Logical Decisions - Classweb

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Identifying Alternatives Alternatives are often clearly defined, such as when you have to choose between three different universities. In other cases it may be very difficult for you to identify the alternatives. If there are many possible alternatives -- such as makes and models of cars (not to mention options and colors) or houses to buy -- you may need to do a preliminary screening to identify a manageable set of alternatives to rank. In other cases you may need to be very creative to describe alternatives in sufficient detail to allow comparisons. For example, how would you describe a "live off the land" lifestyle in enough detail to let you compare it to "become a stockbroker" on an evaluation measure called "amount of leisure time"? Composite Alternatives A more subtle problem in defining alternatives occurs when alternatives are really groups of objects that could be chosen. For example, suppose you manage the R&D section of a large company and you have some research projects you could fund. If the projects don't interact too much (if selecting one project doesn't affect the desirability of the other projects), you could make each project an alternative. Then you could rank them using LDW and select the top ranking projects. If the projects do interact, it might better to make your alternatives groups of projects and rank the groups. Typically, there will be a lot more possible groups of projects than there are individual projects, and you will need to be careful when defining and evaluating ranking measures. LDW cannot directly process composite alternatives (by, for example, ranking all possible sets of research projects given data on each individual project). You must define each composite alternative separately. <strong>Logical</strong> <strong>Decisions</strong>® Portfolio is a tool that can help you analyze composite alternatives. Describing Alternatives In the decision analysis method, you quantitatively describe your alternatives in terms of variables called evaluation measures. 9-4 Section 9 -- In Depth
Each alternative has a raw score (called a level) on each measure. The levels for the measures completely describe an alternative for the purposes of ranking. Thus, it is very important for you to carefully think about how you define the evaluation measures. If you use inappropriate or poorly thought-out measures your ranking results may be non-intuitive and hard to justify. Measures are discussed further on page 9-8. LDW relies on you to gather the measure levels for the alternatives. You should try to be consistent in how you evaluate the different alternatives, so that the same level on a measure always means the same thing. Careful definitions of your measure scales can help. If you gather data about your alternatives from different sources, you should try to make sure the sources all compute the measure in the same way. For example, if you're pricing washing machines from different stores, make sure the prices you're quoted are really comparable. Do they include sales taxes and delivery charges? Have the costs of the options you want been included? Your results will be incorrect if the prices are based on different assumptions. The "Analytic Hierarchy Process" provides a method of evaluating your alternatives without defining their measure levels at all. In this approach, you directly compare the alternatives’ performance as part of the preference assessment process. No scale or units are explicitly defined for the measure. This means that when you are using the AHP approach for a measure, you do not need to define any levels for your alternatives on that measure. In fact, LDW will ignore any levels you have defined for the alternatives. Because the AHP method does not make use of explicit measure levels, it makes it hard to distinguish between the objective measure levels and the more subjective conversion to common units. In addition, you lose traceability between the level for an alternative on the measure and the utility (common units) assigned the alternative on the measure. For these reasons we recommend that you use the AHP approach infrequently. We feel you should only use it for measures that are very subjective and for which you cannot think of a reasonable quantitative or qualitative scale. The "Analytic Hierarchy Process" method is discussed on page 7-15. Section 9 -- In Depth 9-5
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Logical Decisions Decision Support
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Table of Contents Table of Contents
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Assessing Weights with Weight Ratio
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Assessing Interactions Between Meas
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Introduction Real decisions aren't
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S E C T I O N Requirements and Inst
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"Logical Decisions". This program g
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Quick Start Introduction This secti
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Defining goals and measures. In LDW
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Figure 3-1. The SUF for "Years of E
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weights of the measures. All of the
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S E C T I O N Basic Tutorial 4
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Figure 4-1. Tutorial overview. 4-2
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Now lets make sure the alternatives
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Assume you have decided that you wi
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Next we will enter the measures for
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Defining Preferences The alternativ
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1. Select the Assess::Common Units
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almost equally unacceptable, while
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1. Select the Assess::Common Units
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When you do this, the tradeoff grap
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1. Select "Performance" and "Price"
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8. Click on the "Equal" button to t
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Figure 4-11. Display generated by R
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Figure 4-13. Overall ranking for tr
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Figure 4-15. Graph showing sensitiv
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You can see the completed introduct
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Advanced Tutorial This tutorial sec
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Probabilities There is a problem wi
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This information indicates that the
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A uniform distribution is defined b
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On the left is a list of the possib
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Figure 5-2. Example of Results::Unc
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screen a large database for the alt
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9. LDW will ask if you want to appe
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commit to buying their truck before
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see that the rankings for all the a
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S E C T I O N Using LDW 1: Structur
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The Edit::Insert option. The Insert
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! Summary -- view a dialog box that
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structure like an organization char
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If you check the Show Assessment St
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saves it for later pasting. When yo
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You can create a new Matrix view by
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The quick entry view shows the alte
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Structuring Goals The goals in an L
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these two fields to describe each m
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the hierarchy. In the Matrix view,
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! Point Estimate -- use a single nu
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Figure 6-12. Example of a measure l
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Figure 6-14. Example of a measure l
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pass, LDW replaces each probabilist
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Figure 6-17. Dialog box for definin
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Figure 6-18. Measure Category Dialo
