Patent Application
20220405694
The invention relates to managing a workforce, such as agents in a call center, when workers are scheduled in rotating shifts by scheduling agents for handing the communications in a manner that achieves desired service levels.
Assigning workers to shifts in a manner that allows the workers to handle tasks in an efficient manner is a critical part of many businesses. For a business such as a contact center (also referred to herein as a “call center”), workers (e.g., agents) are assigned to tasks (e.g., incoming communications) based on skills associated with each agent and the skills required for the tasks. One mechanism for matching the communications with the skills of an agent is to associate the communications with a “queue” that represents a category of the communication, such as Technical Support, or Billing Issues. Agents with the requisite skills can then be assigned to one or more appropriate queues over specific time intervals. In order to achieve desired service levels. Agents with the requisite skills must be assigned to each queue in a manner that is adequate to provide the service level for each queue based on, for example, historical customer needs at various time intervals. Therefore, agent scheduling can be a very complicated process.
Recently, the concept of “rotating shifts” has become popular to provide workers with time flexibility. “Rotating shifts”, or “rotating work rules”, are a scheduling concept in which agents move through a cycle of working different shifts on different weeks. For example, an agent might work a 4-week rotation with day shifts for 3 weeks, then the night shift for one week, and then the cycle would start again. The rotating work rules can benefit the worker, such as contact center agents by more fairly distributing the different work types. For example, if a worker or group of workers is restricted to the less desirable shifts, their morale and productivity can decrease. This can lead to increased turnover and the associated costs, such as costs for hiring and training new workers. Additionally, because the rotating work rules give workers the ability to work different times on different weeks, each worker can gain experience working in high traffic times as well as lower traffic times where they may have more chances to partake in other work-enriching activities, such as education, coaching, or self-evaluations. Finally, having at least some shifts in specific times, such as weekday regular working hours, may be necessary to allow a worker to attend specific classes or other activities necessary for skill development, certification, and the like.
The disclosed implementations provide a mechanism for applying rotating work rules where it is easy to create a cycle of not just shifts, but also other associated rules, such as break rules and worker preference rules. Templates and rules can be defined and assigned to Agents through a user interface for a single week. Rules are applied based on, for example, required breaks, maximum hours, minimum hours and other parameters to automatically create a rotating shift schedule. As described below, Event Types, Shift Templates, and Break Rules are defined and assigned to a worker, such as an agent in a call center. A scheduling engine then applies rotation week definitions to create a schedule for each worker that includes rotating shifts.
A first aspect of the invention is a method for assigning agents for shifts in a call center environment, the method comprising: providing a shift template data structure for an agent for a single week, the shift template data structure having data fields, the data fields including: an agent work time data field for a plurality of days in a week; an agent weekly minimum hour data field; and an agent weekly maximum hour data field; entering data values for each of the data fields for a specified agent to obtain an agent shift data structure; repeating the providing and entering steps for a plurality of weeks; receiving shift rotation data; and processing the agent shift data structures in accordance with the shift rotation data to assign the agent to a schedule of rotating shifts in accordance with a scheduling engine algorithm.
In some implementations, agents 120 may be assigned to one or more queues 125, and the agents 120 assigned to a queue 125 may handle communications that are placed in the queue by the contact center 150. Agents 120 and queues 125 may each be associated with one or more skills. The skills may include language proficiency (e.g., English, Spanish, and Chinese), proficiency with certain software applications (e.g., word-processors and spreadsheets), training level (e.g., having taken a particular course or passed a particular test), seniority (e.g., number of years working as an agent 120), achievements (e.g., meeting certain performance or quality goals, receiving positive performance reviews, or receiving positive reviews or ratings from customers 120). Other types of skills may be supported. The skills associated with an agent 120 may be the skills that the agent 120 possesses. The skills associated with a queue 125 may be the minimum set of skills that an agent 120 should possess to handle calls from the queue 125. The skills associated with a queue 125 may be set by a user or administrator.
To facilitate the assignment of agents 120 to queues, the environment 100 may further include a scheduler 170. The scheduler 170 may assign agents 120 to queues 125 based on the skills associated with the agents 120, the skills associated with the queues 125, and what is referred to herein as a “staffing” associated with each queue. The staffing associated with a queue 125 may be the minimum number of agents 120 that are needed to work on a queue 125 to maintain a particular service level. The service level may be defined by one or more metrics such as the maximum amount of time a customer 110 can be expected to wait to speak with an agent 120, for example. Other metrics may also be used.
The scheduler 170 may assign agents 120 to queues 125 for one or more intervals. An interval may be the smallest amount of time that an agent 120 can be scheduled for. Intervals used by the contact center 150 may be fifteen minutes, thirty minutes, forty-five minutes, or any appropriate time interval. The particular agents 120 assigned to a queue 125 for an interval is referred to herein as an “agent assignment.” The scheduler 170 may generate the staffing for a queue 125 for an interval based on a predicted workload for the queue 125 during the interval. The predicted workload may be based on historical workload data for the queue 125 and/or contact center 150 or may be provided by a user or administrator. Any method for predicting the workload of a queue 120 may be used.
