SlideShare a Scribd company logo
Quality metrics in project management
In this file, you can ref useful information about quality metrics in project management such as
quality metrics in project managementforms, tools for quality metrics in project management,
quality metrics in project managementstrategies … If you need more assistant for quality metrics
in project management, please leave your comment at the end of file.
Other useful material for quality metrics in project 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 quality metrics in project management
==================
“If you don’t measure something, you can’t change it. The process of leadership is one of
painting a vision, then saying how you’re going to get there, and then measuring whether you’re
actually getting there. Otherwise, you risk only talking about great things but not accomplishing
them.” Mitt Romney
Continual improvement is a prerequisite for any organization’s success. A continual
improvement process, also often called a continuous improvement process (abbreviated
as CIP or CI), is an ongoing effort to improve products, services, or processes. These efforts can
seek “incremental” improvement over time or “breakthrough” improvement all at once. Delivery
(customer valued) processes are constantly evaluated and improved in the light of their
efficiency, effectiveness and flexibility (Wiki).
Gauging whether there is incremental improvement and setting up mechanisms to track and
measure these improvements is the difficult part and this is where Metrics come in. I am
passionate about metrics and have written about my favourite performance management metrics
in business,sales and human resourcesearlier. In this guest post, Kavita Verma draws upon her
PMO experiences to list the most effective metrics that can be used by project managers to
determine the success of their projects.
‘Metric’ is defined as “Standard of measurement by which efficiency, progress, performance,
productivity, quality of a deliverable, process, project or product can be assessed”. Metrics help
in building predictability, improving organization’s decision making ability, and lay out what is
working and what is not working within the organization and help guide the management focus
in the right directions.
Project management performance metrics enable Project managers to:
 Assess status of ongoing project in terms of schedule, cost and profitability.
 Foresee any potential risks.
 Nail down the problems much before they become severe.
 Keep a check on project profitability.
 Assess productivity of team.
 Assess quality of work products to be delivered.
There can be different project management metrics defined based on complexity and nature of
project. However, following five performance metric groups cover all the important aspects of a
project to measure during execution:
Performance Metric #1: Schedule and Effort/Cost Variance
The goal of this metric is to measure the performance as well as progress of the project against
signed baselines. This metric is very important and is the base for profitability of project. The
EVM (Earned Value Management) concept, as defined by PMI standard PMBOK, is the
commonly used method to track this metric. It integrates project scope, cost and schedule
measures to help the PM to assess and measure project performance and progress. The principles
of EVM can be applied to all projects, in any industry. Under this method, at any given point in
time, project performance to date is used to extrapolate the expected costs and duration at project
completion. This technique uses past performance (i.e. actuals) to more accurately forecast future
performance. EVM develops and monitors three key dimensions of each work package:
Planned Value (PV): How much you planned to spend for the work you planned to do i.e. it is
the authorized budget assigned to the work to be accomplished for an activity or work
breakdown structure component. Total PV is also known as Budget at Completion (BAC). PV at
any stage = (Planned % Complete) X (BAC)
Earned Value (EV): Earned value is the value of work performed expressed in terms of the
approved budget assigned to that work for an activity or work breakdown structure component. It
is the authorized work that has been completed, against the authorized budget for such completed
work i.e. EV is ‘how much you planned to spend for the work you actually did’. Earned Value is
also known as the Budgeted Cost of Work Performed (BCWP).
Actual cost (AC): Actual cost is the total cost actually incurred and recorded in accomplishing
work performed for an activity or work breakdown structure component. It is the total cost
incurred in accomplishing the work that the EV measured. I.e. how much you spent for the work
you actually did. Actual Cost is also known as the Actual Cost of Work Performed (ACWP).
Using these three variables project Schedule variance and Cost variance metrics can be derived
which shows if the project is running over or under budget; project is running behind or ahead of
schedule, as follows:
Schedule Variance (SV) is the measure of schedule performance of the project. It is the
difference of Earned value and the planned value i.e. SV = EV – PV
 Positive result means that you are ahead of schedule.
 Negative result means that you are behind schedule.
Cost Variance (CV) is the measure of cost performance on the project. It is equal to earned value
(EV) minus actual costs (AC). Any negative CV is often non-recoverable to the project.
CV = EV – AC
 Positive result means that you are under budget.
 Negative result means that you are over budget.
Since EVM method allows PM to extrapolate the expected costs and duration at project
completion based on project performance to date, PM can develop a forecast for the estimate at
completion (EAC) which may differ from the budget at completion (BAC) based on project
performance. Forecasting of EAC involves making estimates or prediction of conditions and
events in the project’s future based on information and knowledge available at the time of
forecasting. EAC is typically based on actual cost (AC) incurred for work completed, plus an
estimate to complete (ETC) the remaining work. I.e. EAC = AC + ETC.
Based on this PM can also derive another metric, Variance at completion (VAC) = BAC – EAC
Performance Metric #2 – Productivity: Resource Utilization
The objective of this metric is to measure productivity of resources involved in project and let
PM assess over or under-utilization cases.
Utilization% = Total Effort spent by resource/Total Budgeted Effort for the resource
Budgeted effort is the planned billable work of resource. Any over-utilization and under-
utilization indicated by this metric has an impact on the project’s profitability. It is important for
the PM to track this metric very closely and find out the reason for deviations and the action
items to bring back resource utilization to optimal level. Delayed projects, increased ramp up
activities, less work provided by customer, unplanned vacations, less competent resources can
impact this metric. To get better control over this metric, robust time reporting systems should be
