IST 302 : Project Quality Management

The Quadruple Constraint

Scope Time

Cost Quality

The Quadruple Constraint

Scope Time

Cost Quality

The Quadruple Constraint

Scope Time

Cost Quality

The Quadruple Constraint

Scope Time

Cost Quality

Obtaining a consensus on a single definition is difficult. It’s a hard thing to define.

Quality is the totality of characteristics of an entity that bear on its ability to satisfy stated or implied needs.

Quality is the degree to which a set of inherent characteristics fulfils requirements.

ISO8042:1994 – Schwalbe p. 294

ISO9000:2008 - Schwalbe p. 294

Quality…

• Simply put…

Customers want quality products

Organizations want quality projects

Project Quality Management: Why do we care?

Product Quality Problems are Costly

Business Cost/Hour DowntimeATM machines (medium sized bank) $14,500

Package Shipping Service $28,500

Telephone Ticket Sales 69,000

Catalog Sales Center $90,000

Airline Reservation System (small airline) $89,500

Mid-90s

Problem EffectShuttle Software Problem ’81 Launch Aborted

Shuttle o-ring (‘’86) / Shuttle Foam Issue (‘03) Shuttle Explosion

Security Breaches resulting in lost PII Org. investigation; consumer credit

Poor telecommunications installation Loss of customers and credibilityDelays in organizational activites

Poor disaster recovery plan Inability to regain functionlality in a timely manner

• Monster Search (08‐nov‐2010)– Some are contractors

The issue is so significant, there are careers that focus on quality assurance.

PGH BOSTON AUSTIN Phoenix

108 693 285 271

• Salary.com (08‐nov‐2010)– Quality Assurance Specialist I ‐ PGH

• 25th percentile : $50k• Median : $57k• 75th percentile : $64k

– IT Quality Assurance Director ‐ PGH• 25th percentile : $108• Median : $131• 75th percentile : $141

The career can be lucrative.

The Quality Framework organizes the quality landscape.

Quality ConceptQuality Factor

Quality Quality Concept

Quality Concept

Quality Factor

Quality Factor

Quality Metric

Quality Metric

Quality Metric

Example: Installation of a Server Farm (e.g., Cloud)

Quality Concepts: Quality Factors for_________________

Quality Metrics for________________

Concept Example Factor Potential MetricsProcess Defects Arrival Rate : a count produced each week

Phase Rate : a count produced at the end of each phase

Backlog : a count produced each week of defects unaddressed

Response : current average time it takes to fix a defect.

Propagation : fixes that created new defects

Project Scope Changr Requests : count of requests produced each week

Change Approvals : count of approvals produced each week

Schedule Overdue : a count of tasks that should have been finished produced weekly

Tasks that should have started Unstarted : a count of tasks that should be underway but aren’t producedweekly.

Cost Over Budget Items : a count of tasks over budget produced weekly

Earned Value Earned Value : the earned value to date

Resources Over burdening : a count of overburdened resources produced weekly

Turnover Turnover : a count of project team members who quit or were terminatedproduced after each phase

Training Hours Training : the average number of training hours per project team memberproduced after each phase.

Of course, quality isn’t only about the product.

Project Quality Management Processes

Quality Planning

Identifying which quality standards are relevant to the project

and how to satisfy them

Quality Assurance

Evaluating overall project performance to ensure the project

will satisfy the relevant quality

standards

Quality Control

Monitoring specific project results to

ensure they comply with the relevant

quality standards while identifying ways to

improve overall quality

Maturity models are frameworks for assessing quality control effectiveness

• Several models exist– SEI’s CMM / CMMI – Capability Maturity Model / Integrated

– PMI’s OPM3: Organizational Project Management

It is important to measure quality of the project but it is equally important to measure the process for measuring quality.

Players in the Quality Arena

• W. Edwards Deming - Out of Crisis• Worked with Japanese manufacturers

• Joseph Juran - Quality Control Handbook• Stressed top management commitment to quality

• Philip Crosby - Quality is Free• Suggested “Zero Defects”

• Kaoru Ishikawa - Guide to Quality Control• Developed concept of quality circles and fishbone diagrams

• Armand Feigenbaum – Total Quality Control

• Genichi Taguchi – Many books on Quality Engineering• Developed methods for optimizing the process of engineering experimentation

• Focus on stakeholder satisfaction• Prevention not inspection• Improve the process to improve the product

• Fact‐based management

• Quality is everyone’s responsibility

Bottom Line on Quality Management

Where are we?