The scheduler 170 may generate an agent assignment for a queue 125 for each interval based on the staffing generated for the queue 125 for the interval. For example, the call center 150 may use fifteen-minute intervals. The scheduler 170 may generate an agent assignment for the queue 125 for the 8:00 am interval based on the staffing for the interval, another agent assignment for the 8:15 am interval based on the staffing for the interval, and another assignment for the 8:30 am interval based on the staffing for the interval. Further, as described in detail below, the scheduler 170 automatically accommodates rotating shifts.
The skill group engine 210 may divide or assign the agents 120 into skill groups 211. A skill group 211 may be a grouping of agents 120 based on the skills associated with each agent 120. In some implementations, each agent 120 associated with a skill group 211 may be associated with the same skills. The skills associated with a skill group 211 may be the skills associated with each of the agents 120 in the skill group 211. Each agent 120 may be assigned by the skill group engine 120 into only one skill group 211. Any method for assigning agents 120 into skill groups 211 may be used.
In some implementations, the skill group engine 210 may group agents 120 into skill groups 211 that have similar skills, rather than exactly the same skills. This type of grouping is referred to herein as a fuzzy skill group. For example, an agent 120 that is associated with the skills English and Spanish may be added to a skill group 211 associated with the skills English, Spanish, and Portuguese, even though the agent 120 does not speak Portuguese. Depending on the implementation, the skill group engine 210 may determine to “relax” skills that are not popular or that are not associated with many queues 125 in the contact center 150. Continuing the example above, the skill group engine 120 may have determined that the skill Portuguese is associated with very few queues 125, and/or the queues 125 that are associated with the skill Portuguese are not very busy or have low staffing 121.
After all of the agents 120 have been assigned to a skill group 211, the skill group engine 210 may further divide the skill groups 211 into what are referred to herein as networks 213. A network 213 may be a set of skill groups 211 where each skill group 211 in the network 213 has at least one skill in common with at least one other skill group 211 in the network 213. In addition, no skill group 211 in a first network 213 has any skill in common with any skill group 211 in a second network 213.
In some implementations, the skill group engine 210 may create a network 213 by selecting a skill group 211 for the network 213. The skill group engine 210 may determine the queue 125 that the agents 120 associated with the selected skill group 211 could work. Of the determined queues 125, the skill group engine 210 may determine the skill groups 211 whose agents 120 can work in the determined queues 125. These determined skill groups 211 may be added to the network 213. The skill group engine 210 may then continue adding skill groups 211 in this fashion until no more skill groups 211 can be added to the network 213.
The skill group engine 210 may then select a skill group 211 that has not yet been added to a network 213 and may create a network 213 using the selected skill group 211 as described above. As will be clearer based on the disclosure below, because none of the skill groups 211 in one network have any skills in common with the skill groups 211 in another network, the weight engine 220 may perform simulations and may calculate skill group weights 221 for the skill groups 211 in each network 213 in parallel.
The weight engine 220 may calculate a skill group weight 221 for each skill group 211 in a network 213 for each interval. As used herein, a skill group weight 221 for a skill group 211 may be a data structure that includes a weight for each skill associated with the skill group 211 for an interval. The weight for each skill may be based on how often an agent 120 from the skill group 211 worked on a task or communication that involves the skill during the associated interval. For example, if agent 120 in a skill group 211 spent 90% of their time in an interval working on the skill Spanish and 10% of their time in the interval working on the skill English, the skill group weight 221 for the skill group 211 for the interval would be 0.90 and 0.10.
In some implementations, the weight engine 220 may calculate the skill group weight 221 for a skill group 211, by running one or more simulations of the contact center 150. The simulation may be based on historical data for the contact center 150 and may simulate the customers 110, agents 120, and queues 125 associated with the contact center 150 for one or more intervals. Any method for simulating a contact center 150 may be used.
The weight engine 220 may determine from the simulations, how much time each agent 120 of the skill group 211 spent working using each of its skills during an interval. The determined times may be used by the weight engine 220 to determine a distribution of the agent's time across the skills during the interval. The distribution for each skill may be used as the weight for the skill for the interval. For example, If at 8 am on Monday the agent 120 spent 30% of his time on the skill English, 60% on the skill Spanish, and was idle 10% of the time (and the agent 120 is the only one in the skill group 211), the weight for the English skill during the interval Monday 8 am would be 0.333 (i.e., 30%/{30%+60%)) and the weight for the Spanish skill during the interval Monday 8 am would be 0.666 (i.e., 60%/{30%+60%)). Assuming the values are the same for every interval, the skill group weights 221 for three intervals for the skill group 211 of English and Spanish would be English (0.33, 0.33, 0.33) and Spanish (0.67, 0.67, 0.67).
The schedule engine 230 may use the calculated skill group weights 221 for each queue 125 for each interval to determine which queue 120 to place an agent 120 based on the skills associated with the agent 120. Depending on the implementation, the schedule engine 230 may receive a request to generate an agent assignment 233 for a set of queues 125 for one or more intervals. The agent assignment 233 may be an assignment of one or more agents 120 to the queues 125 of the contact center 150 for the one or more intervals. The general operation of scheduler engine 230 can be similar to the scheduler engine described in U.S. patent application Ser. No. 16/668,525.
