Abstract:
A contact center is described along with various methods and mechanisms for administering the same. The contact center proposed herein provides the ability to, among other things, assess contextual information and adjust an outbound dialer&#39;s pacing algorithm based on the assessment thereof. The contextual information may be obtained from sources that are inside the contact center and outside the contact center.

Description:
FIELD OF THE DISCLOSURE 
       [0001]    The present disclosure is generally directed toward communications and more specifically toward contact centers. 
       BACKGROUND 
       [0002]    In traditional contact centers, all agents in an outbound calling campaign are generally considered the same and will be delivered the next outbound call attempt which is successfully answered by a customer in the order that the agents becomes available. In more sophisticated contact centers, the agents may be ranked for outbound calls by skill level and/or idle time. This approach, however, does not optimize the matching of the skills and abilities of the agent with the unique needs of the person being called and, therefore, only achieves average results. 
         [0003]    Meanwhile, outbound dialers are currently optimized to minimize idle time and outbound dialers are paced in order to attempt to perfectly synchronize the answering of outbound call attempts with the availability of agents to service those calls. Additional details of a contact center employing such a pacing function is described in U.S. Pat. No. 7,035,927 to Flockhart et al., the entire contents of which are hereby incorporated herein by reference. 
       SUMMARY 
       [0004]    It is, therefore, one aspect of the present disclosure to provide an outbound dialer that can have its pacing algorithm (e.g., pacing function or pacer) controlled in a more flexible and valuable manner. Specifically, the present disclosure proposes the ability to consider contextual information as an input for adjusting an outbound dialer&#39;s pacing algorithm. 
         [0005]    In some embodiments, a predictive tool is provided which analyzes various types of contextual information and based on that analysis determines whether to adjust the pacing algorithm (e.g., speed up the rate at which outbound calls are made or slow down the rate at which outbound calls are made). In some embodiments, contextual information can be obtained from within the contact center and/or from outside the contact center. 
         [0006]    As one non-limiting example, the characteristics of recent successful or unsuccessful outbound calls (e.g., outbound calls made within a previous and predetermined amount of time) can be analyzed. The analysis of the recent successful or unsuccessful outbound calls can be leveraged to predict the next best outbound call to make. One characteristic that may be analyzed is “hit rate” or the ratio of successful connections made between a customer and agent to the total number of outbound call attempts. As one example, if hit rates are detected to have an increase in a certain geographical region, then it can be predicted that more contacts in the same geographical region will also be successful, perhaps for a predetermined amount of time. 
         [0007]    Continuing the above example, it may also be possible to enable the predictive tool to analyze information about the geographical region (e.g., weather, current time of time in the region, news for the region, known events in the region, etc.) and use that information to adjust outbound dialing rates for outbound call attempts to that region. The information about the geographical region may be obtained from various sources which are internal and/or external to the contact center (e.g., news sources, RSS feeds, social media feeds, etc.). 
         [0008]    In some embodiments, the predictive tool is configured to analyze commonalities for successful outbound contacts and look for patterns of success. It may not even be necessary for the predictive tool to understand why outbound contacts of a certain type are being successful at a certain time. Rather, if the predictive tool observes a spike in success for outbound contacts of a certain type, then the predictive tool can select more outbound contacts from a campaign list that have similarities to the latest set of successful outbound contacts. The predictive tool does not necessarily need to understand why success is being obtained, but the predictive tool may try to increase outbound dialing rates for contacts that are similar in nature to recently-successful ones. 
         [0009]    Alternatively, or in addition, the predictive tool may select more contacts that are similar to recently-successful contacts for dialing from the campaign list without actually increasing outbound dialing rates. Once the abnormality in success decreases for that type of contact, then the predictive tool may re-adjust the dialing rate or set the contact selection back to a more even or random distribution. 
