U.S. patent application number 13/302494 was filed with the patent office on 2012-03-22 for systems and methods for providing workforce optimization to branch and back offices.
Invention is credited to Michael Bourke, Daryl Demos, Jason Fama, Shimon Keren, Nicholas Alexander McLean.
Application Number | 20120072254 13/302494 |
Document ID | / |
Family ID | 45818557 |
Filed Date | 2012-03-22 |
United States Patent
Application |
20120072254 |
Kind Code |
A1 |
McLean; Nicholas Alexander ;
et al. |
March 22, 2012 |
SYSTEMS AND METHODS FOR PROVIDING WORKFORCE OPTIMIZATION TO BRANCH
AND BACK OFFICES
Abstract
Systems and methods for providing workforce optimization are
provided. A representative method includes: planning a first
campaign to implement business goals; scheduling and deploying a
workforce in accordance with the campaign to produce a plurality of
interactions, at least one of the interactions involving a customer
and a first agent of a contact center, at least another of the
interactions involving a customer and a second agent of a branch
office or back office; measuring performance of the first agent and
the second agent on at least a portion of the interactions to
produce a set of quality metrics for the agents; combining at least
a portion of quality metrics to produce performance indicators; and
using the performance indicators in the planning step of a second
campaign or another iteration of the first campaign.
Inventors: |
McLean; Nicholas Alexander;
(Berkshire, GB) ; Keren; Shimon; (Sunnyvale,
CA) ; Demos; Daryl; (Duxbury, MA) ; Bourke;
Michael; (San Francisco, CA) ; Fama; Jason;
(Redwood City, CA) |
Family ID: |
45818557 |
Appl. No.: |
13/302494 |
Filed: |
November 22, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12171090 |
Jul 10, 2008 |
8078486 |
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13302494 |
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Current U.S.
Class: |
705/7.14 |
Current CPC
Class: |
G06Q 10/063114 20130101;
G06Q 10/063 20130101; H04M 3/5191 20130101; G06Q 10/063112
20130101; G06Q 10/06311 20130101 |
Class at
Publication: |
705/7.14 |
International
Class: |
G06Q 10/06 20120101
G06Q010/06 |
Claims
1. A method for providing workforce optimization comprising:
planning a first campaign to implement business goals; scheduling
and deploying a workforce by a forecasting and scheduling component
of a workforce management system implemented on a computer in
accordance with the first campaign to produce a plurality of
interactions, at least a first one of the interactions involving a
first customer and a first agent of a contact center that is
scheduled based on availability of agents of the branch office or
of the back office to accommodate customer contacts, at least a
second one of the interactions involving a second customer and a
second agent of a branch office or back office that is scheduled
such that the second agent is available for receiving redirected
customer contacts, the second of the interactions resulting from at
least one customer contact intended for the contact center being
selectively redirected from the contact center to the branch office
or back office based on a known skill set of the second agent,
wherein the branch office or the back office is part of the same
enterprise as the contact center but the primary purpose is not
handling customer contacts; measuring performance of the first
agent and the second agent on at least a portion of the
interactions by a tracking component of the workforce management
system implemented on the computer to produce a set of quality
metrics for the agents, wherein the performance of the first agent
is measured using a first parameter from an automatic call
distributor (ACD) and the performance of the second agent is
measured using a second parameter from workstation screen activity
for the second agent; combining at least a portion of quality
metrics to produce performance indicators; and using the
performance indicators in the planning step of a second campaign or
another iteration of the first campaign.
2. The method of claim 1, wherein the business goals are defined in
terms of metrics that describe how the agents are expected to
perform.
3. The method of claim 1, further comprising allocating a contact
directed to the contact center to an agent of the branch office or
the back office such that an agent of either the branch office or
an agent of the back office interacts with a customer attempting to
contact the contact center.
4. The method of claim 1, wherein measuring performance of the
second agent comprises: capturing screen data associated with a
workstation of the second agent; and analyzing the screen data to
determine at least some of the quality metrics.
5. The method of claim 1, further comprising recording at least a
portion of the interactions.
6. The method of claim 5, wherein measuring performance comprises
measuring performance by using quality monitoring and call
recording tools to assess at least one quality score and at least
one of the interactions.
7. The method of claim 1, further comprising using analytics to
provide insights on at least one skill or knowledge gap of at least
one of the agents.
8. The method of claim 7, further comprising providing training to
address the at least one skill and knowledge gap for the at least
one of the agents.
9. The method of claim 1, further comprising: analyzing and
identifying opportunities and correlating the opportunities with at
least one key performance indicator and at least one scorecard; and
developing at least one quality monitoring score to be used by the
workforce management system to produce staffing models that
integrate the agents of the contact center and at least one of the
branch office and the back office.
10. A system for providing workforce optimization comprising: a
forecasting and scheduling component of a workforce management
system implemented on a computer operative to plan a first campaign
to implement business goals and to schedule and deploy a workforce
in accordance with the first campaign to produce a plurality of
interactions, at least a first one of the interactions involving a
first customer and a first agent of a contact center that is
scheduled based on availability of agents of the branch office or
of the back office to accommodate customer contacts, at least a
second one of the interactions involving a second customer and a
second agent of a branch office or back office that is scheduled
such that the second agent is available for receiving redirected
customer contacts, the other of the interactions resulting from at
least one customer contact intended for the contact center being
selectively redirected from the contact center to the branch office
of the back office based on a known skill set of the second agent,
wherein the branch office or the back office is part of the same
enterprise as the contact center but the primary purpose is not
handling customer contacts; a tracking component of the workforce
management system implemented on the computer operative to measure
performance of the first agent and the second agent on at least a
portion of the interactions to produce a set of quality metrics for
the agents, wherein the performance of the first agent is measured
using a first parameter from an automatic call distributor (ACD)
and the performance of the second agent is measured using a second
parameter from workstation screen activity for the second agent,
and to combine at least a portion of quality metrics to produce
performance indicators; the forecasting and scheduling component
further operative to use the performance indicators in the planning
step of a second campaign or another iteration of the first
campaign.
11. The system of claim 10, wherein the tasks directed to the
contact center comprise contacts by customers.
12. The system of claim 10, further comprising an automatic call
distributor (ACD) operative to receive customer contacts and to
route the contacts to agents of the contact center.
13. The system of claim 12, wherein at least some of the contacts
are Internet Protocol (IP) telephone contacts and the ACD is
operative to route at least some of the IP telephone contacts, that
were directed to the contact center by customers, to at least one
of the branch office and the back office.
14. The system of claim 10, further comprising a recorder operative
to record interactions between the agents and the customers.
15. The system of claim 10, further comprising a screen capture
engine operative to capture screen shots associated with record
interactions between the customers and the agents of the branch
office or the back office.
Description
RELATED APPLICATIONS
[0001] This application is a continuation and claiming the benefit
of and priority to U.S. Patent Application entitled "SYSTEMS AND
METHOD FOR PROVIDING WORKFORCE OPTIMIZATION TO BRANCH AND BACK
OFFICES," Ser. No. 12/171,090, filed on Jul. 10, 2008, which is
incorporated by reference herein.
TECHNICAL BACKGROUND
[0002] The business of a contact center is to provide rapid and
efficient interaction between agents and customers (or prospective
customers). Existing solutions require the purchase of multiple
hardware and software components, typically from different vendors,
to achieve the business goals of the contact center. The use of
separate systems of components leads to a variety of problems. For
instance, each system typically has its own method of configuration
and its own user interface. Thus, exchanging data between the
systems requires additional work by someone at the contact
center.
