1. Information quality management
In this file, you can ref useful information about information quality management such as
information quality managementforms, tools for information quality management, information
quality managementstrategies … If you need more assistant for information quality management,
please leave your comment at the end of file.
Other useful material for information quality management:
• qualitymanagement123.com/23-free-ebooks-for-quality-management
• qualitymanagement123.com/185-free-quality-management-forms
• qualitymanagement123.com/free-98-ISO-9001-templates-and-forms
• qualitymanagement123.com/top-84-quality-management-KPIs
• qualitymanagement123.com/top-18-quality-management-job-descriptions
• qualitymanagement123.com/86-quality-management-interview-questions-and-answers
I. Contents of information quality management
==================
Effective integration of information technology into an organization's business processes has
become increasingly crucial to prosperity. IT includes such items as the systems software,
application software, computer hardware, networks and databases associated with managing an
organization's information. The chief information officer leads the department that manages most
aspects of an organization's IT. However, when it comes to implementing quality standards in
the IT realm, most CIOs face so many pressures to deliver systems and technologies which meet
the organization's ever-changing needs that quality falls by the wayside.
The industry as a whole has fallen short of delivering technology that people understand and can
use. Many of the problems occur because of the complexity of technology and the rapid pace of
change. Neither of these conditions are likely to abate; in fact, they're accelerating at an alarming
rate. If flawless execution was an elusive goal in the past, it is even more so today.
Nevertheless, performance can be substantially improved by ensuring that tactical decisions to
develop and support IT emphasize quality. Experience tells us that quality improvements in IT
delivery and service support can be achieved by introducing such considerations as user
satisfaction, integration and flexibility early on in the decision process and reinforcing them
throughout the review process.
Although there are no perfect solutions, there are standards in these areas below which an
application and its support cannot be allowed to fall. Quality management means ensuring that
these standards are rigorously enforced and embedded into the thinking of the organization's
entire IT community.
Past experience
Despite the fact that as an organizational rallying point, total quality management has been
eclipsed by other quality processes, those organizations that embraced the concept surely
benefited from it. Most have made good use of TQM's basic concepts, resulting in greater

2. customer satisfaction and improved product quality. The challenge for IT is to mine from these
experiences valuable lessons. Some sound TQM concepts include:
Set quality measures and standards on customer or user wants and needs.
Place ultimate responsibility for quality with line organizations, and mobilize quality
networks or communities within these organizations.
Make quality a shared responsibility.
Create clear standards and measurements, e.g., "dashboard measurements," which provide
quality status information clearly and quickly.
Make use of existing process measures and checkpoints wherever possible rather than
introduce new measures.
Incorporate and align quality measures and business objectives.
Do not limit interventions to identifying failures to meet standards; require corrective action
plans based on root cause analysis.
Focus on correcting the process that contributed to failure rather than installing short-term
fixes to problems.
The main challenge lies in leveraging and incorporating these concepts into the critical
components of an IT quality function. The following approach helps define an IT quality
function.
Create a clear mission
The ultimate mission of the IT quality function must be to add value to the organization as a
whole and, in particular, to improve IT quality in every aspect, including applications, the
infrastructure, even the help desk. However, the IT quality function cannot serve as the sole
owner of quality; it must not try to resolve all quality issues alone. Further, it shouldn't operate in
an after-the-fact quality assurance mode. Instead, it should identify issues that impede quality
and facilitate their rapid resolution.
Taking a broad cross-functional perspective of IT quality issues, the mission of the quality
function must:
Provide discipline and rigor to address quality improvements.
Define top quality goals and measures.
Drive consistent, agreed-to quality measures and corresponding management systems.
Identify and prioritize IT quality issues from an end-to-end perspective.
Serve as a focal point for an extended IT quality network comprised of end users and
providers.
Assign issues to owners for resolution, drive root cause analysis, and track results.
Promote knowledge sharing of best practices relative to quality management in IT.
Drive preventive defect activities so that quality does not become an afterthought.
Set specific objectives
Quality objectives need to focus, ultimately, on user satisfaction and key areas problematic to the
IT area. They should answer the question, "What does the IT quality function want to
accomplish?" Sample objectives include: improve user satisfaction, control IT costs, reduce
defects, improve IT infrastructure and application stability, and improve user perception of IT
quality.
Developsimple strategies

