Following the globalization of Big Data and the phenomenal impact of intelligent computing on logistics, traditional solutions have taken a huge step forward in terms of decision support and visibility. Self-optimizing networks dedicated to real-time visibility and forecasting are taking supply-chain management to the next level, transforming the way B2B companies conceive their strategy.
Data analysis is key for supply chain management optimization. By processing and sorting through the sheer volume of data in circulation, AI is now giving businesses an opportunity to capitalize on this invaluable, yet, under-exploited source of information.
AI and big data are pushing the boundaries set by human intelligence in terms of data management and analysis. By browsing big data and filtering through continuous streams of information, algorithms are now able to find correlating factors and detect patterns, thus providing supply chain managers with tangible information to rethink their supply chain around targeted areas of improvement such as schedule or itinerary.
“This information helps assess the probability of a carrier canceling its booking, or measures how weather influences schedules, which help streamline and automate every Supply Chain process.” McKinsey recently revealed that early adopters with an AI strategy in the transportation and logistics sector enjoyed profit margins greater than 5%.” Says Lucien Besse, COO and co-founder of Shippeo
The ever-growing range of variables built into these self-optimizing models is allowing real-time visibility providers to deliver increasingly accurate predictive analysis but also targeted performance reviews. By using API’s to collect and incorporate data from external analytics systems into their previsions, they are now also making it possible for decision makers to take into consideration risk-factors (weather, terrain, traffic), thereby reducing delays and preventing human and material damage.
ETA calculation and multi-resource scheduling are two other major areas of development for supply chain optimization.
By gathering, aggregating and processing data collected from WMS, TMS or IoT, real time visibility providers can now track vehicles with utmost precision and deliver increasingly accurate estimated times of arrival (ETA) on shipments.
In addition, ‘smart scheduling’ is rethinking the way deliveries and pickups are scheduled in order to optimize transportation flows and the overall productivity of the supply chain. By tracking shipments and estimating their time of arrival on site, yard managers can manage dock allocation with accuracy and warehouse managers can articulate their day around due times of delivery.
Predictive visibility and smart scheduling in distribution are giving logisticians new tools to streamline and securize their entire supply-chain process, thereby cutting down on costs and smartening up their operations.
AI is also reshaping the way we work, boosting productivity by assessing priorities as well as handling most repetitive, tedious, low-yield tasks, allowing employees to focus their energy on research and development. This is a determining factor for innovation-driven fields.
AI is revolutionizing the way we build and operate supply chains, paving the way for a fully automated supply network. it has proven to be an invaluable tool for businesses to gain in agility, enhance the efficiency of their collaborative network and improve their overall performance and margins.
How has AI transformed your strategy ?
Learn about the 5 main objectives that lead market-leading companies to adopt a supply chain visibility solution.
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