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|a 9781282551091
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|a 0470583061
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|a T58.64
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|a George, James A.
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|a Smart data
|b enterprise performance optimization strategy
|c James A. George, James A. Rodger ; with a foreword by David E. Chesebrough
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| 260 |
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|a Hoboken, N.J.
|b John Wiley & Sons
|c 2010
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| 300 |
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|a xxi, 327 pages
|b illustrations
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|a 3 Barriers: Overcoming Hurdles and Reaching a New Performance Trajectory3.1 Barriers; 3.2 Overcoming Barriers; 3.3 Top-Down Strategy; 3.4 Balance of Consequences and Reinforcement; 3.5 Collaboration; 3.6 Enterprise Performance Optimization Process; 3.7 Enterprise Performance Optimization Architecture; 3.8 Scoping, Scheduling, Budgeting, and Project and Program Management; References; 4 Visionary Ideas: Technical Enablement; 4.1 Today's Possibilities; 4.2 Calibrating Executive Expectations; 4.3 Five Years from Now; 4.4 Ten Years From Now; References; 5. CEO's Smart Data Handbook; 5.1 Strategy
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|a Includes bibliographical references and index
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|a SMART DATA; Contents; Wiley Series in Systems Engineering and Management; Foreword; Preface; Acknowledgments; Introduction: A Comprehensive Overview; Predictive Management; IDEF Lexicon for Executives; Organization of This Book; Smart Data in Three Dimensions; Business Rule; Case Study: IT Capital Budgeting Using a Knapsack Problem; Case Study: Better Decision Making: Field Testing, Evaluation and Validation of a Web-Based MedWatch Decision Support System (MWDSS); Engineering an Ubiquitous Strategy for Catalyzing Enterprise Performance Optimization; What Smart Data Provides; References
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|a 5.2 Policy5.3 Organization; 5.4 Actions; 5.5 Timing; 5.6 Funding and Costing Variables; 5.7 Outcomes and Measurements; References; Index
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|a 1 Context: The Case and Place for Smart Data Strategy1.1 Value of Data to the Enterprise; 1.2 Enterprise Performance Versus Enterprise Integration; 1.3 Current Problems and Deficiencies from Poor Data Strategy; 1.4 New Technologies; 1.5 Breaking from Tradition with Improved Results; References; 2 Elements: Smart Data and Smart Data Strategy; 2.1 Performance Outcomes and Attributes; 2.2 Policy and Business Rules; 2.3 Expectations: Managerial and Technical; 2.4 Capacity for Change and Improvement; 2.5 Iteration Versus Big Bang; References
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|a BUSINESS & ECONOMICS / Total Quality Management / bisacsh
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| 653 |
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|a BUSINESS & ECONOMICS / Quality Control / bisacsh
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| 653 |
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|a Information resources management / Quality control
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| 653 |
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|a Gestion de l'information / Qualité / Contrôle
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| 653 |
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|a Database management / Quality control / fast
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| 653 |
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|a Bases de données / Gestion / Qualité / Contrôle
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| 653 |
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|a Database management / Quality control
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| 700 |
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|a Rodger, James A.
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 490 |
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|a Wiley series in systems engineering and management
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| 028 |
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|a 10.1002/9780470583067
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| 015 |
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|a GBB000502
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| 776 |
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|z 9780470583043
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|z 0470583045
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|z 9780470473252
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|u https://learning.oreilly.com/library/view/~/9780470473252/?ar
|x Verlag
|3 Volltext
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|a 658.4/013
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|a 658.4013
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|a 330
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|a The authors advocate attention to smart data strategy as an organizing element of enterprise performance optimization. They believe that "smart data" as a corporate priority could revolutionize government or commercial enterprise performance much like "six sigma" or "total quality" as organizing paradigms have done in the past. This revolution has not yet taken place because data historically resides in the province of the information resources organization. Solutions that render data smart are articulated in "technoid" terms versus the language of the board room. While books such as Ad
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