say we’re OK with them making mistakes, and we’ll still support them making decisions on their own. But not really.

Welcome knowledge seeker! Do you feel dazzled and awed by the great potential of artificial intelligence (AI)? Perhaps hesitant or lost when terms like convolution, deep learning, or autoencoder are thrown around?

In the ever-changing world of quality management, the intersection of innovation and standardization offers both exciting opportunities and tough challenges.

Struggling with underperforming team members while trying to maintain a positive work environment? To help navigate this delicate situation, we’ve turned to insights from CEOs and human resources managers.

The U.S.

From small family-run companies to tech giants, the business world is changing at an unrelenting pace.

In a competitive manufacturing industry, meeting high standards is crucial to quality, sustainability, and safety.

Managers are commonly fed a diet of report-card data. These data have usually been aggregated into summaries, averages, and totals to characterize the big picture. As useful as such summaries can be, they can also be an obstacle to an effective analysis.

Businesses are always searching for methods to improve supply chain operations and increase customer satisfaction in today’s smart business world.

Whether you’re a small machine shop or a large multimillion-dollar manufacturing giant, there’s no doubt you use dimensional gauges to maintain the standards for quality in your production.