Patent Description:
In a modern high-volume customer engagement center(s) (CEC) work allocation is typically subject to routing and queueing rules. This allocation method can often lead to a mix of different work being routed to one department, and queued in that department on a simplistic chronological manner based on arrival time and any relevant service level agreements (SLAs).

This simplistic method of work allocation within a department can lead to inefficiencies because a next available agent method of work allocation blindly allocates the next available agent. Oftentimes, the next available agent may not have an appropriate skillset to handle the next work item appropriately. In other instances, the next available agent may be overqualified to handle the work item assigned whereas the agent after that may then not be assigned a work item because they are underqualified for the remaining work items. The aforementioned inefficiencies typically result in the agent taking a larger amount of time to complete the work item, the work item requiring reallocation to another agent with the appropriate skillset, or a qualified agent being unavailable for an advanced work item because they have been assigned a work item requiring lesser skills.

It is known from the document <CIT> a method and system to select agents in a service center to service individual tasks based on agent skills required to service the tasks. A weight is calculated for each relevant skill according to its relative importance in the skill expression, based on which a set of agents qualified to service the task is derived.

Modern electronic scheduling programs are unable to provide such capabilities. As a result, customers may face inefficient handling of their communications, excessive wait times to speak with a customer service representative (CSR), and excessive transfers of their calls, leading to increased customer dissatisfaction, and CSRs will be handling calls not suited for their skill set, thus wasting an organization's money. Further, some work items may be assigned to agents lacking the skills to handle the work item, while others remain unassigned because the agents that are qualified to handle a complex work item get assigned to a work item they are overqualified to handle.

There is an unmet need in the art for a system and method capable of looking ahead into the work queue in order to optimize assignment of work items to agents such that agents are matched to the work item they are most qualified to handle.

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. The work items are then routed to the agents accordingly.

Accordingly, the present application overcomes the historical problems with other scheduling technology by optimizing the assignment of agents to work items they are most qualified to handle and thereby minimizing the routing of work items to agents not qualified to handle those work items, while at the same time minimizing tying up specialty agents with work items they are overqualified to handle.

An exemplary embodiment of the present application is a method for work allocation optimization. A work allocation engine (WAE) receives a work queue, which includes a set of work items, from the customer engagement center (CEC). The WAE also receives an agent list, which includes at least one agent, from the CEC. The WAE performs a work queue analysis of the work queue using a WAE software module on the WAE and generates an imminent work item list based on the work queue analysis. The WAE also performs an agent analysis of the work queue using the WAE software module on the WAE and generates an available agent list based on the agent analysis. The WAE passes the imminent work item list and the available agent list to a smart work allocator (SWA) and performs an optimization analysis of the first imminent work item based on the available agent list using a SWA software module on the SWA. The SWA determines a best match agent for the first imminent work item based on the optimization analysis of the first imminent work item. The SWA performs an optimization analysis of the best match agent based on the remaining imminent work items using a SWA software module on the SWA and determines a best match work item for the best match agent based on the optimization analysis of the best match agent. The SWA compares the first imminent work item and the best match work item to the best match agent and assigns one of the first imminent work item or the best match work item to the best match agent based on the comparison. The SWA updates the imminent work item list by removing the assigned work item and the available agent list by removing the best match agent.

Another exemplary embodiment of the present application is a system for work allocation optimization. The system includes a processor and a non-transitory computer readable medium programmed with computer readable code that upon execution by the processor causes the processor to execute the above-mentioned method for optimized work allocation.

Another exemplary embodiment of the present application is a non-transitory computer-readable medium programmed with computer-readable code that upon execution by a processor causes the processor to execute the above-mentioned method for work allocation optimization.

The objects and advantages will appear more fully from the following detailed description made in conjunction with the accompanying drawings.

In the present description, certain terms have been used for brevity, clearness and understanding. No unnecessary limitations are to be applied therefrom beyond the requirement of the prior art because such terms are used for descriptive purposes only and are intended to be broadly construed. The different systems and methods described herein may be used alone or in combination with other systems and methods.

