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Problem Solving

Problem Solving

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Problem Solving

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  1. Problem Solving

    Applied Thinking
  2. Three Forms of Applied Thinking According to John Adair in “Decision Making & Problem Solving Strategies” there are three forms of applied thinking needed:
  3. Applied Thinking
  4. Why we need to use Applied Thinking
  5. Understanding how the Mind works There are two aspects to the mind: The information it can store in the memory And what it can do You need to know about a subject but you also need to apply it in a variety of unforeseen situations For example: A doctor is problem solving when he/she tries to diagnose the cause of a weak left leg Decision making and problem solving are bound up with particular kinds of information or knowledge
  6. Functions of the Mind Problem Solving is a combination of different functions of the mind These functions are:
  7. Analysing It is the mental ability to take things (material and non-material) to bits Separating them into their component parts It is related, but not identical, to logical or step-by-step thinking
  8. Synthesizing Synthesizing is putting or placing things together to make a whole It is the reverse process of analysing Synthesizing becomes creative when the resultant whole is formed from parts previously thought to be unconnected, and when it looks new and has real value
  9. Synthesizing Imagination plays a big role in synthesizing We can imagine a picture of a house - the whole is more than the sum of its parts When we see the picture we do not see a pile of bricks The link between creativity and synthesizing process is clear Your mind has a holistic dimension It can think holistically – in terms of whole – as well as analytically (taking wholes to bits)
  10. Valuing Valuing comes into play in mental activities such as Establishing success criteria Evaluating Appraising performance Judging people Criticism is a form of valuing Rather than its form of negative judgement, criticism in its formal use can suggest neutral analysis or even approving evaluation
  11. The Depth Mind Principle We have subconscious and unconscious minds John Adair has named this vital part of thinking the “Depth Mind”
  12. The Depth Mind We can analyse, synthesize and value in our sleep or when we are consciously doing something quite different Far from being chaotic, the Depth Mind plays a large part in scientific discovery and creative art. It is also a source of intuition – a sixth sense
  13. The Art of Effective Decision Making “There is a time when we must firmly choose the course we will follow, or the relentless drift of events will make the decision.” Franklin D Roosevelt Before we look at the tools and techniques used in problem solving we must have a process to follow There is a classic five-step approach to decision making
  14. The Classic Approach to Decision Making
  15. Defining the Objective Defining the objective is important in decision making You need to be clear about where you want to get to Do you know what you are trying to achieve? It can help to write it down Seeing it in writing often helps you to attain the necessary clarity of mind
  16. Defining the Objectives
  17. Collecting Relevant Information Collecting and sifting relevant information Some of it will be immediately apparent But other data may be missing
  18. Collecting Relevant Information It is a good principle not to make decisions in the absence of critically important information Collecting relevant information involves both surveying the available information and then taking steps to acquire the missing but relevant information to the matter in hand
  19. Generate Feasible Options Decision makers who lack skill tend to jump far too quickly to the either-or alternatives Enough time and mental energy is never given to generating at least three or four possibilities As Bismarck used to say to his generals, “You can be sure that if the enemy has only two courses of action open to him, he will choose the third.” The mind needs to be open into wide focus to consider all possibilities, and that is where generating ideas comes in
  20. Generate Feasible Options
  21. Make the Decision The critical preliminary activity here is to establish the selection criteria It is worth dividing them into different levels of priority
  22. Make the Decision Unless the option meets the MUST requirements you should discard it But after the essentials have been satisfied, the list of desirables – highly desirable SHOULDs or pleasant addition MIGHTs – comes into play To help make a decision you can: List the advantages and disadvantages Examine the consequences of each course Test the proposed course against the yardstick of your aim or objective Weigh the risks against expected gains
  23. Implement and Evaluate Decision comes from a Latin verb meaning “to cut off”, you know now you can move into the action phase It is worth identifying what John Adair has called the “Point of No Return (PNR), a term that comes from aviation At the half way point in crossing the Atlantic, it is easier for the pilot to continue in the event of engine trouble than to turn back. The pilot has passed the PNR and is committed In its wider sense the PNR is the point at which it costs you more to turn back or change your mind than to continue with a decision that you know to be an imperfect one Though in most decisions there is always a little leeway before becoming finally committed
  24. Analysis of problems All of us make mistakes of judgement based on faulty analysis We must start organising, or structuring, our analysis of problems In “The Thinker’s Toolkit”, Morgan D. Jones outlines the problems we face when dealing with problem solving and how we should approach problems more effectively
