Four Ways Leaders Can Gain Value From AI and Advanced Analytics
Companies and societies are at the precipice of rebuilding their foundations to compete in an age of advanced analytics, artificial intelligence (AI), and machine learning (ML).
Companies and societies are at the precipice of rebuilding their foundations to compete in an age of advanced analytics, artificial intelligence (AI), and machine learning (ML).
As the skills gap widens and more employees retire, decades of experience and company investment is predicted to walk out the door.
The Manufacturing Institute estimated that 2.4 million job openings in manufacturing—accounting for half of all open positions—will go unfilled between 2018 and 2028 as a direct consequence of the skills gap. This isn’t a future problem.
In a recent article I discussed the traditional 5S audit, shared a set of reservations, and offered some remedies—“The Five Tweaks,” as I called them.
A large portion of a digital project manager’s job is making sure the right parts of the project are being worked on. Projects need to be prioritized. Tasks within projects need to be prioritized, too.
Credit: Orlando Imperatore
Each article in this series presents new tools for increasing return on investment (ROI), enhancing customer satisfaction, creating process excellence, and driving risk from an ISO 9001:2015-based quality management system (QMS).
For those in the manufacturing and industrial sector, what’s commonly known as the skills gap is a well-documented issue.
When the definition of power includes the “ability to exert influence,” then you’re also describing an element of leadership: knowledge. Take, for example, Ann Landers.
If you’re a medical device company manufacturing Class II or Class III devices, you can expect to have the U.S. Food and Drug Administration (FDA) turning up for an inspection. It’s what happens after that inspection that we’re concerned with in this article.
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