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S E C T I O N Using LDW 2: Assessin
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measure utility functions for the g
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information as possible when you ch
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measures with categories require mu
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The "Reset" button deletes any asse
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You can change the shape of the cur
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Figure 7-4. Utility Assessment Scre
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very different from the average of
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Figure 7-6. Assessment matrix for A
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You can, however, leave the assessm
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properties dialog box can be select
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the same level. LDW provides a grap
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options in the Hierarchy menu to ad
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The check box labeled "Allow Repres
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Next you will see a tradeoff assess
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The Tradeoff::Use Alternatives to S
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Figure 7-13. Example of Direct Entr
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You can think of the importance num
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Figure 7-15. Assessment Screen for
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When you have selected two members
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("importance strength") that best d
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clicking on the "Initialize" button
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Set a Small k. The Enter Small k op
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select the tradeoff you would like
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Figure 7-18. Effects of consistency
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Using LDW 3: Reviewing Results Intr
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The curve shows how the utility fun
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The tradeoff graph has one measure
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When you select the option, you are
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the relative weights of the "Price"
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epresents a computer alternative wi
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Figure 8-11. Example of Review::Ass
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e true even if the measure has a ve
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an analysis are included in exactly
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Graph Weights The Graph Weights dis
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Figure 8-16. Results::Rank Alternat
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Figure 8-18. Dialog box for Results
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You can use the measure equivalents
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simulation for each alternative usi
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Sensitivity Graphs Sensitivity grap
Page 199 and 200: You can view a sensitivity table by
Page 201 and 202: Figure 8-28. Example of Results::Sc
Page 203 and 204: Figure 8-30. Example of Results::Sc
Page 205 and 206: In the dialog box, you are asked to
Page 207 and 208: Figure 8-34. Dialog box for Results
Page 209 and 210: Graph an Alternative The graph an a
Page 211 and 212: Figure 8-38. Example of Results::Gr
Page 213 and 214: Finally, the two radio buttons on t
Page 215 and 216: Figure 8-43. Example of Results::Co
Page 217 and 218: Printing and Saving Windows You can
Page 219 and 220: The dialog box will show you the fi
Page 221 and 222: Figure 8-45. Dialog box for Edit::C
Page 223 and 224: Changing the range for utility. You
Page 225 and 226: Figure 8-50. Dialog box for Prefere
Page 227 and 228: the current color for that type of
Page 229 and 230: copies the selected objects to the
Page 231 and 232: analysis with the skeleton analysis
Page 233 and 234: Figure 8-55. Dialog box for File::I
Page 235 and 236: the other measures. The measure nam
Page 237 and 238: The idea of the Import Structure op
Page 239 and 240: Next, LDW asks you if it should app
Page 241 and 242: Other Options utility function for
Page 243: In addition, the Window menu contai
Page 247 and 248: In Depth Introduction This section
Page 249: A third example is a portfolio deci
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Page 255 and 256: Measures in LDW You define measures
Page 257 and 258: computed measure levels to common u
Page 259 and 260: Converting the Measures to Common U
Page 261 and 262: Figure 9-2. Example of linear (stra
Page 263 and 264: For an example of the mid-level spl
Page 265 and 266: Since U(L0) = U(80) = 0 and U(L1) =
Page 267 and 268: Figure 9-5. Summary of SUF assessme
Page 269 and 270: describe two alternatives: A, which
Page 271 and 272: with equal chances of 40 and 70 per
Page 273 and 274: In the original formulation of the
Page 275 and 276: 1 Equal Importance Two activities c
Page 277 and 278: You begin the process by selecting
Page 279 and 280: Figure 9-7. Effects of goals with a
Page 281 and 282: 0.5. Then the weight assigned to "P
Page 283 and 284: ! You can use the "Smarter Method"
Page 285 and 286: allocates this weight before comput
Page 287 and 288: nth root of the product of the rati
Page 289 and 290: Figure 9-8. Summary of estimating t
Page 291 and 292: on the decision maker's response, L
Page 293 and 294: Figure 9-10. MUF assessment figure
Page 295 and 296: Now think of adjusting P so that th
Page 297 and 298: Another approach is to use the rang
Page 299 and 300: Figure 9-12. Quantitative range vs.
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If a measure’s range changes, LDW
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Figure 9-14 is an example of the ov
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Similarly, a single member can have
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chance having 160 hp (the most pref
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A probability of less than 0.5 for
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Interpreting the Ranking Results LD
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S E C T I O N Examples 10
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the idea that other manufactures an
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The completed goals hierarchy is sh
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Buying a House The ranking results
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Figure 10-5. Goals hierarchy for bu
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Overall goal Quality goal Costs goa
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The preference assessments were don
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Figure 10-9. Goals hierarchy for re
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! Noise, ! Agricultural Impacts, an
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S E C T I O N Commands Summary 11
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Assess Menu Edit Menu The Assess me
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File Menu Edit::Insert Lets you add
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utility function” if the active g
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Matrix Menu ! Hierarchy -- options
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Results::Dynamic Sensitivity See th
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Review::Compute Utilities Compute t
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Tradeoff Menu View Menu LDW display
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S E C T I O N Glossary 12
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Common Units Certainty Equivalent C
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LDW File Level Lottery Measure assi
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MUF MUF Formula See also: Alternati
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Preference Set Probabilistic Level
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Tradeoff Trial program decides whic
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Bibliography B
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The classic reference on multiple m
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Appendix This appendix describes th
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= .125 Thus the weight for cost is
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Index adjusted AHP ................
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computing ................8 - 3 int
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