Abstract: The present application includes a method and system for real-time predictive scheduling. The system receives information from at least one workload input and at least one personnel input, calculating an initial schedule based on the information and on analytics rules in a scheduling analytics engine. The system then allocates incoming workloads to customer service representatives according to the initial schedule, while monitoring adherence to the initial schedule by calculating deviation from schedule adherence. If the deviation from schedule adherence exceeds an acceptable deviation from schedule adherence within the analytics rules, the system calculates an updated schedule.

Abstract: The present application includes a method and system for real-time predictive scheduling. The system receives information from at least one workload input and at least one personnel input, calculating an initial schedule based on the information and on analytics rules in a scheduling analytics engine. The system then allocates incoming workloads to customer service representatives according to the initial schedule, while monitoring adherence to the initial schedule by calculating deviation from schedule adherence. If the deviation from schedule adherence exceeds an acceptable deviation from schedule adherence within the analytics rules, the system calculates an updated schedule.

Abstract: The present application includes a method and system for real-time scheduling reallocation. The system receives a schedule which allocates customer service representatives (CSRs) to channels and queues based on analytics rules as well as the forecast work patterns and information on CSR skills and shift patterns. The system then monitors adherence to the schedule by comparing the difference between forecast and current volume and type of work to a reallocation threshold at predetermined intervals. If the difference extends beyond the reallocation threshold, the system reallocates CSRs to update the schedule.

Abstract: The present application includes a method and system for real-time predictive scheduling. The system receives information from at least one workload input and at least one personnel input, calculating an initial schedule based on the information and on analytics rules in a scheduling analytics engine. The system then allocates incoming workloads to customer service representatives according to the initial schedule, while monitoring adherence to the initial schedule by calculating deviation from schedule adherence. If the deviation from schedule adherence exceeds an acceptable deviation from schedule adherence within the analytics rules, the system calculates an updated schedule.

Abstract: The present invention is a system and method for projective channel hopping within a customer engagement center (CEC) system. The CEC system receives a customer through a system entry point and receives, from the customer, a communication in a current customer service representative (CSR) channel in the CEC system. The CEC system assesses its ability to connect the customer with a CSR on the current CSR channel using a smart routing engine (SRE), which also assesses its current ability to connect the customer with a CSR on other equivalent CSR channels. Using the SRE, the CEC system compares its ability to connect the customer with a CSR on current and equivalent CSR channels to determine if the customer should remain on their current CSR channel or transfer to a new one. In the latter case, the CEC system offers the customer a chance to change channels or remain on their current channel.

Abstract: The present invention allows a user to review the routing of various communications. The system receives incoming communications for analysis by a smart routing engine (SRE) software module. The SRE module analyzes the communication at various system routing points, which is used by SRE to route the communication to an appropriate party. The SRE updates a routing log at each point to ensure a record of the reasons for routing the communication in a certain way. The routing log passes with the communication. This ensures that the ultimate recipient of the communication understands why they have received the communication and reduces the time required for a communication to be acted upon.

Abstract: An exemplary embodiment of the present application is a system and method for work allocation optimization. In the present disclosure, analytics are applied to work items while the work items are waiting in a work queue in order to optimize the routing and allocation of work items to agents in the most efficient manner possible, while optimizing the utilization of agents. By performing a look ahead at more than the initial work item, the system assesses the agent skills required by imminent work items in the work queue. This is then compared to a skillset of each available and/or soon to be available agent in order to achieve the optimal allocation of the work items to maximize utilization of agents. The work items are then routed to the agents accordingly.

Abstract: In the present disclosure, analytics are applied to work items while the work items are waiting in a work queue in order to optimize the routing and allocation of work items to agents in the most efficient manner possible, while optimizing agents being assigned to work items they are most qualified to handle. By performing a look ahead at more than the initial work item, the system assesses the agent skills required by imminent work items in the work queue. This is then compared to a skillset of each available and/or soon to be available agent in order to achieve the optimal allocation of the work items to maximize the work item being assigned the best qualified agent. The work items are then routed to the agents accordingly.

Abstract: The present invention allows a user to review the routing of various communications. The system receives incoming communications for analysis by a smart routing engine (SRE) software module. The SRE module analyzes the communication at various system routing points, which is used by SRE to route the communication to an appropriate party. The SRE updates a routing log at each point to ensure a record of the reasons for routing the communication in a certain way. The routing log passes with the communication. This ensures that the ultimate recipient of the communication understands why they have received the communication and reduces the time required for a communication to be acted upon.

Abstract: The present invention allows text analysis and routing of written communications. The system intercepts incoming written communications for analysis by a text analytics service (TAS) software module. The TAS module analyzes the communication to generate communication metadata, which is used by a smart routing engine to route the communication to an appropriate party. This ensures that the ultimate recipient of the communication is capable of effective interaction with the sender and reduces the time required for a communication to be acted upon.

