Product management: value, quality, cost, price, profits, and organization
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
London [u.a.]
Chapman & Hall
1997
|
| Ausgabe: | 1. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIX, 411 S. Ill., graph. Darst. |
| ISBN: | 0412799405 |
Internformat
MARC
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| 245 | 1 | 0 | |a Product management |b value, quality, cost, price, profits, and organization |c H. E. Cook |
| 250 | |a 1. ed. | ||
| 264 | 1 | |a London [u.a.] |b Chapman & Hall |c 1997 | |
| 300 | |a XIX, 411 S. |b Ill., graph. Darst. | ||
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Datensatz im Suchindex
| _version_ | 1804127315866681344 |
|---|---|
| adam_text | Contents
Preface xvii
Acknowledgments xx
1 Product realization in the global marketplace 1
1.1 Structuring the unstructured problem 1
1.2 A product management case study 2
1.2.1 As is versus to be 2
1.2.2 Market research 4
1.2.3 Value of attribute changes 4
1.2.4 Price elasticity and market size 5
1.2.5 Actions of competitors 6
1.2.6 Break even time 6
1.2.7 Making the decision 7
1.2.8 What the case shows 7
1.2.9 Market reaction to the real Concorde, a synopsis 8
1.3 The global marketplace 9
1.4 Performance hill race 13
1.5 Paradigms 14
1.6 Concurrent engineering 16
1.7 Systems viewpoint 18
1.8 Touchstones for product realization 20
1.9 Robust design 21
viii Contents
1.10 Innovation 22
1.10.1 Quantum leaps 22
1.10.2 The S curve 22
1.11 Product development lead time 24
1.11.1 Factoring product development lead time 25
1.12 Customer/company needs loop 26
References 26
Further reading 27
2 Motivation and consumer behavior 29
2.1 Product appeal 29
2.2 Human needs 30
2.3 Aggregate behavior 30
2.4 Flow charting buyer behavior 33
2.5 Three stages of problem solving 35
2.6 Behavioral economics 38
2.6.1 Elementary utility theory 38
2.6.2 Prospect theory 40
2.6.3 Contingent valuation 43
2.6.4 Product value 44
2.7 Consumer behavior assumptions of microeconomic theory 45
2.8 Aggregate product value for a market 46
2.9 Value speculation and market dynamics 48
References 54
3 Enterprise model 56
3.1 Purpose of model 56
3.2 Criteria for a model of the enterprise 58
3.3 S model 59
3.3.1 Cartel reference state 59
Contents ix
3.3.2 Linear demand equation 61
3.3.3 S model value determination from market share and price 62
3.3.4 Logit model 63
3.4 Profits and pricing 63
3.4.1 Price war 66
3.4.2 Value induced price war 67
3.4.3 Ending price wars and equilibrium models 67
3.5 Objective functions for making product decisions 69
3.5.1 A rule of thumb for pricing new products in a 69
competitive market
3.5.2 Profit as an objective function 70
3.5.3 Present worth 71
3.6 Market segmentation by price and value 72
3.6.1 Psychometric pricing of a product line 74
References 76
4 Definition of quality 77
4.1 Attributes of quality 77
4.2 The quality loss function 77
4.3 Total quality 80
4.4 Environmental quality 81
4.5 The driving force for product realization 83
References 84
5 Forecasting the value of future products 85
5.1 Importance of value 85
5.2 Knowledge of your customer 86
5.2.1 Chrysler minivan 87
5.3 Conjoint analysis case study 88
5.4 Direct value method 93
x Contents
5.4.1 Value analysis of binoculars using the DV method 94
5.4.2 Value of Mustang options 95
5.4.3 Guidelines for constructing a DV survey 97
5.5 Functional value 99
5.5.1 Generic product system attributes 99
5.6 Value curves 101
5.6.1 Cost of inferior quality (CIQ) 101
5.6.2 Taguchi s SIB, NIB, and LIB conditions 103
5.6.3 The exponentially weighted parabolic approximation for value 104
5.6.4 Geometric averaging 106
5.7 Critical attributes for automobiles 106
5.7.1 Value of vehicle length 108
5.7.2 Value of 0 to 60 mph acceleration 108
5.7.3 Determining the weighting exponent y 110
5.7.4 Time between events 111
5.7.5 Value of interior room 111
5.7.6 Comparison with multiattribute utility theory 112