• We know we want…– Quality products– Quality processes– Quality projects

• Quality Control– How do we track quality?– How do we know where to make improvements?

There are common tools and techniques for controlling quality

• Example Tool:– Statistical Sampling– Pareto Analysis– Quality Control Charts

• Example Techniques:– Six Sigma

Statistical sampling involves using a subset of a population to understand the population.

• Impossible to inspect every item

• How many items do we have to inspect to feel confident that what we observe is reflective of the population?

Statistical Sampling

Certainty Factor

The number of standard deviations you are asserting the observed value is within the population value,

Simple Sample Size Estimate

SampleSize = 0.25 x

certainty factor

acceptable error( )2

Acceptable Error

Percentage of time your assumption that the observed value is within the specified confidence of the population value is wrong.

Certainty Factors are based on a normal distribution and represent the number of standard deviations from the mean.

95% of the data falls within 1.96 standard deviations of the mean

Commonly Used Certainties

Certainty Certainty Factor Acceptable Error

99% 2.58 0.01

95% 1.960 0.05

90% 1.645 0.10

80% 1.281 0.20

There a several commonly used certainties.

So…

• What is your sample size if you want– 99% certainty? 16, 641– 95% certainty? 384– 90% certainty? 68– 80% certainty? 10

SampleSize = 0.25 x

certainty factor

acceptable error( )2

Certainty Certainty Factor Acceptable Error

99% 2.58 0.01

95% 1.960 0.05

90% 1.645 0.10

80% 1.281 0.20

Pareto Analysis identifies the contributors that account for most of the problems.

Often exhibits 80‐20 rule

• Pareto

• ??

Interesting aside…

Quality Control Charts are graphic displays of data the illustrates the trends of a process over time.

11.90

11.92

11.94

11.96

11.98

12.00

12.02

12.04

12.06

12.08

12.10

0 5 10 15 20 25

Seven Run Rule is used to flag trends that indicate non‐random variances.

• Look for seven points in a row that are– Above the mean– Below the mean– Form an increasing sequence– Form a decreasing sequence

11.90

11.92

11.94

11.96

11.98

12.00

12.02

12.04

12.06

12.08

12.10

0 5 10 15 20 25

Where are the points that satisfy the Seven Run Rule?

Six Sigma is a system for achieving, sustaining, and maximizing business success.

• Driven by disciplined use of – Facts– Data– Statistical analysis

• Focuses on – Managing– Improving– Reinventing

Examples of Six Sigma Organizations

• Motorola, Inc. – 80s : Saved $14B

• Allied Signal/Honeywell– 90s : Saved $600M+

• Other adopters– GE / Raytheon

Basic Information on Six Sigma

• Goal– Less than 3.4 defects per million opportunities

• Six Sigma can apply to a wide variety of processes

• Six Sigma projects follow a five‐phase improvement process (DMAIC)

DMAIC

Define

Identify and define the problem, process and

requirements

DMAIC

DMAIC

Define

Identify and define the problem, process and

requirements

DMAICMeasure

Define metrics; collect and compile data

DMAIC

Define

Identify and define the problem, process and

requirements

DMAICMeasure

Define metrics; collect and compile data

Analyze

Scrutinize process details to find improvement opportunities

DMAIC

Define

Identify and define the problem, process and

requirements

DMAICMeasure

Define metrics; collect and compile data

Analyze

Scrutinize process details to find improvement opportunities

Improve

Generate solutions and ideas for improving the

problem

DMAIC

Define

Identify and define the problem, process and

requirements

DMAICMeasure

Define metrics; collect and compile data

Analyze

Scrutinize process details to find improvement opportunities

Improve

Generate solutions and ideas for improving the

problem

Control

Track and verify the stability of the improvements

Six Sigma Applies to the Organization

• Six Sigma requires an organization‐wide commitment

• Six Sigma organizations adopt contrary objectives– For example, reducing errors and getting things done faster

• Six Sigma is an operating philosophy– Strives to eliminate waste, raise levels of quality, and improve financial performance at breakthrough levels