  25. Analytical Sins We commonly begin our analysis of a problem by formulating our conclusions; we thus start at what should be the end of the analytic process Our analysis usually focuses on the solution we intuitively favour; we therefore give inadequate attention to alternative solutions. The solution we intuitively favour is, more often than not, the first one that seems satisfactory. “satisficing” – a merging of “satisfy” and “suffice”
  26. Analytical Sins We tend to confuse “ discussing/thinking hard” about a problem with “analysing” it, when in fact the two activities are not at all the same Like the traveller who is so distracted by the surroundings that he loses his way, we focus on the substance (evidence, arguments, and conclusions) and not on the process of our analysis. We aren’t interested in the process and don’t really understand it. Most people are functionally illiterate when it comes to structuring their analysis
  27. Problematic Proclivities There is an emotional dimension to almost every thought we have and every decision we make Mental shortcuts our unconscious minds continuously take influence our conscious thinking We are driven to the world around us in terms of patterns We instinctively rely on, and are susceptible to, biases and assumptions
  28. Problematic Proclivities We feel the need to find explanations for everything, regardless of whether the explanations are accurate Humans have a penchant to seek out and put stock in evidence that supports their beliefs and judgements while eschewing and devaluing evidence that does not We tend to cling to untrue beliefs in the face of contradictory evidence
  29. Five Insights into Effective Problem Solving
  30. The Fourteen Tools
  31. The Fourteen Tools
  32. Problem Restatement Restate (redefine) the problem in as many different ways as we can think of Use divergent thinking – let ideas flow freely The aim is to broaden prospective of a problem Identifying central issues and alternative solutions Helps expand our thinking of a problem
  33. Problem Restatement There are four common pitfalls in defining problems: No Focus Definition is too vague or broad Example: What should we do about computers in the workplace? Statement does not identify problem Focus is misdirected Definition is too narrow Example: Johnny’s grades are slipping. How can we get him to study harder? Lack of effort may not be the problem
  34. Problem Restatement Statement is assumption-driven Example: How can we make leading businesses aware of our marketing capabilities? Defines the problem narrowly. If the assumption is invalid, the problem statement misdirects the focus of the analysis. Statement is solution-driven Example: How can we persuade the legislature to build more prisons to reduce prison overcrowding? This narrow-focus statement assumes a solution.
  35. Problem Restatement Techniques for Problem Restatement: Paraphrase: Restate the problem using different words without losing the original meaning 180 Degrees: Turn the problem on its head Broaden the focus: Restate the problem in a larger context Redirect the focus: Boldly, consciously change the focus Ask “Why”: Ask “why” of the initial problem statement. Then formulate a new problem statement based on the answer. Then ask “why” again, and again . Repeat this process until the essence of the “real” problem emerges
  36. Pros-Cons-and-Fixes Humans are compulsively negative Negative thoughts defeat creative objective thinking A technique to help with this is Pros-Cons-Fixes This rigorous technique compensates for negative thinking by forcing us to identify the positives first It also examines the negatives and tries to think of actions that could be taken to “fix” them Converting them into positives Or eliminating them
  37. Pros-Cons-and-Fixes The Six Steps of Pros-Cons-Fixes: List all the Pros The Positives, benefits, merits, and advantages List all the Cons List of all the negatives Review and Consolidate the Cons Consolidate Cons, merging any that are similar and eliminating redundant ones Neutralize as many Cons as possible What can be done What measures can we take to convert each Con into a Pro or neutralize it Compare the Pros and unalterable Cons for all options Analyse – separately, systematically and sufficiently Pick one option
  38. Divergent/Convergent Thinking The purpose of brainstorming or any other divergent technique is to generate creative ideas about a topic To allow ideas of every kind to flow, flourish and multiply in order to enrich the thinking process and the inventiveness of solutions Brainstorming is more than just about quantity, it is also about receptivity We need to be open to ideas, at any time time, form any source, from the very onset to the very end of the analytical process
  39. The Four Commandments of Divergent Thinking The more ideas, the better Keep the ideas coming Build one idea upon another One idea spawns another ad another in rapid succession Wacky ideas are okay They help us break out of conventional thinking and open the way to new, practical ideas The Golden Rule: Don’t evaluate ideas This precludes criticism and ridicule, eliminating people’s fears, which in turn frees their minds
  40. Sorting, Chronologies, and Time Lines Sorting is the most basic structuring technique It is underused and misused All of us tend to believe only complex problems require sorting Analysis of even the simplest problems benefits from sorting Example: in preparing a grocery list, it facilitates shopping to group items on the list according to their location in the store
  41. Sorting, Chronologies, and Time Lines Chronologies and time lines are another highly useful but elementary technique for organising information Humans instinctively think chronologically A chronology: Shows the timing and sequence of relevant events Calls our attention to key events and to sufficient gaps Makes it easier to identify patterns and correlations among events It allows us to understand and appreciate the context in which events occur, are occurring, will occur.