[0003] Furthermore, contact centers are continually tasked with
striking a balance between service quality, efficiency,
effectiveness, revenue generation, cost cutting, and profitability.
As a result, today's contact center agents are charged with
mastering multiple data sources and systems, delivering consistent
service across customer touch points, up-selling, cross-selling,
and saving at-risk customers, while winning new ones.
[0004] In contrast, back offices typically provide indirect
customer contact, in that back office personnel support operations
of a business. By way of example, back office personnel can provide
workflow management and human resources services.
[0005] A branch office may be considered a hybrid of a contact
center and a back office. In particular, a typical branch office
may provide both direct and indirect customer support.
Overview
[0006] Systems and methods for providing workforce optimization are
provided. An exemplary embodiment of such a method comprises:
planning a first campaign to implement business goals; scheduling
and deploying a workforce in accordance with the campaign to
produce a plurality of interactions, at least one of the
interactions involving a customer and a first agent of a contact
center, at least another of the interactions involving a customer
and a second agent of a branch office or back office; measuring
performance of the first agent and the second agent on at least a
portion of the interactions to produce a set of quality metrics for
the agents; combining at least a portion of quality metrics to
produce performance indicators; and using the performance
indicators in the planning step of a second campaign or another
iteration of the first campaign.
[0007] An exemplary embodiment of such a system comprises a
forecasting and scheduling component operative to schedule a
workforce of agents to produce a plurality of interactions, a first
of the agents being assigned to a contact center for interacting
with customers and a second of the agents being assigned to a
branch office or back office for interacting with customers,
wherein at least a portion of tasks directed to agents of the
contact center is designated by the forecasting and scheduling
component for completion by an agent of either the branch office or
the back office.
[0008] Another embodiment of a method for providing workforce
optimization comprises redirecting a customer contact, which was
directed to a customer contact center staffed by agents dedicated
to interacting with customers, to a branch office or a back office
such that an agent of the branch office or of the back office
interacts with the customer associated with the customer contact
instead of an agent of the contact center.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] Many aspects of the disclosure can be better understood with
reference to the following drawings. The components in the drawings
are not necessarily to scale, emphasis instead being placed upon
clearly illustrating the principles of the present disclosure.
[0010] FIG. 1 is a block diagram of a contact center
environment.
[0011] FIG. 2 is a diagram of one embodiment of the integrated
process for optimizing operations at a contact center.
[0012] FIG. 3 is a high-level view of components in one embodiment
of an integrated contact center system.
[0013] FIG. 4 shows a point of integration between the work force
manager (WFM) and the quality monitor of FIG. 3.
[0014] FIG. 5 shows another point of integration between the work
force manager (WFM) and the quality monitor of FIG. 3.
[0015] FIG. 6 shows several points of integration between the WFM
and the learning component of FIG. 3.
[0016] FIG. 7 shows several points of integration between the
performance manager and the learning component of FIG. 3.
[0017] FIG. 8 shows a point of integration between the WFM and the
performance manager of FIG. 3.
[0018] FIG. 9 shows another point of integration between the WFM
and the performance manager of FIG. 3.
[0019] FIG. 10 shows components of the analytics function of FIG.
3.
[0020] FIGS. 11 and 12 are flowcharts that depict the functionality
of embodiments of a system for providing workforce
optimization.
[0021] FIG. 12 is a schematic diagram depicting an embodiment of a
system implemented by a computer.
DETAILED DESCRIPTION
[0022] The systems and methods described herein provide integrated
solutions for performing workforce management, quality monitoring,
e-learning, performance management, analytics and/or coaching
functionality. Combining at least some of the aforementioned
functionality as a unified integrated solution, delivered through a
single platform, enables users to gain more insight and make
smarter decisions faster about sales, service and overall
operations. Notably, this functionality can be used to integrate
not only these functions in a contact center implementation, but
can be used to integrate operations across contact center, back
office and branch office configurations.
[0023] In this regard, some embodiments represent a convergence of
at least some of six contact center technology segments that work
together in support of a greater customer service strategy. In
short, the integrated workforce optimization platforms disclosed
herein can potentially integrate: (1) Quality Monitoring/Call
Recording--voice of the customer; the complete customer experience
across multimedia touch points; (2) Workforce Management--strategic
forecasting and scheduling that drives efficiency and adherence,
aids in planning, and helps facilitate optimum staffing and service
levels; (3) Performance Management--key performance indicators
(KPIs) and scorecards that analyze and help identify synergies,
opportunities and improvement areas; (4) e-Learning--training, new
information and protocol disseminated to staff, leveraging best
practice customer interactions and delivering learning to support
development; (5) Analytics--deliver insights from customer
interactions to drive business performance; and/or (6)
Coaching--identification of substandard performance, scheduling of
supervisor intervention and training, agent feedback and report
generation. These six segments can become part of an interwoven and
interoperable solution, enabling operations to transition from
reactive to proactive, information-rich departments that deliver
strategic value to the organization.
[0024] Further, the integrated workforce optimization platforms
disclosed herein provide closed-loop systems for continuous
performance improvement, that enable an organization to: establish
realistic forecasts and performance goals; schedule and deploy the
right number of staff with the appropriate skills; capture customer
interactions in their entirety by recording all calls, or recording
based on business rules, or on-demand, or randomly; measure
performance to identify execution issues and excellence; analyze
customer interactions to investigate opportunities for optimizing
use of people, processes and technologies; take action by
delivering targeted coaching, training or re-engineering processes;
and/or refine forecasts and performance goals based on the
collected data.
[0025] Reference will now be made to several exemplary embodiments.
With respect to branch and back office integration, however, many
of the aspects relevant to these implementations are dedicated to a
distinct section below.
[0026] One embodiment of the integrated process and system
disclosed herein begins with planning and establishing goals--from
both an enterprise and center perspective--to ensure alignment and
objectives that complement and support one another. Next comes
forecasting and scheduling of the workforce to ensure optimum
service levels. Then recording and measuring performance are
utilized, leveraging quality monitoring/call recording to assess
service quality and the customer experience.
[0027] Next, the process/system analyzes and identifies
opportunities and correlates them with the contact center or
organization's KPIs and scorecards. Then, coaching, e-learning and
company-specific "best practices" (documented through captured
customer interactions) make it possible to address skill and
knowledge gaps efficiently and effectively--as well as quickly
communicate policy or procedural changes across the
center--enabling the contact center to achieve success in whatever
terms it chooses to define. Rather than arbitrarily sending
e-learning training segments and hoping agents use them,
organizations can use advanced workforce management forecasting and
scheduling to select the best time to administer training (which is
proven to be more effective than classroom or group learning) as
well as free supervisors to work one-on-one with agents.
[0028] Quality monitoring scores, including insights from analytics
and/or analytical analysis of structured, unstructured, or
aggregated data, can next be fed into a workforce management to
produce staffing models that prevent companies from unknowingly
scheduling one shift with all the top performers, for example. As a
result, some embodiments of the workforce management component of
the process/system of the present invention can provide a higher
level of consistent service across shifts.
[0029] As can be seen, while each technology segment delivers
value, integration is the key: together the segments deliver
greater impact than the sum of their individual parts. Utilizing
them separately limits the contact center's potential to become a
strategic business asset.