3. Quality strategies should answer the question, "How will we achieve our objectives?" A simple
strategy would be to address only broad, high-priority quality issues that affect the objectives.
Or, the quality function could focus on customer issues rather than internal issues. Another
strategy would be to use a small quality team and an extended quality community rather than
build a large quality organization within the information systems department.
To be effective, the quality function must avoid the tendency to grow a new bureaucracy. It must
be committed to "staying the course" in creating a quality culture for the IT community.
Designa small, focused quality function
The IT quality function must be created with certain design points, which need to include key
aspects, such as:
Size: How large should the quality function be?
Structure: How should the function be organized?
Scope: What should be the focus?
Roles and responsibilities: Who should be responsible for what?
Skills: What kind of talent and capabilities are needed?
Measures: How should performance be tracked?
The quality function should be comprised of a small, focused team within the IT community.
The key is to avoid creating a large, bureaucratic entity, but rather employ a small team that
represents an extended community in the business functions.
The IT quality function should be led by an influential executive reporting directly to the CIO or
the chief financial officer. This will ensure that the new function has the required influence and
can manage across the organization effectively. The small team of quality advocates will report
directly to the quality executive.
The IT quality function should focus on broad, cross-functional quality issues that are high
priority and critical in nature to resolve. From an IT perspective, the scope should include such
areas as application development, networking, databases, data centers and end-user support (help
desk). From a business perspective, the function's responsibilities should include virtually the
entire organization because most business areas will likely have some sort of IT infrastructure or
application.
The IT quality leader will work with business executives and the CIO, while the quality
advocates will work with the extended quality community. The leader's key responsibilities are:
Provide overall leadership in achieving IT quality objectives.
Represent an end-to-end perspective of IT quality issues.
Ensure linkage of IT quality and process improvement activities across the organization.
Communicate clearly the function's mission, objectives, issues, measures, etc.
Include IT quality objectives and initiatives in the IT strategy.
Quality advocates' responsibilities include:
Identify and prioritize IT quality issues.
Drive root cause analysis of IT quality issues.
Assist in creating action plans pursuant to root cause analysis.
Drive preventive actions to eliminate defect replication.
Anticipate and address quality issues in their specific areas.
Serve as focal points for the extended quality network.

4. The IT quality function calls for a high-powered, extremely talented team of "A" players.
Therefore, the quality leader must be able to build and sustain an excellent executive network.
The leader should consistently demonstrate a high sense of urgency and motivate people to
address issues that concern the entire organization.
For their part, quality advocates should be adept at communicating with superiors and peers,
analyzing issues and working in cross-functional teams.
The business executives, the CIO and the IT quality leader must agree to a set of measurements
that will track the progress of IT quality initiatives and issues. While consistency between groups
is desirable, it is more important to relate the measures logically to the activities involved. The
quality measures should reflect the items that remain important to users and those that drive user
satisfaction. Each measure should include a target and time frame. An example of a user-focused
measure: User's perception of IT performance (measure), increase to 75 percent (target), by
second quarter 1999 (time frame).
User-focused measures should be based on the user's view of IT quality. However, the IT quality
function must also measure the internal drivers affecting user measures. For example: Number of
defects per user (measure), reduce by 10 percent (target), by fourth quarter 1999 (time frame).
Take the next steps
In order to jump-start an IT quality effort, find and designate an IT quality leader and enlist IT
quality advocates. Once the team is in place, members can begin to establish connections into the
extended quality community to build its quality network. As the team and the quality network
become established, they can further solidify the components of the IT quality function (mission,
objectives, measures, etc.). Improvements in IT quality will increase over time as the function
and extended quality network evolve, relationships mature and quality issues are resolved.
==================
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

5. 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
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

6. 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
algorithm for producing statistically based acceptance
limits (similar to confidence intervals) for each bar in
the Pareto chart.
4. Scatter plot Method

7. 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
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

8. 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

9. 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]
III. Other topics related to Information quality management (pdf download)
quality management systems
quality management courses
quality management tools
iso 9001 quality management system
quality management process
quality management system example
quality system management
quality management techniques
quality management standards
quality management policy
quality management strategy
quality management books