Where is supply chain software headed?

This is an excerpt of the original article. It was written for the September-October 2018 edition of Supply Chain Management Review. The full article is available to current subscribers.

September-October 2018

If it’s September, it must be time for Gartner’sTop 25 supply chains, the lead article in this issue of Supply Chain Management Review. As I was reading this year’s contribution from Gartner, I was struck by the number of the Top 25 that have launched NextGen Supply Chain initiatives, using Big Data, artificial intelligence (AI), robotic process automation (RPA), machine learning and the like to digitize their supply chains. It made me wonder: Is the rest of the pack falling behind or are they ready to follow the leaders?

Browse this issue archive.

Already a subscriber? Access full edition now.

Need Help?

Contact customer service

847-559-7581   More options

Not a subscriber? Start your magazine subscription.

Real-world advances in machine learning, deep learning and artificial intelligence (AI) are bridging the gap between fact and fiction in the supply chain—a place where science fiction is literally coming to life to help companies work smarter, more efficiently and more economically.

From autonomous robots that work on the dock to drones that manage yard inventory to sensors that track shipment condition during transport, supply chain technology is proliferating on two fronts: the equipment itself and the advanced software that runs the equipment.

Using AI, or the theory and development of computer systems that can perform tasks that normally require human intelligence, for example, machines can think about—and solve—problems at the individual item level and store level. This presents clear advantages for companies struggling under the current labor market constraints and the ongoing need to scale up and meet customer demand.

“Companies can’t just increase their workforces by 100% in this environment; it’s not economically feasible,” says Puneet Saxena, JDA’s GVP of product strategy, supply chain planning. Add AI and machine learning (the science of getting computers to act without being explicitly programmed to do so) to the mix, however, and software developers gain the power of being able to model supply chain problems in more granular detail.

SC
MR