Quality is a form of management that is composed of the double approach of driving an organization towards excellence, while conforming to established standards and laws. The objective of quality confers advantages to companies: it makes them more resilient to change that can be unexpected or even chaotic; it makes them more competitive by identifying those steps in processes that do not offer added value. No longer the concern of a small community of experts, even scientists and engineers working in the private sector will find that they will have to con- front questions related to quality management in their day-to-day professional lives. This volume offers such people an unique entry into the universe of quality management, providing not only a cartography of quality standards and their modes of application – with particular attention to the ISO standards – but also a broader cultural context, with chapters on the history, prizes, deontology and moral implications of systems of quality management. This book thus opens the door to all those eager to take the first steps to learning how the principles of quality are organized today, and how they can be applied to his or her own activity.

We are in what many call “The Age of the Customer.” Customers are empowered more than ever before and demand a high level of customer attention and service. Their increasing expectations and demands worldwide have forced organizations to transform themselves and prepare for the customer experience (CX) battlefield. This landmark book addresses: What customer experience really means Why it matters Whether it has any substantial business impact What your organization can do to deliver and sustain your CX efforts, and How we got to this particular point in CX history This book is the result of exhaustive research conducted to incorporate various components that affect customer experience. Based on the research results, the authors make a case for seeing CX and associated transformations as the next natural evolution of the quality management system (QMS) already in place in most companies. Using an existing QMS as the foundation for CX not only creates a more sustainable platform, but it allows for a faster and more cost effective way to enable an organization to attain world-class CX.

The book describes the most important quality management tools (e.g. QFD, Kano model), methods (e.g. FMEA, Six Sig-ma) and standards (e.g. IS0 9001, ISO 14001, ISO 27001, ISO 45001, SA8000). It reflects recent developments in the field. It is considered a must-read for students, academics, and practitioners.

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You'll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You'll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. - Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges - Enables discussions between business and IT with a non-technical vocabulary for data quality measurement - Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation