This document provides an overview of high quality management and discusses several related topics. It lists various quality management tools like check sheets, control charts, Pareto charts, scatter plots, Ishikawa diagrams, and histograms. It also discusses contents of quality management like recording, quality assurance, workforce management and more. The document examines the quality management/liability recording market trends, noting continued growth driven by new applications and migration to IP-based solutions. It outlines a future outlook with slower but still strong predicted growth over the next few years. Useful links to additional quality management resources are also provided.

1. High quality management
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I. Contents of high quality management
==================
The quality management/liability recording (QM/LR) market had another great year in 2007.
The overall market—sometimes referred to as workforce optimization (WFO)—grew by 13.1
percent, from $2.1 billion in 2006 to $2.4 billion in 2007. The contact center segment of this
market continued to grow steadily at 19.2 percent, and is now approaching $1 billion in annual
sales. The trends sustaining the high growth rate of this mature, yet dynamic, market include
emerging vendors, product innovation, organic growth, acquisitions, and continued migration
toward IP-based recording.
The QM/LR market is complex and continues to expand into new functional areas. DMG
Consulting expects to see this market evolve further into analytical solutions that will both
increase efficiency for contact center managers and add value to the greater enterprise. This
market already encompasses a broad set of related products and services, as can be seen in
Figure 1.
Figure 1: Quality Management/Liability Recording Suites
Source: DMG Consulting LLC, June 2008
The modules in quality management/liability recording suites are recording, quality assurance
(QA), workforce management, coaching, e-learning, surveying, performance management, and
speech analytics.
“Back office” refers to the adaptation of a number of these modules for non–contact center
operating areas of enterprises or their branches. These back-office applications primarily address
recording, workforce management, and a limited amount of quality assurance. This relatively
new trend for the QM/LR vendors began a couple of years ago, picked up momentum in 2007,
and has grown more significantly in 2008. The rollout of contact center WFO products into other
operating areas is expected to substantially increase the revenue opportunity for this market.

2. The Market Remains Strong
The 13.1 percent WFO market growth rate between 2006 and 2007 was substantially smaller
than the 106.1 percent increase realized between 2005 and 2006. A number of factors contributed
to the diminished annual growth rate. In 2006, three contact center infrastructure vendors with
WFO offerings—Aspect Software, Interactive Intelligence, and TeleDirect International (now
known as TDI)—were added to the market analysis. Verint acquired Witness Systems during
2007 and, while the newly merged company continues to grow, it is doing so at a pace slower
than the two companies had separately in the prior year. Additionally, as Verint was absorbing
Witness, these two traditionally acquisitive companies did not introduce revenue from additional
purchases, as each had done in prior years.
The decreased annual rate of growth should not detract from the WFO market’s strong
momentum as it transitions from traditional recording and QA applications to more analytically
oriented ones such as contact center surveying, performance management, and speech analytics.
Additionally, the market is shifting from predominantly hardware-based applications to new
offerings consisting of software running on generic hardware. This increasing software
orientation means that average market margins are growing, even though the actual revenue per
recording sale may be decreasing.
A Maturing Market
The QM/LR market is quite mature, having been around in one form or another since the 1980s.
There are now more than 45 vendors that offer quality management, recording, and some or all
of the modules found in Figure 1. With the exception of a couple of companies that are relatively
new and investing all of their resources into building their suites, all of the vendors claim to be
profitable. Despite the market’s maturity, each year new vendors enter the field. It’s also
interesting to note that there are a number of relatively new regional players located in a variety
of global markets that are coming on strong.
Mergers Impact Market Landscape
As is typical of any maturing market, mergers and consolidations continued in 2007. TDI, a
provider of servicing solutions for sales and revenue generation, acquired Wygant in April 2007.
In May 2007, Verint acquired Witness Systems. (At the time, Verint was considered the third-
largest competitor in the contact center WFO market, and Witness was the second-largest. Based
on total annual revenue, however, Verint was larger than Witness.) And in July 2007, NICE
Systems purchased Actimize, a provider of software solutions for compliance, fraud prevention,
and anti–money laundering. Actimize was not previously included in our coverage of the WFO
market.
Newer Applications Pick Up Momentum
Sales of the newer WFO modules—namely speech analytics, performance management, and
surveying/e-learning/coaching—picked up in 2007. Revenue from core contact center recording
and quality management modules continued to dominate the WFO market, accounting for over
45 percent of total revenue. But the newer applications began to make a significant contribution,
thanks to their attractive value proposition. (See Figure 2.)
Figure 2: 2007 WFO and Recording Solutions Revenue and Market Share by Application
Source: DMG Consulting LLC, Quality Management/Liability Recording Market Share Report,
June 2008
Of the newer solutions, speech analytics had the largest market impact, generating 5.6 percent of
total revenue. Performance management solutions accounted for 3.8 percent of all application
sales and surveying/e-learning/coaching represented 2.7 percent.

