Nice had three patents in big data during Q2 2024. Nice Ltd’s patent involves a workforce management system utilizing machine learning to calculate the approval probability of a time-off request from an agent. The system considers various factors such as staffing data, agent skills, pending time-off requests, and past time-off taken. The approval probability is then displayed on a graphical user interface for both the agent and manager to view. GlobalData’s report on Nice gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Nice had no grants in big data as a theme in Q2 2024.
Recent Patents
Application: System and method for providing probability of time-off getting approved (Patent ID: US20240169280A1)
The patent filed by Nice Ltd. describes a workforce management system that utilizes a trained machine learning model to assess and display the approval probability of time-off requests from agents. The system considers various factors such as staffing data, agent skills, pending requests, and past time-off history to calculate the approval probability. It then presents this information on a graphical user interface for both the agent and the manager to view. Additionally, the system can automatically approve time-off requests based on a predefined threshold probability, notifying the manager accordingly.
The workforce management system outlined in the patent claims leverages a trained machine learning model, specifically a tree-based model like a classification and regression tree (CART), to evaluate and predict the approval probability of time-off requests. It also allows for the consideration of alternate dates, automatic approval based on set criteria, and notification mechanisms for both agents and managers. By incorporating various data points and utilizing machine learning algorithms, the system aims to streamline the time-off request process, enhance decision-making, and improve overall workforce management efficiency.
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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.
