How Does Artificial Intelligence Impact the Supply Chain Environment?
It’s not a magic cure-all, but artificial intelligence has the power to impact every link in the consumer goods supply chain thanks to its ability to optimize data collection to increase visibility into operations, quicken decision making to proactively identify risks, and provide recommendations to head off challenges and seize new opportunities.
Gartner cites AI in supply chain as one of its major areas of opportunities for supply chain technology investments, expecting it to help drive decision making by leveraging human-like problem solving that’s augmented by real-world, adaptable data.
How artificial intelligence is used in supply chains
While adoption is not yet widespread, there are already multiple examples of artificial intelligence in supply chain management use cases.
Demand planning and inventory management: AI can help consumer goods companies improve their demand planning and inventory management by quickly integrating data from disparate sources in order to make decisions about the ideal amount of products to manufacture and ship, and then applying predictive analytics to forecast likely outcomes. In fact, 20% of grocers said adding AI/ML for demand forecasting was a top priority, according to the RIS News/Progressive Grocer Grocery Tech Trends Study.
Cross-Functional Collaboration: Food and beverage brand Danone used artificial intelligence to support its decision-making capabilities and improve collaboration between its commercial, operational, and finance teams. Farzana Allegacone, VP of technology and data for design to delivery, said that rising consumer demand paired with supply chain disruption created a need to digitalize the company’s end-to-end supply chain planning platform so that all stakeholders could collaborate in real-time.
This technology was designed to not only let Danone run its planning processes across every function and time horizon on the integrated platform, but also perform real-time scenario planning to shorten decision-making timelines.
Customer Service: Whether their customers are their retail partners or consumers, artificial intelligence in the form of chatbots can be used to efficiently manage inquiries and resolve problems. By resolving issues quickly before they escalate to a point of no return, consumer goods companies can preserve these crucial customer relationships, maintain brand value, and even generate loyalty.
Sustainability: By improving visibility into operations, consumer goods companies can better manage and optimize their resources. For example, Nestle is leveraging artificial intelligence across its supply chain to reduce its energy and water consumption, as well as improve transportation. Investing in digitally-enabled control towers, which manage more than 16,000 trucks daily, has improved cost efficiency, resilience, and responsiveness.
How can AI be applied to supply chain activities?
The applications of artificial intelligence in logistics and supply chain are wide and varied, with the future of AI in supply chain promising. Kraft Heinz, for example, has developed a supply chain control tower that’s designed to provide real-time visibility into plant operations and automation of its supply chain distribution across its product categories.
As part of this, it’s creating digital twins for nearly three dozen manufacturing facilities in North America. This enables it to test and refine solutions and processes, including by identifying optimal product capacity and proactively addressing issues to reduce mechanical downtime.
What is an example of artificial intelligence in transportation?
Kimberly-Clark leveraged an AI-enabled tool to automate its distribution planning and deployment process, as well as improve scheduling, in order to reduce order bunching. The technology helped Kimberly-Clark connect disparate systems and make recommendations that the company can execute more efficiently.
With the integration, the consumer goods company also increased visibility into where it may have underutilized the cubic intensity of its trailers, enabling its customer service and distribution teams to take proactive measures.
The platform is now deployed across all Kimberly-Clark North American operations. As a result of both the process improvements and new technology, the company reduced variability daily by 40%, particularly in locations where production plants are shipping to its distribution centers. This substantially improved on-time delivery and customer service performance, and reduced North American distribution costs by several million dollars, according to DeGroot.
How AI can make supply chains more sustainable
Artificial intelligence can help supply chains be more sustainable by enabling companies to reduce the amount of unnecessary inventory that they produce. By obtaining a better understanding of the number of products they are likely to sell at retail, as well as being proactive about the ideal places to source the raw materials required to develop them, manufacturers are less likely to produce products that end up in landfills.
Reducing unnecessary inventory not only decreases the number of unwanted products, but it also lessens the amount of harmful emissions that are created during their manufacturing and transport.