available in the organization. Using this, PM can analyze effort distribution across different
project phases/activities. For e.g. Effort distribution can tell PM that how much effort is being
spent on defect resolution, customer support or design activities. PM can take corrective actions
based on this, if required. For instance, if the resource is complaining that customer support is
taking considerable time but the effort distribution shows it otherwise, PM can see where the
corrections are needed on what resource is doing. Effort distribution from time reporting systems
can also tell the areas of improvement for better estimations/planning for the next project.
Performance Metric #3: Change requests to Scope of work
Signed Scope baseline with customer forms the baseline for the entire project planning and
development. Any change to signed scope should happen in controlled manner. So here comes
another important metric for PM to track i.e. the number of change requests coming from
customer for the already signed scope of work. Each and every change request, once approved
by internal change control board (CCB), requires update to Scope baseline which in turn has a
cascade impact on cost baselines and schedule baselines and resource plans. Uncontrolled
change requests often result in project scope creep and further impact negatively on the project
cost/schedule, which is the worst thing to happen for any project. PM should never allow such
scope creep. Based on the magnitude of the variance from original scope baseline, CCB should
decide whether to accept or reject the change request and this decision should be communicated
back to customer. In case of acceptance of change request, the impact on project cost and
schedule should be clearly communicated in written form to customer and a written agreement
from customer secured on those from customer before proceeding.
Performance Metric #4: Quality and Customer Satisfaction
Throughout the execution of project, Quality Assurance should always be on the radar of project
manager. Quality here is defined as the number of severe, medium or low defects delivered
through the lifetime of the project. It indicates the health of the deliverable to the end user and
drives the Customer Satisfaction. PM needs to define, based on project type, what severe, low
and medium means. Quality should be reported throughout the life of the project; the later
defects are caught, the more impact they will have on the project. Under quality metrics,
following are the key ones to track:
Defect density = Total number of defects found/ Measure of size.
For e.g. in case of software projects this can be: how many defects are found in 1KLOC (Kilo
line of code). In general, size measure can be considered as planned effort like ‘person day total
planned effort’.
Defect age
Number of days since the defect is open and not fixed. It can also be inferred as the time
customer has been waiting for their issues to get resolved,
Defect resolution rate = Total number of defects resolved/ Total effort spent
Rate of closing the open defects over a period of time. If the rate of resolution is not in line with
the defects being opened over a particular time, this indicates to the PM a situation of concern.
Number of defects reported by customer
PM should keep this as a separate metric to differentiate from the defects reported out of internal
testing and the defects reported by end user i.e. Customer. Customer satisfaction depends a lot on
the quality of deliverable provided and on how fast defects raised by customer are resolved.
As said above, the later defects are caught, the more impact they will have on the project, it is
worth to mention here about Pareto’s principle i.e. 80/20 principle, which PM can use to
categorize causes of defects and late time entry relationship. As per this law 80% of the problems
are due to 20% of the causes. PM can concentrate on these 20% causes impacting the project
most.
Performance Metric #5: Gross Margin
Gross Margin (as I wrote in my earlier post on key performance metrics) is the mother of all
metrics and the quickest way to determine if your business in on track or not and acts as an early
warning system to put in place margin improvement initiatives. Ultimate goal of project
execution is to bring revenue to organization with the approved gross margin. Gross margin
(GM) is basically the difference of total revenue and the total cost spent on project i.e. profit.
When a project is started, certain GM levels for the project are approved by project sponsor. This
approved GM value is generally based on project scope definition, duration, a forecast of
resources: onsite, offshore and organization’s investment analysis. Project PNL (Profit and Loss)
statement gives a way to PM for tracking his/her projects GM metric at any point of time. For
this, PNL statements and forecasts should be current documents i.e. changes in project
parameters need to be reflected quickly in this statement to keep the PM informed about any
potential risks to project profitability. All the above four project management performance
metrics impact this metric, if not handled in controlled manner. A good organizational level PNL
tool rather than manual excel sheets reduces the overhead on PM here.
While working with all of these metrics, following points should be very clear in the project
manager’s mind:
 What to measure
 How to measure
 How to gather data to measure and represent
 How to analyze gathered data and what actions to be defined based on that
 How to show improved effectiveness of metrics by using improved numbers ‘before’ and ‘after’
In my view these five project management performance metrics are critical metrics to be tracked
while taking charge and during execution of a project. The continued analysis of these metrics
provides additional insights into what is working and what is not, allowing the PM to make
appropriate improvements. These metrics also help in building up historical data for similar kind
of projects so that in future, better project planning can be done. Success story of project can be
then built up based on the effectiveness of defined metrics by showing the improved numbers
“before” and “after”. This ensures that the effort spent by team in collection and measurement of
data for these metrics is leading to continuous improvements and not just an overhead activity.
In summary, metrics improve decision making ability by providing the foundation and rationale
for the decision by making explicit what is usually implicit in the decision-making process.
So what are your experiences when it comes to project management performance metrics and
tracking? What are some of the other project management metrics you have been tracking? We
would love to hear and learn from you.
==================
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
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
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
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.
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
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 Quality metrics in project 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