Referring to <FIG> and <FIG>, CEC system <NUM> allows CSRs to engage with customers by ensuring agents <NUM> are allocated to work items <NUM> they are most qualified to handle while minimizing assigning agents <NUM> to work items <NUM> they are overqualified to handle. A number of benefits are realized by implementing such a system <NUM> and method <NUM>. First, the general efficiency of the CEC <NUM> is improved as routing work items <NUM> that have specific skill requirements from an imminent work queue <NUM> to properly qualified available agents <NUM> having optimized skillsets reduces the instances of rerouting, reduces the work time for any particular work item <NUM>, results generally in more efficient execution of the imminent work queue <NUM>, and minimizes the number of available agents <NUM> who are not assigned work items <NUM>. Second, by ensuring that available agents <NUM> with specialist skills are not prematurely matched with a work item <NUM> when another available agent <NUM> may be more appropriate for the work item <NUM> and it can be determined that the available agent <NUM> with specialized skills may be required for another work item <NUM> that is imminent but not immediate in the imminent work queue <NUM>, the throughput of the CEC <NUM> can be maximized. In other words, specialist work items <NUM> will not be delayed because specialist available agents <NUM> have been utilized to complete standard work items <NUM> (i.e. work items <NUM> with common skill requirements), while at the same time available agents <NUM> with common skills will not be left waiting for work because their skill sets are not sufficient for the remaining work items in the imminent work queue <NUM>.

By optimizing the decision to allocate work items <NUM> in the imminent work queue <NUM> to the most qualified available agent <NUM>, the CEC system <NUM> and method <NUM> avoids starving available specialized agents <NUM> of work items <NUM> by blindly holding them in reserve in anticipation of specialist work items <NUM> which may not even have entered the imminent work queue <NUM>. Further, by optimizing the decision to allocate work items <NUM> in the imminent work queue <NUM> to the most qualified available agent <NUM>, the CEC system <NUM> and method <NUM> avoids starving available common agents <NUM> of work items <NUM> by blindly assigning work items to specialized agents to the first work items <NUM> in the imminent work queue <NUM> when the remainder of the work items <NUM> in the imminent work queue <NUM> may not be suitable for the available common agents <NUM>.

<FIG> depicts an exemplary embodiment of CEC system <NUM> for work allocation optimization.

CEC system <NUM> includes a work acquisition engine (WAE) unit <NUM> having a WAE software module <NUM> and an optional WAS storage <NUM>. WAE unit <NUM> may be a processor or a combination of a processing system and a storage system. WAE unit <NUM> receives the work queue <NUM> and list of agents <NUM> from the CEC system.

The work queue <NUM> contains a set of work items with associated required skills <NUM>. Work items <NUM> are any task that needs to be routed to an agent in the CEC system for processing. For example, work items <NUM> may be a direct communication from a customer such as an email, text chat, phone call, letter, etc. Work items <NUM> may also be case work items such as a request for a skilled individual to perform a specific task as part of a multi-step case type. Work items <NUM> may be received from outside the CEC through any form that the CEC has available to receive incoming communications and requests, including audio communication such as a telephone call, a voice message, a video chat, or any other type of audio communication, written communication such as an email, an online posting, a direct message from a customer, or any other written communication. Work items <NUM> may also originate from inside the CEC. For instance, a manager may input a case work item into the CEC for processing or the CEC system may automatically generate work items based on certain conditions in the system being met. For example, in a CEC system where transactions occur, if a transaction occurs that is over a specified value, the system may automatically refer the transaction to the underwriting department or the fraud department and would autonomously generate a work item for the transaction. Each work item <NUM> has a set of required skills associated with the work item <NUM>. The required skills correlate to skills associated with an agent's abilities. For example, work item i may require a Spanish-speaking agent, whereas work item i+<NUM> may require an English-speaking agent with skills in returns. The required skills associated with a work item <NUM> may be an unordered listing of the necessary skills. In other embodiments, the required skills associate with the work item <NUM> may be an ordered list with the most essential/important skill listed first and the least essential/important skill listed last. In other embodiments, the required skills associated with the work item <NUM> may be labeled as mandatory or optional. In other embodiments, the required skills may be grouped by level of importance such as primary skills, secondary skills, tertiary skills, etc. It should be understood that the number of work items <NUM> in the work queue <NUM> may continually change and the system will dynamically adjust to include all waiting work items in the work queue <NUM> when received by the WAE <NUM>.

