Project Management PTM721S Faculty of Computing and Informatics 10 July 2017 Project Management PTM721S Lesson 8 – Project quality management

Introduction to project management Faculty of Computing and Informatics Introduction to project management What is a project quality management? Quality management processes Quality planning Quality assurance Quality control Tools and techniques for quality control Maturity models

What is a project quality management? Faculty of Computing and Informatics What is a project quality management? Quality is the “totality of characteristics of an entity that bear on its ability to satisfy stated or implied needs” Quality is “conformance to requirements” – project’s processes and products meet certain specifications Quality is “fitness for use” – a product is used as intended Project quality management is ensuring that the project satisfies the needs for which it was undertaken

Project quality management processes Faculty of Computing and Informatics Project quality management processes Quality planning: includes identifying which quality standards are relevant to the project and how to satisfy those standards, e.g. allowing for systems growth; planning a reasonable response time for a system; ensuring that the system produces consistent and accurate information Quality assurance: involves periodically evaluating overall project performance to ensure the project will satisfy the relevant quality standards Quality control: involves monitoring specific project results to ensure that they comply with the relevant quality standards while identifying ways to improve overall quality

Project quality management processes: Quality planning Faculty of Computing and Informatics Project quality management processes: Quality planning DESIGN OF EXPERIMENTS is a quality planning technique that helps identify which variables have the most influence on the overall outcome of the process - Functionality – is the degree to which a system performs its intended function - System outputs – screens and reports the system generates - Performance – addresses how well a product /service performs the customer’s intended use - Reliability – is the ability of a product/service to perform as expected

Quality assurance plan contents Faculty of Computing and Informatics Quality assurance plan contents 1.0 Draft Quality Assurance Plan 2.0 Management 2.1 Organisational structure 2.2 Roles and responsibilities 3.0 Required Documentation 4.0 Quality Assurance Procedure 4.1 Walkthrough Procedure 4.2 Review process 4.3 Audit process 4.4 Evaluation process Process Improvement 5.0 Problem Reporting Procedures 6.0 Quality Assurance Metrics

Project quality management processes: Quality assurance Faculty of Computing and Informatics Project quality management processes: Quality assurance Includes all activities related to satisfying the relevant quality standard for a project Quality assurance tools - Design of experiments - Benchmarking generates ideas for quality improvements by comparing specific project practices or product characteristics to those of other projects or products within or outside the performing organisations - Quality audit – a structured review of specific quality management activities that help identify lessons learnt that could improve current or future projects

Project quality management processes: Quality control Faculty of Computing and Informatics Project quality management processes: Quality control The outputs of this process are acceptance decisions, rework and process adjustments Acceptance decisions determine if the products/services produced as part of the project will be accepted or rejected Rework is actin taken to bring rejected items into compliance with product requirements or specifications or other stakeholder expectations Process adjustments – correct or prevent further quality problems based on quality measurements, e.g. purchase a new server to improve response time

Pareto Analysis Statistical Sampling Six Sigma Maturity models Faculty of Computing and Informatics Tools and techniques for quality control Pareto Analysis Statistical Sampling Six Sigma Maturity models

Tools and techniques for quality control – Pareto analysis Faculty of Computing and Informatics Tools and techniques for quality control – Pareto analysis Pareto analysis – 80/20 rule, 80% of the problems are due to 20% of the causes Pareto diagrams are column charts representing a frequency distribution that helps identify and prioritise problem areas E.g. analyse user complaints and help the Project Manager decide which one to address first

Tools and techniques for quality control – Statistical sampling Faculty of Computing and Informatics Tools and techniques for quality control – Statistical sampling Uses certainty factor, standard deviation and variability Certainty levels examples Desired certainty Certainty factor 95% 1.960 90% 1.645 80% 1.281

Tools and techniques for quality control – Statistical sampling Faculty of Computing and Informatics Tools and techniques for quality control – Statistical sampling A company wants to develop an EDI system for handling data on invoices from its suppliers. The total number of invoices is 50,000 from 200 different suppliers. The representative sample of the total that systems developers need to look at to design the system is: Sample size = 0.25 x (certainty factor/acceptable error) 2 E.g for a 95% certainty level required: Sample size = 0.25 x (1.960 / 0.05) 2 = 384

