Kimberly-Clark is focused on optimizing its supply chain for its well-known products such as Kleenex, Cottonelle and Huggies. With 45,000 employees and more than $20 billion in annual revenues, the company is actively working to improve, digitize and optimize its North American distribution network. It ships between 1,100 and 1,500 trucks daily, 55% to 60% of which go directly to customers, while the remainder is used to maintain inventories at production sites and off-site.
In this post-pandemic context, the company is focused on improving product availability and restoring margins. According to Scott DeGroot, vice president of global planning and logistics, “Availability drives revenue and growth,” while the second objective seeks to avoid unnecessary expenses in fulfillment, logistics and distribution.
In the evaluation of its logistics operations, the company identified the accumulation of orders during the week, generating delays in fulfillment, especially from Monday to Wednesday. “That order-bunching was causing us to delay some shipments, and it was also forcing us to pay more money than we needed to in terms of our DC picking labor—and especially in transport,” says DeGroot.
The company has successfully implemented LevelLoad, a cloud-based application designed to optimize transportation planning. This tool using machine learning and optimization algorithms has been shown to reduce daily variability by 40%, improve on-time deliveries and save millions of dollars in transportation costs during the pilot phase.
Scott DeGroot, vice president of global planning and logistics, highlights LevelLoad’s speed and efficiency, driven by machine learning and optimization algorithms. The platform bridged the gap between supply planning and execution, improving Transportation Management Systems (TMS) and balancing cost and site capabilities to meet customer service objectives.
This move toward logistics optimization is part of the company’s efforts to digitize its supply chain and boost its performance on a global scale. There is an expressed interest in the application of artificial intelligence for inbound freight management, as well as in the future expansion of the LevelLoad methodology to production programs. The successful implementation of LevelLoad underscores the relevance of prioritizing business processes and the search for specific technology solutions to address logistical challenges.