         [0010]    In some embodiments, the predictive tool may be configured to analyze other sources of information and control the outbound dialer&#39;s pacing algorithm based on such an analysis. In particular, the present disclosure proposes to use one or both of Weighted Advance Time (WAT) and well-matched criteria to adjust the pacing algorithm. Specifically, pacing adjustments can be made based on well-matched (e.g., has appropriate skill or skill level, speaks language natively, is primary role) and/or WAT. 
         [0011]    In a non-limiting example, a best call to place next can be chosen based on well-matched and WAT inputs. When considering well-matched criteria, if there is one or no agents that have a well-matched skill set for a set of possible outbound calls (e.g., all calls in the campaign list or the next X possible calls in the campaign list), then the pacing algorithm may be slowed down. Slowing down the pacing algorithm in this situation may be beneficial because if a predetermined number of outbound calls are connected with agents, then it is likely that those connected calls will take longer than an average handle time to be completed (e.g., because the agents currently available to handle such calls are not well-matched to the calls). However, if there are a large number of agents that are well-matched to handle the calls in the set of possible outbound calls, then the pacing algorithm may be sped up. Speeding up the pacing algorithm in this situation may be beneficial because if the same predetermined number of outbound calls are connected with agents, there is a higher probability that the calls will be handled in less than an average amount of time. 
         [0012]    When considering WAT, if the WAT is relatively high (e.g., slow moving) for a skill, then outbound dialing rates for that skill may be decreased. Conversely, if WAT is relatively low (e.g., fast moving) for a skill, then outbound dialing rates may be increased for that skill. 
         [0013]    Both well-matched and WAT criteria may be considered simultaneously as inputs for adjusting the outbound dialing rate. In some embodiments, various combinations of contextual information, well-matched information, and WAT information can be used to control the outbound dialer&#39;s pacing algorithm. it rates may also be used to adjust the pacing (track immediate hit-rate to slow down or speed up pacing) 
         [0014]    Embodiments of the present disclosure are not limited to calls, but can be employed for any contact type (e.g., email, text, IM chat, call, video call, etc.), whether inbound or outbound. 
         [0015]    In accordance with at least some embodiments of the present disclosure, a method of controlling an outbound dialer in a contact center is provided which generally comprises:
       analyzing at a first time at least one of (i) characteristics of successful outbound contacts that have occurred within a predetermined amount of time prior to the first time, (ii) well-matched criteria between a subset of agents in the contact center and potential outbound calls in a campaign list, and (iii) Weighted Advance Time (WAT) for one or more skills in the contact center; and   based on the analysis step, adjusting the outbound dialer&#39;s pacing algorithm.       
 
         [0018]    The phrases “at least one”, “one or more”, and “and/or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “at least one of A, B and C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B, or C” and “A, B, and/or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B and C together. 
         [0019]    The term “a” or “an” entity refers to one or more of that entity. As such, the terms “a” (or “an”), “one or more” and “at least one” can be used interchangeably herein. It is also to be noted that the terms “comprising”, “including”, and “having” can be used interchangeably. 
         [0020]    The term “automatic” and variations thereof, as used herein, refers to any process or operation done without material human input when the process or operation is performed. However, a process or operation can be automatic, even though performance of the process or operation uses material or immaterial human input, if the input is received before performance of the process or operation. Human input is deemed to be material if such input influences how the process or operation will be performed. Human input that consents to the performance of the process or operation is not deemed to be “material”. 
         [0021]    The term “computer-readable medium” as used herein refers to any tangible storage that participates in providing instructions to a processor for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, NVRAM, or magnetic or optical disks. Volatile media includes dynamic memory, such as main memory. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, magneto-optical medium, a CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, a solid state medium like a memory card, any other memory chip or cartridge, or any other medium from which a computer can read. When the computer-readable media is configured as a database, it is to be understood that the database may be any type of database, such as relational, hierarchical, object-oriented, and/or the like. Accordingly, the disclosure is considered to include a tangible storage medium and prior art-recognized equivalents and successor media, in which the software implementations of the present disclosure are stored. 