[0030] The integrated systems for workforce optimization disclosed
herein potentially solve many deficiencies. For instance, at an
operational level, organizations are focused on optimizing customer
sales/service representative (CSR) performance. In the process,
they may be working under constraints, such as cost control and
infrastructures that provides only bare essentials. They may also
face the challenge of matching demand with resources, retaining
effective agents, prioritizing coaching/training, and delivering
consistent customer experiences. Leveraging an integrated system
and its components, such as forecasting and scheduling,
voice/screen capture/recording, evaluations and best practice
training, enables them to focus on reducing risk, decreasing
average handle time, improving quality scores, driving down average
time to answer, ensuring adherence and managing occupancy.
[0031] At a more advanced level, organizations are focused on
optimizing performance. They face the challenge of balancing
productivity with quality, increasing center-driven revenue,
standardizing service across touch points, and growing transaction
complexities. Organizations are examining such metrics as first
call resolution, shrinkage, up-selling and cross-selling, and
customer satisfaction as driven though the contact center. As
disclosed herein, the forecasting and scheduling, adherence,
business rules-driven recording, lesson management, and
agent/organizational scorecard functionality--for example--unites
contact center experiences, provides flexible scheduling, and
promotes the initiation of a performance improvement culture.
[0032] The subject matter disclosed herein is related to the
subject matter disclosed in several pending U.S. patent
applications. One is entitled "Enterprise Manager for Recorders
from a Central Point of Administration," Ser. No. 11/359,325,
Attorney Docket No. 762301-1180, filed Feb. 22, 2006, and entirely
incorporated by reference herein. The subject matter of the 1180
application is centralized administration of voice, video, and data
recorders, and enabling role-based access control of recorders
which do not have role-based security concepts.
[0033] Another is "Systems and Methods for Scheduling Call Center
Agents using Quality Data," Ser. No. 11/359,909, Attorney Docket
No. 762301-1280, filed Feb. 22, 2006, and entirely incorporated by
reference herein.
[0034] Another is "Systems and Methods for Scheduling Call Center
Agents using Quality Data and Correlation-Based Discovery," Ser.
No. 11/359,731, Attorney Docket No. 762301-1010, filed Feb. 22,
2006, and entirely incorporated by reference herein.
[0035] Another is "System and Method for Integrating Learning
Systems and Scorecards Systems", Ser. No. 11/359,359, Attorney
Docket No. 762301-1090, filed Feb. 22, 2006, and entirely
incorporated by reference herein.
[0036] Another is "System and Method for Integrating Learning
Systems and Workforce Management Systems", Ser. No. 11/359,194,
Attorney Docket No. 762301-1150, filed Feb. 22, 2006, and entirely
incorporated by reference herein.
[0037] Another is U.S. application Ser. No. 10/136,705, entitled
"Method and System for Presenting Events Associated with Recorded
Data Exchanged between a Server and a User," and entirely
incorporated by reference herein. The subject matter of the 705
application includes capturing and graphically displaying events
that occur during an interaction between a customer and an agent. A
reviewer is presented with a summarized voice interaction session,
in the form of a call timeline, including a list of event
identifiers. The reviewer selects one of the event identifiers in
the timeline, and the interaction session, starting with the
selected event, is presented to the user. The user could choose to
start listening to the exchange at an event by selecting the
event.
[0038] Another is U.S. application Ser. No. 10/137,480, entitled
"Method and System for Selectively Dedicating Resources for
Recording Data Exchanged between Entities Attached to a Network,"
filed on Apr. 30, 2002, and entirely incorporated by reference
herein. The subject matter of the '480 application includes
determining whether to use an active tap or a passive tap to record
data passing through a particular node based upon an objective for
recording as noted by predefined business rules.
[0039] Another is U.S. Ser. No. 10/136,735, entitled "Methods and
Systems for Categorizing and Cataloguing Recorded Interactions,"
filed on Apr. 30, 2002, and entirely incorporated by reference
herein. The subject matter of the 735 application includes
categorizing data upon storing the captured data. The categories
are based upon predefined business rules for storing captured
data.
[0040] Another is U.S. application Ser. No. 10/061,469, entitled
"Method, Apparatus, and System for Capturing Data Exchanged between
a Server and a User," filed on Jan. 31, 2002, and entirely
incorporated by reference herein. The subject matter of the '469
application includes capture of exchange data by a capture module
that operates independently from the server and the user.
[0041] Another is U.S. application Ser. No. 10/061,489, entitled
"Method, Apparatus, and System for Processing Data Captured during
Exchanges between a Server and a User," filed on Jan. 31, 2002, and
entirely incorporated by reference herein. The subject matter of
the '489 application includes selective recordation of captured
data based upon whether the data satisfies predetermined business
rules.
[0042] Another is U.S. application Ser. No. 10/061,491, entitled
"Method, apparatus, and system for replaying data selected from
among data captured during exchanges between a server and a user,"
filed on Jan. 31, 2002, and entirely incorporated by reference
herein. The subject matter of the '491 application includes
replaying data captured during a session, wherein search criteria
are based upon business rules.
[0043] The following is a list of other U.S. utility applications
which may include related subject matter, each of which is
incorporated by reference: U.S. utility application, entitled,
"Method and Apparatus for Long-Range Planning," having Ser. No.
09/899,895, filed Oct. 3, 2002; U.S. utility application entitled,
"Interface System and Method of Building Rules and Constraints For
a Resource Scheduling System," having Ser. No. 09/680,131, filed
Oct. 2, 2000; U.S. Utility Application entitled, "System and Method
for Complex Schedule Generation," having Ser. No. 09/825,589, filed
Apr. 3, 2001; U.S. utility application entitled, "Method and
Apparatus for Long-Range Planning," having Ser. No. 09/899,895,
filed Jul. 5, 2001; U.S. utility application entitled, "Method and
Apparatus for Multi-Contact Scheduling," having Ser. No.
11/037,604, filed Jan. 18, 2005; and U.S. Utility application
entitled, "Method and Apparatus for Concurrent Error Identification
in Resource Scheduling," having Ser. No. 11/237,456, filed Sep. 27,
2005.
Contact Center Environment
[0044] FIG. 1 is a block diagram of a contact center environment
100. The contact center 100 is staffed by agents who handle
incoming and/or outgoing contacts. Although the traditional and
most common form of contact is by phone, other types of contacts
are becoming more common (e.g., text chat, web collaboration,
email, and fax). An agent workspace includes an agent phone 110 and
a workstation computer 120. A network 130 connects one or more of
the workstations 120.
[0045] A call router 140 distributes incoming contacts to available
agents. When the contacts are made by traditional phone lines, the
call router 140 operates by connecting outside trunk lines 150 to
agent trunk lines 160. In this environment, the call router 140 may
be implemented by an automatic call distributor (ACD), which queues
calls until a suitable agent is available. Other types of contacts,
such as Voice over Internet Protocol (VoIP) calls and
computer-based contacts (e.g., chat, email) are routed over one or
more data networks. These contacts are distributed over network 130
to one of the agent workstations 120.
[0046] During a customer contact, the agent interacts with one or
more applications 170 running on the workstation 120. Example
workstation applications give the agent access to customer records,
product information, ordering status, and transaction history, for
example.
[0047] The business purpose of a contact center is to provide rapid
and efficient interaction between agents and customers. To achieve
this purpose, a contact center follows a business process having
stages, in that one stage affects subsequent stages.
[0048] In a conventional contact center business process, there is
a relatively high degree of separation between stages. In contrast,
in the integrated contact center business process 200 (FIG. 2)
described here, multiple stages are connected into a loop, with
each stage of the process feeding input into another stage down the
line.