  42. Sorting, Chronologies, and Time Lines Sometimes putting events in chronological order points to a solution We can interpret the significance of each event with respect to the problem The Two Steps for a Chronology: Step 1: As you are researching a decision or problem, make a list of relevant events and their dates, but always list the dates first. Step 2: Construct a chronology, crossing off events on the list as they are included.
  43. Causal Flow Diagramming Without fully understanding the problem or what is causing it we resort to trial and error with its focus glued to the first plausible corrective option we think of All events in life are the results, the outcomes, of previous events Every problem we analyse is the product of a definable cause-and-effect system We must identify the systems components – the major factors – and how they interact to produce the problem We must ask: what is causing this problem? How are the major factors interacting to produce this result?
  44. Causal Flow Diagramming There are five steps for defining and analysing a problem’s cause-and-effect system: Identify major factors Identify cause-and-effect relationships Characterise the relationships as direct or inverse Diagram the relationships Analyse the behaviour of the relationships as an integrated system
  45. Causal Flow Diagramming Identifies the major factors – the engines – that drive the system, how they interact, and whether these interactions are direct or inverse relationships or form feedback loops Enables us to view these cause-and-effect relationships as an integrated system and to discover linkages that were either dimly understood or obscured altogether Facilitates our determining the main source(s) of the problem Enables us to conceive of alternative corrective measures and to estimate what their respective effects would be
  46. The Matrix A Matrix is a grid with as many cells as needed for whatever problem is being analysed It is one of the handiest, clearest methods of sorting information
  47. The Matrix A Matrix enables us to: Separate elements of a problem Categorise information by type Compare one type of information with another Compare pieces of information of the same type See correlations (patterns) among the information You can combine a matrix and chronology which helps further sort through information and help us see a problem more clearly
  48. The Decision/Event Tree A Decision/Event Tree is a diagram that graphically shows choices and their outcomes at different junctures in alternative sequences or chains of events Each sequence or chain of events is a separate scenario The dilemma posed by Frank Stokton’s famous story, “The Lady or the Tiger”, in which a man must choose between two doors, one leading to a beautiful lady, the other to a ravenous tiger, serves to illustrate the decision/event tree
  49. The Decision/Event Tree This example demonstrated the two immutable, universal characteristics of a decision/event tree; The branches of the tree are mutually exclusive, if the actor picks Door 1, he can’t also pick Door 2. And if he picks Door 1, he gets the lady, not the tiger. The branches are collectively exhaustive, the alternative at each branch incorporate all possibilities; no other options are possible at that point in the sequence or scenario. (There is no third door, nor is there anything other than a lady or a tiger waiting behind the doors.)