         [0022]    The terms “determine”, “calculate”, and “compute,” and variations thereof, as used herein, are used interchangeably and include any type of methodology, process, mathematical operation or technique. 
         [0023]    The term “module” as used herein refers to any known or later developed hardware, software, firmware, artificial intelligence, fuzzy logic, or combination of hardware and software that is capable of performing the functionality associated with that element. Also, while the disclosure is described in terms of exemplary embodiments, it should be appreciated that individual aspects of the disclosure can be separately claimed. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0024]    The present disclosure is described in conjunction with the appended figures: 
           [0025]      FIG. 1  is a block diagram of a communication system in accordance with embodiments of the present disclosure; 
           [0026]      FIG. 2  is a block diagram depicting details of a work assignment mechanism in accordance with embodiments of the present disclosure; 
           [0027]      FIG. 3  is a block diagram depicting a data structure used in accordance with embodiments of the present disclosure; and 
           [0028]      FIG. 4  is a flow diagram depicting a method of controlling an outbound dialer in a contact center in accordance with embodiments of the present disclosure. 
       
    
    
     DETAILED DESCRIPTION 
       [0029]    The ensuing description provides embodiments only, and is not intended to limit the scope, applicability, or configuration of the claims. Rather, the ensuing description will provide those skilled in the art with an enabling description for implementing the embodiments. It being understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the appended claims. 
         [0030]      FIG. 1  shows an illustrative embodiment of a communication system  100  in accordance with at least some embodiments of the present disclosure. The communication system  100  may be a distributed system and, in some embodiments, comprises one or more communication networks  104 . In some embodiments, the communication network  104  connects one or more customer communication devices  108  to a work assignment mechanism  116 , which may be owned and operated by an enterprise administering a contact center in which a plurality of resources  112  are distributed. 
         [0031]    The resources  112  may be capable of handling incoming work items (in the form of contacts) from the customer communication devices  108 . Incoming work items are typically originated outside of the contact center, for example, by a customer operating the customer communication device  108 . The resources  112  may also be capable of handling outgoing work items (also in the form of contacts). Outgoing work items, also referred to herein as outbound work items, are typically originated from within the contact center. One example of an outbound work item is a call placed by the contact center to a customer communication device  108 . Some resources  112  may be only capable of handling one type of work item (e.g., either inbound or outbound) whereas other resources may be capable of handling both types of work items, sometimes simultaneously (e.g., an inbound non-real-time work item such as an email and an outbound real-time work item such as a call). 
         [0032]    In accordance with at least some embodiments of the present disclosure, the communication network  104  may comprise any type of known communication medium or collection of communication media and may use any type of protocols to transport messages between endpoints. The communication network  104  may include wired and/or wireless communication technologies. The Internet is an example of the communication network  104  that constitutes an Internet Protocol (IP) network consisting of many computers, computing networks, and other communication devices located all over the world, which are connected through many telephone systems and other means. Other examples of the communication network  104  include, without limitation, a standard Plain Old Telephone System (POTS), an Integrated Services Digital Network (ISDN), the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Session Initiation Protocol (SIP) network, a cellular network, and any other type of packet-switched or circuit-switched network known in the art. In addition, it can be appreciated that the communication network  104  need not be limited to any one network type, and instead may be comprised of a number of different networks and/or network types. As one example, embodiments of the present disclosure may be utilized to increase the efficiency of a grid-based contact center. Examples of a grid-based contact center are more fully described in U.S. patent application Ser. No. 12/469,523 to Steiner, the entire contents of which are hereby incorporated herein by reference. Moreover, the communication network  104  may comprise a number of different physical signal carriers such as coaxial cable, copper cable/wire, fiber-optic cable, antennas for transmitting/receiving wireless messages, and combinations thereof. 