More Related Content

What's hot

The role of the project manager
The role of the project managerThe role of the project manager
The role of the project manager
Project Management Solutions
 
Project Management and Process
Project Management and ProcessProject Management and Process
Project Management and Process
Muhammad Rehman
 
08 pmp quality management exam
08 pmp quality management exam08 pmp quality management exam
08 pmp quality management exam
Jamil Faraj , PMP
 
Project scope management
Project scope managementProject scope management
Project scope management
Anit Roy
 
PMP Training - 10 project communication management
PMP Training - 10 project communication managementPMP Training - 10 project communication management
PMP Training - 10 project communication management
ejlp12
 
Roles of project managers in oe
Roles of project managers in oeRoles of project managers in oe
Roles of project managers in oe
Aswin prakash i , Xantus Technologies
 
1 successful project management, & concepts
1 successful project management, & concepts1 successful project management, & concepts
1 successful project management, & concepts
Daw Juguilon
 
Project management
Project managementProject management
Project management
Susmitha RANGU
 
06. Project Management Process Groups
06. Project Management Process Groups06. Project Management Process Groups
06. Project Management Process Groups
BhuWan Khadka
 
PMO (Project Management Office)
PMO (Project Management Office)PMO (Project Management Office)
PMO (Project Management Office)
Dilawar Abbas
 
Integrated Project Management
Integrated Project ManagementIntegrated Project Management
Integrated Project Management
Inam Khosa
 
Projectcontrol
ProjectcontrolProjectcontrol
Projectcontrol
Raj Sampat
 
Template kick off-meeting
Template kick off-meeting Template kick off-meeting
Template kick off-meeting
Hari Krishna
 
9.0 Project Resource Management Overview
9.0 Project Resource Management Overview9.0 Project Resource Management Overview
9.0 Project Resource Management Overview
DavidMcLachlan1
 
Project Management: Integrating a PMO Case Study by David Bustin
Project Management: Integrating a PMO Case Study by David BustinProject Management: Integrating a PMO Case Study by David Bustin
Project Management: Integrating a PMO Case Study by David Bustin
David Bustin
 
Project integration management
Project integration managementProject integration management
Project integration management
Prabudh Dhingra
 
Project Management Concepts (from PMBOK 5th Ed)
Project Management Concepts (from PMBOK 5th Ed)Project Management Concepts (from PMBOK 5th Ed)
Project Management Concepts (from PMBOK 5th Ed)
Jeremy Jay Lim
 
Project cost management-slides
Project cost management-slidesProject cost management-slides
Project cost management-slides
masilamani ramasamy
 
Project Management
Project ManagementProject Management
Project Management
Hamdard University
 
PMP Lecture 3: Project Management Processes
PMP Lecture 3: Project Management ProcessesPMP Lecture 3: Project Management Processes
PMP Lecture 3: Project Management Processes
Mohamed Loey
 

What's hot (20)

The role of the project manager
The role of the project managerThe role of the project manager
The role of the project manager
 
Project Management and Process
Project Management and ProcessProject Management and Process
Project Management and Process
 
08 pmp quality management exam
08 pmp quality management exam08 pmp quality management exam
08 pmp quality management exam
 
Project scope management
Project scope managementProject scope management
Project scope management
 
PMP Training - 10 project communication management
PMP Training - 10 project communication managementPMP Training - 10 project communication management
PMP Training - 10 project communication management
 
Roles of project managers in oe
Roles of project managers in oeRoles of project managers in oe
Roles of project managers in oe
 
1 successful project management, & concepts
1 successful project management, & concepts1 successful project management, & concepts
1 successful project management, & concepts
 
Project management
Project managementProject management
Project management
 
06. Project Management Process Groups
06. Project Management Process Groups06. Project Management Process Groups
06. Project Management Process Groups
 
PMO (Project Management Office)
PMO (Project Management Office)PMO (Project Management Office)
PMO (Project Management Office)
 
Integrated Project Management
Integrated Project ManagementIntegrated Project Management
Integrated Project Management
 
Projectcontrol
ProjectcontrolProjectcontrol
Projectcontrol
 
Template kick off-meeting
Template kick off-meeting Template kick off-meeting
Template kick off-meeting
 
9.0 Project Resource Management Overview
9.0 Project Resource Management Overview9.0 Project Resource Management Overview
9.0 Project Resource Management Overview
 
Project Management: Integrating a PMO Case Study by David Bustin
Project Management: Integrating a PMO Case Study by David BustinProject Management: Integrating a PMO Case Study by David Bustin
Project Management: Integrating a PMO Case Study by David Bustin
 
Project integration management
Project integration managementProject integration management
Project integration management
 
Project Management Concepts (from PMBOK 5th Ed)
Project Management Concepts (from PMBOK 5th Ed)Project Management Concepts (from PMBOK 5th Ed)
Project Management Concepts (from PMBOK 5th Ed)
 
Project cost management-slides
Project cost management-slidesProject cost management-slides
Project cost management-slides
 
