Smart Data Enterprise Performance Optimization Strategy
by George, James A.; Rodger, James A.Edition: 1st
Format: Hardcover
Pub. Date: 2010-03-15
Publisher(s): Wiley
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Summary
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 Adaptive Information by Pollock and Hodgson ably describe the current state of the art, their necessarily technical tone is not conducive to corporate or agency wide qualitative change.
Author Biography
James A. George is a performance improvement consultant to the federal government and commercial customers. He is presently Director at SAM, Inc., Rockville, Maryland. James A. Rodger, PhD, is a professor in the MIS/Decision Sciences Department of the Eberly College of Business and Information Technology at the Indiana University of Pennsylvania. He has done consulting work for the Department of Defense, among many other federal agencies.
Table of Contents
| Foreword | p. xi |
| Preface | p. xiii |
| Acknowledgments | p. xxi |
| Introduction: A Comprehensive Overview | p. 1 |
| Predictive Management | p. 8 |
| IDEF Lexicon for Executives | p. 10 |
| Organization of This Book | p. 12 |
| Smart Data in Three Dimensions | p. 14 |
| Business Rule | p. 16 |
| Case Study: IT Capital Budgeting Using a Knapsack Problem | p. 17 |
| Case Study: Better Decision Making: Field Testing, Evaluation and Validation of a Web-Based MedWatch Decision Support System (MWDSS) | p. 19 |
| Engineering an Ubiquitous Strategy for Catalyzing Enterprise Performance Optimization | p. 21 |
| What Smart Data Provides | p. 24 |
| References | p. 24 |
| Context: The Case and Place for Smart Data Strategy | p. 27 |
| Value of Data to the Enterprise | p. 27 |
| Enterprise Performance Versus Enterprise Integration | p. 46 |
| Current Problems and Deficiencies from Poor Data Strategy | p. 54 |
| New Technologies | p. 62 |
| Breaking from Tradition with Improved Results | p. 78 |
| References | p. 83 |
| Elements: Smart Data and Smart Data Strategy | p. 85 |
| Performance Outcomes and Attributes | p. 85 |
| Policy and Business Rules | p. 90 |
| Expectations: Managerial and Technical | p. 92 |
| Capacity for Change and Improvement | p. 93 |
| Iteration Versus Big Bang | p. 94 |
| References | p. 128 |
| Barriers: Overcoming Hurdles and Reaching a New Performance Trajectory | p. 129 |
| Barriers | p. 129 |
| Overcoming Barriers | p. 130 |
| Top-Down Strategy | p. 151 |
| Balance of Consequences and Reinforcement | p. 173 |
| Collaboration | p. 173 |
| Enterprise Performance Optimization Process | p. 174 |
| Enterprise Performance Optimization Architecture | p. 175 |
| Scoping, Scheduling, Budgeting, and Project and Program Management | p. 187 |
| References | p. 189 |
| Visionary Ideas: Technical Enablement | p. 191 |
| Today's Possibilities | p. 191 |
| Calibrating Executive Expectations | p. 236 |
| Five Years from Now | p. 242 |
| Ten Years From Now | p. 277 |
| References | p. 277 |
| CEO's Smart Data Handbook | p. 279 |
| Strategy | p. 279 |
| Policy | p. 314 |
| Organization | p. 316 |
| Actions | p. 316 |
| Timing | p. 320 |
| Funding and Costing Variables | p. 320 |
| Outcomes and Measurements | p. 320 |
| References | p. 320 |
| Index | p. 323 |
| Wiley Series in Systems Engineering and Management | p. 329 |
| Table of Contents provided by Ingram. All Rights Reserved. |
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