Tools and techniques for quality control – Six Sigma Faculty of Computing and Informatics Tools and techniques for quality control – Six Sigma Six Sigma – “a comprehensive and flexible system for achieving, sustaining and maximizing business success” Six Sigma’s target for perfection is the achievement of no more than 3.4 defects, errors or mistakes per million opportunities

Faculty of Computing and Informatics Six Sigma - DMAIC Five phase improvement process called DMAIC (Define, Measure, Analyse, Improve, Control Define – problem/opportunity, process and customer requirements (project charter, customer requirements, process maps, voice of customer, i.e. complaints, surveys, market research Measure – define measures, collect, compile and display data Analyse – scrutinize process details to find improvement opportunities Improve – generate solutions and ideas for improving problem Control – track and verify stability of improvements and predictability of solution

Quality control charts and the seven run rule Faculty of Computing and Informatics Quality control charts and the seven run rule A control chart is a graphic display of data that illustrates the results of a process over time – to prevent defects When the process is out of control – identify causes of non-random events and adjust process to correct them Seven Rub Rule states that if the seven data points in a row are below the mean, above the mean or are all increasing / decreasing, then the process needs to be examined for non-random problems

Quality control - Testing Faculty of Computing and Informatics Quality control - Testing Unit test – to test each individual component (often a program) to ensure it is as defect-free as possible Integration testing – to test the functionality of grouped components Systems testing – testing the entire system as one entity User acceptance testing – test performed by end-user prior to accepting the delivered system

Faculty of Computing and Informatics The cost of quality The cost of quality is the cost of conformance plus the cost of non-conformance Conformance means delivering products that meet requirements and fitness to use The cost of non-conformance means taking responsibility for failures or not meeting quality expectation

Faculty of Computing and Informatics The cost of quality Five major cost categories related to quality include: Prevention cost – the cost of planning and executing a project so that it is error-free Appraisal cost – the cost of evaluating processes and their outputs to ensure that a project is error-free Internal failure cost – a cost incurred to correct an identified defect External failure cost – a cost that relates to all errors not detected and not corrected before delivery to the customer, e.g. warranty cost, field service personnel training, product liability suits, complaints handling, future business losses Measurement and test equipment costs – the capital cost of equipment used to perform prevention and appraisal activities

Faculty of Computing and Informatics Maturity models Maturity models are frameworks to help organisations improve processes and systems Software Quality Function Deployment (SQDF) – defines user requirements and planning software projects – technical product specifications Capability Maturity Model (CMM) – 5 level model laying out a generic path to process improvement for software development in organisations Project Management Maturity Model

Maturity models – Capability Maturity Model (CMM) Faculty of Computing and Informatics Maturity models – Capability Maturity Model (CMM) Initial – Software development processes at this level are ad-hoc / chaotic. Few processes are defined and success depends on individual effort Repeatable – Organisations at this maturity level have established basic PM processes to track cost, schedule and functionality for software projects Defined - At this level the software processes for both management and S.E. activities are documented, standardized and integrated Managed – At this maturity level organisations collect detailed measures of the software processes and product quality Optimising – Organisations can enable continuous process improvement by using quantitative feedback from processes and piloting innovative ideas

Maturity models – Project Management Maturity Models Faculty of Computing and Informatics Maturity models – Project Management Maturity Models Ad Hoc - Software development processes at this level are ad-hoc / chaotic. Few processes are defined and success depends on individual effort Abbreviated- Organisations at this maturity level have established basic PM processes to track cost, schedule and functionality for software projects Organised – Standardised documented project management processes and systems that are integrated. Project success more predictable, cost and schedule performance improved Managed – Management collects and uses detailed measures of effectiveness of project management. Project success is uniform and the cost and schedule performances conform to plan Adaptive – Feedback from project management and from piloting innovative ideas and technologies enables continuous improvement

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