  50. The Decision/Event Tree By graphically representing points in a chain of decision or events, the decision/event tree enables us to structure analysis of a problem in a way no other technique offers: It dissects a scenario into sequential events It shows clearly the cause-and-effect linkages, indicating which decisions and events precede and follow others It shows which decisions or events are dependant on others It shows where the linkages are strongest and weakest It enables us to visually compare how one scenario differs from another Most important of all, it reveals alternatives we might otherwise not perceive and enables us to analyse them – separately, systematically, and sufficiently
  51. The Decision/Event Tree The Four Steps in Constructing a Decision/Event Tree Identify the problem Identify the major factors/issues (the decision and events) to be addressed in the analysis Identify alternatives for each of these factors/issues Construct a tree portraying all important alternative scenarios Ensure that the decision/events at each branch of the tree are mutually exclusive Ensure that the decisions/events at each branch are collectively exhaustive
  52. The Decision/Event Tree Should you use a Matrix or a Tree? There are trade-offs between trees and matrices These trade-offs become evident when we convert a matrix into a decision/event tree and vice versa Which is preferable depends on the nature of the problem and what the analyst is seeking Experimenting with both is recommended because the advantages and disadvantages of each then become clear and will inform our decision as to which is more useful in analysing a given problem Structuring is the first step; it organises the elements of the problem; it doesn’t analyse them For that you have to use your mind; but structuring makes that a whole lot easier
  53. Weighted Ranking Humans are constantly ranking things whether we realise it or not: the food we buy, the clothes we wear, the route we drive to work etc. It is an unconscious but instinctive process that facilitates (perhaps even enables) our decision making To rank means to assign a position to something relative to other things Different people will rank things differently for various reasons depending on personal experiences, likes, dislikes, and so on
  54. Weighted Ranking The main defect in our instinctive method lies in the tendency to view problems one-dimensionally: to focus on the first solution that makes sense, that offers an explanation The moment we think of a reason – any sound persuasive reason, we tend to latch on to that reason, make our ranking on that basis, and move on without considering out other likes and dislikes, which may actually be more important to us
  55. Weighted Ranking When choosing a place to reside, we survey several neighbourhoods and dislike one because the traffic is too heavy, like another because it’s close to an elementary school, dislike one because it lacks city sewers and so on We make our decision and after moving are disappointed because the roof of the house leaks and the heating bills are too expensive It is well and good to use stringent criteria making decisions, but we should be sure we have considered all relevant criteria and have applied all of the criteria equitably to all of the decisions
  56. Weighted Ranking By applying different criteria to different ranking decisions, we distort our analysis Which can lead to gravely disappointing outcomes that make us wonder want went wrong The answer is to use a technique called “weighted ranking” One of the main features used by weighted ranking is its method of ranking each item against every other, known as “pair ranking”
  57. Weighted Ranking Pair ranking example: Rank four options: A, B, C, and D To pair-rank them we list them in a column one beneath the other: Option A Option B Option C Option D We then as ourselves: which is better, A or B? Put a pencil mark after the one we decide is better, say B.
  58. Weighted Ranking Option A Option B Option C Option D We then ask why B is better and record our reasoning separately Which is better A or C? Pencil mark again, say C, and record our reasoning. Option A Option B Option C Option D
  59. Weighted Ranking Which is better, A or D? Mark, say D, record our reasoning. Option A Option B Option C Option D Which is better, B or C? We mark B and record our reasoning. Option A Option B Option C Option D
  60. Weighted Ranking Which is better, B or D? We mark B and record our reasoning Option A Option B Option C Option D Which is better, C or D? We mark C and record our reasoning Option A Option B Option C Option D
  61. Weighted Ranking We thus systematically compare each item with every other item With consistency in the ranking, one of the items will have three marks, one will have two, one will have one, and one will have none. The item with the three votes is the most favoured and is thus ranked first and the others subsequently If by chance two items end up with the same number of votes because our analysis is inconsistent, we simply rank these two items head to head to break the tie
  62. Weighted Ranking The benefits of pair ranking aren’t noticeable with short lists of four or five items, but with longer lists they are unmistakable You may feel uncomfortable with pair ranking and think its too mechanical and laborious It goes against the minds grain, against the way it prefers to operate Once it becomes accustomed to pair ranking, it will feel at home with the technique It is systematic and doesn’t permit us to take analytical shortcuts that short change our analysis We must analyse and make a decision on each member of every pair
  63. Weighted Ranking The Nine Steps of Weighted Ranking List all of the major criteria for ranking Pair-rank the criteria Select the top several criteria and weight them in percentiles Construct a Weighted Ranking Matrix and enter the items to be ranked, the selection criteria, and the criteria weights Pair-rank all of the items by each criterion, recording in the appropriate spaces the number of “votes” each item receives
  64. Weighted Ranking The Nine Steps of Weighted Ranking Multiply the number of votes by the respective criterion’s weight Add the weighted values for each item and enter the sums in the column labelled “Totalled Votes” Determine the final rankings and enter them in the last column, labelled “Final Ranking.” (The item with the most points is ranked highest.) Perform a sanity check
  65. Hypothesis Testing A hypothesis is a declarative statement that has not been established as true We assert the truth of a hypothesis by offering supporting evidence Karl Popper established in his writings that we can never really prove a hypothesis true We can and do, however, accept hypothesis as true until they are proven to be false We disprove a hypothesis with evidence “Information” becomes “evidence” only when we connect it with a hypothesis
  66. Hypothesis Testing We scan “information” looking for “evidence” When we find “evidence”, we should try to establish its validity by answering four questions: Who or what was the source? What was the source’s access? How did the source obtain the information? Was the method plausible? For example, if the source of the information claims he or she read the information in a certain document, is it reasonable that the source had access to that document?