Project Management
Project ManagementProject Management
Project Management
 
PMP Lecture 3: Project Management Processes
PMP Lecture 3: Project Management ProcessesPMP Lecture 3: Project Management Processes
PMP Lecture 3: Project Management Processes
 

Viewers also liked

Project Metrics & Measures
Project Metrics & MeasuresProject Metrics & Measures
Project Metrics & Measures
Anand Subramaniam
 
Quality Metrics
Quality Metrics Quality Metrics
Quality Metrics
Haroon Abbu
 
Quality Metrics
Quality MetricsQuality Metrics
Project Quality Management
Project Quality ManagementProject Quality Management
Project Quality Management
GiO Friginal
 
5 of 5 Quality Metrics & Science by Obaid Ali
5 of 5  Quality Metrics & Science by Obaid Ali5 of 5  Quality Metrics & Science by Obaid Ali
5 of 5 Quality Metrics & Science by Obaid Ali
Obaid Ali / Roohi B. Obaid
 
InfinityQS_Quality Metrics Survival Handbook final_042413
InfinityQS_Quality Metrics Survival Handbook final_042413InfinityQS_Quality Metrics Survival Handbook final_042413
InfinityQS_Quality Metrics Survival Handbook final_042413
Vanessa Stirling
 
Overview of Multidimensional Quality Metrics (QTLaunchPad)
Overview of Multidimensional Quality Metrics (QTLaunchPad)Overview of Multidimensional Quality Metrics (QTLaunchPad)
Overview of Multidimensional Quality Metrics (QTLaunchPad)
Arle Lommel
 
Wind Power in Maine
Wind Power in MaineWind Power in Maine
Wind Power in Maine
Hall-Dale
 
Project quality (and test process) metrics
Project quality (and test process) metricsProject quality (and test process) metrics
Project quality (and test process) metrics
Zbyszek Mockun
 
Quality metrics project management
Quality metrics project managementQuality metrics project management
Quality metrics project management
selinasimpson1501
 
3 of 5 Creating the Quality Culture by Sultan Ghani
3 of 5  Creating the Quality Culture by Sultan Ghani3 of 5  Creating the Quality Culture by Sultan Ghani
3 of 5 Creating the Quality Culture by Sultan Ghani
Obaid Ali / Roohi B. Obaid
 
Software Quality KPI
Software Quality KPISoftware Quality KPI
Software Quality KPI
cherapa
 
Quality kpi examples
Quality kpi examplesQuality kpi examples
Quality kpi examples
gallasbrows
 
Software Quality Metrics for Testers - StarWest 2013
Software Quality Metrics for Testers - StarWest 2013Software Quality Metrics for Testers - StarWest 2013
Software Quality Metrics for Testers - StarWest 2013
XBOSoft
 
Project quality management.ppt msm
Project quality management.ppt msmProject quality management.ppt msm
Project quality management.ppt msm
Development Associates Link International (DALI) Inc
 
10 principles for designing quality control scorecard and KPIs
10 principles for designing quality control scorecard and KPIs10 principles for designing quality control scorecard and KPIs
10 principles for designing quality control scorecard and KPIs
Aleksey Savkin
 
Project quality management
Project quality managementProject quality management
Project quality management
Mohammad Ashraf Khan, PMP
 
Quality Process KPIs Metrics
Quality Process KPIs MetricsQuality Process KPIs Metrics
Quality Process KPIs Metrics
Douglas Gabel
 
Construction quality management plan (Construction Productivity Analysis)
Construction quality management plan (Construction Productivity Analysis)Construction quality management plan (Construction Productivity Analysis)
Construction quality management plan (Construction Productivity Analysis)
Jayson Narito
 
Quality management slides
Quality management slidesQuality management slides
Quality management slides
Saba Afaq
 

Viewers also liked (20)

Project Metrics & Measures
Project Metrics & MeasuresProject Metrics & Measures
Project Metrics & Measures
 
Quality Metrics
Quality Metrics Quality Metrics
Quality Metrics
 
Quality Metrics
Quality MetricsQuality Metrics
Quality Metrics
 
Project Quality Management
Project Quality ManagementProject Quality Management
Project Quality Management
 
5 of 5 Quality Metrics & Science by Obaid Ali
5 of 5  Quality Metrics & Science by Obaid Ali5 of 5  Quality Metrics & Science by Obaid Ali
5 of 5 Quality Metrics & Science by Obaid Ali
 
InfinityQS_Quality Metrics Survival Handbook final_042413
InfinityQS_Quality Metrics Survival Handbook final_042413InfinityQS_Quality Metrics Survival Handbook final_042413
InfinityQS_Quality Metrics Survival Handbook final_042413
 
Overview of Multidimensional Quality Metrics (QTLaunchPad)
Overview of Multidimensional Quality Metrics (QTLaunchPad)Overview of Multidimensional Quality Metrics (QTLaunchPad)
Overview of Multidimensional Quality Metrics (QTLaunchPad)
 
Wind Power in Maine
Wind Power in MaineWind Power in Maine
Wind Power in Maine
 
Project quality (and test process) metrics
Project quality (and test process) metricsProject quality (and test process) metrics
Project quality (and test process) metrics
 
Quality metrics project management
Quality metrics project managementQuality metrics project management
Quality metrics project management
 
