Machine learning, the latest incarnation of artificial intelligence (AI), works by detecting complex patterns in past data and using them to predict future data.

‘It’s the shoes!” Spike Lee yelled into the camera on the Air Jordan ads.

Government bureaucracies are inefficient. They waste taxpayer dollars, and they have no incentive to improve. We’ve all heard and probably repeated these axioms about wasteful government spending.

Lean: an employee-championed method of waste reduction. Six Sigma: a robust method of defect reduction. Embracing both methods provides organizations with multiple tools for continuous improvement.

At the University of California at San Diego, lean concepts have taken hold. Along with its process improvement curriculum, the university applies what it teaches through initiatives around campus.

Lean looks at ways to reduce waste and improve flow. The principles are relevant to virtually every organizational sector and vertical. It’s no surprise, then, that so many organizations tout lean and devote resources to lean initiatives.

Understanding the causes of faults and defects, and then improving the system or process so it won’t happen again, is central to lean manufacturing.

‘Lean” is such a convenient term; everyone uses it based on their own definition. People frequently use “lean” in place of “efficiency,” probably because it sounds more cool. Another round of cost cutting? Sure, let’s tell everyone we’re “going lean,” again.

The Automotive Industry Action Group’s (AIAG’s) and German Association of the Automotive Industry’s (VDA’s) new Failure Mode and Effects Analysis Handbook (AIA

‘I have been offered a significant increase in salary by another employer and am giving my two-week notice.”