5.8 Perceived versus real value in service 113
5.8.1 Value of reliability 113
5.9 Prospect theory implications on value curves 117
5.10 Value benchmarking 118
5.11 Linking subsystem and component performance to value 119
5.12 Value trends 121
References 122
6 Total quality management 124
6.1 Introduction 124
6.2 The three streams of net value 125
6.3 Special and general forms of the universal metric 125
6.4 Enterprise order and management 127
Contents xi
6.5 Organization structure 132
6.5.1 Classical administrative criteria 132
6.5.2 Functionalization criterion for product realization 133
6.6 The natural flow of product realization 134
6.6.1 System task 137
6.6.2 Subsystems tasks 137
6.6.3 Components tasks 138
6.7 Total quality performance against objectives 140
6.7.1 Traditional practices 140
6.7.2 What should performance measurements do? 141
6.7.3 System/subsystem organization 142
6.8 Activity based strategic accounting 145
6.8.1 Concept 145
6.8.2 Toward ABSA practice 149
6.9 Managing environmental quality 149
6.9.1 Mission of the regulatory agency 150
6.10 Unemployment and fair trade 153
6.11 Metric taxonomy 154
References 156
7 Product planning and quality deployment 157
7.1 Product decision making 157
7.2 Quality function deployment (QFD) 158
7.3 Strategic planning within the systems perspective 159
7.4 SQD planning at the system level 162
7.4.1 Situation analysis 162
7.4.2 Brainstorming 163
7.4.3 Reduce alternatives to a manageable number 165
7.4.4 Test alternatives 165
7.4.5 Select alternatives 166
xii Contents
7.4.6 Transmit requirements 168
7.5 SQD at subsystem level 168
7.6 SQD at component level 171
7.7 Interactions 173
7.8 Application example of system level planning 174
7.8.1 Situation analysis application 174
7.8.2 Search for and selection of opportunities 177
7.9 Making decisions for new products under uncertainty 184
References 185
8 Parameter and tolerance design 186
8.1 Introduction 186
8.1.1 Shaft design example 186
8.2 Latitude and robustness 189
8.2.1 Shirt collar example 189
8.2.2 Scaling factor: lawn mower shear pin 190
8.3 Objective functions for parameter design 192
8.3.1 Profitability 192
8.3.2 Loss function 193
8.4 Single attribute parameter design 195
8.4.1 Signal to noise ratio 195
8.4.2 NIB1 196
8.4.3 SIB, NIB2, and LIB 197
8.4.4 Single attribute CIQ and loss function 200
8.5 Orthogonal arrays 201
8.6 Noise factors and the outer array 205
8.7 The steps for single attribute parameter design 207
8.8 Production examples of parameter design 207
8.8.1 CVD process example 208
8.8.2 Dielectric bond process optimization 208
Contents xiii
8.8.3 Printed circuit board drill bits 209
8.8.4 Truck leaf springs 209
8.9 A NIB1 case study 210
8.10 Controversy 212
References 213
9 Significance of results 214
9.1 Introduction 214
9.1.1 Risk 214
9.1.2 Risk management 214
9.1.3 Types of uncertainties 216
9.1.4 Approach to risk assessment 216
9.2 NIB1 example 217
9.2.1 Statistical significance of the two variances 217
9.2.2 Statistical significance of the two averages 219
9.2.3 Best set point 219
9.2.4 Strategic significance 219
9.2.5 Incorporating cost differences into the distribution 223
9.3 Type I and Type II errors in experimental design 226
9.3.1 Demonstration of Type I and Type II errors 226
9.3.2 Experiment wise error 228
9.4 Steps in single attribute significance testing 229
9.5 NIB1 example from Chapter 8 234
9.6 Unsaturated designs 238
9.7 Saturated designs 240
9.8 Concluding remarks regarding the analysis of strategic experiments 243
References 245
10 Costs 246
10.1 Activity based costing 246
xiv Contents 10.2 Cost drivers 247
10.3 Boothroyd and Dewhurst design for manual assembly 249
10.3.1 Fixed length sheer example 252
10.4 Shipping and inventory costs 252
10.5 Just in time 256
10.6 Target costing using the S model 258
References 260
11 Statistical quality control 262
11.1 End of line inspection 262
11.2 Statistical process control 262