         [0033]    The communication devices  108  may correspond to customer communication devices. In some embodiments, the communication devices may be configured to process work items in the form of a telephone call, a packet or collection of packets (e.g., IP packets transmitted over an IP network), an email message, an Instant Message, an SMS message, a fax, and combinations thereof. Outbound work items, in particular, may be similar or identical in nature to traditional inbound work items except that they are originated by the contact center rather than the customer. 
         [0034]    In some embodiments, the communication may not necessarily be directed at the work assignment mechanism  116 , but rather may be on some other server in the communication network  104  where it is harvested by the work assignment mechanism  116 , which generates a work item for the harvested communication. An example of such a harvested communication includes a social media communication that is harvested by the work assignment mechanism  116  from a social media network or server. Exemplary architectures for harvesting social media communications and generating work items based thereon are described in U.S. patent application Ser. Nos. 12/784,369, 12/706,942, and 12/707,277, filed Mar. 20, 1010, Feb. 17, 2010, and Feb. 17, 2010, respectively, each of which are hereby incorporated herein by reference in their entirety. 
         [0035]    The format of the work item may depend upon the capabilities of the communication device  108  and the format of the communication. In particular, work items are logical representations within a contact center of work to be performed in connection with servicing a communication received at the contact center (and more specifically the work assignment mechanism  116 ). The communication may be received and maintained at the work assignment mechanism  116 , a switch or server connected to the work assignment mechanism  116 , or the like until a resource  112  is assigned to the work item representing that communication at which point the work assignment mechanism  116  passes the work item to a routing engine  136  to connect the communication device  108  which initiated (for inbound work items) or was the target of (for outbound work items) the communication with the assigned resource  112 . 
         [0036]    Although the routing engine  136  is depicted as being separate from the work assignment mechanism  116 , the routing engine  136  may be incorporated into the work assignment mechanism  116  or its functionality may be executed by the various work assignment engines  120  and/or  124 . 
         [0037]    In accordance with at least some embodiments of the present disclosure, the communication devices  108  may comprise any type of known communication equipment or collection of communication equipment. Examples of a suitable communication device  108  include, but are not limited to, a personal computer, laptop, Personal Digital Assistant (PDA), cellular phone, smart phone, telephone, or combinations thereof. In general each communication device  108  may be adapted to support video, audio, text, and/or data communications with other communication devices  108  as well as the processing resources  112 ,  148 . The type of medium used by the communication device  108  to communicate with other communication devices  108  or processing resources  112 ,  148  may depend upon the communication applications available on the communication device  108 . 
         [0038]    In accordance with at least some embodiments of the present disclosure, the work item is sent toward a collection of processing resources  112  via the combined efforts of the work assignment mechanism  116  and routing engine  136 . The resources  12  can either be completely automated resources (e.g., Interactive Voice Response (IVR) units, processors, servers, or the like), human resources utilizing communication devices (e.g., human agents utilizing a computer, telephone, laptop, etc.), or any other resource known to be used in contact centers. 
         [0039]    In some embodiments, the work assignment mechanism  116  comprises an inbound work assignment engine  120  which enables the work assignment mechanism  116  to make intelligent routing decisions for work items originated by customers. The work assignment mechanism  116  may also comprise an outbound work assignment engine  125  which enables the work assignment mechanism  116  to originate contacts and when a customer answers the attempted contact to assign the outbound contact to a resource  112  as an outbound work item. 
         [0040]    Although the inbound work assignment engine  120  is depicted as being separate and distinct from the outbound work assignment engine  124 , it should be appreciated that the functionality of both engines can be integrated into a single work assignment engine. It should also be appreciated that certain capabilities discussed herein with respect to one work assignment engine can be incorporated into the other work assignment engine without departing from the scope of the present disclosure. 
         [0041]    In some embodiments, the work assignment engines  120 ,  124  are configured to administer and make work assignment decisions in a queueless contact center, as is described in U.S. patent application Ser. No. 12/882,950, the entire contents of which are hereby incorporated herein by reference. The work assignment engines  120 ,  124  may also be configured to administer and make work assignment decisions in a traditional queue-based contact center where skill-based routing is used to assign work items to resources  112 . 
