
Smart Decisions
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In Smart Decisions: A Structured Approach to Decision Analysis using MCDA, a distinguished team of decision-making specialists delivers a comprehensive and insightful exploration of the fundamentals of Multi-Criteria Decision Analysis methods. The book offers guidance on modeling decision problems using some of the most powerful methods in operations research.
Each chapter introduces a core MCDA method and guides the reader through a step-by-step approach to the implementation of the method using Microsoft® Excel® and then using R, a popular analytical language.
The book also includes:
* A thorough, step-by-step guide to Multi-Criteria Decision Analysis methods and the application of these methods in Microsoft Excel and R
* Extensive illustrations, R code, and software screenshots to aid the reader's understanding of the concepts discussed within
* A starter's guide to Excel and R programming
Perfect for graduate students in MBA programs and business schools, Smart Decisions: A Structured Approach to Decision Analysis Using MCDA is also an ideal resource for practitioners who apply MCDA in business, finance, applied mathematics, and engineering.
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Persons
Dr. Richard Edgar Hodgett is the MBA director and an associate professor in business analytics and decision science at Leeds University Business School. He previously was the director of student education for the Management Department and the program director of the MSc in Business Analytics and Decision Sciences. Richard specialises in creating decision support systems and working with industry to solve analytical problems. Prior to his academic career, Richard was an Innovation Specialist who developed software now used by some of the world?s leading companies in the pharmaceutical and speciality chemical sectors.
Dr. Sajid Siraj is an associate professor in business analytics and the program director for a postgraduate program in business analytics and decision sciences. He is an active researcher in the field of decision support systems. He started his career as an electrical engineer working on microchip designing and developing device drivers. He also worked in the telecom sector for many years working on machine learning tools to identify potential frauds. Dr Siraj has developed open-source decision support tools which have been downloaded around the globe and has been used in numerous organisations. Dr Siraj has published in quality journals in the fields of operational research and decision support. His main research interests are in the field of explainability and fairness in decision support systems, primarily focusing on the machine learning algorithms.
Dr. Ellen Louise Hogg is a lecturer in business analytics who specialises in teaching data analytics, interactive visualisations and statistics. Louise gained her PhD at the University of Bristol investigating the mechanisms of memory that are affected during Alzheimer?s disease. She then moved on to become a postdoctoral researcher at the University of Bradford where she further investigated how inflammatory factors effect mechanisms of memory and specifically the role that these could be playing in associated diseases. It is the statistical and analytical skills that she learnt here that lead her to becoming interested in data analytics.
Content
Preface vii
Acknowledgements ix
Chapter 1 - Introduction 1
1.1 How to Structure Your Decisions? 3
1.2 Different Stages in Decision-making 4
Chapter 2 - Get Started with Excel and R 9
2.1 Get Started with R 9
2.1.1 Types of Data in R 11
2.1.2 Work with Data in R 14
2.2 Get Started with Excel 16
2.2.1 Freeze Panes 18
2.2.2 Excel Formulas 18
2.2.3 Formatting Cells 19
2.2.4 Conditional Formatting 20
2.2.5 IF Statements 22
2.2.6 Charts 22
2.2.7 Searching and Sorting 26
2.2.8 Pivot Tables 28
2.2.9 Excel Solver 29
Chapter 3 - Direct Rating Methods 33
3.1 Select a House Using a Direct Rating Method in Excel 35
3.2 Select a House Using a Direct Rating Method in R 44
3.3 Further Problems to Test Your Direct Rating Method Skills 45
3.3.1 Purchase a New Laptop Using a Direct Rating Method 45
3.3.2 Select Manufacturing Equipment Using a Direct Rating Method 46
Chapter 4 - Pairwise Comparison Methods 47
4.1 Select a Candidate to Hire Using AHP in Excel 52
4.2 Select a Candidate to Hire Using AHP in R 60
4.3 Further Problems to Test Your AHP Skills 61
4.3.1 Select Equipment to Build Using AHP 62
4.3.2 Select a Server to Buy Using AHP 62
Chapter 5 - Ideal Point Methods 65
5.1 Select a Car to Purchase Using TOPSIS in Excel 68
5.2 Select a Car to Purchase Using TOPSIS in R 76
5.3 Further Problems to Test Your TOPSIS Skills 77
5.3.1 Select Office Space Using TOPSIS 77
5.3.2 Select Venue for Lunch Using TOPSIS 78