The list of agents <NUM> contains the customer service representatives (CSR) for the CEC system. In some embodiments, the list of agents <NUM> may be a list of all agents for the CEC system. In other embodiments, the list of agents <NUM> may be the CSRs scheduled to work the current work shift. In yet other embodiments, the list of agents <NUM> may be dynamically generated based on the CSRs who have signed into the CEC system. The agents <NUM> contained on the list of agents <NUM> may be at various stages of preforming work and may or may not be available to be assigned work. Each agent <NUM> in the list of agents <NUM> has a set of agent abilities associated with the agent. Every agent <NUM> will have at least one ability. The agent abilities are the types of skills in which the agent is qualified. For example, agent A may speak English and Spanish and may also be skilled in returns; whereas agent B may speak English and Spanish and be skilled in new accounts. As indicated above, the agent abilities will correlate to the required skills for work items <NUM>. In embodiments, agent abilities may be an unordered list of skills. In other embodiments, agent abilities may be an ordered list where the agent's best skill is listed at the top and the agent's worst skill is listed at the bottom. In another embodiment, the agent abilities may be ordered by including a proficiency skill level associated with each ability for each agent <NUM>. Still in further embodiments, the agent abilities may simply be designated as primary or secondary for each agent <NUM>. These are merely examples of how agent abilities may be ordered and should not be considered limiting. It should be understood that an agent's skill level/designation in an agent ability may change over time based on experience. Further in addition to agent abilities, each agent <NUM> has metadata that indicates whether the agent is actively assigned a work item <NUM>, the type of work item assigned, the average handling time (AHT) for that type of work item based on the agent's abilities, and the time the work item was started.

The WAE <NUM> analyzes the list of agents <NUM> based on the metadata associated with each agent <NUM>, using the WAE software module <NUM> to determine available agents <NUM> and passes the list of available agents <NUM> to a smart work allocator (SWA) <NUM>. The list of available agents <NUM> contains agents <NUM> who are not currently assigned a work item <NUM> and agents <NUM> who are assigned a work item <NUM>, but are soon-to-be available (collectively available agents <NUM>). The WAE can use a number of ways to determine if an agent is soon-to-be available. One embodiment of determining if an agent is soon-to-be available is based on the monitored AHT for each given type of work on any given channel. For example, the metadata includes if an agent <NUM> is working on a billing enquiry email and the AHT for that type of work item is <NUM> minutes. If the agent has been working on the work item for <NUM> minutes, the WAE can predict the agent will become free in <NUM> minute and based on a time threshold <NUM> within WAS software module <NUM> for soon-to-be available can add that agent to the list of available agents at the appropriate time. The time threshold <NUM> includes rules that may be conditioned on the number of agents <NUM>, the number of work items <NUM>, the number of agents not currently assigned work items, and the AHT for a work item. For example, the time threshold <NUM> could be based on a set time (<NUM> minute, <NUM> minutes, <NUM> seconds, etc.), a percentage of time remaining based on the AHT for the work item, or a percentage of time remaining based on the amount of work items in the work item queue. In embodiments, a soon to be available agent could also be an agent whose schedule indicates they will be scheduled to be available within the time threshold <NUM>. For example, if the time threshold is <NUM> minutes and the agent's schedule indicates the agent will be back from a break or a meeting or otherwise available within the time threshold <NUM>, that agent would be considered an available agent. These are merely examples of how the time threshold <NUM> could be determined and should not be considered limiting.