  67. Hypothesis Testing What is the source’s reliability? Is the source reputable? Has other information from the source proven to be accurate? Is the information plausible? From the standpoint of everything we know about the problem and from just plain old common sense, does the information seem to make sense? Is such information common or rare?
  68. Hypothesis Testing Hypothesis plays a vital role in analysis However when yielding to the mind’s proclivity to focus on one solution, it may lead to “satisficing”, excluding alternatives In order to offset our natural tendency we must structure our analysis to ensure all hypothesis are considered sufficiently to test their validity This is called Hypothesis Testing
  69. Hypothesis Testing Hypothesis Testing ranks competing hypotheses by the degree to which relevant evidence is inconsistent The favoured hypothesis is the one with the least inconsistent evidence, not the one with the most consistent evidence Consistent evidence proves nothing, because evidence can, and usually does, support more than one hypothesis A Hypothesis-Testing Matrix can be used to structure the key pieces of evidence and hypotheses
  70. Hypothesis Testing The eight steps of Hypothesis Testing: Generate hypothesis Write down as many hypotheses as you can think of Eliminate the implausible and combine the similar Narrow down the list Construct a matrix Label the first column “Evidence” Label the other columns on the right “Hypotheses” Enter descriptors of the hypotheses atop the columns The hypotheses must be mutually exclusive
  71. Hypothesis Testing List “significant” evidence down the left-hand margin Include “absent” evidence (divergent thinking) What evidence not included in the matrix would refute one or more of the hypotheses? Find it. Working across the matrix, test the evidence for consistency with each hypothesis, one item of evidence at a time Work horizontally with one item of evidence at a time, determine whether the evidence is consistent (C), inconsistent (I), or ambiguous (?)
  72. Hypothesis Testing Refine the matrix Add or reword hypotheses Add “significant” evidence relevant to new or reworded hypotheses and test it against all hypotheses Delete, but keep a record of, evidence that is consistent with all hypotheses Working downward, evaluate each hypothesis Re-evaluate and confirm the validity of inconsistent evidence, and check underlying assumptions Delete any hypotheses for which there is significant inconsistent evidence
  73. Hypothesis Testing Rank the remaining hypotheses by the weakness of inconsistent evidence The hypothesis with the weakest inconsistent evidence is the most likely Perform a sanity check Review the findings, the hypotheses, the evidence, and the principal underlying assumptions
  74. Devil’s Advocacy Devil’s Advocacy is a technique closely related to hypothesis testing It is believed to have originated in the Roman Catholic Church as a means of critically examining a deceased person’s qualifications for sainthood Learned churchmen took the devil’s position simply for argument’s sake to challenge the rationale presented in the nomination for sainthood The idea being that through this process the truth, perforce, would out
  75. Devil’s Advocacy The power of devil’s advocacy lies in our compulsion to focus Focusing tends to make us favour a particular outcome or solution early on in the analytic process, before objectively analysing the evidence and reaching a conclusion Devil’s advocacy is analytically useful because it by design focuses on a contrary or opposite viewpoint In doing so it activates all of the instinctive behaviours associated with focusing: viewing the problem one-dimensionally through the lens of biases connected with that view point Eschewing alternative solutions Valuing evidence that supports that viewpoint Devaluing and discarding evidence that does not
  76. Devil’s Advocacy It promotes objectivity and takes us a step further by seeking out and obtaining new evidence At no time does the prime or the devil’s advocate have to be concerned with negative, contradictory evidence As the “Pro” evidence supporting the devil’s advocate’s position is the “Con” evidence opposing prime position, and vice versa Thus, both the prime advocate and the devil’s advocate can disregard non-supportive evidence and focus entirely on the supportive
  77. Devil’s Advocacy Devil’s advocacy will open your mind to new dimensions and perceptions of the problem poking holes in fallacious self-serving arguments and stripping away thinly supported analysis Either devise two teams to each take a side and draw conclusions and then analyse the two Or by yourself analyse a problem then leave it for a few days and let your focus, mind-sets, and biases relax and fade a bit, then work on the other side Your perspective of the problem will broaden Devil’s advocacy compels divergent thinking and imposes objectivity whether or not you are consciously seeking it
  78. The Probability Tree Understanding and dealing with probability are crucial because probability permeates analysis both explicitly and implicitly It lies hidden in the information we analyse and is a crutch for our analytical judgements Probability is difficult to deal with because the laws of probability are often counterintuitive and the judgements resulting from the application of those laws are imprecise and ambiguous when expressed verbally