3. Workforce management is not a new module; however, it only started to be offered as a
component of WFO solutions during 2006. By 2007, workforce management accounted for 13.1
percent of application sales. It’s also interesting to note that non–contact center recording
solutions—which are used in public-safety applications and in other parts of the enterprise, such
as on trading floors and in branch offices—is a growing sector, accounting for 17.2 percent of
market revenue. Video recording, which is used for security purposes, was responsible for 11.8
percent of the revenue.
Sales of IP-based Recording Solutions Increase
Sales of IP-based recording solutions continued to pick up momentum last year. In fact, for the
first time, their overall sales exceeded sales of solutions based on time division multiplexing
(TDM), faring particularly well outside the contact center. Among contact centers, however,
sales of TDM-based recording solutions outpaced those of IP-based solutions. This is because
many contact centers still have TDM-based infrastructure in place; while a growing number are
migrating to IP-based solutions, most contact centers do not want to rip out and replace their core
TDM-based solutions until absolutely necessary. As a result, these contact centers continue to
upgrade TDM-based recording solutions, and are expected to do so for years to come. This is the
primary reason why many WFO vendors, both large and small, continue to sell TDM-based
recording solutions when they would really prefer to simplify their product lines and concentrate
on newer, IP-based solutions.
Future Market Outlook
We expect 2008 to be another year of significant market expansion, despite the economic
slowdown. Because many of the applications in the WFO market are considered efficiency
enhancers or solutions that improve customer retention, they are capable of weathering
challenging economic times. The quality management/liability recording market is expected to
grow by 8 percent in 2008 and 7 percent in 2009. While these growth rates are slower than what
we have seen in the recent past, they are strong, considering the challenges presented by the
current size of this market and adverse economic conditions. For a detailed revenue and market-
share analysis of 20 top vendors in the market, see DMG Consulting’s 2008 Quality
Management/Liability Recording Market Share Report. The report analyzes revenue and market
share by technology segment, geography, hardware/software/services, sales approach, etc. It
provides growth comparisons between 2006 and 2007, with five- and four-year trend analyses
for many market views.
==================
III. Quality management tools
1. Check sheet

4. The check sheet is a form (document) used to collect data
in real time at the location where the data is generated.
The data it captures can be quantitative or qualitative.
When the information is quantitative, the check sheet is
sometimes called a tally sheet.
The defining characteristic of a check sheet is that data
are recorded by making marks ("checks") on it. A typical
check sheet is divided into regions, and marks made in
different regions have different significance. Data are
read by observing the location and number of marks on
the sheet.
Check sheets typically employ a heading that answers the
Five Ws:
 Who filled out the check sheet
 What was collected (what each check represents,
an identifying batch or lot number)
 Where the collection took place (facility, room,
apparatus)
 When the collection took place (hour, shift, day
of the week)
 Why the data were collected
2. Control chart
Control charts, also known as Shewhart charts
(after Walter A. Shewhart) or process-behavior
charts, in statistical process control are tools used
to determine if a manufacturing or business
process is in a state of statistical control.
If analysis of the control chart indicates that the
process is currently under control (i.e., is stable,
with variation only coming from sources common
to the process), then no corrections or changes to
process control parameters are needed or desired.
In addition, data from the process can be used to
predict the future performance of the process. If
the chart indicates that the monitored process is
not in control, analysis of the chart can help
determine the sources of variation, as this will

5. result in degraded process performance.[1] A
process that is stable but operating outside of
desired (specification) limits (e.g., scrap rates
may be in statistical control but above desired
limits) needs to be improved through a deliberate
effort to understand the causes of current
performance and fundamentally improve the
process.
The control chart is one of the seven basic tools of
quality control.[3] Typically control charts are
used for time-series data, though they can be used
for data that have logical comparability (i.e. you
want to compare samples that were taken all at
the same time, or the performance of different
individuals), however the type of chart used to do
this requires consideration.
3. Pareto chart
A Pareto chart, named after Vilfredo Pareto, is a type
of chart that contains both bars and a line graph, where
individual values are represented in descending order
by bars, and the cumulative total is represented by the
line.
The left vertical axis is the frequency of occurrence,
but it can alternatively represent cost or another
important unit of measure. The right vertical axis is
the cumulative percentage of the total number of
occurrences, total cost, or total of the particular unit of
measure. Because the reasons are in decreasing order,
the cumulative function is a concave function. To take
the example above, in order to lower the amount of
late arrivals by 78%, it is sufficient to solve the first
three issues.
The purpose of the Pareto chart is to highlight the
most important among a (typically large) set of
factors. In quality control, it often represents the most
common sources of defects, the highest occurring type
of defect, or the most frequent reasons for customer
complaints, and so on. Wilkinson (2006) devised an

6. algorithm for producing statistically based acceptance
limits (similar to confidence intervals) for each bar in
the Pareto chart.
4. Scatter plot Method
A scatter plot, scatterplot, or scattergraph is a type of
mathematical diagram using Cartesian coordinates to
display values for two variables for a set of data.
The data is displayed as a collection of points, each
having the value of one variable determining the position
on the horizontal axis and the value of the other variable
determining the position on the vertical axis.[2] This kind
of plot is also called a scatter chart, scattergram, scatter
diagram,[3] or scatter graph.
A scatter plot is used when a variable exists that is under
the control of the experimenter. If a parameter exists that
is systematically incremented and/or decremented by the
other, it is called the control parameter or independent
variable and is customarily plotted along the horizontal
axis. The measured or dependent variable is customarily
plotted along the vertical axis. If no dependent variable
exists, either type of variable can be plotted on either axis
and a scatter plot will illustrate only the degree of
correlation (not causation) between two variables.
A scatter plot can suggest various kinds of correlations
between variables with a certain confidence interval. For
example, weight and height, weight would be on x axis
and height would be on the y axis. Correlations may be
positive (rising), negative (falling), or null (uncorrelated).
If the pattern of dots slopes from lower left to upper right,
it suggests a positive correlation between the variables
being studied. If the pattern of dots slopes from upper left
to lower right, it suggests a negative correlation. A line of
best fit (alternatively called 'trendline') can be drawn in
order to study the correlation between the variables. An
equation for the correlation between the variables can be
determined by established best-fit procedures. For a linear
correlation, the best-fit procedure is known as linear

7. regression and is guaranteed to generate a correct solution
in a finite time. No universal best-fit procedure is
guaranteed to generate a correct solution for arbitrary
relationships. A scatter plot is also very useful when we
wish to see how two comparable data sets agree with each
other. In this case, an identity line, i.e., a y=x line, or an
1:1 line, is often drawn as a reference. The more the two
data sets agree, the more the scatters tend to concentrate in
the vicinity of the identity line; if the two data sets are
numerically identical, the scatters fall on the identity line
exactly.
5.Ishikawa diagram
Ishikawa diagrams (also called fishbone diagrams,
herringbone diagrams, cause-and-effect diagrams, or
Fishikawa) are causal diagrams created by Kaoru
Ishikawa (1968) that show the causes of a specific
event.[1][2] Common uses of the Ishikawa diagram are
product design and quality defect prevention, to identify
potential factors causing an overall effect. Each cause or
reason for imperfection is a source of variation. Causes
are usually grouped into major categories to identify these
sources of variation. The categories typically include
 People: Anyone involved with the process
 Methods: How the process is performed and the
specific requirements for doing it, such as policies,
procedures, rules, regulations and laws
 Machines: Any equipment, computers, tools, etc.
required to accomplish the job
 Materials: Raw materials, parts, pens, paper, etc.
used to produce the final product
 Measurements: Data generated from the process
that are used to evaluate its quality
 Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates
6. Histogram method

8. A histogram is a graphical representation of the
distribution of data. It is an estimate of the probability
distribution of a continuous variable (quantitative
variable) and was first introduced by Karl Pearson.[1] To
construct a histogram, the first step is to "bin" the range of
values -- that is, divide the entire range of values into a
series of small intervals -- and then count how many
values fall into each interval. A rectangle is drawn with
height proportional to the count and width equal to the bin
size, so that rectangles abut each other. A histogram may
also be normalized displaying relative frequencies. It then
shows the proportion of cases that fall into each of several
categories, with the sum of the heights equaling 1. The
bins are usually specified as consecutive, non-overlapping
intervals of a variable. The bins (intervals) must be
adjacent, and usually equal size.[2] The rectangles of a
histogram are drawn so that they touch each other to
indicate that the original variable is continuous.[3]
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