Abstract: The present invention allows a user to review the routing of various communications. The system receives incoming communications for analysis by a smart routing engine (SRE) software module. The SRE module analyzes the communication at various system routing points, which is used by SRE to route the communication to an appropriate party. The SRE updates a routing log at each point to ensure a record of the reasons for routing the communication in a certain way. The routing log passes with the communication. This ensures that the ultimate recipient of the communication understands why they have received the communication and reduces the time required for a communication to be acted upon.

Abstract: The present invention is a system and method for projective channel hopping within a customer engagement center (CEC) system. The CEC system receives a customer through a system entry point and receives, from the customer, a communication in a current customer service representative (CSR) channel in the CEC system. The CEC system assesses its ability to connect the customer with a CSR on the current CSR channel using a smart routing engine (SRE), which also assesses its current ability to connect the customer with a CSR on other equivalent CSR channels. Using the SRE, the CEC system compares its ability to connect the customer with a CSR on current and equivalent CSR channels to determine if the customer should remain on their current CSR channel or transfer to a new one. In the latter case, the CEC system offers the customer a chance to change channels or remain on their current channel.

Abstract: The present invention is a system and method for projective channel hopping within a customer engagement center (CEC) system. The CEC system receives a customer through a system entry point and receives, from the customer, a communication in a current customer service representative (CSR) channel in the CEC system. The CEC system assesses its ability to connect the customer with a CSR on the current CSR channel using a smart routing engine (SRE), which also assesses its current ability to connect the customer with a CSR on other equivalent CSR channels. Using the SRE, the CEC system compares its ability to connect the customer with a CSR on current and equivalent CSR channels to determine if the customer should remain on their current CSR channel or transfer to a new one. In the latter case, the CEC system offers the customer a chance to change channels or remain on their current channel.

Abstract: An exemplary embodiment of the present application is a system and method for work allocation optimization. In the present disclosure, analytics are applied to work items while the work items are waiting in a work queue in order to optimize the routing and allocation of work items to agents in the most efficient manner possible, while optimizing the utilization of agents. By performing a look ahead at more than the initial work item, the system assesses the agent skills required by imminent work items in the work queue. This is then compared to a skillset of each available and/or soon to be available agent in order to achieve the optimal allocation of the work items to maximize utilization of agents. The work items are then routed to the agents accordingly.

Abstract: In the present disclosure, analytics are applied to work items while the work items are waiting in a work queue in order to optimize the routing and allocation of work items to agents in the most efficient manner possible, while optimizing agents being assigned to work items they are most qualified to handle. By performing a look ahead at more than the initial work item, the system assesses the agent skills required by imminent work items in the work queue. This is then compared to a skillset of each available and/or soon to be available agent in order to achieve the optimal allocation of the work items to maximize the work item being assigned the best qualified agent. The work items are then routed to the agents accordingly.

Abstract: The present application includes a method and system for real-time scheduling reallocation. The system receives a schedule which allocates customer service representatives (CSRs) to channels and queues based on analytics rules as well as the forecast work patterns and information on CSR skills and shift patterns. The system then monitors adherence to the schedule by comparing the difference between forecast and current volume and type of work to a reallocation threshold at predetermined intervals. If the difference extends beyond the reallocation threshold, the system reallocates CSRs to update the schedule.

Abstract: The present invention is a system and method for projective channel hopping within a customer engagement center (CEC) system. The CEC system receives a customer through a system entry point and receives, from the customer, a communication in a current customer service representative (CSR) channel in the CEC system. The CEC system assesses its ability to connect the customer with a CSR on the current CSR channel using a smart routing engine (SRE), which also assesses its current ability to connect the customer with a CSR on other equivalent CSR channels. Using the SRE, the CEC system compares its ability to connect the customer with a CSR on current and equivalent CSR channels to determine if the customer should remain on their current CSR channel or transfer to a new one. In the latter case, the CEC system offers the customer a chance to change channels or remain on their current channel.

Abstract: The present application includes a method and system for real-time predictive scheduling. The system receives information from at least one workload input and at least one personnel input, calculating an initial schedule based on the information and on analytics rules in a scheduling analytics engine. The system then allocates incoming workloads to customer service representatives according to the initial schedule, while monitoring adherence to the initial schedule by calculating deviation from schedule adherence. If the deviation from schedule adherence exceeds an acceptable deviation from schedule adherence within the analytics rules, the system calculates an updated schedule.

Abstract: The present invention allows a user to review the routing of various communications. The system receives incoming communications for analysis by a smart routing engine (SRE) software module. The SRE module analyzes the communication at various system routing points, which is used by SRE to route the communication to an appropriate party. The SRE updates a routing log at each point to ensure a record of the reasons for routing the communication in a certain way. The routing log passes with the communication. This ensures that the ultimate recipient of the communication understands why they have received the communication and reduces the time required for a communication to be acted upon.

Abstract: The present invention allows text analysis and routing of written communications. The system intercepts incoming written communications for analysis by a text analytics service (TAS) software module. The TAS module analyzes the communication to generate communication metadata, which is used by a smart routing engine to route the communication to an appropriate party. This ensures that the ultimate recipient of the communication is capable of effective interaction with the sender and reduces the time required for a communication to be acted upon.