         [0042]    If a queueless contact center is implemented, the work assignment engine  120  and/or  124  can generate bitmaps/tables and determine, based on an analysis of the bitmaps/tables, which of the plurality of processing resources  112  is eligible and/or qualified to receive the work item and further determine which of the plurality of processing resources  112  is best suited to handle the processing needs of the work item. In situations of work item surplus, the work assignment engine  120  and/or  124  can also make the opposite determination (i.e., determine optimal assignment of a work item to a resource). 
         [0043]    In some embodiments, the work assignment mechanism  116  may further include a context engine  128  and a resource monitoring engine  132 . The context engine  128  may be configured to gather contextual information from within or outside the contact center. The context engine  128  may further assimilate the gathered contextual information, process it as necessary, and provide the processed contextual information to one or both of the work assignment engines  120 . In some embodiments, the context engine  128  may be configured to gather contextual information from information sources such as websites (e.g., by sending http GET requests to web servers), enterprise servers (e.g., by analyzing email communications, document activities, meetings, agendas, etc.), social networks (e.g., by monitoring posts on a social network or of a particular social network user), RSS feeds (e.g., by subscribing to RSS feeds), real-time news sources, weather informational sources, traffic informational sources, emergency service providers (e.g., by monitoring 9-1-1 call center activity), and so on. 
         [0044]    The resource monitoring engine  132  may be configured to analyze the activity of the contact center and determine one or more metrics that can be used to describe a current state of the contact center. In some embodiments, the resource monitoring engine  132  may be configured to analyze the speed with which inbound contacts having a certain attribute (e.g., skill requirement) are being assigned to resources  112 . In some embodiments, the resource monitoring engine  132  may be configured to determine a WAT for one or more skills within the contact center. The resource monitoring engine  132  may also be adapted to analyze other aspects of contact center performance such as Estimated Wait Time (EST), Key Performance Indicators (KPIs) (e.g., First Call Resolution, $/contact, $/min, Profit/contact, Profit/min, Average Handle Time, Abandon Rate, agent preference, closure rate, quality score, commit to pay rate, revenue/target, and/or customer satisfaction), hit rate for outbound contact attempts, and the like. As will be discussed in further detail herein, the information obtained by the context engine  128  and/or resource monitoring engine  132  may be used by the outbound work assignment engine  124  to intelligently control the pacing algorithm of the outbound dialer (e.g., by controlling the rate at which outbound calls are placed and/or the types of outbound calls that are placed). 
         [0045]    The work assignment engine(s)  120 ,  124  may reside in the work assignment mechanism  116  or in a number of different servers or processing devices. In some embodiments, cloud-based computing architectures can be employed whereby one or more components of the work assignment mechanism  116  are made available in a cloud or network such that they can be shared resources among a plurality of different users. 
         [0046]    With reference now to  FIG. 2 , additional details of the work assignment mechanism  116  will be described in accordance with embodiments of the present disclosure. Specifically, the outbound work assignment engine  124  may comprise an outbound dialer  224  that has a pacing algorithm  228  contained therein. The pacing algorithm  228  may be an operating parameter of the outbound dialer or it may be a function that is called or otherwise made available to the outbound dialer  224 . 
         [0047]    The outbound dialer  224 , and specifically the pacing algorithm  228 , may be controlled by an outbound workflow controller  204 . The outbound workflow controller  204  may comprise one or more components that enable the outbound workflow controller  204  to analyze various types of information and based on such an analysis determine whether and to what extent the pacing algorithm  228  should be adjusted. 
         [0048]    In some embodiments, the outbound workflow controller  204  comprises a pacing controller  208 , a context analyzer  212 , a well-matched analyzer  216 , and a WAT analyzer  220 . The outbound workflow controller  204  may also be referred to as a predictive tool for controlling the pacing algorithm  228  based on contextual information, well-matched information, and/or WAT information. In addition to receiving information from the resource monitoring engine  132  and context engine  128 , the outbound workflow controller  204  may also have access to resource pool information  232  and a campaign list  236 . These data sources may be built by and maintained within the outbound work assignment engine  124  or they may be built by other components in the contact center and made accessible to the outbound work assignment engine  124  as requested. 