3 of 5 Creating the Quality Culture by Sultan Ghani
3 of 5  Creating the Quality Culture by Sultan Ghani3 of 5  Creating the Quality Culture by Sultan Ghani
3 of 5 Creating the Quality Culture by Sultan Ghani
 
Software Quality KPI
Software Quality KPISoftware Quality KPI
Software Quality KPI
 
Quality kpi examples
Quality kpi examplesQuality kpi examples
Quality kpi examples
 
Software Quality Metrics for Testers - StarWest 2013
Software Quality Metrics for Testers - StarWest 2013Software Quality Metrics for Testers - StarWest 2013
Software Quality Metrics for Testers - StarWest 2013
 
Project quality management.ppt msm
Project quality management.ppt msmProject quality management.ppt msm
Project quality management.ppt msm
 
10 principles for designing quality control scorecard and KPIs
10 principles for designing quality control scorecard and KPIs10 principles for designing quality control scorecard and KPIs
10 principles for designing quality control scorecard and KPIs
 
Project quality management
Project quality managementProject quality management
Project quality management
 
Quality Process KPIs Metrics
Quality Process KPIs MetricsQuality Process KPIs Metrics
Quality Process KPIs Metrics
 
Construction quality management plan (Construction Productivity Analysis)
Construction quality management plan (Construction Productivity Analysis)Construction quality management plan (Construction Productivity Analysis)
Construction quality management plan (Construction Productivity Analysis)
 
Quality management slides
Quality management slidesQuality management slides
Quality management slides
 

Similar to Quality metrics in project management

Project Management 12
Project Management 12Project Management 12
Project Management 12
Tathagat Varma
 
UNIT 14 GROUP ASSIGNMENTPart 11. Describe how a project manager ca.docx
UNIT 14 GROUP ASSIGNMENTPart 11. Describe how a project manager ca.docxUNIT 14 GROUP ASSIGNMENTPart 11. Describe how a project manager ca.docx
UNIT 14 GROUP ASSIGNMENTPart 11. Describe how a project manager ca.docx
ouldparis
 
Presentation on Quality Management
Presentation on Quality ManagementPresentation on Quality Management
Presentation on Quality Management
Md. Masudur Rahman, PMP
 
Project Cost Management
Project Cost ManagementProject Cost Management
Project Cost Management
mohamed elashri
 
2.07 cost management 1
2.07 cost management 12.07 cost management 1
2.07 cost management 1
reddvise
 
formation.docx
formation.docxformation.docx
formation.docx
GuendouzGuendouz
 
A brief on project cost management
A brief on project cost managementA brief on project cost management
A brief on project cost management
Imran Jamil
 
CPM lecture note 4,5,6&7.pdf
CPM lecture note 4,5,6&7.pdfCPM lecture note 4,5,6&7.pdf
CPM lecture note 4,5,6&7.pdf
DejeneTsegaye6
 
CPM lecture note 4,5,6&7.pdf
CPM lecture note 4,5,6&7.pdfCPM lecture note 4,5,6&7.pdf
CPM lecture note 4,5,6&7.pdf
DejeneTsegaye6
 
Project cost control
Project cost controlProject cost control
Project cost control
Sourabh Modgil
 
Construction Cost Control
Construction Cost ControlConstruction Cost Control
Construction Cost Control
Sunayana Miglani
 
Chap05_Project Monitoring and Control.pdf
Chap05_Project Monitoring and Control.pdfChap05_Project Monitoring and Control.pdf
Chap05_Project Monitoring and Control.pdf
VarunSubramanyam
 
Basic Concepts of Earned Value Management.pdf
Basic Concepts of Earned Value Management.pdfBasic Concepts of Earned Value Management.pdf
Basic Concepts of Earned Value Management.pdf
Elyes ELEBRI
 
engineering economics lect 8-10 final.pptx
engineering economics lect 8-10 final.pptxengineering economics lect 8-10 final.pptx
engineering economics lect 8-10 final.pptx
Dr. ABEER KHALID MANSOUR
 
INFORMATION SYTEMS .docx
INFORMATION SYTEMS                                                .docxINFORMATION SYTEMS                                                .docx
INFORMATION SYTEMS .docx
pauline234567
 
T24 Temenos Earned Value Management & Project Planning Presentation
T24 Temenos Earned Value Management & Project Planning PresentationT24 Temenos Earned Value Management & Project Planning Presentation
T24 Temenos Earned Value Management & Project Planning Presentation
Michael Gowlett PMP, Prince 2 Practitioner
 
Project Mangement
Project MangementProject Mangement
Project Mangement
Gaurav Shrivastava
 
07.cost management updated
07.cost management updated07.cost management updated
07.cost management updated
Shraddha PMP
 
Project Cost Management
Project Cost ManagementProject Cost Management
Project Cost Management
Kateri Manglicmot
 
L03 integration management
L03 integration managementL03 integration management
L03 integration management
Asa Chan
 

Similar to Quality metrics in project management (20)

Project Management 12
Project Management 12Project Management 12
Project Management 12
 