As illustrated in
A shift template is a data structure storing, for each day of a week a shift start time, a primary event type, and duration that an agent would work each day. For example, an agent might be assigned a full-time night shift which starts between 7 PM and 9 PM, is primarily composed of the “Available for Interactions” Event Type, and is 8.5 hours in duration. In
In order to create a flexible rotating shift schedule, rotating shift module must also consider worker parameters applied individually to each worker or a group of workers.
In the example of
At 412, the minimum and maximum number of hours per week (or other time period) for a worker are respectively entered in UI elements. At 414, one or more break rules that will apply to the worker are selected. Break rules are described in detail below. At 416 consistent work start times with tolerance can be selected. If this is selected, then all of the agent's shifts will start at the same time during the week and if a tolerance greater than 0 is specified, the maximum difference between any two start times that week will be less than or equal to the specified tolerance (e.g. 90 minutes as shown in
The break rules noted above with respect to element 414 of
Once break rules, or other rules, have been defined and assigned to an agent for a given week, as described above, the user (an administrator for example) can choose to specify that the agent works a rotation instead of having the same rules every week. To indicate an employee is working a rotation, the user can, for example, click on the “Add week” button, at 422 of
Additionally, once one week is added, a dropdown list is added to select which week of the rotations should be active on the current week. And, any week's configuration can be viewed and updated by clicking on the tab. The user can also choose to remove the week on the currently selected tab. If a week is removed, then subsequent weeks (if any) are renumbered such that weeks are numbered contiguously without gaps. The user can click Change Week Order to move the week forward or backward to another place in the cycle. All weeks will be renumbered when this is done. Of course, various methods can be applied to streamline data entry. For example, worker parameters can be copied from one worker to one or more other workers via a copy button. Additionally, a default set of work parameters can be set up for a team to allow new workers to be added with sensible defaults.
When the scheduling engine 230 runs to place shifts and breaks for agents, the rotation shift module 232 of the scheduling engine 230 will be passed all of the worker parameters, the rotation templates, and the break rules along with an alignment date indicating when the rotation cycle starts so the scheduling engine can determine appropriate work rules to apply to each week in the scheduling period.
The elements of the disclosed implementations can include computing devices including hardware processors and memories storing executable instructions to cause the processor to carry out the disclosed functionality. Numerous other general purpose or special purpose computing system environments or configurations may be used. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use include, but are not limited to, personal computers, servers, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, network personal computers (PCs), minicomputers, mainframe computers, embedded systems, distributed computing environments that include any of the above systems or devices, and the like. Computer-executable instructions, such as program modules, being executed by a computer may be used. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Distributed computing environments may be used where tasks are performed by remote processing devices that are linked through a communications network or other data transmission medium. In a distributed computing environment, program modules and other data may be located in both local and remote computer storage media including memory storage devices.
The computing devices can include a variety of tangible computer readable media. Computer readable media can be any available tangible media that can be accessed by device and includes both volatile and non-volatile media, removable and non-removable media. Tangible, non-transient computer storage media include volatile and non-volatile, and 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 data.
The various data and code can be stored in electronic storage devices which may comprise non-transitory storage media that electronically stores information. The electronic storage media of the electronic storage may include one or both of system storage that is provided integrally (i.e., substantially non-removable) with the computing devices and/or removable storage that is removably connectable to the computing devices via, for example, a port (e.g., a USB port, a firewire port, etc.) or a drive (e.g., a disk drive, etc.). The electronic storage may include one or more of optically readable storage media (e.g., optical disks, etc.), magnetically readable storage media (e.g., magnetic tape, magnetic hard drive, floppy drive, etc.), electrical charge-based storage media (e.g., EEPROM, RAM, etc.), solid-state storage media (e.g., flash drive, etc.), and/or other electronically readable storage media.
Processor(s) of the computing devices may be configured to provide information processing capabilities and may include one or more of a digital processor, an analog processor, a digital circuit designed to process information, an analog circuit designed to process information, a state machine, and/or other mechanisms for electronically processing information. As used herein, the term “module” may refer to any component or set of components that perform the functionality attributed to the module. This may include one or more physical processors during execution of processor readable instructions, the processor readable instructions, circuitry, hardware, storage media, or any other components.
The contact center 150 of
Although the present technology has been described in detail for the purpose of illustration based on what is currently considered to be the most practical and preferred implementations, it is to be understood that such detail is solely for that purpose and that the technology is not limited to the disclosed implementations, but, on the contrary, is intended to cover modifications and equivalent arrangements that are within the spirit and scope of the appended claims. For example, it is to be understood that the present technology contemplates that, to the extent possible, one or more features of any implementation can be combined with one or more features of any other implementation.
While implementations and examples have been illustrated and described, it is to be understood that the invention is not limited to the precise construction and components disclosed herein. Various modifications, changes and variations may be made in the arrangement, operation and details of the method and apparatus disclosed herein without departing from the spirit and scope of the invention defined in the appended claims.