Chapter 6 - Outranking Methods 79
6.1 Introduction to ELECTRE 80
6.1.1 Concordance and Discordance 82
6.1.2 Credibility 85
6.1.3 Distillation 86
6.2 ELECTRE in Microsoft Excel 87
6.3 ELECTRE in R 92
6.4 Further Problems to Test Your ELECTRE Skills 94
Chapter 7 - Promethee 97
7.1 Theme Park 99
7.2 PROMETHEE in Excel 103
7.3 PROMETHEE in R 106
7.4 Further Problems to Test Your PROMETHEE Skills 107
Chapter 8 - Goal Programming 109
8.1 Select How Many Products to Manufacture Using Goal Programming in Excel 110
8.2 Select How Many Products to Manufacture Using Goal Programming in R 121
8.3 Further Problems to Test Your Goal Programming Skills 122
Chapter 9 - Evolutionary Optimisation 125
9.1 European Road Trip 125
9.2 Model the European Road Trip in Excel 126
9.3 Model the European Road Trip in R 132
9.4 Further Problems to Test Your Evolutionary Optimisation Skills 134
Chapter 10 - Dealing with Uncertainty 137
10.1 Select the Best Way to Cut Down a Tree in Excel 140
10.2 Select the Best Way to Cut Down a Tree in R 148
10.3 Further Problems to Test Your SURE Skills 149
10.3.1 Project Planning 149
10.3.2 Taking a Job 150
Index 151
1
Introduction
Welcome to Smart Decisions where you will learn about many ways to model and solve complex decision problems using Multi-Criteria Decision Analysis (MCDA). Each chapter will take you through a simple and common decision problem that most people face in their lifetimes, showing you how to solve it with a structured decision-making methodology in both Microsoft Excel and R. Microsoft Excel is the primary tool used in business and education for making spreadsheets and interactive formulaic templates while R is a popular tool used by specialists in analytics, data science and statistics. If you are not familiar with either Excel or R, don't worry! Chapter 2 is dedicated to telling you all about these software packages and how to use them. Trust me you will be an Excel and R whizz-kid in no time. That being said, this is not the primary aim of this book. The core of this book is to teach you about all of the wonderful and powerful decision-making methodologies out there which will help you justify and make better decisions at work and at home.
Let's start by discussing a hypothetical decision problem. Imagine you are a student who has just graduated and after years of partying and hard work you now have to decide what to do with your life. You are considering three distinct options; (1) find a job, (2) do further studies, or (3) start your own business. Your parents tell you to find a job related to your degree but your university professor suggests that you should do further studies before starting a professional career. To make matters more difficult, your friend, a recently established entrepreneur, has a great business idea and suggests you become a partner in their business. How do you decide what to do?
There are lots of interesting behavioural aspects to consider here, such as do you unconsciously favour the first option you discussed with your friend (this is referred to as anchoring) or do you prefer to stay in education as you haven't worked or started a business before (referred to as familiarity bias)? Although it is very important to acknowledge and understand the behavioural aspects of human decision-making, this will be rarely discussed in this book as the focus here is on the process of decision-making and not on the psychology of decision-making. That being said, it is important to understand both areas of decision-making and therefore if you want to read more about behavioural decision-making we recommend reading Thinking Fast and Slow by Daniel Kahneman, Psychology of Judgment and Decision Making by Scott Plous and Preference, Belief, and Similarity by Amos Tversky.
Most people who study decision-making now agree that there are two systems of decision-making, system 1 which is based on intuition or gut, and system 2 which is controlled, conscious and requires considerable effort (and time). We will be focusing on the methods and techniques that can be used for important and complex decisions that fit within system 2, or as we like to call it methods for structured decision-making.
Going back to the example we discussed about the recent graduate choosing what to do with their life. This is a particular problem where alternative options are already known to the decision-maker and the decision problem is to evaluate each of these options in order to select one of these alternatives based on several different criteria. This is referred to as an evaluation problem where the ultimate goal is to obtain a ranking or rating for each alternative. Other examples of such problems would be a regulatory authority wishing to publish the ranking of all universities in a country or a food agency seeking to rate all food shops from 1 (inadequate) to 5 (outstanding).