  79. The Probability Tree How do you determine probability? Two ways: Computation Frequency-and-experience When we have all the facts and the data, as in a deterministic problem, we calculate probability by arithmetic computation When we don’t have all the facts we estimate probability based on frequency and experience
  80. The Probability Tree Frequency is how often an event has occurred in the past Experience is what happened during each event Laplace (1949-1827) stated that if we’re trying to determine which of two or more outcomes will occur, but we don’t have reliable evidence to judge which is more likely, we should assume the probability is equal for all outcomes
  81. The Probability Tree Types of Probability Events: Mutually exclusive Conditionally dependant Mutually exclusive events: These preclude one another E.g. the tossing of a coin involves mutually exclusive events, or mutually exclusive outcomes. Because a coin has two sides , one outcome (heads or tails) precludes the other, thus they are mutually exclusive
  82. The Probability Tree Conditionally dependant events: The occurrence of one event depends upon the occurrence of another The events thus occur in sequence E.g. starting the engine of an automobile. We insert the key into the ignition switch, we turn the key, the starter rotates the engine, and the engine ignites. The engine won’t ignite if it isn’t rotated; the starter won’t rotate the engine unless we turn the ignition key; and so on. The first event conditions the second, meaning the second event occurs on condition that the first occurs etc.
  83. The Probability Tree The Six Steps for a Probability Tree: Identify the problem Identify the major decisions and events to be analysed Construct a decision/event tree portraying all important alternative scenarios
  84. The Probability Tree Construct a decision/event tree portraying all important alternative scenarios Ensure that decision/events at each branch are mutually exclusive Ensure that decisions/each branch are collectively exhaustive Calculate the conditional probability of each individual scenario Calculate the answers to probability questions relating to the decisions/events
  85. The Utility Tree Utility is the benefit that someone has received, is receiving, or expects to receive from some situation It is what that person has gained, is gaining, or expects to gain It is the reason why that person has taken, is taking, or will take a certain action Utility is the profit, the prize, the dividend, the trophy, the advantage, the motive, the goal, the objective, the hope
  86. The Utility Tree Do you own a car? Why? Lots of reasons? What are they? These reasons are the utilities you enjoy from owning or not owning a car Why are you doing BIS? Are you going to stay and finish the degree? Why? What are your reasons? They are the utilities you expect from remaining or not remaining in BIS We do things for reasons These reasons are utilities
  87. The Utility Tree The purpose of utility analysis is to rank any number of options according to how they serve the decision maker’s self-interest Options are alternative courses of action Life is an endless series of choices; choices are options When options are complex, utility analysis can greatly simplify making the best decision by assessing and comparing the advantages and disadvantages of each option separately, systematically, and sufficiently
  88. The Utility Tree When analysing options, they must be mutually exclusive – distinctive enough from one another to permit meaningful comparisons Options need not be collectively exhaustive – encompass all possibilities The second element of utility analysis is the outcome An outcome is what happens as a result of implementing a certain course of action or selecting an option
  89. The Utility Tree Outcomes are the sole basis for analysing the utility of options We measure one option against another Outcomes as a general rule should be collectively exhaustive – inclusive of all possible outcomes The nature of the problem – the factors driving it and the solution – dictate which outcomes to consider Always try to boil down the outcomes to as few as possible, keeping in mind the principle of major factors
  90. The Utility Tree Perspectives are “points of view” with respect to outcomes and are critical in analysing the utility of outcomes Most often the perspective is that of the decision maker Alternatively, we can analyse the utility from the perspective of another, for example, an owner, a client, etc. and choose an option that will most benefit them We, the analyst, must decide whose perspective – whose point of view – will be reflected in our analysis
  91. The Utility Tree It is not always clear If we are analysing other people’s or organisations’ options, we must “role-play” their perspective trying to view the world as they view it We must see where their self-interest lies and to understand how their choice among options would be influenced by the perspective of others When we ponder, for example, what a business competitor is likely to do, the first question we should address is what are my competitor’s utilities?