[0049] FIG. 2 is a diagram of an embodiment of the integrated
process for optimizing operations at a contact center (200), in
which several interfaced organizations are combined as a single
integrated operational process and/or platform. In the first stage
(210), the business goals of the contact center are defined. Goals
are defined in terms of metrics that describe how the contact
center is expected to perform. Some metrics relate to expected
revenue, such as revenue/hour or revenue/agent. Other metrics
relate to service level, such as time-to-answer and rate of
first-call resolution. Persons familiar with contact center
operations will understand these and many other business goals and
metrics.
[0050] The first stage (210) may also include campaign planning.
Profiles for campaigns are defined, for example, by inbound or
outbound, how many contacts are expected, date and duration of the
campaign, and what sorts of agent skills are needed.
[0051] Information about the goals and campaign(s) produced by the
first stage (210) is provided to the second stage (220). In the
second stage (220), a workforce of agents is scheduled to staff the
campaign(s). In determining the number of agents scheduled for a
campaign, the goals/metrics and campaign characteristics from the
first stage (210) are considered. The schedule also uses as input a
workload forecast, which predicts contact volume during each
interval of the campaign, based on historical data. Using this
schedule, the contact center manager deploys the appropriate number
and mix of agents during the campaign times.
[0052] The output of the second stage (220) is the customer-agent
interactions that occur during a campaign. The third stage (230)
measures or assesses the interactions in various ways. One typical
assessment ("adherence") measures how well an agent complies with
contact center policies (e.g., call duration). In the third stage
(230), at least a portion of the interactions are recorded and then
examined. This examination produces a variety of quality metrics
that assess an agent's skills in various categories (product
knowledge, selling, listening, etc.)
[0053] The various assessments are provided as input to the fourth
stage (240). In this stage, these inputs are analyzed in various
ways. The analysis may rate interactions on a "good" to "bad"
scale, considering the customer point of view, the business
point-of-view, or both. For example, a contact that resulted in a
sale would be an indicator of a "good" interaction while a contact
that exceeded average duration would be an indicator of a "bad"
interaction.
[0054] Once "bad" interactions are identified, an attempt is made
to determine a root cause. In some cases, the root cause may lie
with an agent (e.g., weak product skills). In other cases, the
cause may be in the contact center infrastructure or operations
(e.g., customer database is slow). The cause might also be rooted
in a business process of the enterprise that is sponsoring the
campaign. For example, the billing process used by the enterprise,
or the process by which the enterprise dispatches field service
units could be the cause.
[0055] The fifth stage (250) uses the analysis produced by the
fourth stage (230) to adapt and change operations accordingly.
Agent skills can be improved by training in the deficient areas.
The information may be used to change an aspect of contact center
operations, or to make a recommendation to the sponsoring
enterprise for it to change its processes or operations. The
results of the analysis, as well as the raw metrics used as input
to the analysis, are combined into data sets ("scorecards") that
allow the contact center operators to determine whether or not the
business goals are met and whether the metrics show progress toward
the goals or away from the goal ("trending"). These data sets are
provided as input to the first stage (210), which closes the
feedback loop of the integrated contact center business process
200.
[0056] FIG. 3 is a high-level view of components in an embodiment
of an integrated contact center system 300. The integrated system
300 includes two or more of the following components: a work force
manager (WFM) 310; a quality monitoring component 320 (also herein
"quality manager"); a learning component 330; and a performance
management component 340 (also herein "performance manager"). These
components (310-340) cooperate to implement the integrated contact
center business process (200) as described earlier.
[0057] As will be described, combining agent quality metrics from
the quality monitor 320 (e.g., synchronous such as voice,
asynchronous such as e-mail or chat) with WFM 310 (e.g., agent
planning, scheduling) may provide insight that contact center
supervisors can use to confirm the value provided by agents to the
business as a whole.
[0058] The WFM 310 performs many functions related to the agent
workforce. For example, WFM 310 can: schedule single, multiple, or
virtual contact centers across multiple time zones; accommodate a
dedicated, blended, or task-switching environment; schedule
meetings or training without impact on service levels; allow agents
to bid for shifts and provide input into their schedules; automate
compliance with government and union regulations; create
centralized forecasts and schedules with a single point of control
over the entire network, or decentralized schedules that allow for
decision-making at individual sites; schedule based on skill
priorities that align with the contact center's routing strategy;
and create and schedule teams as a unit to support training and
accommodate employee preferences.
[0059] The functionality of the entire WFM 310 is typically divided
among several applications, executables, processes, or services. A
forecast and scheduling component (350) calculates staffing levels
and agent schedules based on historical interaction (contact)
patterns. A tracking component (355) provides a contact center
supervisor or manager with information about agent activities and
agent-customer interactions, both historical and real-time. An
adherence component (360) supplies the supervisor with information
on how well each agent complies with call center policies. For
example, once schedules are created, the contact center should
ensure that agents follow the schedules.
[0060] Most preferably, the adherence component 360 provides a
real-time view of every activity across each channel in the contact
center, including those in the front and back office, so
supervisors/contact centers can see how their staff spends its
time. In an enhancement, alerts can be set to notify supervisors
when agents are out-of-adherence and exception management can help
ensure agents are correctly recognized for work they have
performed.
[0061] The quality monitor 320 includes a content recorder (370)
for recording agent-customer interactions. The content recorder 370
can be configured to capture all interactions, or a selected set of
interactions based on user-defined business rules.
[0062] The content recorder 370 can capture voice and data
interactions from both traditional and IP telephony environments
and can handle high-volume recording for compliance and sales
verification. The content recorder 370 can also record all voice
transactions across multiple sites, or randomly capture a subset of
transactions that may be of particular interest, as well as record
contacts on-demand. Using the content recorder 370 a user can
record all contacts or establish advanced business rules to capture
only those transactions of particular interest. User-defined
business rules can trigger the recordings, initiate enterprise
collaboration by notifying individuals or groups of the captured
contacts and emerging trends, and allow users to assign attributes
or "tags" to the contacts for quick identification. All data
related to a customer interaction--including navigation of
automated systems, agent keystrokes and desktop activities--can be
stored automatically in folders for search and retrieval. Different
users in an enterprise can share and review transactions, as well
as hear customer feedback first-hand.
[0063] The quality manager 320 stores the interactions in an
interactions database 375, which may include descriptive
information as well as recorded content. Contact center personnel
play back some of the interactions and use an evaluation component
(380) to score the agent in various categories (product knowledge,
selling, listening, etc.)
[0064] Furthermore, contact center supervisors and quality analysts
can then tap into these recorded interactions to review, evaluate,
and score agent performance. An analytics component (385) can
analyze interactions in various ways, including the use of speech
analytics. Examples of analysis include categorizing calls based on
content, analyzing a call against an expected call pattern and
reporting exceptions to the pattern, and providing a visualization
layer for recorded interactions that displays other data attributes
such as agent activities coincident with call events.
[0065] The learning component 330 allows a contact center manager
to develop training lessons for agents and assign lessons to
agents. The learning component 330 provides automated training
processes by identifying, scheduling, and delivering online
learning directly to agent desktops. The lesson content can include
recorded interactions, which can be used to create a library of
best practices for training agents and other personnel. Using
actual interactions, a contact center can develop E-learning
content specific to the organization. In an enhancement, these
training lessons can include assessments to help track and measure
agent performance, skill acquisition, and knowledge retention.
[0066] The learning component 330 can also deliver targeted
learning sessions over a network, using e-mail, or a hyperlink to a
Web site, or directly to the agent desktop. Supervisors can select
the appropriate training sessions from a library of courseware or
create sessions themselves using a contact-editing feature. Then
supervisors can assign course material and monitor completion
automatically.
