Robin Lamerson

SUPPLY CHAINS TODAY are awash in data and technology: artificial intelligence (AI), advanced analytics, automation platforms and cloud systems promise greater visibility, responsiveness and efficiency than ever before. Yet for all the dollars flowing into these digital tools, companies are struggling to unlock their full value because workforce capabilities lag behind technological adoption.

THE U.S. ECONOMY is facing two conflicting dynamics with a rare coexistence of momentum and uncertainty. Gross domestic product (GDP) growth has been much better than many expected, and the U.S. labor market remains relatively tight. Meanwhile, U.S. inflationary pressures have eased meaningfully, although year-on‑year rates remain above the Fed’s 2% target.

THERE IS NO doubt about it, the dawn of the artificial intelligence (AI) age is no longer approaching. It has arrived—in full force. As a result, end users must understand how predictive analytics and digital twins are influencing fundamental, traditional reliability practices. After all, they’re jointly strengthening reliability practices throughout the entire material handling industry. How so?