         [0049]    The context analyzer  212  may be the component of the outbound workflow controller  204  that receives context information from the context engine  128  and analyzes such information to determine whether adjustments can be made to the pacing algorithm  228  to help the contact center be more efficient in its outbound dialing campaign. In some embodiments, the context analyzer  212  may also obtain context information from the resource pool information  232 . In some embodiments, the context analyzer  212  comprises the ability to monitor the success of outbound calls (or other types of outbound contact attempts), determine if there is any common characteristic or set of characteristics among the recently-successful outbound calls, and if such a common characteristic or set of characteristics exists, provide such information to the pacing controller  208 . Characteristics of an outbound call that may be considered by the context analyzer  212  include, without limitation, geographical location of the customer, time of day, day of week, current weather around the geographical location of the customer, current world-wide events, current local events associated with the geographical location, product recall information, customer complaints, customer satisfaction, other information obtained from a customer database, and combinations thereof. 
         [0050]    The well-matched analyzer  216  may be the component of the outbound workflow controller  204  that analyzes potential outbound calls in the campaign list  236 , compares the skill requirements of the potential outbound calls with skills of resources  112  that are currently available or predicted to become available within a predetermined amount of time, and, based on that comparison, determines whether adjustments can be made to the pacing algorithm  228  to help the contact center be more efficient in its outbound dialing campaign. As can be appreciated, the information concerning the resources  112  may be acquired from the resource monitoring engine  132 . The analytical results obtained by the well-matched analyzer  216  may be provided to the pacing controller  208 , which implements the adjustments to the pacing algorithm  228 , if necessary. 
         [0051]    The WAT analyzer  220  may be the component of the outbound workflow controller  204  that determines a WAT for a skill (or equivalent grouping of work items), and, based on that determination, determine whether adjustments can be made to the pacing algorithm  228  to help the contact center be more efficient in its outbound dialing campaign. The information needed to calculate the WAT (or similar metric such as EWT, Actual Wait Time, etc.) may be obtained from the resource monitoring engine  132 , the resource pool information  232 , or some other analytical tool in the work assignment mechanism  116  that is capable of monitoring the efficiency with which the contact center processes work items. The analytical results obtained by the WAT analyzer  220  may be provided to the pacing controller  208 , which implements the adjustments to the pacing algorithm  228 , if necessary. 
         [0052]    As noted above, the pacing controller  208  may receive multiple inputs from multiple analyzers  212 ,  216 ,  220 . In some situations one analyzer may provide the pacing controller  208  with instructions to adjust the pacing algorithm  228  in one way (e.g., speed up the rate at which outbound calls are dialed) whereas another analyzer may provide the pacing controller  208  with instructions to adjust the pacing algorithm  228  in a different way (e.g., slow down the rate at which outbound calls are dialed). The pacing controller  208  may be provided with an arbitration function that enables the pacing controller  208  to manage conflicting instructions from different analyzers. The arbitration function may simply comprise a rule or set of rules that define what action should be taken under various circumstances. The rule(s) may be as simple as obey instructions from one analyzer over instructions from another analyzer. Alternatively, the rule(s) may be complex equations or optimization functions that weigh (equally or unequally) the various inputs from the analyzers and determines whether and to what extent the pacing algorithm  228  should be adjusted. 
