《Management Science：Decision Making Through Systems Thinking.pdf》由会员分享，可在线阅读，更多相关《Management Science：Decision Making Through Systems Thinking.pdf（615页珍藏版）》请在三一文库上搜索。
1、Management science Decision making through systems thinking Hans G. Daellenbach and Donald C. McNickle Management science Decision making through systems thinking This page intentionally left blank Management science Decision making through systems thinking Hans G. Daellenbach Donald C. McNickle Uni
2、versity of Canterbury, Christchurch, New Zealand H. G. Daellenbach and D. C. McNickle 2005 All rights reserved. No reproduction, copy or transmission of this publication may be made without written permission. No paragraph of this publication may be reproduced, copied or transmitted save with writte
3、n permission or in accordance with the provisions of the Copyright, Designs and Patents Act 1988, or under the terms of any licence permitting limited copying issued by the Copyright Licensing Agency, 90 Tottenham Court Road, London W1T 4LP. Any person who does any unauthorised act in relation to th
4、is publication may be liable to criminal prosecution and civil claims for damages. The authors have asserted their rights to be identified as the authors of this work in accordance with the Copyright, Designs and Patents Act 1988. First published 2005 by PALGRAVE MACMILLAN Houndmills, Basingstoke, H
5、ampshire RG21 6XS and 175 Fifth Avenue, New York, N. Y. 10010 Companies and representatives throughout the world PALGRAVE MACMILLAN is the global academic imprint of the Palgrave Macmillan division of St. Martins Press LLC and of Palgrave Macmillan Ltd. Macmillan is a registered trademark in the Uni
6、ted States, United Kingdom and other countries. Palgrave is a registered trademark in the European Union and other countries. ISBN 1403941742 This book is printed on paper suitable for recycling and made from fully managed and sustained forest sources. A catalog record for this book is available fro
7、m the Library of Congress. 10987654321 14131211100908070605 Printed and bound in China A catalogue record for this book is available from the British Library. “If we investigate our ideas, we have to be willing to give them up.” Gordon Hewitt, PhD Wellington This page intentionally left blank Conten
8、ts Prefacexiii 1Introduction1 1.1Motivation1 1.2Systems thinking5 1.3Overview of what follows6 Part 1Systems and systems thinking: Introduction 2Systems thinking10 2.1Increased complexity of todays decision making10 2.2Efficiency and effectiveness13 2.3Unplanned and counterintuitive outcomes15 2.4Re
9、ductionist and cause-and-effect thinking17 2.5Systems thinking18 2.6Chapter highlights19 Exercises19 3System concepts21 3.1Pervasiveness of systems21 3.2Out-there and inside-us view of systems22 3.3Subjectivity of system description24 3.4Formal definition of the concept system27 3.5System boundary a
10、nd relevant environment29 3.6Some examples of system descriptions30 3.7Systems as black boxes34 3.8Hierarchy of systems35 3.9System behaviour37 3.10Different kinds of system40 3.11Feedback loops42 3.12Control of systems44 3.13Chapter highlights49 Exercises50 4The problem situation53 4.1The problem s
11、ituation and what is a problem?53 4.2Stakeholders or roles of people in systems56 4.3Problem situation summary mind maps59 4.4Rich picture diagrams61 vii 4.5Guidelines for mind maps and rich pictures63 4.6Uses and strengths of rich pictures and mind maps65 4.7Cognitive mapping66 4.8Cognitive map for
12、 NuWave Shoes67 4.9Problem definition and boundary selection73 4.10Some conclusions75 4.11Chapter highlights75 Exercises76 5Systems models and diagrams81 5.1System models81 5.2Approaches for describing a relevant system83 5.3Essential properties of good models87 5.4The art of modelling90 5.5Causal l
13、oop diagrams92 5.6Influence diagrams95 5.7Other system diagrams99 5.8Chapter highlights105 Exercises106 Part 2Management science methodologies: Introduction 6Overview of hard OR methodology113 6.1Hard OR paradigm and diagrammatic overview113 6.2Problem formulation or problem scoping114 6.3The projec
14、t proposal or go-ahead decision116 6.4The problem modelling phase119 6.5The implementation phase123 6.6The nature of the hard OR process123 6.7The Lubricating Oil Division a situation summary125 6.8Identifying the problem to be analysed128 6.9Relevant system for stock replenishment problem131 6.10Pr
15、oject proposal for LOD133 6.11A complete definition of the relevant LOD system134 6.12Mathematical models137 6.13Mathematical model for LOD: first approximation140 6.14Second approximation for LOD model142 6.15Exploring the solution space for T(L, Q)143 6.16Testing the LOD model147 6.17Sensitivity a
16、nd error analysis of the LOD solution147 6.18Project report and implementation150 6.19Deriving a solution to the model150 6.20Reflections on the hard OR methodology154 6.21Chapter highlights156 viiiContents Exercises157 Appendix 1163 Appendix 2166 7Soft systems thinking171 7.1Soft system paradigm an