11.3 Target practice example 263
11.4 Classical long run SPC 267
11.5 Process capability 273
11.6 Statistical tolerancing 274
11.7 Short production runs 276
11.7.1 General considerations 277
11.7.2 Short run variance limits 279
11.7.3 Short run average limits 282
11.7.4 Short run capability 283
11.7.5 Short run control 283
11.7.6 Short run example 284
11.8 Continuous improvement (Motorola s Six Sigma Process) 284
11.8.1 Motorola s Six Sigma SPC Program 286
References 288
Case study 1 NIB1 single attribute thin film 289
CS1.1 The problem 289
CS1.2 The experimental design 289
CS1.3 Thickness measurements 290
Contents xv
CS1.4 TestofHl0 293
CS1.5 TestofH20 294
CS1.6 Strategic significance 294
CS1.7 Strategic implications 297
Case study 2 NIB2 problem 298
Reference 307
Case study 3 LIB problem 308
Reference 315
Case study 4 Significance testing a multi attribute problem 316
CS4.1 Multi attribute value 317
CS4.2 Sample measurements 319
CS4.3 Coefficients for variances and averages 320
CS4.4 The y(VjV2v3) value product coefficients 324
Reference 329
Case study 5 Error analysis for direct value (DV) method 330
Reference 333
Case study 6 Use of the direct value (DV) method when
considering multiple attributes jointly 334
Appendix A Probability and statistics 339
A.1 Concept of probability 339
A.2 Frequency functions, expectations, and the normal distribution 341
A.3 Central limit theorem 343
A.4 Normal probability plots 344
A.5 Hypothesis testing 344
A.6 The chi squared distribution 349
A.7 The F distribution (significance between two measured 351
sample variances)
xvi Contents
A.8 Selecting points at random from distributions 356
A.8.1 Simulating t and chi squared distributions 356
A.8.2 Simulating the lognormal distribution 359
A.9 Significance of £j coefficients 360
References 362
Appendix B Design of experiments 364
B.I Introduction 364
B.2 The lambda set point series 364
B.2.1 Number of unknowns equals the number of trials 366
B.2.2 Number of trials is greater than the number of unknowns 367
B.3 Comparison to Taylor s series 368
B.4 The phi set point series 369
B.5 Baseline considerations 370
B.6 [X] array construction rules 370
B.6.1 Construction of [X] for an orthogonal array 371
B.7 Comparisons with full factorial arrays 371
B.8 Designing an experiment 375
B.8.1 Efficient experimental design 376
B.8.2 Confounding 376
B.8.3 The not quite orthogonal array 378
B.9 Student s t for A coefficients 380
B.9.1 Orthogonal arrays (OA) versus one at a time (OaaT) 382
B.10 [X]A versus [X]^ for significance testing 383
References 389
Index 391
|
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| spelling | Cook, Harry E. Verfasser aut Product management value, quality, cost, price, profits, and organization H. E. Cook 1. ed. London [u.a.] Chapman & Hall 1997 XIX, 411 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Productbeleid gtt Product management Produktmanagement (DE-588)4125960-9 gnd rswk-swf Produktmanagement (DE-588)4125960-9 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008600394&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Product management value, quality, cost, price, profits, and organization |
| title_auth | Product management value, quality, cost, price, profits, and organization |
| title_exact_search | Product management value, quality, cost, price, profits, and organization |
| title_full | Product management value, quality, cost, price, profits, and organization H. E. Cook |
| title_fullStr | Product management value, quality, cost, price, profits, and organization H. E. Cook |
| title_full_unstemmed | Product management value, quality, cost, price, profits, and organization H. E. Cook |
| title_short | Product management |
| title_sort | product management value quality cost price profits and organization |
| title_sub | value, quality, cost, price, profits, and organization |
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