[0067] The performance manager 340 displays key performance
indicators (KPIs), which can be predefined on a scorecard. The
scorecard, which can be role-appropriate, provides a statistical
measure of how well an agent or group of agents is performing
(against their goals). The KPI metrics are derived from quality
evaluations and/or WFM call routing data.
[0068] A centralized administration component 390 consolidates
agent administration across the various components into a single
point of entry, and provides a single logon to all components for
agents and administrators. The administration component 390 may
also include a centralized reporting component, even across
multiple sites. A consistent user interface 395 reduces training
time on the various system components.
[0069] An integrated contact center system such as system 300
allows contact center analysts to quickly access the right
information. Such an integrated system allows valuable and
previously undiscovered information to be uncovered. This new level
of visibility into contact center operations should allow personnel
to make better decisions faster.
[0070] FIG. 4 shows a point of integration between two components
of the integrated contact center system 300, for instance the WFM
310 and the quality monitor 320. Conventional call center systems
provide an "interactions" application that allows playback of
recorded interactions and live monitoring of interactions.
Importantly, these conventional systems did not integrate
interactions with WFM adherence information. The integration
between the WFM 310 and the quality monitor 320 described in FIG. 4
allows a supervisor to "drill down" and examine a particular
recorded interaction from a display of agent activity and/or
adherence information.
[0071] In this disclosure, the term "interaction" refers to a
record of the content of agent activities related to a call. Note
that agent activities are not limited to audio of the call itself.
Other forms of media are included. Examples of other types of
interactions are: video recording of the agent; application
activity on the agent's workstation 120; web pages delivered to the
agent and/or customer during collaborative sessions; messages
delivered through e-mail, instant messaging, or other messaging
technologies. Also, the agent activities in an interaction are not
limited to the duration of the call, but can occur after the call
(a state called "wrap up" or "research").
[0072] The tracking component 355 of the WFM 310 provides
information about agent activities to the WFM adherence component
360. Agent activities, which describe work activities performed by
agents, are collected from various sources. The call router 140
(FIG. 1) reports agent call states (Available, After-Call-Work,
etc.). An application monitor on agent workstation 120 tracks agent
activity on the workstation (e.g., switching between applications,
screen data, keyboard input, etc.).
[0073] The adherence component 360 displays a view (410) of agent
activities, typically one agent per line, with activities arranged
across a timeline. Exceptions to agent adherence (e.g.,
non-compliance with contact center policy) are displayed in
conjunction with the activities and the timeline.
[0074] The adherence component 360 obtains a list (420) of recorded
interactions available for agents during the displayed time period.
This list of interactions is presented to the user in the same
adherence view (410).
[0075] From this adherence view, a user can "drill down" to a
recorded interaction by selecting (430) the interaction from the
list, and then activating a playback tool. The adherence component
360 retrieves (440) the selected interaction from the interactions
database 375, and the interaction is then played back using an
appropriate application (e.g. media player, desktop activity
player, web content player). A user can also select an agent
activity that is presently occurring and either record on demand
(450) or live monitor (460) the selected activity.
[0076] Integration between the WFM 310 and the quality monitor 320
is further described in the U.S. patent application "System and
Method for Integrated Display of Recorded Interactions and Call
Agent Data," Attorney Docket Number 762301-1160, filed Feb. 22,
2006 by the same assignee as the instant application.
[0077] FIG. 5 shows an additional point of integration between the
WFM 310 and the quality monitor 320, in which agent activity,
adherence, and/or scheduling information is used to trigger
selective recording in a selective recording environment, or to
perform smart selection of recording for evaluation in a total
recording environment. In a conventional quality monitor 320, the
content recorder 370 can be configured to record a certain number,
or percentage, of agent-customer interactions. This parameter is
typically fixed for the duration of a campaign, though it can vary
from one campaign to the next.
[0078] In the integrated system 300a, the WFM 310 generates call
recording parameters 510 based on information contained in the
forecast 520 (e.g., call volume and call type) and/or the schedule
530. The recording parameters 510 are provided to the content
recorder 370 in the quality monitor 320. This integration allows
the content recorder 370 to adapt recording behavior during a
campaign.
[0079] As an example of how this feature is useful to a contact
center, consider a marketing campaign that starts on a Monday and
lasts all week. It is expected that call quality for agents on this
campaign will be relatively low on Monday, since the material is
new to the agents. By the end of the week, the agents are more
familiar with the material, so that agent quality scores are
expected to increase.
[0080] The recording parameters 510 provided to the content
recorder 370 in the integrated system 300a allow a contact center
manager to increase the percentage of interactions recorded at the
start of the campaign, and to reduce the percentage as the campaign
progresses. Recording parameters 510 can be further associated with
one agent, or a set of agents, so that inexperienced agents (e.g.,
agents with low scores) have a higher percentage of recorded
interactions as compared to more experienced agents.
[0081] Other examples of using WFM data to determine recording
behavior include: trigger or select recording based on relative
elapsed time from the beginning of the shift; trigger or select
recording before or after specific activities (e.g., after lunch or
before break activity); and trigger or select recording based on
adherence data (e.g., agent is on call but not adhering to
schedule).
[0082] FIG. 6 shows several points of integration between the WFM
310 and the learning component 330. The learning component 330
includes lessons 610. Each lesson 610 is designed to improve an
agent's competence in a particular area. Lessons are assigned,
either manually or automatically, through a lesson assignment
component 620, which communicates information about the assignment
(630) to the scheduler 350 in the WFM 310. In one embodiment, the
information 630 includes an agent identifier, a lesson identifier,
a lesson duration, and a lesson completion date. After receiving
the lesson assignment information 630, the scheduler 350 modifies
the schedule 530 to include a training activity for the identified
agent. If possible, the new training activity is scheduled before
the lesson completion date.
[0083] An agent receives training through a lesson presentation
function 640. The presentation may take the form of viewing a video
and/or listening to audio on the agent workstation 120. The lesson
presentation function 640 maintains a lesson log 650, which tracks
the presentation of lessons 610 to agents. In one implementation
the lesson log 650 includes an agent identifier, a lesson
identifier, the time when the lesson presentation began, and an
indication of whether the lesson has been completed.
[0084] In yet another point of integration between WFM 310 and the
learning component 330, the lesson log 650 is provided to the
adherence component 360 in the WFM 310. The adherence component 360
uses information in the lesson log 650 to determine whether an
agent has met the lesson completion date. If not, the adherence
component 360 notes the incomplete lesson as an exception to
adherence.
[0085] Scheduling assigned lessons and tracking adherence to these
assignments is further described in the U.S. patent application
"Tracking of Lesson Adherence in a Call Center Environment," Ser.
No. 11/359,194, Attorney Docket Number 762301-1150, filed on Feb.
22, 2006 by the same assignee as the instant application.
[0086] FIG. 7 shows several points of integration between the
performance manager 340 and the learning component 330. The
performance manager 340 maintains more key performance indicators
(KPIs) 710 that measure how well an agent or group of agents is
performing. The KPIs 710 may be based one or more source
measurements 720, such as evaluations from the quality monitor 320
and call statistics from call router 140 (e.g., call duration, hold
time during call, etc.)
[0087] The performance manager 340 does analysis on the KPIs 710
and/or the source measurements 720 to produce scorecards 730. The
analysis may include calculating statistics such as average,
variation, etc., aggregating by time period or groups of agents,
and determining trends. The scorecards 730 are then presented in
visual form to a user. Examples of scorecards are a daily scorecard
for an agent or a team, and a scorecard of all agents for the past
month.