UNIT 14 GROUP ASSIGNMENTPart 11. Describe how a project manager ca.docx
UNIT 14 GROUP ASSIGNMENTPart 11. Describe how a project manager ca.docxUNIT 14 GROUP ASSIGNMENTPart 11. Describe how a project manager ca.docx
UNIT 14 GROUP ASSIGNMENTPart 11. Describe how a project manager ca.docx
 
Presentation on Quality Management
Presentation on Quality ManagementPresentation on Quality Management
Presentation on Quality Management
 
Project Cost Management
Project Cost ManagementProject Cost Management
Project Cost Management
 
2.07 cost management 1
2.07 cost management 12.07 cost management 1
2.07 cost management 1
 
formation.docx
formation.docxformation.docx
formation.docx
 
A brief on project cost management
A brief on project cost managementA brief on project cost management
A brief on project cost management
 
CPM lecture note 4,5,6&7.pdf
CPM lecture note 4,5,6&7.pdfCPM lecture note 4,5,6&7.pdf
CPM lecture note 4,5,6&7.pdf
 
CPM lecture note 4,5,6&7.pdf
CPM lecture note 4,5,6&7.pdfCPM lecture note 4,5,6&7.pdf
CPM lecture note 4,5,6&7.pdf
 
Project cost control
Project cost controlProject cost control
Project cost control
 
Construction Cost Control
Construction Cost ControlConstruction Cost Control
Construction Cost Control
 
Chap05_Project Monitoring and Control.pdf
Chap05_Project Monitoring and Control.pdfChap05_Project Monitoring and Control.pdf
Chap05_Project Monitoring and Control.pdf
 
Basic Concepts of Earned Value Management.pdf
Basic Concepts of Earned Value Management.pdfBasic Concepts of Earned Value Management.pdf
Basic Concepts of Earned Value Management.pdf
 
engineering economics lect 8-10 final.pptx
engineering economics lect 8-10 final.pptxengineering economics lect 8-10 final.pptx
engineering economics lect 8-10 final.pptx
 
INFORMATION SYTEMS .docx
INFORMATION SYTEMS                                                .docxINFORMATION SYTEMS                                                .docx
INFORMATION SYTEMS .docx
 
T24 Temenos Earned Value Management & Project Planning Presentation
T24 Temenos Earned Value Management & Project Planning PresentationT24 Temenos Earned Value Management & Project Planning Presentation
T24 Temenos Earned Value Management & Project Planning Presentation
 
Project Mangement
Project MangementProject Mangement
Project Mangement
 
07.cost management updated
07.cost management updated07.cost management updated
07.cost management updated
 
Project Cost Management
Project Cost ManagementProject Cost Management
Project Cost Management
 
L03 integration management
L03 integration managementL03 integration management
L03 integration management
 

More from selinasimpson1601

Quality software project management
Quality software project managementQuality software project management
Quality software project management
selinasimpson1601
 
Quality management system template free
Quality management system template freeQuality management system template free
Quality management system template free
selinasimpson1601
 
Quality management system planning
Quality management system planningQuality management system planning
Quality management system planning
selinasimpson1601
 
Quality management system iso
Quality management system isoQuality management system iso
Quality management system iso
selinasimpson1601
 
Quality management project
Quality management projectQuality management project
Quality management project
selinasimpson1601
 
Quality management programs
Quality management programsQuality management programs
Quality management programs
selinasimpson1601
 
Quality management maturity grid
Quality management maturity gridQuality management maturity grid
Quality management maturity grid
selinasimpson1601
 
Quality management courses in india
Quality management courses in indiaQuality management courses in india
Quality management courses in india
selinasimpson1601
 
Operations and quality management
Operations and quality managementOperations and quality management
Operations and quality management
selinasimpson1601
 
Information quality management
Information quality managementInformation quality management
Information quality management
selinasimpson1601
 
European foundation of quality management
European foundation of quality managementEuropean foundation of quality management
European foundation of quality management
selinasimpson1601
 
Data quality management tools
Data quality management toolsData quality management tools
Data quality management tools
selinasimpson1601
 
Applying quality management in healthcare
Applying quality management in healthcareApplying quality management in healthcare
Applying quality management in healthcare
selinasimpson1601
 

More from selinasimpson1601 (13)

Quality software project management
Quality software project managementQuality software project management
Quality software project management
 
Quality management system template free
Quality management system template freeQuality management system template free
Quality management system template free
 
Quality management system planning
Quality management system planningQuality management system planning
Quality management system planning
 
Quality management system iso
Quality management system isoQuality management system iso
Quality management system iso
 
Quality management project
Quality management projectQuality management project
Quality management project
 
Quality management programs
Quality management programsQuality management programs
Quality management programs
 
Quality management maturity grid
Quality management maturity gridQuality management maturity grid
Quality management maturity grid
 
Quality management courses in india
Quality management courses in indiaQuality management courses in india
Quality management courses in india
 
Operations and quality management
Operations and quality managementOperations and quality management
Operations and quality management
 
Information quality management
Information quality managementInformation quality management
Information quality management
 
European foundation of quality management
European foundation of quality managementEuropean foundation of quality management
European foundation of quality management
 
Data quality management tools
Data quality management toolsData quality management tools
Data quality management tools
 
Applying quality management in healthcare
Applying quality management in healthcareApplying quality management in healthcare
Applying quality management in healthcare
 