The WAE <NUM> also analyzes the work queue <NUM> using the WAE software module <NUM> based on a set of imminent work item rules (IWIR)<NUM> to determine imminent work items <NUM> and passes the list of imminent work items <NUM> to the SWA <NUM>. The list of imminent work items <NUM> includes the required skills associated with each work item <NUM> from the work queue <NUM>.

The imminent work item rules <NUM> determine the order work items <NUM> are removed from the work queue <NUM> and the number of work items <NUM> that are included in the imminent work items <NUM>. The imminent work item rules <NUM> may be conditioned on the number and type of work items <NUM> in the work queue <NUM> and/or the number and type of available agents <NUM>. For example, IWIR <NUM> may indicate that imminent work items <NUM> are taken from the work queue <NUM> in a first-in first-out order. In embodiments, some work items <NUM> may be designated as urgent, and the IWIR <NUM> may indicate that urgent work items <NUM> should be included as imminent work items <NUM> ahead of other work items <NUM> in the work queue <NUM>. In some embodiments, the IWIR <NUM> may indicated that the imminent work items <NUM> will be based on the SLA of the work item, such that the closer a work item is to breaching SLA the sooner it will be transferred to the imminent work item list <NUM>. In embodiments, the number of imminent work items <NUM> is a set predetermined number. In this embodiment, it should be understood that if the number of current work items in the work queue is less than the predetermined number of imminent work items, the SWA <NUM> will receive all current work items from the work queue as the set of imminent work items. In other embodiments, the number of imminent work items the SWA <NUM> receives is dynamically determined by the IWIR <NUM>. The analysis may be based on a percentage of total work items <NUM> in the work queue <NUM>, the analysis may be based on the number of available agents <NUM>, the analysis may be based on a combination of the number of work items <NUM> in the work queue <NUM> balanced against the number of agents available <NUM>.

CEC system <NUM> also includes the SWA <NUM> having an SWA software module <NUM> and optional SWA storage <NUM>. SWA <NUM> may be a processor or a combination of a processing system and a storage system. SWA <NUM> receives the set of imminent work items <NUM> with their required skills and the list of available agents <NUM> with their agent abilities and metadata from WAE unit <NUM> and analyzes the first imminent work item from the imminent work items list <NUM> and available agents <NUM> using SWA software module <NUM> to determine a best match agent from the list of available agents <NUM> for the first imminent work item from the imminent work items list <NUM> based on a determination of an optimal available agent using predetermined criteria <NUM> within SWA software module <NUM> and assigns the first imminent work item from the imminent work items list <NUM> to the best match agent if the best match agent's abilities are an exact match for the required skills of the first imminent work item. The best match agent will become the assigned agent <NUM> and the first imminent work item will become the assigned work item <NUM>. Optionally, SWA <NUM> may also permanently or temporarily save a copy of the set of imminent work items <NUM>, the list of available agents <NUM>, the assigned agent <NUM>, and/or the assigned work item <NUM> to internal or external SWA storage <NUM>.