[0088] In the integrated system 300b, the KPIs 710 are also
provided (740) to the learning component 330. As described earlier,
the learning component 330 maintains lessons 610, which can be
assigned to an agent for review. In the integrated system 300b,
each lesson 610 is associated with one or more KPIs 710. The lesson
assignment component 620 examines one or more of the KPIs 710 for a
particular agent, and makes an assignment (750) for a lesson 610
associated with that KPI 710, based on criteria associated with a
KPI or a competency. In one implementation, the criteria is a
comparison of one or more KPIs 710 for an agent to threshold
values, and the lesson assignment component 620 assigns a lesson
610 if the KPI 710 is lower than the threshold. This point of
integration therefore allows automatic lesson assignment based on
KPI 710.
[0089] Automatic lesson assignment is further described in the U.S.
patent application "Integration of E-Learning and Scorecards in
Call Center Operation," Attorney Docket Number 762301-1090, filed
Feb. 22, 2006 by the same assignee as the instant application.
[0090] The presentation may also include a test that is given to
the agent to determine competency in the area associated with the
lesson 610. In yet another point of integration between WFM 310 and
the learning component 330, the agent test score 760 for an agent
is provided to the performance manager 340. The performance manager
340 updates the KPIs 710 to reflect the agent competency described
by the test score 760.
[0091] FIG. 8 shows a point of integration between the WFM 310 and
the performance manager 340. Conventional schedulers allow agents
to set preferences for shift assignments (e.g., one agent prefers
to work weekends and another prefers to work nights). Since most
agents are expected to prefer a day shift rather than a midnight
shift, shift preferences are typically combined with agent ranking
or seniority, so that someone works the midnight shift. This leads
to a situation where the midnight shift is staffed with all of the
"worst" agents.
[0092] As described earlier, the performance manager 340 maintains
KPIs 710 that measure agent and/or group performance. In the
integrated system 300c shown in FIG. 8, the scheduler 350 considers
agent KPIs 710 when scheduling, so that some "good" agents are also
added to the shift. The KPI 710 may reflect, for example, an
evaluation of the agent's performance on a set of customer
interactions. In one embodiment, the scoring is done by a human
while playing back the recorded interaction. In another embodiment,
the scoring is at least partly automated through the use of speech
analytics.
[0093] The agent KPIs 710 are provided to the scheduler 350 in the
WFM 310. Also provided to the scheduler 350 are quality goals 810
for a particular schedule interval. Examples of quality goals are
"50% of agents have a score at of least 80" and "average score is
at least 80." The scheduler 350 considers the quality goals 810 and
the KPIs 710, along with other inputs, to determine a schedule 530,
which includes agent assignments to work activities at specific
times.
[0094] The scheduler 350 also considers other inputs, such as a
workload forecast 820, agent skill sets 830 and agent shift
preferences 840. The scheduler 350 then chooses a mix of agents to
work a shift, so that the agent scores combine to meet the quality
goals 810. Integration of KPIs and the scheduler is further
described in the U.S. patent application "Systems and Methods for
Scheduling Call Center Agents Using Quality Data," Ser. No.
11/359,731, Attorney Docket Number 762301-1010, filed Feb. 22, 2006
by the same assignee as the instant application.
[0095] FIG. 9 shows another point of integration between the WFM
310 and the performance manager 340. As described earlier, the
performance manager 340 maintains KPIs 710 that measure agent
and/or group performance, and produces scorecards 730 from the KPIs
710. The scorecards 730 provide a quick way for a manager to
determine areas that require attention. For example, if a
particular agent is out of adherence or has a low competency score,
then the adherence or competency KPI can be flagged with a warning
icon. Typically, the manager wants more detailed information about
the flagged problem area. A conventional contact center solution
requires the manager to open up a particular application, such as
Adherence or Quality Monitoring, to obtain detailed information
about the problem area. Once in the application, the manager must
then navigate to the root cause of the problem (e.g., the activity
that was out of adherence).
[0096] In contrast, the integrated system 300d allows a user to
quickly view details associated with the flagged problem area, in
the appropriate application context. Several examples of this use
of application context are shown in FIG. 9. When interacting with
the performance manager 340, selecting an adherence-related KPI
(910) in a scorecard 730 brings the user to a view (920) of
adherence information. Furthermore, the particular agent activities
that resulted in the out-of-adherence flag are highlighted or
otherwise brought to the user's attention in the view 920. As
another example, selecting a quality score-related KPI (930) (e.g.,
product knowledge KPI) brings the user to the quality monitor 320,
and more specifically to the particular evaluation form 940 which
contains the score 930.
[0097] As yet another example, selecting a call statistic-related
KPI (950), such as call duration or hold time, brings the user to
the quality monitor 320. The quality monitor 320 presents a list of
recorded interactions (from the interactions database 375) which
contributed to, or are in someway related to, the flagged
call-statistic score 950. The user can then play back (960) one of
the recorded interactions. The integrated system 300d thus greatly
simplifies root cause analysis for contact center personnel.
[0098] Call recording and monitoring are vital to contact center
operations and the business. Every day, insight and feedback on the
organization are gained from customer interactions. Valuable
business intelligence can be extracted from these calls to help
call center executives improve operational efficiency, customer
satisfaction, and profitability. Yet management can only listen to
a small segment of recorded calls. Managers must search manually
through an enormous number of calls just to find the calls they
need to analyze. The process is not only inefficient and expensive,
but valuable information is continually ignored, leaving only a
small sample of data needed to make informed business
decisions.
[0099] Referring now to FIG. 10, with the analytics function 385 of
the present invention (first introduced in FIG. 3), contact centers
can now convert all call recordings into actionable business
intelligence. Management can discern important competitive and
business insight and easily identify trends from customer
interactions, by analyzing speech, telephony, agent, and recording
data together. In an enhancement, the analytics function 385 also
streamlines the quality monitoring process by automatically
classifying and scoring calls, based on selection criteria that may
include any or part of the data captured by the integrated systems
disclosed herein, including speech analytics.
[0100] The analytics function 385 of the present invention enables
businesses to: (1) have a more accurate view of the customer
experience, which allows executives across the organization to
uncover critical customer attitudes, needs, and requirements; (2)
automatically score and classify calls for easy retrieval and
examination, which enables call centers to digitally score calls to
conduct automated quality and customer satisfaction surveys; and
(3) discover trends related to customer behavior (e.g. churn,
product adoption) that impact the business.
[0101] The analytics function 385 preferably uses speech
recognition 1000 to convert the recorded calls into a searchable
repository that allows for the query of words and/or phrases
contained within the recorded calls. This repository may manifest
itself as a text transcript or searchable phonetic model of the
recorded calls. The analytics function 385 may apply additional
unstructured data analysis techniques to refine and extract the
context and further meaning from the conversations. Examples of
various techniques that may be applied to refine the context of the
mined speech, or the speech-to-text conversion, include:
statistical modeling of grammar using a statistical model of
grammar 1010 module; and natural language processing using a
natural speech patterns 1020 module. Further, the analytics
function 385 identifies the critical words and phrases within the
context of the conversation. All this enables the embodiments
disclosed herein to capture the intent of the call, rather than
merely the words of the call.
[0102] In an alternative embodiment, the analytics function 385
converts the audio of the conversation into a phonetic
representation of the call and uses a word-spotting method 1030 (or
a query analysis), which flags or tags calls by a specific word,
phrase, proximity, inflection, tempo, or emotion. Queries may be
performed on an ad-hoc basis or stored for pattern analysis.