         [0053]    The campaign list  236  may comprise an ordered list of numbers that are to be dialed by the outbound dialer  224  according to the order in which they are listed (e.g., first number is to-be dialed first, second number is to-be dialed second, etc.). Alternatively, the campaign list  236  may comprise an unordered pool of work items. In some embodiments, the pacing controller  208  may also be configured to re-order the campaign list  236 , especially if instructed to do so by the well-matched analyzer. Alternatively, or in addition, the pacing controller  208  may instruct the pacing algorithm  228  to re-order the campaign list  236  or select certain numbers from the campaign list  236  so as to maximize the efficiency of the contact center. As a non-limiting example, the well-matched analyzer  216  may determine that an agent or multiple agents are currently available to handle outbound calls of a certain type with a certain degree of efficiency (e.g., based on one or more skills or attributes of the agent(s)). The well-matched analyzer  216  may instruct the pacing controller  208  that a well-matched condition exists and that the pacing algorithm  228  should be adjusted to capitalize on the well-matched condition. Accordingly, the pacing controller  208  may instruct the pacing algorithm  228  to select certain numbers from the campaign list  236  that have skill requirements or known attributes that match the skills or attributes of the available or soon-to-be-available agents. 
         [0054]      FIG. 3  depicts one example of a data structure  300  which may be generated and used by the various components of the work assignment mechanism  116 . In particular, a contact center may use the data structure  300  or multiple similar data structures to help determine how and when the pacing algorithm  228  of the outbound dialer  224  should be adjusted. In particular, the pacing controller  208  may maintain or at least employ parts of the data structure  300 . 
         [0055]    The information fields that may be contained in the data structure  300  include, for example, a current outbound dialing pace field  304 , a contextual analysis information field  308  a WAT information field  312 , a well-matched information field  316 , and a pacing adjustment options field  320 . 
         [0056]    The current outbound dialing pace  304  may comprise information describing the rate at which the outbound dialer  224  is current dialing outbound calls. The dialing pace may be described in total outbound call attempts per minute (or any other measure of time). Alternatively, or in addition, the dialing pace may be described on a per-skill basis. Thus, each type of outbound contact may have its own dedicated data structure  300  or at least a different row (or column) within a common data structure. 
         [0057]    The contextual analysis information field  308  may comprise results of the analysis carried out by the context analyzer  212 . Specifically, this information field may comprise the data that was analyzed by the context analyzer  212  (e.g., data obtained from the context engine  128 ) and/or results of the analysis of the contextual information. Further still, the contextual analysis information field  308  may comprise instructions for the pacing controller  208  to adjust the pacing algorithm  228  if such a decision could be based solely on the analysis of contextual information. 
         [0058]    The WAT information field  312  may comprise results of the analysis carried out by the WAT analyzer  220 . Specifically, this information field may comprise the current WAT for certain skills or for multiple skills. Alternatively, or in addition, a WAT for every inbound contact in the contact center may be calculated and maintained in the WAT information field  312 . Further still, this data field may comprise instructions for the pacing controller  208  to adjust the pacing algorithm  228  if such a decision could be based solely on the analysis of the WAT information. 
         [0059]    The well-matched information field  316  may comprise results of the analysis carried out by the well-matched analyzer  216 . Specifically, this information field may comprise skill or attribute information for every potential work item in the campaign list  236 , if such information is known. Additionally, the well-matched information field  316  may comprise skill or attribute information for every agent in the contact center, for currently available agents, for agents predicted to soon be available, or combinations thereof. This information field may further comprise information regarding the comparison of skill or attribute information for agents with skill or attribute information for potential work items in the campaign list  236 . As with the other data fields, this data field may comprise instructions for the pacing controller  208  to adjust the pacing algorithm  228  if such a decision could be based solely on the analysis of the WAT information. 
         [0060]    The pacing adjustment options field  320  may comprise any arbitration function or similar decision-making criteria that can be used by the pacing controller  208  to determine whether and to what extent the pacing algorithm  228  should be adjusted. The information in the pacing adjustment options field  320  may be based on the data in the other fields. For instance, the adjustment options may include variables that are linked to data in the other fields of the data structure  300 . 
