Kinaxis has developed a dynamic supply chain planning system that utilizes machine learning algorithms to analyze historical lead time data, weather data, and financial data to forecast future lead times. The system automatically adjusts planned lead times for future purchase orders based on the analysis. GlobalData’s report on Kinaxis gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Kinaxis, Predictive modeling techniques was a key innovation area identified from patents. Kinaxis's grant share as of January 2024 was 20%. Grant share is based on the ratio of number of grants to total number of patents.
Dynamic supply chain planning system using machine learning for lead times
A recently granted patent (Publication Number: US11887044B2) outlines a computer-implemented method for supply chain planning that involves receiving historical lead time data, extracting source and destination locations, and shipment dates, as well as weather and economic indicators data. The method includes generating processed data, constructing a time series, and clustering the data using a machine learning algorithm. The system further allows for the adjustment of planned lead times for future purchase orders based on the clustered data.
The patent also describes a system and a non-transitory computer-readable storage medium that implement the method outlined in the claims. These systems involve receiving and processing historical lead time data, weather data, and economic indicators data to generate a time series and a set of features associated with it. The systems then cluster the data, separate it into tolerance zones, and adjust planned lead times for future purchase orders accordingly. The method also includes features related to linearity and seasonality, as well as the ability to prune clusters and divide them into subclusters for more detailed analysis and planning. Overall, the patent presents a comprehensive approach to supply chain planning using historical data, weather information, and economic indicators to optimize lead times and improve decision-making processes in the supply chain industry.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
