Edge computing. Edge computing allows Internet of Things (IoT) devices to act on data in near real time by processing it at the “edge” of a company’s network. Processing data through edge computing is faster than using the cloud. As more enterprises use IoT endpoint devices within many supply chain functions, they can use edge machine learning to process large “exhaust data”— the data left by users during online activity, both unstructured and structured. This can support near real-time supply chain optimization. SUSTAINABILITY TECH Operating more sustainably often improves a supply chain’s nancial
performance, as well as its impact on the environment. Shared truckload technology. A large cost for most supply chain organizations is transportation. Boosting transportation ef ciency often cuts costs and emissions. Yet given increasing pressure to ship goods on-time and damage- free, businesses often reserve entire trucks, regardless of whether they have enough pallets to ll them, explains Lu Saenz, chief technology of cer with Flock Freight. The company’s shared truckload technology uses arti cial intelligence and probabilistic pricing engines to keep trucks full by connecting shippers whose
FASTER COMPUTING As supply chains become increasingly digital and collect massive volumes of data, speedy computing becomes critical. Quantum computing. Quantum computers can handle problems that require calculating a large number of possible combinations. Organizations can use quantum computing to optimize supply chain network design, including determining the optimal number and location of DCs, and retail outlets. “This involves solving large-scale mixed-integer linear programming problems, which can be computationally intensive,” Wright says. Quantum computing speeds the process and enables more accurate and ef cient network designs.
SUPPLY CHAIN TECH ON THE SILVER SCREEN
These technologies will see their name in lights in supply chain management during the next five years, say industry insiders. Using tech tools to analyze and derive actionable insights from supply chain data will become industry-standard best practices, allowing logistics managers to monitor performance and optimize for quality and financial success. –Elizabeth Goulding, Director, CTM Operations, Coyote Logistics In the next five years, we will see a massive influx of automation into all aspects of the supply chain, as well as a greater understanding and use of data by supply chain and logistics companies. Automation will be realized in areas such as picking and placing, loading or unloading a pallet, and more. In addition, logistics and supply chain organizations will be able to use the wealth of data they have to better track industry trends and be able to predict supply and demand, limiting future disruptions. The combination of automation and data-based decision- making will transform the industry. –Matt Somerville, Director of Sales, North America, Realtime Robotics Retailers must be better prepared to pivot when abrupt changes in demand and consumption occur. Implementing AI- based technology that drives eciency and agility—overcoming just-in-time fulfillment limitations—allows retailers to build resilience across the supply chain and all channels while presenting the opportunity to improve sustainability footprints. -Troy Prothero, SVP, Product Management - Supply Chain Solutions, SymphonyAI Retail CPG We’re moving toward a world run by platforms. Data and visibility are now table stakes. Automated decision making is what’s next. –Daniel Sokolovsky, CEO and Co-Founder, WARP
52 Inbound Logistics • April 2023
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