         [0061]    With reference now to  FIG. 4 , a method of controlling and dynamically adjusting the outbound dialer&#39;s pacing algorithm  228  will be described in accordance with embodiments of the present disclosure. The method begins with the pacing controller  208  determining the current outbound dialing pace and any other information necessary to qualify how the pacing algorithm  228  is currently behaving (step  404 ). This information may be obtained directly from the outbound dialer  224  or it may be inferred by analyzing the campaign list  236  and changes made thereto. 
         [0062]    The method continues with the outbound workflow controller  204  receiving contextual information (step  408 ), WAT information (step  412 ), and/or well-matched information (step  416 ). This information may be received as raw data, as changes made relative to a last measurement of such data, or in any other format that can be analyzed by the various analyzers  208 ,  212 ,  216  of the outbound workflow controller  204 . 
         [0063]    The information received at the outbound workflow controller  204  is then analyzed by the appropriate analyzer (step  420 ). Results of each informational analysis may be provided to the pacing controller  208  where the analyses are combined and further analyzed, as a whole, by the pacing controller  208 . 
         [0064]    Based on the analyses made by the analyzers  212 ,  216 ,  220  and/or the further analysis thereof made by the pacing controller  208 , the method continues with the pacing controller  208  determining whether and to what extent the outbound dialer&#39;s pacing algorithm  228  should be adjusted (step  424 ). As noted above, this decision may include an arbitration step where the inputs from the various analyzers  212 ,  216 ,  220  are weighed. If the decision is made not to adjust the pacing algorithm  228 , then the method returns to step  404 . 
         [0065]    Alternatively, the method will continue with the pacing controller  208  generating and providing instructions to the outbound dialer  224  that cause the outbound dialer  224  to adjust the pacing algorithm  228  in one way or another (step  428 ). In some embodiments, the adjustment of the pacing algorithm may include altering an operating parameter of the pacing algorithm  228  to increase or decrease the rate with which the outbound dialer  224  attempts outbound contacts. Alternatively, or in addition, the adjustment of the pacing algorithm may include re-ordering the campaign list  236  or instructing the outbound dialer  224  to dial certain contacts or certain types of contacts before dialing other contacts. 
         [0066]    After the pacing algorithm  228  has been adjusted by the pacing algorithm  208 , the method returns to step  404 . 
         [0067]    In the foregoing description, for the purposes of illustration, methods were described in a particular order. It should be appreciated that in alternate embodiments, the methods may be performed in a different order than that described. It should also be appreciated that the methods described above may be performed by hardware components or may be embodied in sequences of machine-executable instructions, which may be used to cause a machine, such as a general-purpose or special-purpose processor (GPU or CPU) or logic circuits programmed with the instructions to perform the methods (FPGA). These machine-executable instructions may be stored on one or more machine readable mediums, such as CD-ROMs or other type of optical disks, floppy diskettes, ROMs, RAMs, EPROMs, EEPROMs, magnetic or optical cards, flash memory, or other types of machine-readable mediums suitable for storing electronic instructions. Alternatively, the methods may be performed by a combination of hardware and software. 
         [0068]    Specific details were given in the description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits may be shown in block diagrams in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments. 
         [0069]    Also, it is noted that the embodiments were described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed, but could have additional steps not included in the figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination corresponds to a return of the function to the calling function or the main function. 
         [0070]    Furthermore, embodiments may be implemented by hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. When implemented in software, firmware, middleware or microcode, the program code or code segments to perform the necessary tasks may be stored in a machine readable medium such as storage medium. A processor(s) may perform the necessary tasks. A code segment may represent a procedure, a function, a subprogram, a program, a routine, a subroutine, a module, a software package, a class, or any combination of instructions, data structures, or program statements. A code segment may be coupled to another code segment or a hardware circuit by passing and/or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, etc. 
         [0071]    While illustrative embodiments of the disclosure have been described in detail herein, it is to be understood that the inventive concepts may be otherwise variously embodied and employed, and that the appended claims are intended to be construed to include such variations, except as limited by the prior art.