17、d working modes172 7.2Checklands soft systems methodology175 7.3SSM applied to the NuWave Shoe problem177 7.4Strategic option development and analysis182 7.5Strategic choice approach184 7.6SCA applied to NuWave Shoes187 7.7Survey of other problem structuring approaches192 7.8Critical systems heurist
18、ics, critical systems thinking, meta-methodologies196 7.9Concluding remarks201 7.10Chapter highlights202 Exercises203 8Implementation and code of ethics205 8.1Implementation and its difficulties205 8.2Planning for implementation207 8.3Controlling and maintaining the solution210 8.4Following up imple
19、mentation and model performance212 8.5Ethical considerations213 8.6Chapter highlights216 Exercises217 Part 3Assessing costs and benefits, and dealing with time 9Relevant costs and benefits219 9.1Explicit, implicit, and intangible costs219 9.2Accounting versus economics concepts of costs221 9.3Releva
20、nt costs and benefits223 9.4Champignons Galore problem formulation228 9.5Champignons Galore analysis of costs232 9.6Mathematical model for annual profit235 9.7Computation of cost factors for each subsystem237 9.8Analysis of Champignons Galore by spreadsheet238 9.9Chapter highlights238 Exercises241 A
21、ppendix: Champignons Galore situation summary245 10 Discounted cash flows251 10.1The time value of money252 Contentsix 10.2The present value of a series of cash flows254 10.3Annuities and perpetuities257 10.4Accept/reject criteria for financial projects258 10.5Choice of target rate of return259 10.6
22、Spreadsheet financial functions262 10.7Dependent and mutually exclusive projects264 10.8Replacement decisions268 10.9Chapter highlights275 Exercises 11 Decision making over time282 11.1The planning horizon283 11.2Situation summary for seasonal production plan286 11.3Choice of planning horizon288 11.
23、4Influence diagram for production planning problem289 11.5Spreadsheet model290 11.6Finding the optimal production plan293 11.7Considerations for practical implementation297 11.8An example of a rolling planning horizon298 11.9Minimum length of planning horizon303 11.10Chapter highlights303 Exercises3
24、04 Part 4Hard MS/OR methods 12 Marginal and incremental analysis310 12.1Marginal analysis versus incremental analysis310 12.2Total costs, marginal and average costs311 12.3Total revenue and marginal revenue317 12.4Breakeven analysis318 12.5Basic principle of marginal analysis321 12.6Applications of
25、marginal analysis322 12.7Marginal analysis for continuous variables325 12.8Marginal analysis and differential calculus326 12.9Incremental analysis327 12.10 A logistics analysis328 12.11 An investment portfolio selection336 12.12 Chapter highlights338 Exercises 13 Constrained decision making342 13.1R
26、esource constraint on a single activity343 13.2Sensitivity analysis346 13.3Shadow price of a constraint347 xContents 13.4Interpretation and uses of shadow price350 13.5Several activities sharing a limited resource352 13.6Discrete and irregular sized requirements of a resource354 13.7Chapter highligh
27、ts356 Exercises356 14 Multiple constraints: linear programming359 14.1Constrained optimization360 14.2A product mix example362 14.3A linear programming model365 14.4Solution by computer368 14.5Effect of forcing production of luxury378 14.6Pineapple Delight case study379 14.7A transportation problem3
28、86 14.8Chapter highlights391 Exercises392 Appendix: Graphical solution to an LP401 15 Uncertainty407 15.1Linguistic ambiguity about uncertainty408 15.2Causes of uncertainty410 15.3Types and degrees of uncertainty411 15.4Prediction and forecasting412 15.5Predictions by expert judgement415 15.6Probabi
29、lity measures and their interpretation418 15.7Behavioural research on subjective probabilities420 15.8Random variables and probability distributions425 15.9Expected value and standard deviation426 15.10 Approaches to deal with/reduce uncertainty427 15.11 Decision criteria under uncertainty430 15.12
30、Chapter highlights431 Exercises432 16 Waiting lines: stochastic systems434 16.1Waiting lines435 16.2What causes queues to form?438 16.3Formulas for some simple queueing models443 16.4The NZ Forest Products weighbridge case451 16.5The two-weighbridge option457 16.6Some conclusions458 16.7Chapter high
31、lights459 Exercises460 Contentsxi 17 Simulation and system dynamics463 17.1The weighbridge problem revisited464 17.2The structure of simulation models472 17.3How is a simulation planned and run?477 17.4Computer simulation packages483 17.5Other simulation structures485 17.6System dynamics continuous
32、system simulation487 17.7A simple health and social services model in ithink488 17.8Process design in UK health care and social services490 17.9Conclusions on simulation as a tool496 17.10 A comparison of the weighbridge queueing and simulation models500 17.11 Chapter highlights501 Exercises502 18 D
33、ecision and risk analysis506 18.1Setting up a decision problem507 18.2A decision problem with monetary outcomes511 18.3The expected value of perfect information516 18.4Capturing the intrinsic worth of outcomes518 18.5Utility analysis521 18.6Risk analysis: basic concepts526 18.7Risk analysis for a sk