  92. The Utility Tree The Eight Steps of Utility-Tree Analysis: Identify the options and outcomes to be analysed Identify the perspective of the analysis Construct a set of decision/event tree for each outcome Assign a utility value to each option-outcome combination – each scenario – by asking the Utility Question: If we select this option, and this outcome occurs, what is the utility from the perspective of…?
  93. The Utility Tree Assign a probability to each outcome. Determine or estimate this probability by asking the Probability Question: If this option is selected, what is the probability this outcome will occur? The probabilities of all outcomes for a single option must add up to 1.0. Determine the expected values by multiplying each utility by its probability and then adding the expected values for each option Determine the ranking of alternative options Perform a sanity check
  94. The Utility Matrix A matrix offers two important advantages over a tree for performing utility analysis The relative differences in utility values of outcomes are more easily perceived in a matrix than in a tree Arithmetic calculations are easier to perform A tree is busy, it sprawls out and is unsymmetrical A matrix is a compact, tightly organised, symmetrical unit
  95. The Utility Matrix The Eight Steps of Utility-Matrix Analysis Identify the options and outcomes to be analysed Identify the perspective of the analysis Construct a utility matrix Assign a utility value of 0 to 100 (unless dollars are used) to each option-outcome combination – each cell of the matrix – by asking the utility Question: If we select this option, and this outcome occurs, what is the utility from the perspective of…? There must be at least one 100 unless dollars are used
  96. The Utility Matrix Assign a probability to each outcome. Determine or estimate this probability by asking the Probability Question: If this option is selected, what is the probability this outcome will occur? The probability of all outcomes for a single option must add up to 1.0 Determine the expected values by multiplying each utility by its probability and then adding the expected values for each option Determine the ranking of the alternative options Perform a sanity check
  97. Advanced Utility Analysis It is frequently advisable, even necessary, to assess utilities from the vantage of more than one perspective This techniques for utility analysis of multiple perspectives has wide application in problem-solving situations where conflicting interests render a choice among alternative courses of action Multiple perspective utility analysis produces decisions that take equitable account of each party’s interest, especially when these parties actively participate in the analysis
  98. Advanced Utility Analysis The Thirteen Steps of Multiple-Perspective Utility Analysis Identify the options and outcomes to be analysed Identify and weight the perspectives to be analysed Construct an identical utility matrix for each perspective – same options, same outcomes Perform Steps 4 through 7 with each matrix From each matrix’s particular perspective, assign utilities from 0 to 100 to the outcome of each option-outcome combination (each cell of the matrix). There must be at least one 100
  99. Advanced Utility Analysis Assign a probability to the outcome of each option-outcome combination (each cell) Compute expected values for each option-outcome combination (each cell) Add expected values for each option and enter the total in a “Total EV” column Construct a single “merged” matrix with the same options as in the perspective matrices Enter opposite each option the total expected values for that option from the perspective matrices
  100. Advanced Utility Analysis Multiply the total expected values under each perspective by the perspective’s weight Add the resulting products (weighted expected values) for each option and enter the sums in a column “Total Weighted EV” Rank the options. The one with the greatest total weighted expected value is the preferred option Perform a sanity check