Another category of decision problems would be those where we search for a feasible solution which is not explicitly known to us. This category of problems can be labelled as design problems, for example, product pricing or time-tabling problems. A product can be priced with any value on a continuum but the decision-maker is interested in finding the most feasible price on this continuum. Similarly, one may find it difficult to manually schedule a timetable with no conflicts whatsoever, and therefore seek to find a feasible solution. In these two examples, the former one involves selection of a single value while the latter can be visualised as the selection of multiple values. The problems involving multiple values (sometimes called multivariate) can also be referred to as allocation problems. Table 1.1 summarises these categories of decision-making problems along with an example for each possible type of problems.
Table 1.1 Examples of evaluation and design decision problems.
Evaluation Design Selection Hiring a candidate Product pricing Ranking Ranking universities Rating Rating hotels Allocation Allocate money and possessions in a will Time-tabling classroomsAnother important categorisation is to consider the number of decision-makers. In the case of two or more decision-makers, conflicts may occur, usually due to different preferences, interests, or each person's level of knowledge. By contrast, those decisions involving a single decision-maker may not face these kinds of conflicts, although conflicts among different objectives/criteria may still occur, for example, searching to buy the cheapest house but wanting to live in a nice area.
1.1 How to Structure Your Decisions?
Whilst there can be many ways to structure a decision problem, Hammond J.S., Keeney R.L., and Raiffa H. (2002) proposed a very nice and simple framework known as PrOACT, which is an acronym for Problem, Objectives, Alternatives, Consequences, and Trade-offs.
Problem: The first element in this structure is the "Problem" itself. A good decision maker always questions the definition of the problem before identifying the ways to solve it. It is useless to find or suggest a wonderful solution to the wrong problem; therefore, it is important to identify the real problem before any further action.
Objective: After clearly identifying the real underlying problem, it is important to set objectives that can make us evaluate all the possible solutions. Some people may refer to these objectives as criteria. Linguistically, these two terms have slight difference, for example, a criterion can be "price", but the objective can be "finding cheapest price" or, if you are a rich person who wants to show off, the objective can be "finding the most expensive". In this example, both objectives are about the same price criterion, but one is trying to minimise while the other is trying to maximise. In most real-life problems, there are multiple criteria/objectives, and often these objectives are in conflict with each other. For example, one may dream of getting the cheapest item but with the highest quality.
Alternative: Consider a situation where there is only one possible course of action or choice. Will it be a decision problem? Not really, because the decision problem becomes a problem only when you have multiple alternative options, and you have to pick only one of these choices. Therefore, it is important to realise that identifying multiple alternative options is a very important step. One may miss a great (or best) solution without realising that it exists.
Consequences: After generating a good set of alternative options, it is important to evaluate the consequences of each of these alternatives. Usually this is done by creating a table where alternatives are placed in rows, objectives are places in columns, and then the consequences are penned down in each cell of this table. When describing the consequences in these cells, it is important to make sure they are as accurate as possible. Bad assessments will generate bad results, as they say "garbage in, garbage out".
Trade-offs: As we mentioned earlier, multiple objectives are often in conflict with each other, and therefore, you might end up with a table of consequences where there is no single clear winner. In this case, a trade-off analysis will be required where we need to sacrifice (or trade) something from one objective if we want to gain at least a little on another one.
In ProACT, there are three more elements that decision makers should consider in their decision-making exercise. These are Uncertainties, Risks, and Linked Decisions; but we will not discuss them here in detail. If you are interested in reading more about ProACT, we recommend reading the original book from Hammond J.S., Keeney R.L., and Raiffa H. (2002).
1.2 Different Stages in Decision-making
It is fair to say that every decision process starts with a need or desire to decide. The decision-maker realises this need when multiple alternatives appear viable to them whether known or unknown to them at the time of realisation. This realisation leads them to the two often-intertwined phases of structuring and exploration. For example, you have just moved to a new house and you realise you really need an air-conditioner. While exploring the various air-conditioning products on a popular shopping website, you make yourself aware of the criteria that must be taken into consideration when purchasing an air-conditioner. This is mostly true when the...
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