Predetermined criteria <NUM> include rules conditioned on the list of available agents and each agent's abilities <NUM> and the first imminent work item and its required skills <NUM> to determine the optimal match agent for the first imminent work item <NUM>. The determination of a best match agent <NUM> can be based off of any combination of matching available agent abilities <NUM> to the required skills for the first imminent work item <NUM>, depending on the information available for each set of skills and the level of ordered detail for the agent abilities and the required skills for the work item <NUM>. For example, in the preferred embodiment, the predetermined criteria <NUM> may have a sliding goal for the best match agent. In this example the best match agent may be an available agent <NUM> who has an agent skill set that matches exactly the required skills for the imminent work item <NUM> (no more skills and no less skills than what is exactly required by the imminent work item <NUM>). If there is no available agent with an exact skill set match, then the optimal match agent may be the first available agent <NUM> that has at least all of the required skills for the imminent work item <NUM> or the optimal match agent may be an available agent <NUM> that has at least all of the required skills for the imminent work item <NUM>, but also has the least number of additional skills that are not required skills for the imminent work item <NUM>. If there is no available agent who has all of the skills required for the imminent work item <NUM>, then the next optimal match may be the available agent <NUM> who has the greatest number of skills of the required skills for the imminent work item <NUM>. In this embodiment, the level of agent abilities and the level of skill required for the imminent work item <NUM> can also be taken into consideration, if that information is available, when determining the optimal match. In another embodiment, the predetermined criteria <NUM> for the optimal match agent may require that the available agent have at least the required skills of the imminent work item <NUM> and not consider an available agent <NUM> that does not have the required skills. In other embodiments, the predetermined criteria <NUM> for the optimal match may use the weight of the agents skills such that if two available agents <NUM> have the same skill set, but one agent has a necessary skill that is indicated to be a primary skill of that agent and the other agent does not have that skill indicated as a primarily skill the agent with the primary skill would be considered the optimal match. In some embodiments, agents will not be allowed to be matched with work items if they do not have at least all of the agent abilities indicated by the required skills of the work item. It should be understood that these are merely examples of predetermined criteria for determining the optimal match and should not be limiting.

When the best match agent does not have the exact agent abilities as the requires skills of the first imminent work item, the SWA software module <NUM> will analyze the best match agent and the imminent work items list to determine a best match imminent work item for the best match agent based on qualification criteria <NUM>. The SWA will compare the required skills for the first imminent work item, the required skills for the best match work item, and the agent abilities for the best match agent and determine which work item, best match work item or first imminent work item, to assign to best match agent based on match selection rules <NUM>. The SWA then assigns determined work item <NUM> to the best match agent <NUM>.

Qualification criteria <NUM> determine which work item <NUM> on the imminent work item list <NUM>, aside from the first imminent work item, is best suited for assignment to the best match agent based on what skills and/or level of skills are necessary for an agent to possess to be considered qualified to handle a work item. In one embodiment, the qualification criteria <NUM> will be based on the predetermined criteria <NUM> as described above. In embodiments where the system has information pertaining to the level of skill needed for a work item and the level of skill possessed by agents, the qualification criteria <NUM> may require that the best match agent not only possess at least the skills required by the required skills of the imminent work item <NUM>, but also possess skills at least at the required level as required by the imminent work item <NUM> for the imminent work item to be a best match work item. In another embodiment, the qualification criteria <NUM> may require the best match agent to have at least one skill at the required level of the imminent work item <NUM> for the imminent work item to be considered the best match work item. In some embodiments, agents will not be allowed to be matched with work items if they do not have at least all of the agent abilities indicated by the required skills of the work item. It should be understood that these are merely examples of predetermined rules for determining which agents are considered qualified to handle an imminent work item and should not be limiting.

Match selection rules <NUM> determine which of the best match work item or the first imminent work item should be routed to the best match agent. In one embodiment, the match selection rules <NUM> will be an adaptation of the predetermined criteria <NUM> described above such that the work item selected to be routed to the best match agent will be the work item whose required skills most closely match the agent's abilities. In some embodiments, agents will not be allowed to be matched with work items if they do not have at least all of the agent abilities indicated by the required skills of the work item. In embodiments where the system has information pertaining to the level of skill needed for a work item and the level of skill possessed by agents, the match selection rules <NUM> may favor the work item where that the best match agent not only possess at least the skills required by the required skills of the imminent work item <NUM>, but also possess skills at least at the required level as required by the imminent work item <NUM>. In another embodiment, the match selection rules <NUM> may favor the work item where the best match agent has at least one skill at the required level of the imminent work item <NUM> for the imminent work item.