34、i-field development527 18.8Chapter highlights534 Exercises535 19 Decisions with multiple objectives540 19.1Three real MCDM problem situations541 19.2Traditional MS/OR approach544 19.3Some basic issues in MCDM545 19.4The process of evaluating choices548 19.5Conference venue selection550 19.6Sensitivi
35、ty analysis556 19.7Chapter highlights557 Exercises557 20 Reflections on MS/OR560 Bibliography564 Glossary of technical terms571 Index592 xiiContents xiii Preface This text is a substantive revision of Systems and Decision Making, published by John Wiley the number of automatic bank teller or cash di
36、spensing machines to install for 24-hour access. the number of crews needed by a repair or service outfit, such as an appliance ser- vice firm or a photocopying machine service firm. the number of nurses and/or doctors on duty at an emergency clinic during various hours of the week. the degree of re
37、dundancy built into equipment to prevent failure breakdown. Vehicle scheduling Pick-up and delivery firms, like courier services, pick up and drop off goods at a number of places. The locations of these pick-ups and drop-offs may differ daily or even hourly, with new locations added to the list of l
38、ocations to visit. Certain of the customers may specify a given time period or time window during which the visit must occur. The vehicle used may have a limited carrying capacity. The length of time drivers can be on the road in one shift may be subject to legal restrictions. Add to this the proble
39、m of traffic density on various city arterial roads and the consequent change in travel times between locations during the day. It is also clear that even for a small problem, the number of possible distinct sequences for visiting all locations is very large. For example, for 10 locations, there are
40、 10! = 3,628,800 different itineraries, while for 20 this number grows to about 2,432,902,000,000,000,000. Although a majority can easily be ruled out as bad, it is still a non-trivial task to select the best combination or sequence of pick-ups and deliveries from those that remain, such that all co
41、mplicating factors are taken into account. It may even be difficult to decide which criterion should be chosen for best. Is it minimum distance, or minimum time, or minimum total cost, or a compromise between these considerations? Similar types of combinatorial sequencing problems are faced by airli
42、nes for the 1.1 Motivation3 scheduling of aircraft and air crews, public bus or railroad companies for the scheduling of buses or engines and drivers, or the city rubbish collectors for determining their collection rounds. A mission statement for an organization It seems that in todays world no orga
43、nization is viewed as responsible, forward- looking, and success-oriented without having a formal mission statement. Gone are the days when it was good enough to have a group of like-minded people, under the leadership of an energetic person with good interpersonal skills, who all shared a vision, a
44、lbeit often somewhat vague. Now most organizations prominently exhibit a mission statement of what they are all about. It is proudly shown as a framed document in the CEOs office and on the organizations website. These statements are rather curious documents that literally promise the moon, but all
45、too often hardly bring about any substantive change in how the organization goes about its business, except maybe to increase the amount of paperwork to fill the many reports that claim to measure how well the organization meets its missions. Producing a meaningful mission statement is a rather diff
46、icult project. It has to be relevant for the purpose of the organization, set achievable goals that can be measured and, most importantly, get the active cooperation of its members. The trouble is that even in an a priori like-minded group of people there will be conflicts and differences in prefere
47、nce about the aims they would like the organization to pursue and their vision for its future, as well as how they see their own role in that scheme. Unless the CEO can simply impose her or his will in a dictatorial manner, coming to a meeting of minds that satisfies the three properties of relevant
48、, achievable, and measurable, and secures the active cooperation of everybody, a mission statement has to be a compromise. It is usually obtained by a lengthy process, starting out with canvassing the views of some or all members, followed by assembling them in some organized fashion, combining simi
49、lar ones, eliminating those that are subordinate to others (e.g. if A serves to achieve B, A can be dropped), restating them such that their achievement level can be measured in a meaningful way, and finally reducing the number to an essential few. This process will involve many meetings and negotiation. One of the so-called soft operations research approaches or problem structuring methods, surveyed in Chapter 7, could provide the right vehicle for this process. In most cases, to be successful it will also need a skilful facilitator to guide and cont