Californian ports join forces to push data flow between stakeholders
The five largest ports in California have teamed up to open data silos to enable ...
GM: RAISING THE ROOF GGM: IN FULL THROTTLE GZIM: MAERSK BOOST KNIN: READ-ACROSSMAERSK: NOT ENOUGHMAERSK: GUIDANCE UPGRADEZIM: ROLLERCOASTERCAT: HEAVY DUTYMAERSK: CATCHING UP PG: DESTOCKING PATTERNSPG: HEALTH CHECKWTC: THE FALLGXO: DEFENSIVE FWRD: RALLYING ON TAKEOVER TALKODFL: STEADY YIELDVW: NEW MODEL NEEDEDWTC: TAKING PROFIT
GM: RAISING THE ROOF GGM: IN FULL THROTTLE GZIM: MAERSK BOOST KNIN: READ-ACROSSMAERSK: NOT ENOUGHMAERSK: GUIDANCE UPGRADEZIM: ROLLERCOASTERCAT: HEAVY DUTYMAERSK: CATCHING UP PG: DESTOCKING PATTERNSPG: HEALTH CHECKWTC: THE FALLGXO: DEFENSIVE FWRD: RALLYING ON TAKEOVER TALKODFL: STEADY YIELDVW: NEW MODEL NEEDEDWTC: TAKING PROFIT
Inevitably we are going to writing more and more about Big Data this year. It is, so the saying goes, gaining traction. And rightly so, because while many supply chain managers – and the boards they report to – might find themselves bemused and befuddled by the pace of change in today’s society, much of it propelled by the super-speed connectivity of today’s society, Big Data represents a chance to make sense of those changes, almost as they are happening. “Advanced algorithms and machine learning can facilitate increased forecast accuracy across a company’s SKUs, which drives greater turns, less waste, less inventory, and fewer stock-outs, which leads to higher EBITDA, lower working capital, and greater competitiveness.”
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