In some embodiments, the SWA <NUM> receives the set of imminent work items <NUM> with their required skills and the list of available agents <NUM> with their agent abilities and metadata from WAE unit <NUM> and analyzes the first imminent work item from the imminent work items list <NUM> and available agents <NUM> using SWA software module <NUM> to determine a best match agent from the list of available agents <NUM> for the first imminent work item from the imminent work items list <NUM> based on a determination of an optimal available agent using predetermined criteria <NUM> within SWA software module <NUM>. The SWA software module <NUM> will next analyze the best match agent and the remaining items on the imminent work items list to determine a best match imminent work item for the best match agent based on qualification criteria <NUM>. The SWA will compare the required skills for the first imminent work item, the required skills for the best match work item, and the agent abilities for the best match agent and determine which work item, best match work item or first imminent work item, to assign to best match agent based on match selection rules <NUM>. The SWA then assigns determined work item <NUM> to the best match agent <NUM>.

In the exemplary embodiment, CEC system <NUM> also includes at least one CEC desktop (not pictured) used by the assigned agent <NUM> for receiving assignment of imminent work items <NUM>. CEC desktop may also receive input for updating imminent work item rules <NUM>, time threshold <NUM>, predetermined criteria <NUM>, qualification criteria <NUM>, and match selection rules <NUM>.

<FIG> depicts a flowchart of an exemplary embodiment of method <NUM> for work allocation optimization.

At step <NUM>, a WAE receives the work queue <NUM> from the CEC and determines if there are work items in the work queue. The CEC system provides a work queue <NUM> for work items <NUM> to be routed to agents <NUM>.

If, at step <NUM>, there are no work items <NUM> in the work queue, the method ends, otherwise the process moves on to step <NUM>.

At step <NUM>, the WAE receives a list of agents along with each agent's skill set <NUM>.

At step <NUM>, the WAE determines available agents <NUM> from the list of agents <NUM> and transfers the list of available agents <NUM> to a SWA. Available agents <NUM> are agents who are not currently assigned a work item <NUM> and agents that are soon-to-be available. Soon-to-be available agents are agents currently assigned a work item <NUM>, but, as described above in <FIG>, the WAE determines the agents are soon-to-be available based on the time threshold rules.

At step <NUM>, the WAE analyzes the work queue <NUM>, determines a set of imminent work <NUM> based on the analysis and passes the set of imminent work items <NUM> to the SWA. It should be understood that steps <NUM> and <NUM> may be performed in reverse order, simultaneously, or near simultaneously.

If, at step <NUM>, there are no available agents <NUM>, then the method repeats from step <NUM>, otherwise the process moves on to step <NUM>.

At step <NUM>, the SWA receives the list of available agents <NUM> and the set of imminent work items <NUM> from the WAE. The list of available agents <NUM> includes the agent abilities and metadata. The set of imminent work items <NUM> includes the required skills.

At step <NUM>, the SWA will compare the required skills for the first imminent work item from the imminent work items list <NUM> to the agent skills for the available agents <NUM> and will determine a best match agent for the first imminent work item based on predetermined criteria <NUM>. In the preferred embodiment, the best match agent will be an available agent <NUM> who has an agent skill set that matches exactly the requires skills for the imminent work item, this is considered the best match. If there is no available agent <NUM> with an exact skill set match (no more skills and no less skills than what is exactly required by the imminent work item), then the best match agent will be the first available agent that has all of the skills required for the imminent work item. If there is no available agent who has all of the skills required for the imminent work item, then the best match will be the available agent who has the greatest number of skills for the skills required by the imminent work item.

If the best match agent is an exact match for an imminent work item, at step <NUM>, the first imminent work item is routed to the best match agent and the first imminent work item becomes the assigned work item <NUM> and the best match agent becomes the assigned agent <NUM>.

At step <NUM>, the imminent work items <NUM> and the available agents <NUM> are updated, removing the assigned work item <NUM> from the imminent work items <NUM> and removing the assigned agent <NUM> from the available agents list <NUM>.

If there are still imminent work items that have been received by the SWA, the process will repeat from step <NUM> with the updated imminent work items and the updated available agents. If no imminent work items remain, the system will repeat from step <NUM>.