Quality metrics in project management

  • 1. Quality metrics in project management In this file, you can ref useful information about quality metrics in project management such as quality metrics in project managementforms, tools for quality metrics in project management, quality metrics in project managementstrategies … If you need more assistant for quality metrics in project management, please leave your comment at the end of file. Other useful material for quality metrics in project 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 quality metrics in project management ================== “If you don’t measure something, you can’t change it. The process of leadership is one of painting a vision, then saying how you’re going to get there, and then measuring whether you’re actually getting there. Otherwise, you risk only talking about great things but not accomplishing them.” Mitt Romney Continual improvement is a prerequisite for any organization’s success. A continual improvement process, also often called a continuous improvement process (abbreviated as CIP or CI), is an ongoing effort to improve products, services, or processes. These efforts can seek “incremental” improvement over time or “breakthrough” improvement all at once. Delivery (customer valued) processes are constantly evaluated and improved in the light of their efficiency, effectiveness and flexibility (Wiki). Gauging whether there is incremental improvement and setting up mechanisms to track and measure these improvements is the difficult part and this is where Metrics come in. I am passionate about metrics and have written about my favourite performance management metrics in business,sales and human resourcesearlier. In this guest post, Kavita Verma draws upon her
  • 2. PMO experiences to list the most effective metrics that can be used by project managers to determine the success of their projects. ‘Metric’ is defined as “Standard of measurement by which efficiency, progress, performance, productivity, quality of a deliverable, process, project or product can be assessed”. Metrics help in building predictability, improving organization’s decision making ability, and lay out what is working and what is not working within the organization and help guide the management focus in the right directions. Project management performance metrics enable Project managers to:  Assess status of ongoing project in terms of schedule, cost and profitability.  Foresee any potential risks.  Nail down the problems much before they become severe.  Keep a check on project profitability.  Assess productivity of team.  Assess quality of work products to be delivered. There can be different project management metrics defined based on complexity and nature of project. However, following five performance metric groups cover all the important aspects of a project to measure during execution: Performance Metric #1: Schedule and Effort/Cost Variance The goal of this metric is to measure the performance as well as progress of the project against signed baselines. This metric is very important and is the base for profitability of project. The EVM (Earned Value Management) concept, as defined by PMI standard PMBOK, is the commonly used method to track this metric. It integrates project scope, cost and schedule measures to help the PM to assess and measure project performance and progress. The principles of EVM can be applied to all projects, in any industry. Under this method, at any given point in time, project performance to date is used to extrapolate the expected costs and duration at project completion. This technique uses past performance (i.e. actuals) to more accurately forecast future performance. EVM develops and monitors three key dimensions of each work package:
  • 3. Planned Value (PV): How much you planned to spend for the work you planned to do i.e. it is the authorized budget assigned to the work to be accomplished for an activity or work breakdown structure component. Total PV is also known as Budget at Completion (BAC). PV at any stage = (Planned % Complete) X (BAC) Earned Value (EV): Earned value is the value of work performed expressed in terms of the approved budget assigned to that work for an activity or work breakdown structure component. It is the authorized work that has been completed, against the authorized budget for such completed work i.e. EV is ‘how much you planned to spend for the work you actually did’. Earned Value is also known as the Budgeted Cost of Work Performed (BCWP). Actual cost (AC): Actual cost is the total cost actually incurred and recorded in accomplishing work performed for an activity or work breakdown structure component. It is the total cost incurred in accomplishing the work that the EV measured. I.e. how much you spent for the work you actually did. Actual Cost is also known as the Actual Cost of Work Performed (ACWP). Using these three variables project Schedule variance and Cost variance metrics can be derived which shows if the project is running over or under budget; project is running behind or ahead of schedule, as follows: Schedule Variance (SV) is the measure of schedule performance of the project. It is the difference of Earned value and the planned value i.e. SV = EV – PV  Positive result means that you are ahead of schedule.  Negative result means that you are behind schedule. Cost Variance (CV) is the measure of cost performance on the project. It is equal to earned value (EV) minus actual costs (AC). Any negative CV is often non-recoverable to the project. CV = EV – AC  Positive result means that you are under budget.  Negative result means that you are over budget.
  • 4. Since EVM method allows PM to extrapolate the expected costs and duration at project completion based on project performance to date, PM can develop a forecast for the estimate at completion (EAC) which may differ from the budget at completion (BAC) based on project performance. Forecasting of EAC involves making estimates or prediction of conditions and events in the project’s future based on information and knowledge available at the time of forecasting. EAC is typically based on actual cost (AC) incurred for work completed, plus an estimate to complete (ETC) the remaining work. I.e. EAC = AC + ETC. Based on this PM can also derive another metric, Variance at completion (VAC) = BAC – EAC Performance Metric #2 – Productivity: Resource Utilization The objective of this metric is to measure productivity of resources involved in project and let PM assess over or under-utilization cases. Utilization% = Total Effort spent by resource/Total Budgeted Effort for the resource Budgeted effort is the planned billable work of resource. Any over-utilization and under- utilization indicated by this metric has an impact on the project’s profitability. It is important for the PM to track this metric very closely and find out the reason for deviations and the action items to bring back resource utilization to optimal level. Delayed projects, increased ramp up activities, less work provided by customer, unplanned vacations, less competent resources can impact this metric. To get better control over this metric, robust time reporting systems should be available in the organization. Using this, PM can analyze effort distribution across different
