Levi Strauss & Co. is an American clothing company known worldwide for its Levi’s brand of denim jeans. They have over 500 stores, and their products are available in 110 countries around the world. Due to lack of visibility into the demand at SKU level, products are moved from one distribution centre to the other. Consequently, increasing the transit costs.
Levis Strauss & Co. was looking for a pilot partner in ML/Ai to drive increased operational efficiency that leads to profitable growth.
Pluto7 has been working with Levi Strauss & Co. to solve many of their Supply Chain problems with ML solutions. We started our journey with Levi’s to solve their problem which was to predict the optimal number of SKUs that needed to fit in a carton. With our experience of obtaining high forecast accuracies for other enterprises using machine learning, Pluto7 team leveraged Google Cloud Platform, Demand ML and Inventory ML set of solution components to help the Levi’s ’s team see the benefits of the same.
Pluto7 is a solution company focused on leveraging the power of Google Cloud (GCP) technology to drive innovation across the Supply chain industry. With our Data and Analytics award-winning depth in Google Cloud combined with ML Specialization and domain we provide unique innovative services and solutions.
Levi’s introduces thousands of products every season including a wide range of styles and sizes. With this wide range of products it is important to know folded dimensions so that operations like packaging, transportations and others can be optimised. The first challenge came in with the large number of vendors to get the accurate dimensions from them and update the current system to make it consistent. This led Levis to explore Predictive analytics to predict the dimensions of the new products.
With our team of experts at Pluto7, we provided the customer with Logistics ML Solution that enabled the optimization of packaging. This helped Levis to reduce costs, eliminate errors and improved the prediction accuracy by 90% in 6 weeks.
The client was facing another challenge in forecasting product volumes. With multiple suppliers in Asia that provide multiple products till date Levis Strauss & Co could provide a rolling forecast to the carriers but their 3PLs were still unable to pre-book containers/air freight space with Levi Strauss & Co nominated service providers.
As Levis Strauss & Co had already explored the predictive analytics solutions they were interested in using a similar algorithm to forecast product volumes as opposed to a simple rolling forecast calculation. So, Pluto7 built a Machine Learning model prototype for each supplier using historical purchase order data. These models helped Levis Strauss & Co to plan for any remediation actions to be taken and forecast product volumes.
The accuracy of 90% was achieved in predicting the product dimensions in 6 weeks. The Pluto7 team was successful in eliminating errors for the upcoming products by providing accurate outputs to the vendors. Levis Strauss & Co in collaboration with Google Cloud and Pluto7 was able to plan for any remediation actions well to be taken well in advance.