[0103] With the recorded calls converted to searchable content (via
a transcribed call 1040 represented in FIG. 10), the analytics
function 385 allows users to look back in time to discover what
customers have said. In the preferred embodiment, users do not need
to know in advance what they are looking for. For example, if there
was a spike in call volume last week, the analytics function 385
can enable the contact center to understand the reason for the
increased calls. Also, the user can incorporate metadata obtained
from telephony or CRM systems to gain further insight into the
reasons for the call spike.
[0104] In an enhancement, the analytics function 385 also uses a
pattern recognition module 1050 to pull meaning out of the results
generated by speech recognition. The pattern recognition module
1050 discerns the call's pattern and automatically places the call
into one or several categories once the call is ingested into the
speech engine, based on the context the pattern recognition module
1050 is able to extract from the speech mining function. The
patterns are used not only to classify calls but also to determine
if a particular activity has occurred during the call, or to
automatically score individual evaluation or survey questions based
on this data. For instance a call score might be correlated to an
existing evaluation or customer survey question during the call
(e.g., "did the agent offer a cross sell", "did the agent remember
to read the corporate policy"). By automating the labor-intensive
quality monitoring processes, contact centers can realize not just
a fast return on investment, but also deploy resources where they
are strategic to the call center.
[0105] The analytics function 385 can link the call content to the
metadata from, for example, a quality monitoring component (see
FIG. 3), to relate characteristics such as agent 10, time/date,
speaker's name, workgroup 10, and call routing. The analytics
function 385 can link to custom data sources that may contain other
information related to the agent/customer interaction, for example,
a CRM system.
[0106] The analytics function 385 also includes a search function
1060. An append feature in the search function allows the user to
modify the initial search by tacking on additional criteria and
logic. A refine feature function allows the user to add to the
search criteria, which are then used on the results of the last
search. A remove feature allows the user to modify the initial
search by tacking on additional criteria and logic. An undo allows
any of the modifications just described to be reversed. In one
enhancement, results from the initial search string using the
search function 1060 can be refined to help focus on particular
calls of interest. In another enhancement, users can combine the
search functionality described above with data from the CTI, ACD
and other sources via a CTI ACD integration 1070 module.
[0107] Different individuals use different words or phrases to
depict a similar meaning. Recognizing this fact, the analytics
function 385 enables users to expand single words into complete
concepts, which convey intent and meaning, rather than being tied
to one narrow possibility. An expansion option 1080 allows users to
include plural, synonym, homonym, and containing words, in a single
clean screen. For example, instead of searching for the single word
"bill", the user can select to search for "bill, bills, account,
charges, invoice, statement, billing, billed, bell", which will
most likely return better results because it takes into account the
differences of expression.
[0108] In one enhancement, the expansion option 1080 allows for the
identification of temporal relationships between words, phrases and
other collected events in order to better identify the context of
the conversation. For example, a search that includes the word
"supervisor" in a temporal relationship with words like "transfer
me to", or in relationship to a call transfer event, can provide
much more context than a search for "supervisor". The expansion
option allows users to capture more instances of the concept that
they are exploring and furthermore establish the intent of the
calls. This improves upon keyword-spotting technologies, which are
not good enough to perform ad-hoc searching for concepts, which is
the ultimate goal in content discovery.
[0109] The analytics function 385 further enables the user a
variety of ways to derive insight from the search results. The Call
Replay 1090 component allows the user to listen to an audio file
from the search results, in part or its entirety. Playing a portion
of the audio allows the user to more efficiently go through the
search results without having to waste time listening to the whole
conversation. The Text Display 1092 component shows a continuous
text for the entire recognized content when playing back part or
all of a call. This allows users to quickly capture terms and
expressions exchanged in the call that might be of importance. The
Save Searches 1094 component allows a user to save and easily
retrieve searches for further refinement and analysis. The Export
component 1096 allows search results to be exported to a wide
variety of formats, such as Microsoft Excel or Adobe PDF format.
The Search Statistics component 1098 displays information on the
current search (e.g. calls counted, search time). In one
enhancement, the analytics function 385 further includes call
visualization component which includes an interface for displaying
the text of a set of calls along with other data captured by the
integrated system of the present invention along with integrated
sources. A call visualization component is more fully described in
the 705 application and incorporated by reference above.
[0110] Preferably, the analytics function 385 automatically
classifies and scores calls via classify calls module 1062 and a
score calls module 1064. This feature can greatly reduce the time
and effort that contact centers spend on the quality monitoring
process by "structuring" unstructured voice recordings and
categorizing them. The classify calls module 1062 preferably
classifies calls based on the content. A call may be classified
into one or more "buckets." The analytics function 385 relies on
the concept that all conversational threads have at their core one
or more "patterns" of speech.
[0111] Patterns are complex descriptions of different ways that
people communicate information, not just simple "words" for
matching. These patterns of speech do not have to contain exact
word matches for particular search terms, but they only "look" like
a specific pattern. Each pattern is defined and assigned a weight
by the pattern developer, and each area of intent is assigned a
threshold. If a group of patterns match and their added weights
exceed the threshold, then that conversation is said to "look" like
and contain that intent.
[0112] The weights and threshold are user definable and therefore
easily tweaked to produce better and more accurate results. A
typical intent "bucket" will contain anywhere from five to 100
"patterns" to match. Patterns can be shared across domains and
industries, and pattern bases can evolve forward to deliver ever
more accurate and finely tuned pattern matching.
[0113] The analytics function 385 uses patterns not only to
classify calls via the classify calls module 1062, but also to
evaluate if a particular activity occurred during a call via the
score calls module 1064. The user begins by designating the
objective criteria on which the calls are to be scored into the
application. A set of patterns is then described for the criteria.
A call is then scored based on the extent to which the criteria
patterns were fully met, partially met, or not met at all. Each
weighted threshold for each score level can be customizable.
[0114] The analytics function 385 allows the user to create a
graphical representation of trends found in the calls via a
graphical representation module 1066. This enables a user to view
statistics about complex trends over a large time period.
[0115] The trend view displays a suite of ad-hoc reports that can
be easily configured by the parameters in Table 1.
TABLE-US-00001 TABLE 1 Time/Day Interval Value to Calculate
Segementation Day of Week Avg # Words Per Call By Agent Month Avg
Call Length In Seconds By Agent Group By Week Call Count By Content
Group By Quarter Hit Total By Customer Account By Year Sum
(WAVLength) By Department By Location
[0116] By visualizing the information by the parameters above, the
user can gain a more detailed view on the particularities of the
search phrases.
[0117] Another trending capability is the display of, for example,
the top 200 words mentioned in the recorded calls (where the number
of top words is customizable). The analytics function 385
proactively shows the words that are unusually more frequent than
before or compared to the standard language. This acts as an "early
warning system" to enable organizations to understand how the
conversations have changed from one period to the next.
[0118] Preferably, the analytics function 385 organizes and
delivers results customized to the end-users requirements via a
reports module 1068. In an enhancement, reports module 1068 allows
for scheduling options that enable users the ability to vary
frequency of report delivery so analysts can zoom in on critical
data metrics hourly, daily, monthly, etc. Users can customize and
automate reporting. Once a query is created, the user can save the
query to run automatically. Users can create and view reports in
different formats while using the web-based viewer. For example,
reports can be output as Excel or PDF files, and then emailed. The
reports are interactive, in that calls can be played back live from
the results of the report. The reports module 1068, which is
preferably based on industry-standard databases such as SQL, can be
used to customize reports, to extract, format and report from the
underlying data. In another enhancement, the reports module 1068 is
a dashboard reporting system which can, for example, link the
actual calls detected for each event or report.
