Deming's profound changes: when will the sleeping giant awaken?
Increasingly, the demise of many businesses and organizations is being blamed on current western management practicewhich can be traced directly back to the 19th century and Frederick Taylor's theory of scientific management. Although W. Edwards Deming proposed a new, more modern philosophy of management decades ago, the western world, instead, continued to practice Taylor's philosophyby now adulterated and corrupted many times over into a new form of its own (neo-Taylorism). This volume exploresin depthneo-Taylorism (where it came from and what its beliefs are), Deming's philosophy (his system of profound knowledge and his 14 points), and suggests how Deming's philosophyif adoptedcould be an antidote for today's managerial ineffectiveness.Shows organization and technical managers how to changeusing Deming's principlesin order to improve quality in delivered services and products and in employee satisfaction. Analyzes the flaws of Taylorism and Neo-Taylorism with point-by-point comparison with Deming's philosophy. Clearly explains the Deming quality philosophy from a conceptual framework that can then be applied (rather than from a recipe or case study format, which has proven to be ineffective).For Executive and Technical Managers (all industries); Quality Managers and Practitioners; Quality, Productivity, Organizational Development Consultants.
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Flaws of Scientific Management
Types of Variation
Gaining New Knowledge
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achieve action chains Adam Smith Alfie Kohn American Axiom behavior bottlenecks capital causes communication competition context level Contrast Deming's control charts cooperation cost create culture customers David Packard deadband Deming says Deming's philosophy Deming's profound changes develop discussed division and concurrency division of labor economic Edwards Deming effect effort employees entropy example extension chain flaws Fourteen Points goals important individual industry Japan Japanese Konosuke Matsushita leadership level of complexity management's manipulation means ment motivation nonlinear observed operation optimal optimum system organization organizational output paradigm shifts PDSA PDSA cycle performance phase of learning predictable problem Promotes Complexity random Red Bead Demonstration reducing complexity responsibility rewards scientific management scientific method Shewhart cycle solving statistical control suboptimization suppliers tampering target tasks teaching theory thinking tion top management trade trying understand variation Walter Shewhart workers