This document provides information about quality management processes and tools. It discusses project management practices used including assigning a project manager, using online project management tools, and source control version management. It also outlines the organization's quality management approach including adopting CMMI and ISO 9001 standards, ensuring process, technology, and workforce quality, and protecting client commitments through business continuity plans and intellectual property controls. Finally, it describes several quality management tools used including check sheets, control charts, Pareto charts, scatter plots, Ishikawa diagrams, histograms, and others.

1. Quality management processes
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I. Contents of quality management processes
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Our team has highly skilled project managers who have successfully delivered projects for big
companies like Intel, Google & Yahoo. Our senior project managers are also certified by PMI as
PMP (Project Management Professional). The Project Management Institute (PMI) is a
professional organization for the project management profession with the purpose of advancing
project management. PMI aims for standards that describe good practices, globally recognized
credentials that certify project management expertise, and resources for professional
development, networking and community.
Project manager assigned to your project will be closely working with you and development
team to make sure timely delivery and will be speaking to you at regular intervals to present the
project progress reports and share deliverable for milestones etc.
We use online project management and collaboration tool for Milestones, Tickets and Task
Tracking and also documentation for important discussions. Every communication related with
the product must be done through this tool. This is required for effective tracking of all the
communications and change requests.
We use SVN for Version management and it is hosted on our Amazon EC2 Instance. This is
required for organized release management and version rollbacks in case of any need.
Quality Management
We strive to deliver software solutions that exceed customer expectations, through an
organizational culture of continuous improvement of the Quality Management System and
individual commitment to quality.
To ensure the maintenance of quality, we adopt the SEI CMMI model’s best practices for
planning, testing, project management, requirements and configurations. To complement this and

2. to further enhance and improve our technology, we also apply ISO 9001:2000 best practices for
controlling and measuring our performance and process quality.
Each of our team members – from the bottom to the top of the organization – adheres to our
internal standards of quality. Our management is focused on keeping the work environment
quality conscious for the benefit of our clients at all times. By streamlining our services our
client is assured of an on-time, in-budget delivery.
We synergize three important factors for their different processes and functions to inculcate
stringent quality adherence:
Process Quality
Our processes have been optimized according to industry standards and regulations to ensure
smooth functioning. Our Quality Control Department supervises our entire software
development process which gives us a clear view of the level of quality being provided to each
of our clients.
Technology Quality
We are committed to harnessing up-to-date technologies to give our clients the most beneficial
solutions possible. We therefore work with the newest tools and applications in order to compete
and help our client compete in the dynamic marketplace.
Workforce Quality
We realize that excellent work output relies on the people who are behind it. Based on this belief,
we hire only the most professional, experienced, and talented personnel possible. In addition to
our strict recruitment standards, we provide our team members with an open and friendly
environment which gives them an opportunity for self-improvement and growth.
Client Protection
Our reputation and business in the market depends on deliverable quality standards. Hence, we
will never compromise on Quality. In addition to the above, we strive to protect the
commitments we make to our clients through organizational and project level:
Organization Level
Business Continuity / Disaster Recovery: A disaster recovery mechanism is in place to cover
access to the software, data, and/or hardware that are needed to resume the performance of
normal, critical business functions after the event of either a natural disaster or a disaster caused
by human error.
IP Control: All team members sign Intellectual Property Protection agreements which prevent
them to share any project / product related information to anyone outside the organization. There
are full blown policies in place to handle sensitive business information. Read more about IP
Control click here
Project Level
Prototype Requirement Management: We utilize both agile & Prince2 methodologies. We
undertake requirement validation at each step, typically by way of building quick prototypes/
wireframes. This control mechanism ensures that the end product matches the requirements.
Source Control – our SVN repository is used for management of source code. Access to the
source code can be given to stakeholders. The source code is backed up on multiple servers to
ensure that there is no data loss at any stage.

3. Staging Management – All the development work is first deployed on a staging server. User
Acceptance Testing is performed on the staging server. Typically the development team has
access to the staging server only, the deployment team having access to the live server. This
ensures both the minimization of errors and continuity of the live server.
Bug Management – A bug management system is used to manage product Quality. Manual and
Automated Test Cases: The test cases are built at the early stage of the project, then validated by
the client, and serving as the project completion criteria.
Unit Testing – The code is written with Unit Test Cases. This control ensures a comprehensive
change management process without introducing bugs.
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III. Quality management tools
1. Check sheet
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

4. 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
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

5. 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
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

6. 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
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.

7. 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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