A system and method for determining market share of an organization. The method encompasses receiving, at least one of a voice of customer data, an internal data of the organization and an external data. The method thereafter leads to determining, one or more set of target features based on at least one of the voice of customer data, the internal data of the organization and the external data. Further the method comprises generating, one or more pre-trained dataset based at least on the one or more set of target features. The method thereafter encompasses receiving, at least one of a first set of feature constraints and a second set of feature constraints. Further the method comprises determining, the market share of the organization based at least on the one or more pre-trained dataset, the first set of feature constraints and the second set of feature constraints.

A system and method for managing virtual queues. A cloud-based queue service manages a plurality of queues hosted by one or more entities. The queue service is in constant communication with the entities providing queue management, queue analysis, and queue recommendations. The queue service is likewise in direct communication with queued persons. Sending periodic updates while also motivating and incentivizing punctuality and minimizing wait times based on predictive analysis. The predictive analysis uses “Big Data” and other available data resources, for which the predictions assist in the balancing of persons across multiple queues for the same event or multiple persons across a sequence of queues for sequential events.

A computer-implemented method, computer program product and computing system for receiving a complex task; processing the complex task to define a plurality of discrete tasks each having a discrete goal; executing the plurality of discrete tasks on a plurality of machine-accessible public computing platforms; determining if any of the plurality of discrete tasks failed to achieve its discrete goal; and if a specific discrete task failed to achieve its discrete goal, defining a substitute discrete task having a substitute discrete goal.

To provide an action evaluation system capable of more efficiently planning a new action based on an execution result of a test for limited action conditions. A condition change tracking unit determines, based on execution result information obtained by executing a test related to an action for an action target having a predetermined action condition, a condition change which is a change in the action condition before and after the test. A result verification unit calculates, based on the execution result information, an evaluation value obtained by evaluating an effect of the action. A reward distribution unit calculates a change contribution degree which is a degree of contribution of the condition change to the evaluation value.

Methods, systems, and computer programs are presented for estimating downtime and recovery time after a disaster. One method includes an operation for calculating component fragility functions for components of a facility that are vulnerable to damage after a disaster. Further, the method includes calculating component recovery functions for the components of the facility. The component recovery functions indicate a probability of recovery after a disaster over time. The method further includes operations for calculating a facility fragility function and a facility recovery function based on the component fragility functions and the component recovery functions, and for determining a downtime for the facility for a given intensity associated with the disaster. Further, the method includes an operation for causing presentation of the downtime for the facility on a user interface (UI).

A business plan generation device including a business plan definition unit configured to define a first business plan for a first business and a set of target business outcomes, a business information acquisition unit configured to acquire a set of business state information that includes at least a set of internal business information or a set of competitor business information, and a business plan generation unit configured to use a machine learning model to generate a set of output data that includes at least a set of revised business plans for achieving the set of target business outcomes, and output the set of output data.

Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. A server retrieves a set of nodes and generates a primary prediction model using data aggregated based on all nodes. The server then executes various clustering algorithms in order to segment the nodes into different clusters. The server then generates a secondary (corrective) prediction model to calculate a correction needed to improve the results achieved by executing the primary prediction model for each cluster. When a node with unknown/limited data and attributes is identified, the server identifies a cluster most similar the new node and further identifies a corresponding secondary prediction model. The server then executes the primary prediction model in conjunction with the identified secondary prediction model to populate a graphical user interface with an accurate predicted future attribute for the new node.

An example method includes obtaining data associated with a plurality of process workflows, performing an automated workflow analysis of the data at least by (i) evaluating workflow structures to identify at least one similarity between one or more portions of the process workflows, wherein the workflow structures are modeled from the process workflow data and, (ii) responsive to evaluating the workflow structures, clustering, based on the at least one similarity, the portions of the process workflows into at least one common process group that is shared between the process workflows, identifying, based on the at least one common process group shared between the process workflows, at least one process improvement that is associated with at least one of the process workflows, and outputting, by the computing system, a recommendation associated with the at least one process improvement.

An apparatus, method and computer program is described comprising: receiving interaction information via at least one user device, wherein the interaction information is related to at least one user using at least one user device in relation to a first content creation task; receiving sensor data relating to the at least one user from one or more sensors; and determining data, using a first model, the data comprising content creation performance data and user state data, wherein: the content creation performance data indicates performance of the at least one user in relation to the first content creation task, based, at least in part, on the interaction information and a first content created when the at least one user performs the first content creation task; and the user state data is based, at least in part, on the received sensor data in relation to the first content creation task.

Project modeling is conducted using variable defect arrival rate or variable defect rate density parameters. These defect rates may be updated on an iteration by iteration basis and may be used to provide remediation and further project modeling, remediation, and prediction.