Forecasting and Management of Technology

by Porter, Alan L.; Cunningham, Scott W.; Banks, Jerry; Roper, A. Thomas; Mason, Thomas W.; Rossini, Frederick A.

• ISBN13: 9781118047989
• ISBN10: 1118047982
• Edition: 2nd
• Format: eBook
• Copyright: 2011-07-06
• Publisher: Wiley

Summary

Published in 1991, the first edition of Forecasting and Management of Technology was one of the leading handful of books to deal with the topic of forecasting of technology and technology management as this discipline was emerging. The new, revised edition of this book will build on this knowledge in the context of business organizations that now place a greater emphasis on technology to stay on the cutting edge of development. The scope of this edition has broadened to include management of technology content that is relevant to now to executives in organizations while updating and strengthening the technology forecasting and analysis content that the first edition is reputed for.

Updated by the original author team, plus new author Scott Cunningham, the book takes into account what the authors see as the innovations to technology management in the last 17 years: the Internet; the greater focus on group decision-making including process management and mechanism design; and desktop software that has transformed the analytical capabilities of technology managers. Included in this book will be 5 case studies from various industries that show how technology management is applied in the real world.

Author Biography

ALAN THOMAS ROPER (retired) was a professor at Rose-Hulman Institute of Technology in Terre Haute, Indiana. He is the past editor of the journal Impact Assessment and Project Appraisal and the past director of the Center for Technology and Policy Studies at Rose-Hulman.

SCOTT W. CUNNINGHAM obtained a MSc in public policy from the Georgia Institute of Technology and a DPhil in science, technology, and innovation policy from the University of Sussex. He is currently Assistant Professor of Policy Analysis in the Department of Technology, Policy, and Management at Delft University of Technology.

ALAN L. PORTER has led development of "technology opportunity analysis" and mining electronic, bibliographic data sources to generate intelligence on emerging technologies. He holds an MA in psychology and a PhD in engineering psychology, both from UCLA. He is currently Director of Research and Development for Search Technology, Inc., in Norcross, Georgia.

THOMAS W. MASON was the founding head of the Engineering Management Department (www.rose-hulman.edu/msem). While on a three-year leave from Rose-Hulman, he served as CFO and CEO of a 140-person network management systems business.

FREDERICK A. ROSSINI (retired) is a former provost at George Mason University in Fairfax, Virginia.

JERRY BANKS is Professor Emeritus, Department of Industrial and Systems Engineering, Georgia Institute of Technology in Atlanta, Georgia.

