Managing Complexity
Thomas Michael Fehlmann
Cite this publication as
Thomas Michael Fehlmann, Managing Complexity (2017), Logos Verlag, Berlin, ISBN: 9783832599775
226
accesses
accesses
Description / Abstract
The rise of Information and Communication Technology (ICT) in the second half of the 20^{thcentury became the dominant force in economics. Its rise accelerates in the first 15 years of this century at an astonishing speed. The world of ICT right now is in the process of cosmic inflation. In the early universe, quantum fluctuations in a microscopic inflationary agile region became the seed for growing structures in the universe of galactic nebula, galaxies and stars, making the universe transparent. This phenomenon, familiar to physicist and cosmologists, happens right now to ICT. The current observation is that ``things'' of the physical world become intelligent, receive IP addresses and connect to the Internet. The possibilities to create new ICT-based products seem unlimited; however, sponsors must fuel the inflation.
Complexity was already an issue when developing software in the early days of ICT. Software development is often done in projects that turn out to be exploratory in the sense that they aim at translating human voices, uttering requirements, into a machine-readable language. Requirements for the software to be build are usually not known at the beginning; the project must uncover them. Developing software without knowing the outcome in advance is a complex undertaking. Predicting the outcome of software projects by proven methods of civil engineering did not work out well.
Now, new levels of complexity arise with ICT. Agile approaches are appropriate for software development; however, predicting the outcome of projects still is difficult. New techniques must manage the growing levels of complexity within ICT. Fortunately, mathematics has provided these new techniques. They rely on transfer functions and Eigenwert theory. Its usefulness already has been proven in major search engines of this century. However, this is not the end of the story.
This books makes the mathematics of Lean Six Sigma transfer functions available to ICT practitioners. It provides the basic theory, explained with many examples, and even more suggestions, how Six Sigma Transfer Functions help with complex problems.
Complexity was already an issue when developing software in the early days of ICT. Software development is often done in projects that turn out to be exploratory in the sense that they aim at translating human voices, uttering requirements, into a machine-readable language. Requirements for the software to be build are usually not known at the beginning; the project must uncover them. Developing software without knowing the outcome in advance is a complex undertaking. Predicting the outcome of software projects by proven methods of civil engineering did not work out well.
Now, new levels of complexity arise with ICT. Agile approaches are appropriate for software development; however, predicting the outcome of projects still is difficult. New techniques must manage the growing levels of complexity within ICT. Fortunately, mathematics has provided these new techniques. They rely on transfer functions and Eigenwert theory. Its usefulness already has been proven in major search engines of this century. However, this is not the end of the story.
This books makes the mathematics of Lean Six Sigma transfer functions available to ICT practitioners. It provides the basic theory, explained with many examples, and even more suggestions, how Six Sigma Transfer Functions help with complex problems.
Table of content
- BEGINN
- Part One: Transfer Functions and Quality Function Deployment
- Chapter 1: Lean Six Sigma
- 1.1 Six Sigma – Reducing Variation
- 1.2 The Secrets of Six Sigma
- 1.3 The Three Fundamental Six Sigma Metrics
- 1.4 Lean Six Sigma
- 1.5 Linking Responses to Controls in QFD
- 1.6 Conclusions
- Chapter 2: Transfer Functions
- 2.1 Introduction
- 2.2 Transfer Functions – Mathematical Foundations
- 2.3 Single Response Transfer Functions
- 2.4 Multiple Response Transfer Functions
- 2.5 Conclusions
- Chapter 3: What is AHP?
- 3.1 Introduction
- 3.2 The Details behind the AHP
- 3.3 AHP Project Management Applications
- 3.4 The Kitchen Knife Case
- 3.5 Productivity Impact Factor Determination by AHP
- 3.6 Conclusion
- Chapter 4: Quality Function Deployment
- 4.1 Quality Function Deployment in a Nutshell
- 4.2 Early Adoption of Quality Function Deployment
- 4.3 Quality Function Deployment Basics
- 4.4 Eliciting the Voice of the Customer
- 4.5 Transfer Functions in a QFD Context
- 4.6 Transfer Functions as QFD Matrices
- 4.7 Designing Solutions for Business Drivers
- 4.8 Conducting a QFD Workshop
- 4.9 Comprehensive QFD – The Deming Chain
- 4.10 Conclusion
- Chapter 5: Voice of the Customer by Net Promoter®
- 5.1 Introduction
- 5.2 WOM Economics
- 5.3 Voice of the Customer Analysis
- 5.4 A Sample NPS Survey
- 5.5 Applying NPS
- 5.6 Conclusion
- Part Two: Lean Six Sigma for Software
- Chapter 6: Functional Sizing
- 6.1 Functional Sizing Overview
- 6.2 ISO/IEC 20926:2009 IFPUG Functional Sizing
- 6.3 ISO/IEC 19761 COSMIC Functional Sizing
- 6.4 ISO/IEC 29881 FiSMA Functional Sizing
- 6.5 How to Choose the Best Sizing Method
- 6.6 Metrology and Measurement Accuracy
- 6.7 Conclusion
- Chapter 7: The Modern Art of Developing Software
- 7.1 Using UML 2.0 Sequence Diagrams in Agile
- 7.2 Counting Data Movement Maps with ISO/IEC 19761
- 7.3 The Employee Database sized with ISO/IEC 19761
- 7.4 The Sphygmomanometer Case
- 7.5 The Web Ticket Shop Case
- 7.6 Mobile ID: Use Smartphone for Authentication
- 7.7 Conclusion
- Chapter 8: Lean & Agile Software Development
- 8.1 Introduction
- 8.2 Lean & Agile Software Development
- 8.3 A Sample Travel Helpdesk Project
- 8.4 Early Project Estimation the Six Sigma Way
- 8.5 Conclusion
- Chapter 9: Requirements Elicitation
- 9.1 The New Economics by Deming
- 9.2 Requirements Prioritization By Customer†™s Needs
- 9.3 The Car Door Example
- 9.4 Uncovering Hidden Requirements
- 9.5 The Kitchen Helper Case
- 9.6 Conclusions
- Chapter 10: Software Testing and Defect Density Prediction
- 10.1 Introduction
- 10.2 Key Factors for Defect Density
- 10.3 A Model for Defect Density Calculation
- 10.4 Defect Density Prediction by Measurement
- 10.5 The Ticket App Example
- 10.6 Defect Density Prediction by � Control Charts
- 10.7 Conclusions
- Part Three: Lean Six Sigma Applications
- Chapter 11: Application to Product Management
- 11.1 Transfer Functions in Product Management
- 11.2 A Call Center Example from Long Time Ago
- 11.3 The Ideal Situation
- 11.4 The Web Portal Example
- 11.5 Overcoming Difficulties
- 11.6 Conclusions
- Chapter 12: Effort Estimation for ICT Projects
- 12.1 Why is Software Project Estimation so Difficult?
- 12.2 The Traditional Approach to Parametrization
- 12.3 Parametric Approaches to Cost Prediction
- 12.4 Estimation Stacks as Transfer Functions
- 12.5 Quality of Estimations in Practice
- 12.6 Conclusion
- Chapter 13: Dynamic Sampling of Topic Areas
- 13.1 Introduction
- 13.2 Combinatory Logic
- 13.3 Universal Models
- 13.4 Testing the Internet of Things
- 13.5 Automated Test Case Generation
- 13.6 Conclusions
- Appendices
- Linear Algebra in a Nutshell
- Eigenvalues and Eigenvectors
- The Perron-Frobenius Theory
- Bibliography
- Reference Index