Back Office and Branch Office Integration
[0119] As will be described in greater detail here, some
embodiments of workforce optimization systems and methods can
involve integration of contact centers, back offices and/or branch
offices. In this regard, it should be noted that back and branch
offices have traditionally involved a process centric approach to
optimization, whereas contact centers have tended to involve a
workforce centric approach to optimization. Despite these
differences, however, embodiments of workforce optimization systems
and methods can integrate these environments in such a manner that
potentially offers improvements in efficiency of operations.
[0120] With respect to the integration of both branch and back
offices relative to workforce optimization, various functions such
as workforce management, quality monitoring, e-learning,
performance management, analytics and/or coaching functionality can
be involved. Each of these areas is described in greater detail
below.
[0121] For workforce management, tasks such as forecast and
scheduling, and adherence monitoring of personnel performance can
be used. In this regard, a forecasting and scheduling component
(e.g., component 350 of FIG. 3) can calculate staffing levels and
schedules based on historical interaction patterns. Notably, such
interaction levels may not be based on ACD information as may be
commonplace with information regarding contact center agents. In
this case, such information may include historically high customer
traffic times at a branch office. Thus, much like scheduling of
agents at a contact center, scheduling of agents at a branch or
back office can be accommodated.
[0122] Another aspect of forecasting and scheduling involves the
concept of an integrated workforce to the extent that agents
assigned to a branch office or back office may possess the
requisite skills to perform tasks typically allocated to contact
center agents. In this regard, the personnel at either a branch or
back office could be scheduled to handle customer contacts, e.g.,
incoming phone calls, which are typically routed to contact center
agents by an ACD, for example. In those embodiments that provide
such a level of integration, a bank teller, for example, could be
scheduled for interacting with customers that call into a related
contact center during historically low customer volume times at the
bank. In this manner, an additional agent need not be scheduled to
work at the contact center.
[0123] A tracking component (e.g., component 355 of FIG. 3) can
provide a supervisor or manager with information about agent
activities and agent-customer interactions, both historical and
real-time. An adherence component (e.g., component 360 of FIG. 3)
supplies the supervisor with information on how well each agent
complies with policies. For example, once schedules are created,
these components enable a supervisor to ensure that agents follow
the schedules.
[0124] Unlike a typical contact center, however, the parameters
used to evaluate various aspects of branch and back office
personnel can be different. By way of example, adherence monitoring
of a contact center agent typically is conducted with reference to
activity of an ACD, which routes calls to available agents. In a
branch or back office, however, the activity of responding to
customer calls may not take place on a regular enough basis for
this activity alone to server as an accurate indicator of
adherence. Thus, other indicators can be used. For instance,
on-screen activity can be monitored, that is, a screen capture
engine can be used to acquire information corresponding to the
workstation activity of the agents, thereby providing an indication
of whether the agent is at the workstation.
[0125] Thus, the concept of integrating contact center, branch
office and back office agents involves multiple aspects of
utilization personnel of resources. In this regard, FIG. 11 is a
flowchart that depicts the functionality of an embodiment of a
system for providing workforce optimization. As shown in FIG. 11,
the functionality (or method) may be construed as involving
redirecting a customer contact, which was directed to a customer
contact center staffed by agents dedicated to interacting with
customers, to a branch office or a back office. This enables an
agent of the branch office or of the back office to interact with
the customer associated with the customer contact instead of an
agent of the contact center.
[0126] Another embodiment of a method for providing workforce
optimization is depicted in FIG. 12. As shown in FIG. 12, the
functionality (or method) may be construed as beginning at block
1202, in which a first campaign is planned to implement business
goals. In block 1204, a workforce is scheduled and deployed in
accordance with the campaign to produce a plurality of
interactions, at least one of the interactions involving a customer
and a first agent of a contact center, at least another of the
interactions involving a customer and a second agent of a branch
office or back office. In block 1206, performance of the first
agent and the second agent is measured on at least a portion of the
interactions to produce a set of quality metrics for the agents and
in block 1208, at least a portion of quality metrics are combined
to produce performance indicators. Then, as depicted in block 1210,
the performance indicators are used in the planning step of a
second campaign or another iteration of the first campaign.
[0127] FIG. 13 is a hardware block diagram of a general-purpose
computer 1300 that can be used to implement one or more of the
components of the integrated contact center systems 300 (e.g.,
300a-300d) disclosed herein, or the integrated contact center
processes or methods disclosed herein. The computer 1300 contains a
number of components that are well known in the art of call center
software, including a processor 1310, a network interface 1320,
memory 1330, and non-volatile storage 1340. Examples of
non-volatile storage include, for example, a hard disk, flash RAM,
flash ROM, EEPROM, etc. These components are coupled via a bus
1350. The memory 1330 contains instructions which, when executed by
the processor 1310, implement the methods and systems disclosed
herein. Omitted from FIG. 13 are a number of conventional
components, known to those skilled in the art that are unnecessary
to explain the operation of the system 1300.
[0128] The systems and methods disclosed herein can be implemented
in software, hardware, or a combination thereof. In some
embodiments, the system and/or method is implemented in software
that is stored in a memory and that is executed by a suitable
microprocessor (IJP) situated in a computing device. However, the
systems and methods can be embodied in any computer-readable medium
for use by or in connection with an instruction execution system,
apparatus, or device. Such instruction execution systems include
any computer-based system, processor-containing system, or other
system that can fetch and execute the instructions from the
instruction execution system. In the context of this disclosure, a
"computer-readable medium" can be any means that can contain,
store, communicate, propagate, or transport the program for use by,
or in connection with, the instruction execution system. The
computer readable medium can be, for example but not limited to, a
system or propagation medium that is based on electronic, magnetic,
optical, electromagnetic, infrared, or semiconductor
technology.
[0129] Specific examples of a computer-readable medium using
electronic technology would include (but are not limited to) the
following: an electrical connection (electronic) having one or more
wires; a random access memory (RAM); a read-only memory (ROM); an
erasable programmable read-only memory (EPROM or Flash memory). A
specific example using magnetic technology includes (but is not
limited to) a portable computer diskette. Specific examples using
optical technology include (but are not limited to) optical fiber
and compact disc read-only memory (CD-ROM).
[0130] It should be noted that any process descriptions or blocks
in flowcharts should be understood as representing modules,
segments, or portions of code which include one or more executable
instructions for implementing specific logical functions or steps
in the process. As would be understood by those of ordinary skill
in the art of the software development, alternative embodiments are
also included within the scope of the disclosure. In these
alternative embodiments, functions may be executed out of order
from that shown or discussed, including substantially concurrently
or in reverse order, depending on the functionality involved.
[0131] This description has been presented for purposes of
illustration and description. It is not intended to be exhaustive
or to limit the disclosure to the precise forms disclosed. Obvious
modifications or variations are possible in light of the above
teachings. The embodiments discussed, however, were chosen to
illustrate the principles of the disclosure, and its practical
application. The disclosure is thus intended to enable one of
ordinary skill in the art to use the disclosure, in various
embodiments and with various modifications, as are suited to the
particular use contemplated. All such modifications and variation
are within the scope of this disclosure, as determined by the
appended claims when interpreted in accordance with the breadth to
which they are fairly and legally entitled.
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