Table of Contents

Acknowledgments xv

1 Introduction 1

1.1 About This Book, 1

1.2 Technology and Society, 2

1.2.1 Social Change, 3

1.2.2 Technological Change, 4

1.3 Management and the Future, 6

1.3.1 Management and Innovation Processes, 7

1.3.2 The Role of Technology Forecasting, 9

1.3.3 The Importance of Technology Forecasting, 10

1.3.4 The Role of Social Forecasting, 12

1.4 Conclusions, 13

References, 13

2 Technology Forecasting 15

2.1 What Is Technology Forecasting?, 15

2.1.1 Models of Technology Growth and Diffusion, 17

2.1.2 Technology Forecasting in Context, 18

2.1.3 What Makes a Forecast Good?, 20

2.1.4 Common Errors in Forecasting Technology, 21

2.2 Methodological Foundations, 23

2.2.1 The Technology Delivery System, 24

2.2.2 Inquiring Systems, 28

2.3 Technology Forecasting Methods, 31

2.3.1 Overview of the Most Frequently Used Forecasting Methods, 33

2.3.2 Method Selection, 37

2.4 Conclusion, 37

References, 38

3 Managing the Forecasting Project 40

3.1 Information Needs of the Forecasting Project, 40

3.1.1 The Technology Manager’s Needs, 42

3.1.2 The Forecast Manager’s Needs, 43

3.1.3 Information about Team Members, 44

3.2 Planning the Technology Forecast, 46

3.3 Team Organization, Management, and Communications, 47

3.3.1 Organizing and Managing the Technology Forecast, 50

3.3.2 Communications, 54

3.3.3 Summary Conclusions about Project Management and Organization, 55

3.4 Success: The Right Information at the Right Time, 56

3.5 Project Scheduling, 57

3.5.1 Program Evaluation and Review Technique (PERT), 58

3.5.2 Gantt Chart, 60

3.5.3 Project Accountability Chart (PAC), 60

3.5.4 Project Scheduling Software, 61

3.6 Conclusions, 62

References, 62

4 Exploring 65

4.1 Establishing the Context—the TDS, 65

4.1.1 Societal and Institutional Contexts, 66

4.1.2 Technology Context, 67

4.1.3 Stakeholders, 68

4.1.4 Understanding the TDS, 69

4.1.5 An Example TDS Model, 70

4.2 Monitoring, 72

4.2.1 Why Monitor?, 74

4.2.2 Who Should Monitor?, 75

4.2.3 Monitoring Strategy, 76

4.2.4 Monitoring Focused on Management of Technology Issues, 79

4.2.5 Monitoring Focused on the Stage of the Technology Development, 81

4.3 The Stimulation of Creativity, 81

4.3.1 Five Elements of Creativity, 81

4.3.2 Group Creativity, 92

4.4 Conclusion, 95

References, 95

5 Gathering and Using Information 98

5.1 Expert Opinion, 99

5.1.1 Selecting Experts, 99

5.1.2 Selecting Expert Opinion Techniques, 100

5.2 Gathering Information on the Internet, 105

5.2.1 Science and Technology on the Internet, 106

5.2.2 Society and Culture on the Internet, 109

5.3 Structuring the Search, 113

5.4 Preparing Search Results, 116

5.5 Using Search Results, 117

5.6 Developing Science, Technology, and Social Indicators, 119

5.6.1 Science and Technology Indicators, 119

5.6.2 Social Indicators, 122

5.7 Communicating Search Results, 122

5.8 Conclusions, 123

References, 124

6 Analyzing Phase 129

6.1 Perspective on Data and Methods, 129

6.1.1 Overview and Caveats, 130

6.1.2 Internet Time Series Data and Trends, 132

6.1.3 Analytical Modeling, 133

6.2 Linear Regression and Extensions, 134

6.3 Growth Models, 138

6.3.1 The Models, 138

6.3.2 Dealing with the Data, 143

6.3.3 Regression and Growth Modeling: What Can Go Wrong?, 144

6.4 Simulation, 145

6.4.1 Quantitative Cross-Impact Analysis, 146

6.4.2 Qualitative Cross-Impact Analysis, 152

6.5 Monte Carlo Simulation, 153

6.5.1 Generating and Displaying Random Values, 153

6.5.2 Sampling Multiple Random Variables, 154

6.5.3 RFID Application in a Hospital Decision, 156

6.6 System Dynamics, 158

6.6.1 The System Dynamics Modeling Cycle, 159

6.6.2 A Technology Forecasting Example: The Cable-to-the-Curb Model, 162

6.7 Gaming, 164

6.7.1 Decision Trees, 165

6.7.2 Bayesian Estimation, 166

6.7.3 Value of Information, 167

6.7.4 Real Options Analysis, 169

6.8 Software Suggestions, 170

6.8.1 Software for Regression, 170

6.8.2 Simulation Analysis Software, 170

6.8.3 Software for Analysis of Decisions, 170

6.8.4 Real Options Super Lattice Software, 170

6.8.5 Software Sites, 171

References, 171

7 Focusing Phase: Using Scenario Analysis 174

7.1 Uncertainty, 175

7.1.1 Uncertainty Frameworks, 175

7.1.2 Source and Nature of Uncertainty, 176