If the best match agent is not an exact match for the first imminent work item, at step <NUM>, the SWA will determine, from the queue of remaining imminent work items <NUM>, the best match work item for the best match agent's set of skills based on qualification criteria <NUM>.

At step <NUM>, the SWA will compare the skills of the best match agent to the skills needed for the first imminent work item and to the skills needed for the best match work item and determine based off of match selection rules <NUM> which work item will be routed to the best match agent.

If next best match work item has been chosen at step <NUM>, at step <NUM> the next best match work item is routed to the best match agent and the best match work item becomes the assigned work item <NUM> and the best match agent becomes the assigned agent <NUM>.

At step <NUM>, the imminent work items <NUM> and the available agents <NUM> are updated, removing the assigned work item <NUM> from the imminent work items <NUM> and removing the assigned agent <NUM> from the available agents list <NUM>. The method will repeat from step <NUM> with the updated imminent work item list <NUM> and the updated available agent list <NUM>.

If the first imminent work item is chosen at step <NUM>, at step <NUM> the first imminent work item is routed to the best match agent and the first imminent work item becomes the assigned work item <NUM> and the best match agent becomes the assigned agent <NUM>.

If there are still imminent work items that have been received by the SWA, the system will repeat from step <NUM> with the updated imminent work item list <NUM> and the updated available agent list <NUM>. If no imminent work items remain, the system will repeat from step <NUM>.

<FIG> depicts a flowchart of exemplary embodiment of method <NUM> for SWA work allocation optimization. In this embodiment, the WAE method is as described above in <FIG>; however, the SWA follows the method below, rather than the method described above in <FIG>.

At step <NUM>, the SWA will determine, from the queue of remaining imminent work items <NUM>, the best match work item for the best match agent's set of skills based on qualification criteria <NUM>.

If there are still imminent work items that have been received by the SWA, the system will repeat from step <NUM> with the updated imminent work item list <NUM> and the updated available agent list <NUM>. If no imminent work items remain, the system will return to the WAE method as described in <FIG>, steps <NUM> through <NUM>.

<FIG> depicts an exemplary embodiment of system <NUM> for work allocation optimization using CEC system <NUM>.

System <NUM> is generally a computing system that includes a processing system <NUM>, a storage system <NUM>, software <NUM>, a communication interface <NUM>, and a user interface <NUM>. Processing system <NUM> loads and executes software <NUM> from the storage system <NUM>, including a software module <NUM>. When executed by computing system <NUM>, software module <NUM> directs the processing system <NUM> to operate as described in herein in further detail in accordance with the method <NUM>.

Computing system <NUM> includes a software module <NUM> for performing the function of CEC system <NUM>. Although computing system <NUM> as depicted in <FIG> includes two software modules <NUM> for performing the functions of Work Acquisition Engine (WAE) software module <NUM> and/or SWA software module <NUM> in the present example, it should be understood that one or more modules could provide the same operation. Similarly, while the description as provided herein refers to a computing system <NUM> and a processing system <NUM>, it is to be recognized that implementations of such systems can be performed using one or more processors, which may be communicatively connected, and such implementations are considered to be within the scope of the description. It is also contemplated that these components of computing system <NUM> may be operating in a number of physical locations.

The processing system <NUM> can comprise a microprocessor and other circuitry that retrieves and executes software <NUM> from storage system <NUM>. Processing system <NUM> can be implemented within a single processing device but can also be distributed across multiple processing devices or sub-systems that cooperate in existing program instructions. Examples of processing systems <NUM> include general purpose central processing units, application specific processors, and logic devices, as well as any other type of processing device, combinations of processing devices, or variations thereof.

The storage system <NUM> can comprise any storage media readable by processing system <NUM>, and capable of storing software <NUM>. The storage system <NUM> can include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other information. Storage system <NUM> can be implemented as a single storage device but may also be implemented across multiple storage devices or sub-systems. Storage system <NUM> can further include additional elements, such a controller capable of communicating with the processing system <NUM>.

