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184 Applying simulation to decision problems Applying simulation to a decision problem The Elite Pottery Company We will now show how simulation can be applied to a decision problem. The Elite Pottery Company is planning to market a special product to commemorate a major sporting event which is due to take place in a few months’ time. A large number of possible products have been considered, but the list has now been winnowed down to two alternatives: a commemorative plate and a figurine. In order to make a decision between the plate and the figurine the company’s managing director needs to estimate the profit which would be earned by each product (the decision will be made solely on the basis of profit so that other objectives such as achieving a prestigious company image, increasing public awareness of the company, etc. are not considered to be important). There is some uncertainty about the costs of manufacturing the products and the levels of sales, although it is thought that all sales will be made in the very short period which coincides with the sporting event. The application of simulation to a problem like this involves the following stages: (1) Identify the factors that will affect the payoffs of each course of action. (2) Formulate a model to show how the factors are related. (3) Carry out a preliminary sensitivity analysis to establish the factors for which probability distributions should be assessed. (4) Assess probability distributions for the factors which were identified in stage 3. (5) Perform the simulation. (6) Apply sensitivity analysis to the results of the simulation. (7) Compare the simulation results for the alternative courses of action and use these to identify the preferred course of action. We will now show how each of these stages can be applied to the Elite Pottery Company problem. Stage 1: Identify the factors The first stage in our analysis of Elite’s problem is to identify the factors which it is thought will affect the profit of the two products. For brevity, we will only consider in detail the factors affecting the potential
Applying simulation to a decision problem 185 Profit Sales revenue Costs Sales Price Fixed costs Variable costs Figure 7.1 – Identifying the factors which will affect the profit earned by the commemorative plate profit of the commemorative plate. A tree diagram may be helpful in identifying these factors, since it enables them to be subdivided until the decision maker feels able to give a probability distribution for the possible values which the factor might assume. Figure 7.1 shows a tree for this problem. Of course, it might have been necessary to extend the tree further, perhaps by subdividing fixed costs into different types, such as advertising and production set-up costs or breaking sales into home and export sales. It is also worth noting that subsequent analysis will be simplified if the factors can be identified in such a way that their probability distributions can be considered to be independent. For example, we will assume here that variable costs and sales are independent. However, in practice, there might be a high probability of experiencing a variable cost of around $7 per plate if less than 10 000 plates are sold, while we might expect costs of around $5 if more than 10 000 are sold because of savings resulting from the bulk purchase of materials, etc. It is possible to handle dependence, as we will show later, but it does add complications to the analysis. Stage 2: Formulate a model Having identified the factors for which probability distributions can be assessed, the next step is to formulate a mathematical model to show how they affect the variable of interest, in this case profit. For Elite’s problem the following model is thought to be appropriate: Profit = (Price − Variable cost) × Sales − Fixed costs Of course, this is only a model and therefore almost certainly a simplification of the real problem. In practice, a large number of factors and relationships which we have not included in the model may affect profit. For example, at higher sales levels more breakages may occur
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Decision Analysis for Management Ju
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Decision Analysis for Management Ju
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To Mary and Josephine, Jamie, Jerom
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viii Contents Chapter 16 The analyt
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x Foreword real problems, and it is
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xii Preface accountancy, where rece
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1 Introduction Complex decisions Im
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The role of decision analysis 3 you
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Applications of decision analysis 5
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Overview of the book 11 and profit.
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References 13 8. Walls, M. R., Mora
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16 How people make decisions involv
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28 Decisions involving multiple obj
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72 Introduction to probability Beca
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74 Introduction to probability prac
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76 Introduction to probability we w
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78 Introduction to probability whet
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80 Introduction to probability give
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82 Introduction to probability prob
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84 Introduction to probability deci
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86 Introduction to probability that
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88 Introduction to probability inte
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90 Introduction to probability subj
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92 Introduction to probability (5)
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94 Introduction to probability (a)
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96 Decision making under uncertaint
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98 Decision making under uncertaint
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100 Decision making under uncertain
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Page 150 and 151: 134 Decision making under uncertain
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Page 165 and 166: Decision trees and utility 149 succ
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Page 169 and 170: Practical applications of decision
Page 171 and 172: Assessment of decision structure 15
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Page 175 and 176: Eliciting decision tree representat
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Page 179 and 180: Summary 163 where the resulting dec
Page 181 and 182: Exercises 165 other elements of the
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Page 187 and 188: Exercises 171 failing to meet the p
Page 189 and 190: Exercises 173 why it was rational f
Page 191 and 192: Exercises 175 (11) In the Eagle Mou
Page 193 and 194: References 177 ABC Chemicals are pl
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Page 197 and 198: Monte Carlo simulation 181 Of cours
Page 199: Monte Carlo simulation 183 Table 7.
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Page 213 and 214: Applying simulation to investment d
Page 221 and 222: Summary 205 Hull 10 ), some of them
Page 223 and 224: Exercises 207 (c) Use your simulati
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Page 227 and 228: Exercises 211 (b) Suppose that your
Page 229: References 213 6 million Therefore
Page 232 and 233: 216 Revising judgments in the light
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234 Revising judgments in the light
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9 Biases in probability assessment
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Introduction 249 of people watching
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The availability heuristic 251 make
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The representativeness heuristic 25
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The anchoring and adjustment heuris
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The anchoring and adjustment heuris
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Other judgmental biases 263 Other j
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Is human probability judgment reall
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Exercises 271 Did you receive timel
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References 273 have been taken from
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References 275 18. Hamilton, D. L.
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10 Methods for eliciting probabilit
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Preparing for probability assessmen
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Consistency and coherence checks 28
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Assessment of the validity of proba
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Assessment of the validity of proba
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Assessing probabilities for very ra
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Exercises 293 Odds in favor of even
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References 295 13. Wright, G. and W
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298 Risk and uncertainty management
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310 Decisions involving groups of i
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330 Resource allocation and negotia
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14 Decision framing and cognitive i
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How people frame decisions 357 Figu
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Imposing imaginary constraints and
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Inertia in strategic decision makin
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Studies in the psychological labora
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Overcoming inertia? 369 it is diffi
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Discussion questions 373 frame anal
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References 375 References 1. Luchin
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15 Scenario planning: an alternativ
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Introduction 379 documented in Chap
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Scenario construction: the extreme-
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Using scenarios in decision making
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Using scenarios in decision making
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Scenario construction: the driving
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Case study of a scenario interventi
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Table 15.1 - The components of the
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Illustrative case study 403 (b) Att
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Illustrative case study 405 Stage 4
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Illustrative case study 407 importa
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Conclusion 409 combinations. Often
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References 411 2. Van der Heijden,
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414 The analytic hierarchy process
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17 Alternative decision-support sys
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Expert systems 429 generally agreed
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Expert systems 431 that knowledge e
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Expert systems 433 (1) That the sub
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Expert systems 435 information syst
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Expert systems 437 to focus on ‘t
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Expert systems 439 On the basis of
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Is there any intention/expectation
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Expert systems 443 described above
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Expert systems 445 body of knowledg
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Statistical models of judgment 447
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Comparisons 453 ‘broken leg’ cu
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Some final words of advice 455 Ques
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Some final words of advice 457 of t
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References 459 Table 17.1 - Summary
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References 461 20. Eisenhart, J. (1
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Chapter 3 Suggested answers to sele
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Suggested answers to selected quest
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472 Index Brown, C.E. 446 Brown, S.
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474 Index HIVIEW 58 Hodgkinson, G.P
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476 Index scenario intervention cas
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