PMP Certification Study Notes 8 – Project Quality Management

Please note that the study notes below is intended to include only the most important or esaily confused PMP concepts. It is by no means complete in the sense that one can rely on it to be fully prepared for the PMP Exam. Aspirants are advised to make use of this piece of study notes for revision purposes. Wish you PMP success!

Project Quality Management

• Quality: the degree to which a set of inherent characteristics fulfills requirements, decrease rework/costs, increase productivity/stakeholder satisfaction
• everyone in the organization is responsible for the quality (project team for destined parts while PM for project quality), the project manager is ultimately responsible for the project quality
• The project manager is required to perform continuous improvement activities (quality assurance), verify quality before completion of deliverables (control quality)
• prevention over inspection
• continuous improvement to ensure quality (quality assurance) — Quality Management processes are so focused on reviewing EVERY deliverable – not just the final product, but all of the components, designs and specifications too.
• some costs of quality will be borne by the organization (organization quality policy, e.g. quality audit, ISO accreditation)
• Quality Management Concepts
  • Crosby Zero Defects: identify processes to remove defects, quality is built in to the processes
  • Juran Fitness for Use: does the product/service meet customer’s need? i) Grade, ii) Quality conformance, iii) Reliability/maintainability, iv) Safety, v) Actual Use
  • W. Edwards Deming: 85% of quality problem is managers’  responsibility, develop “System of Profound Knowledge” [system = components working together to achieve an aim] i) Appreciation for system, ii) Knowledge about variation (special cause vs common cause) , iii) Theory of Knowledge (built up by prediction/observation/adjustment) , iv) Psychology
  • Six Sigma: achieve 3.4/1 mil defect level (99.999%) using DMAIC (Define, Measure, Analyze, Implement, Control) or [Design for Six Sigma] DMADV (Define, Measure, Analyze, Design, Validate) approach, refine the process to get rid of human error and outside influences with precise measurements, variations are random in nature
  • Just In Time: eliminate build up of inventory
  • Total Quality Management (TQM): ISO 8402 all members to center on quality to drive customer satisfaction , refine the process of producing the product
  • Kaizen改善: implement consistent and incremental improvement, to reduce costs, cycle time, drive customer satisfaction using PDCA (Plan Do Check Act)
  • The Plan-Do-Check-Act cycle is a way of making small improvements and testing their impact before you make a change to the process as a whole. It comes from W. Edwards Deming’s work in process improvement, which popularized the cycle that was originally invented by Walter Shewhart in the 1930s.
  • Capability Maturity Model Integration (CMMI): improve overall software quality (design, development and deployment)
  • ISO9000: ensures the defined processes are performed in accordance to the plan
• Important Terms:
  • outliers are singular measurements outside the control limits
  • Grade (fit for use or not) vs Quality (conformance to stated requirements)
  • Accuracy (correctness) vs Precision (consistence, how closely conforms to target, standard deviation is a measure of precision, smaller standard deviation higher precision)
  • under control: the process is predictable and repeatable

Plan Quality Management

• Inputs: Project Charter, Project Management Plan, Project Documents (assumption log, requirements traceability matrix, risk register, stakeholder register), EEF, OPA
• Tools & Techniques: Expert Judgement, Data Gathering, Data Analysis, Decision Making, Data Representation, Test and Inspection Planning, Meetings
• Outputs: Quality Management Plan, Quality Metrics, Project Management Plan Updates, Project Documents Updates

• quality policy (either organizational or just for the project), methods and procedures to meet the objectives and satisfy customer’s needs
  • including identifying the quality requirements and document how to achieve
  • The goal is to refine the process so that human errors and outside influences no longer exist, and any remaining variations are completely random
• Quality Metrics: function points, MTBF (mean time between failure), MTTR (mean time to repair)
• Data Gathering Tools:
  • Benchmarking: compare to past activities/standard/competition
  • Brainstorming
  • Interviews
• Data Analysis tools:
  • Cost-benefit Analysis: cost of implementing quality requirements against benefits
  • Cost of Quality:
    • Cost of Quality is the total cost of quality efforts throughout the product’s lifecycle
    • cost of conformance + cost of non-conformance: cost of conformance (prevention cost, appraisal cost) vs cost of non-conformance (failure cost [internal/external])
    • lowest quality cost is prevention, highest quality cost (poor quality) is rework and defect repair (as high as 5000 times the cost for carrying out unit testing), lost reputation and sales, failure cost may be internal/external (found by customer)
    • Warranty claims are external cost of quality — internal/external is reference to the project (not the organization)
  • Cause-and-effect / Ishikawa / Fishbone Diagram: for identifying the cause
  • Flowchart: (e.g. SIPOC diagram) for identifying failing process steps and process improvement opportunities
  • Check Sheets (tally sheets): collecting data/documenting steps for defeat analysis
  • Histograms: does not consider the influence of time on the variation that exits within a distribution
  • Pareto Chart: based on 80/20 principle, a prioritization tool to identify critical issues in descending order of frequency, sort of a histogram
  • Statistical Process Control (SPC) Chart: determine if a process is stable/predictable using statistical sampling (assessed by accuracy[conformance] and precision[standard deviation]), identity the internally computed control limits (UCL/LCL) and specification limits (USL/LSL) by the customer/PM
  • run chart is similar to control chart, but without the control
    • usually +-3sigma i.e. a range of 6 sigma
    • a form of time series
    • if a process is within control limit but beyond specification limit, the process is experiencing common cause variation (random) that cannot be corrected by the system, management help is needed (special cause can be tackled but NOT common cause)
  • Stability Analysis / Zone Test: rule of seven (7 consecutive on either side of the mean = out of control), rule of six (six consecutive with a trend = out of control), rule of ten (10 as a saw-tooth pattern around the mean), rule of one (1 point beyond control limit) [signal in the noise]
  • Scatter Diagram: for trending, a form of regression analysis
• Data Representation tools:
  • Flowcharts
  • Logical data model
  • Matrix Diagrams: House of Quality (HOQ) used in Quality Function Deployment (QFD) (method to transform user demands [VOC]  into design quality)
  • Mind mapping
• Test and Inspection Planning
  • used to determine how to test or inspect the product, deliverable, or service to meet the stakeholders’ needs and expectations
    • alpha/beta releases
    • inspections
    • field tests
• Other quality tools:
  • Design of Experiments (DOE): change several factors at a time for each experiment, to determine testing approaches and their impact on cost of quality
  • Loss Function: a financial measure of the user’s dissatisfaction with product performance
  • Kano Model: differentiate features as satisfy, delight or dissatisfy
  • Marginal Analysis: cost-benefit analysis
  • Force Field Analysis (FFA): reviews any proposed action with proactive and opposing forces
  • Process Improvement Plan: process boundaries, configuration, process metrics/efficiencies, targets for improved performance
  • Quality Checklists: checklist to verify a series of steps have been performed
  • Marginal Analysis: ROI of quality measures

