Abstract: The disclosed system and method focus on applying machine learning to monitor, analyze, and optimize operational procedures. A role-tailored user interaction with a dashboard that enables a user with multiplicity of views, including but not limited to operational data feeds, analytic and visualization feeds, supervisory, policy making, personnel management and other organizational capabilities is disclosed. The multiplicity of dashboard features relates to measurement and assessment of an organization's compliance with operational performance metrics, that are quantified based on real-time, near real-time data feeds, statistical and algorithmic models. The metrics on the dashboard may be presented in the role-tailored fashion with statistical view of the next best action and recommendations when analyzed metrics exceed safe limits. Alert and communication features may be implemented in the dashboard to promote timely response to suggested corrective actions across the organization.

Abstract: A device may determine a set of trip attributes, associated with a driving trip, based on at least two of: location data associated with the driving trip, geospatial data associated with the driving trip, or weather data associated with the driving trip. The device may derive a set of driving style variables, associated with a manner in which the vehicle is driven during the driving trip, based on at least two of: the location data, the geospatial data, the weather data, acceleration data associated with the driving trip, or a location-based variable derived from the location data. The device may generate a trip risk score, associated with the driving trip and based on the set of trip attributes and the set of driving style variables, that includes a metric indicating a level of risk associated with the driving trip. The device may provide information associated with the trip risk score.

Abstract: Systems and methods for predicting and preventing returns using transformative data-driven analytics and machine learning is provided. The systems and methods may include data stores to store and manage data within a network, as well as servers to facilitate operations using information from the one or more data stores. The systems and methods may also include an analytics subsystem having a data access interface to: receive data associated with a plurality of customers; and receive data associated with a plurality of transactions associated with the plurality of customers, where the plurality of transactions are transactions comprising at least a purchase, return, an exchange, or refund of an item.

Abstract: A device may determine a set of trip attributes, associated with a driving trip, based on at least two of: location data associated with the driving trip, geospatial data associated with the driving trip, or weather data associated with the driving trip. The device may derive a set of driving style variables, associated with a manner in which the vehicle is driven during the driving trip, based on at least two of: the location data, the geospatial data, the weather data, acceleration data associated with the driving trip, or a location-based variable derived from the location data. The device may generate a trip risk score, associated with the driving trip and based on the set of trip attributes and the set of driving style variables, that includes a metric indicating a level of risk associated with the driving trip. The device may provide information associated with the trip risk score.