  • 5. project phases/activities. For e.g. Effort distribution can tell PM that how much effort is being spent on defect resolution, customer support or design activities. PM can take corrective actions based on this, if required. For instance, if the resource is complaining that customer support is taking considerable time but the effort distribution shows it otherwise, PM can see where the corrections are needed on what resource is doing. Effort distribution from time reporting systems can also tell the areas of improvement for better estimations/planning for the next project. Performance Metric #3: Change requests to Scope of work Signed Scope baseline with customer forms the baseline for the entire project planning and development. Any change to signed scope should happen in controlled manner. So here comes another important metric for PM to track i.e. the number of change requests coming from customer for the already signed scope of work. Each and every change request, once approved by internal change control board (CCB), requires update to Scope baseline which in turn has a cascade impact on cost baselines and schedule baselines and resource plans. Uncontrolled change requests often result in project scope creep and further impact negatively on the project cost/schedule, which is the worst thing to happen for any project. PM should never allow such scope creep. Based on the magnitude of the variance from original scope baseline, CCB should decide whether to accept or reject the change request and this decision should be communicated back to customer. In case of acceptance of change request, the impact on project cost and schedule should be clearly communicated in written form to customer and a written agreement from customer secured on those from customer before proceeding. Performance Metric #4: Quality and Customer Satisfaction
  • 6. Throughout the execution of project, Quality Assurance should always be on the radar of project manager. Quality here is defined as the number of severe, medium or low defects delivered through the lifetime of the project. It indicates the health of the deliverable to the end user and drives the Customer Satisfaction. PM needs to define, based on project type, what severe, low and medium means. Quality should be reported throughout the life of the project; the later defects are caught, the more impact they will have on the project. Under quality metrics, following are the key ones to track: Defect density = Total number of defects found/ Measure of size. For e.g. in case of software projects this can be: how many defects are found in 1KLOC (Kilo line of code). In general, size measure can be considered as planned effort like ‘person day total planned effort’. Defect age Number of days since the defect is open and not fixed. It can also be inferred as the time customer has been waiting for their issues to get resolved, Defect resolution rate = Total number of defects resolved/ Total effort spent Rate of closing the open defects over a period of time. If the rate of resolution is not in line with the defects being opened over a particular time, this indicates to the PM a situation of concern. Number of defects reported by customer PM should keep this as a separate metric to differentiate from the defects reported out of internal testing and the defects reported by end user i.e. Customer. Customer satisfaction depends a lot on the quality of deliverable provided and on how fast defects raised by customer are resolved.
  • 7. As said above, the later defects are caught, the more impact they will have on the project, it is worth to mention here about Pareto’s principle i.e. 80/20 principle, which PM can use to categorize causes of defects and late time entry relationship. As per this law 80% of the problems are due to 20% of the causes. PM can concentrate on these 20% causes impacting the project most. Performance Metric #5: Gross Margin Gross Margin (as I wrote in my earlier post on key performance metrics) is the mother of all metrics and the quickest way to determine if your business in on track or not and acts as an early warning system to put in place margin improvement initiatives. Ultimate goal of project execution is to bring revenue to organization with the approved gross margin. Gross margin (GM) is basically the difference of total revenue and the total cost spent on project i.e. profit. When a project is started, certain GM levels for the project are approved by project sponsor. This approved GM value is generally based on project scope definition, duration, a forecast of resources: onsite, offshore and organization’s investment analysis. Project PNL (Profit and Loss) statement gives a way to PM for tracking his/her projects GM metric at any point of time. For this, PNL statements and forecasts should be current documents i.e. changes in project parameters need to be reflected quickly in this statement to keep the PM informed about any potential risks to project profitability. All the above four project management performance metrics impact this metric, if not handled in controlled manner. A good organizational level PNL tool rather than manual excel sheets reduces the overhead on PM here. While working with all of these metrics, following points should be very clear in the project manager’s mind:
  • 8.  What to measure  How to measure  How to gather data to measure and represent  How to analyze gathered data and what actions to be defined based on that  How to show improved effectiveness of metrics by using improved numbers ‘before’ and ‘after’ In my view these five project management performance metrics are critical metrics to be tracked while taking charge and during execution of a project. The continued analysis of these metrics provides additional insights into what is working and what is not, allowing the PM to make appropriate improvements. These metrics also help in building up historical data for similar kind of projects so that in future, better project planning can be done. Success story of project can be then built up based on the effectiveness of defined metrics by showing the improved numbers “before” and “after”. This ensures that the effort spent by team in collection and measurement of data for these metrics is leading to continuous improvements and not just an overhead activity. In summary, metrics improve decision making ability by providing the foundation and rationale for the decision by making explicit what is usually implicit in the decision-making process. So what are your experiences when it comes to project management performance metrics and tracking? What are some of the other project management metrics you have been tracking? We would love to hear and learn from you. ================== III. Quality management tools 1. Check sheet
  • 9. 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
  • 10. 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
  • 11. 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
  • 12. 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
  • 13. 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 Quality metrics in project 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