7.1.3 Uncertainty and the Adaptive Paradigm, 177

7.1.4 Techniques for Addressing Uncertainty, 177

7.2 Scenarios, 178

7.2.1 Steps in Creating Scenarios, 178

7.2.2 Types of Scenarios, 182

7.3 Examples and Applications, 184

7.3.1 Scenarios for Renewable Energy Planning, 184

7.3.2 Pervasive Computing Scenarios, 185

7.3.3 Scenarios for Social Change, 186

7.4 Scenarios: Extensions and Advanced Techniques, 187

7.4.1 Scenarios in Multimethodology Forecasts, 187

7.4.2 Extensions of Scenario Analysis, 189

7.5 Conclusions, 191

References, 192

8 Economic and Market Analysis 194

8.1 The Context, 194

8.1.1 Markets and Innovation, 197

8.1.2 Technology and Institutions, 199

8.2 Forecasting the Market, 203

8.2.1 The Consumer/Customer Marketplace, 204

8.2.2 Qualitative Techniques for Appraising Market Potential, 206

8.2.3 A Quantitative Approach—Adoption and Substitution: S-Curve Models, 207

8.3 Forecasting the Economic Context, 208

8.3.1 Macroeconomic Forecasting, 209

8.3.2 Input-Output Analysis, 210

8.3.3 General Equilibrium Models, 214

8.3.4 Hedonic Technometrics, 215

8.4 Forecasting in an Institutional Context, 216

8.4.1 Institutional Arrangements and the Market, 216

8.4.2 Game Theory, 218

8.4.3 Agent-Based Models, 219

8.5 Conclusion, 219

References, 220

9 Impact Assessment 223

9.1 Impact Assessment in Technology Forecasting, 223

9.2 Impacts on Technology and Impacts of Technology, 224

9.3 A Comprehensive Approach to Impact Assessment, 225

9.4 Impact Identification, 226

9.4.1 Scanning Techniques, 226

9.4.2 Tracing Techniques, 227

9.4.3 Narrowing the Impact Set and Estimating Effects, 229

9.4.4 A Final Word, 229

9.5 Impact Analysis, 230

9.5.1 Analyzing Impacts on and Impacts of the Technology, 230

9.5.2 Analyzing Technological Impacts, 232

9.5.3 Analyzing Economic Impacts, 234

9.5.4 Analyzing Environmental Impacts, 234

9.5.5 Analyzing Social Impacts, 238

9.5.6 Analyzing Institutional Impacts, 239

9.5.7 Analyzing Political Impacts, 240

9.5.8 Analyzing Legal and Regulatory Impacts, 241

9.5.9 Analyzing Behavioral, Cultural, and Values Impacts, 242

9.5.10 Analyzing Health-Related Impacts, 243

9.6 Impact Evaluation, 244

9.7 Conclusion, 245

References, 245

10 Cost-Benefit and Risk Analysis 248

10.1 Opportunity Costs and Choices, 248

10.2 Cost-Benefit Analysis, 249

10.2.1 Cost-Benefit Analysis within the Organization, 249

10.2.2 Societal Stake and the Organizational Response, 253

10.2.3 Cost-Benefit Analysis Methods, 260

10.2.4 Economic Value Added, 263

10.2.5 Earned Value Management, 264

10.2.6 The Balanced Scorecard, 265

10.3 Accounting for Risk and Uncertainty, 265

10.3.1 Accounting for Risk within Organizations, 265

10.3.2 Accounting for Risk—the Social Dimension, 269

10.4 Concluding the Focusing Phase, 273

References, 274

11 Implementing the Technology 277

11.1 Forecasting Continues, 277

11.2 Implementation Issues, 278

11.3 Strategic Planning for Technology Implementation, 278

11.4 Selecting from among Alternative Implementations of the Technology, 279

11.4.1 Measurement, 282

11.4.2 Interpretive Structural Modeling, 284

11.4.3 Analytic Hierarchy Process, 285

11.4.4 Wrap-Up, 286

11.5 Technology Roadmapping, 286

11.6 Summary and Concluding Observations, 287

References, 287

12 Managing the Present from the Future 289

12.1 The Overall Approach, 289

12.2 Selecting Methods and Techniques, 290

12.2.1 Using the TDS and the Major Families of Techniques, 290

12.2.2 The 80–20 Rule, 291

12.3 Alternative Perspectives, 291

12.4 Learning from Past Forecasts and Assessments, 293

12.5 Visions, 295

12.6 A Final Word, 295

References, 296

Appendix A Case Study on Forecasting Dye-Sensitized Solar Cells 297

A.1 Framing the Case Study, 297

A.1.1 Characterizing the Technology, 298

A.1.2 Dye-Sensitized Solar Cells, 299

A.2 Methods, 299

A.2.1 Engaging Experts and Multipath Mapping, 299

A.2.2 Developing the TDS, 300

A.2.3 Tech Mining (Chapter 5) and Science Overlay Mapping, 304

A.2.4 Trend Analyses, 310

A.2.5 Cross-charting and Social Network Analyses, 311

A.3 The Rest of the Story, 313

A.3.1 Market Forecasts, 314

A.3.2 Scenarios, 315

A.3.3 Technology Assessment, 315

A.3.4 Further Analyses and Communicating Results, 316

References, 316

Index 319