Manage Quality (formerly “perform quality assurance”)

• Inputs: Project Management Plan, Project Documents, OPA
• Tools & Techniques: Data Gathering, Data Analysis, Decision Making, Data Representation, Audits, Design for X (DfX), Problem Solving, Quality Improvement Methods
• Outputs: Quality Report, Test and Evaluation Documents, Change Requests, Project Management Plan Updates, Project Documents Updates

• Manage Quality is in the Executing Process Group
  • ensures the quality standards are being followed, to ensure unfinished works would meet the quality requirements
  • by quality assurance department or sponsor/customer not actively involved in the project
  • primarily concerned with overall process improvement for activities and processes (rather than the deliverable)
  • utilize the data collected in Control Quality Process
• Data Analysis tools:
  • Alternatives analysis
  • Document analysis
  • Process analysis — to identify opportunities for process improvements
  • Root cause analysis
• Data Representation tools:
  • Affinity Diagrams: like a mind-mapping diagram, organize thoughts on how to solve problems
  • Cause and Effect Diagrams
  • Flowcharts
  • Histograms
  • Matrix Diagrams: e.g. ‘house of quality’ in QFD
  • Scatter Diagrams
• Design for X (Design for Excellence, DfX)
  • a set of technical guidelines that may be applied during the design phase of a product to optimize specific aspects of the design
  • may be able to improve the final characteristics of the product (in aspects like cost reduction, quality improvement, better performance and customer satisfaction)
• Quality Audit: to verify quality of processes, to seek improvement, identify best practices, reduce overall cost of quality, confirm implementation of approved changes, need quality documentation
• Quality Review: to review the quality management plan
• change requests are mostly procedural changes
• Quality Improvement Methods are used to analyze and evaluate opportunities for improvements:
  • Plan-Do-Check-Act
  • Six Sigma
• Quality Reports
  • can be graphical, numerical or qualitative
  • to provide information to help take corrective actions to fulfil project quality expectations
  • includes quality management issues escalated by the team; recommendations for process, project and product improvements; corrective action recommendations (can be rework, defect, bug repair, inspection, etc.), summary findings
• Test and Evaluation Documents
  • used to evaluate the achievement of quality objectives
  • may include checklists and detailed requirements traceability matrices

Control Quality

• Inputs: Project Management Plan, Project Documents, Approved Change Requests, Deliverables, Work Performance Data, EEF, OPA
• Tools & Techniques: Data Gathering, Data Analysis, Inspection, Testing/product Evaluations, Data Representation, Meetings
• Outputs: Quality Control Measurements, Verified Deliverables, Work Performance Information, Change Requests, Project Management Plan Updates, Project Documents Updates

• verify the deliverables against customer’s specifications to ensure customer satisfaction
• validate the changes against the original approved change requests
• conditional probability (events somewhat related) vs statistical independence (events not interrelated) vs mutual exclusivity
• statistical sampling for control quality
• variable (continuous) data: measurements, can do maths on e.g. average
• attribute (discrete) data: yes/no, no.123, just an identifier, can’t do maths on
• QC includes the PM process (lesson learnt, budget, scope)
• tolerance (spec limits, deliverables acceptable) vs control limits (process acceptable)
• if within control limit but outside tolerance: rework the process to give better precision
• all control and execution processes may generate lesson learned
• Data Analysis Techniques:
  • Performance reviews
  • Root cause analysis
• Testing/Product Evaluations
  • an organized investigation to provide objective information about the quality of the product/service in accordance with project requirements