Examples of storage media include random access memory, read only memory, magnetic discs, optical discs, flash memory, virtual memory, and non-virtual memory, magnetic sets, magnetic tape, magnetic disc storage or other magnetic storage devices, or any other medium which can be used to store the desired information and that may be accessed by an instruction execution system, as well as any combination or variation thereof, or any other type of storage medium. In some implementations, the storage media can be a non-transitory storage media. In some implementations, at least a portion of the storage media may be transitory. Storage media may be internal or external to system <NUM>.

User interface <NUM> can include one or more CEC desktops, a mouse, a keyboard, a voice input device, a touch input device for receiving a gesture from a user, a motion input device for detecting non-touch gestures and other motions by a user, and other comparable input devices and associated processing elements capable of receiving user input from a user. The user interface <NUM> through the CEC desktops is also integrated into the CEC system <NUM> allowing the user to access the CEC telephone system, the CEC internet system, the CEC text communications systems, among other CEC systems. Output devices such as a video display or graphical display can display assigned work items <NUM>, the agent <NUM> to which the work item is assigned, or another interface further associated with embodiments of the system and method as disclosed herein. Speakers, printers, haptic devices and other types of output devices may also be included in the user interface <NUM>. A CSR, a supervisor or other staff can communicate with computing system <NUM> through the user interface <NUM> in order to view assigned work items <NUM> and assigned agents <NUM>, and in order to update time threshold rules <NUM>, imminent work item rules <NUM>, predetermined criteria <NUM>, qualification criteria <NUM>, match selection rules <NUM>, or any number of other tasks the CSR, supervisor or other staff may want to complete with computing system <NUM>.

As described in further detail herein, computing system <NUM> receives and transmits data through communication interface <NUM>. In embodiments, the communication interface <NUM> operates to send and/or receive data, such as, but not limited to, current work queue <NUM> and the listing of working agents with their respective skills <NUM> to/from other devices and/or systems to which computing system <NUM> is communicatively connected, and to receive and process input into the system. Such information can include input related to work item skill requirements and personnel skill sets.

It should be understood that the system and method it intended and capable of being operable in real-time or close to real-time to dynamically and automatedly assign work items <NUM> in the work queue <NUM> to a dynamically changing list of available agents <NUM> to optimize the assignment of work items. However, it is also contemplated and possible for the system to receive a set work queue <NUM> and an initial list of available agents <NUM> to create a work assignment schedule by assigning work items <NUM> to available agents <NUM> and then assigning the remainder of the work items from the work queue by simulating the work flow using the methods stated above for determining when an agent will become available to receive additional work items <NUM>.

Claim 1:
A method for optimized work item assignment, comprising:
receiving a work queue from the customer engagement center , CEC, at a work allocation engine, WAE, wherein the work queue includes a set of work items;
receiving an agent list from the CEC at the WAE, wherein the agent list includes at least one agent;
performing a work queue analysis of the work queue using a WAE software module on the WAE;
generating an imminent work item list based on the work queue analysis of the WAE software module;
performing an agent analysis of the work queue using the WAE software module on the WAE;
generating an available agent list based on the agent analysis of the WAE software module;
passing the imminent work item list and the available agent list to a smart work allocator, SWA;
performing an optimization analysis of the first imminent work item based on the available agent list using a SWA software module on the SWA;
determining a best match agent for the first imminent work item based on the optimization analysis of the first imminent work item;
performing an optimization analysis of the best match agent based on the remaining imminent work items using a SWA software module on the SWA;
determining a best match work item for the best match agent based on the optimization analysis of the best match agent;
comparing the first imminent work item and the best match work item to the best match agent;
assigning one of the first imminent work item or the best match work item to the best match agent based on the comparison;
updating the imminent work item list by removing the assigned work item; and
updating the available agent list by removing the best match agent.