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DIT 1141: OPERATIONS MANAGEMENT DEPARTMENT OF DECISION AND INFORMATION TECHNOLOGIES COLLEGE OF COMMERCE AND FINANCE VILLAN...
INTRODUCTION
INTRODUCTION <ul><li>Operations management is the process of obtaining and utilizing resources to produce useful goods and...
INTRODUCTION <ul><li>Production management is concerned with the manufacturing of goods: </li></ul><ul><li>Examples of goo...
INTRODUCTION <ul><li>Operations management is also concerned with the management of service industries as well as the manu...
INTRODUCTION <ul><li>Examples of services: </li></ul><ul><li>retailing/food </li></ul><ul><li>banking </li></ul><ul><li>ed...
OVERVIEW OF OPERATIONS MANAGEMENT MODEL Transformation Process Output Goods or Services Control Input: resources raw mater...
OVERVIEW OF OPERATIONS MANAGEMENT MODEL <ul><li>Operations management considers  how  the input are transformed into goods...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input </li></ul>
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input </li></ul><ul><li>steel, plast...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input </li></ul><ul><li>steel, plast...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input Output </li></ul><ul><li>steel...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input Output </li></ul><ul><li>steel...
OPERATIONS MANAGEMENT QUESTIONS <ul><li>1. How many items will be demanded next month? </li></ul><ul><li>2. How many items...
OPERATIONS MANAGEMENT QUESTIONS <ul><li>4. If a plant is built, how should the activities be scheduled so that the project...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input   </li></ul>
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input   </li></ul><ul><li>patients, doctors </...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input   </li></ul><ul><li>patients, doctors </...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input   Output </li></ul><ul><li>patients, doc...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input   Output </li></ul><ul><li>patients, doc...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul>
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input Output </li></ul><ul><li>students, pro...
EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input Output </li></ul><ul><li>students, pro...
DECISION MAKING IN OPERATIONS:  THE ANALYTIC HIERARCHY PROCESS
<ul><li>What is the Analytic Hierarchy Process (AHP)? </li></ul><ul><li>The AHP, developed by Tom Saaty, is a decision-mak...
<ul><li>AHP problems are structured in at least three levels: </li></ul><ul><li>The goal , such as selecting the best car ...
<ul><li>The decision-maker: </li></ul><ul><li>measures the extent to which each alternative achieves each criterion, and  ...
APPROACH <ul><li>How does AHP capture human judgments? </li></ul><ul><li>AHP  never  requires you to make an absolute judg...
APPROACH <ul><li>Suppose the weights of two stones are being assessed.  AHP would ask: How much heavier (or lighter) is st...
APPROACH <ul><li>Individual AHP judgments are called  pairwise comparisons . </li></ul><ul><li>These judgments can be base...
APPROACH <ul><li>However, suppose stone A is a diamond worth $1,000.00 and stone B is a ruby worth $300.00. </li></ul><ul>...
APPROACH <ul><li>Consistency of judgments can also be measured.  Consistency is important when three or more items are bei...
APPROACH <ul><li>AHP does not require perfect consistency, however, it does provide a measure of consistency.  </li></ul><...
AHP APPLICATIONS <ul><li>AHP has been successfully applied to a variety of problems. </li></ul><ul><li>1. R&D projects and...
AHP APPLICATIONS <ul><li>The product and service evaluations prepared by consumer testing services is another potential ap...
AHP APPLICATIONS <ul><li>Would you make your purchasing decision based  solely on this score? </li></ul><ul><li>Probably n...
RANKING SPORTS RECORDS <ul><li>The AHP has been used to rank outstanding season, career, and single event records across s...
RANKING SPORTS RECORDS <ul><li>Career </li></ul><ul><li>1. Johnny Unitas, 1956-70: touchdown passes in 47 consecutive game...
RANKING SPORTS RECORDS <ul><li>How do we compare records from different sports? </li></ul><ul><li>It all depends on the cr...
RANKING SPORTS RECORDS <ul><li>Did this article end all arguments about sports records? </li></ul><ul><li>Absolutely not! ...
A FINAL POINT ABOUT SPORTS <ul><li>In reading the sports pages we often see discussion of how well teams match up across d...
AHP APPLICATIONS <ul><li>Our culture is obsessed with quantitative rankings of all sorts of things. </li></ul><ul><li>Ther...
<ul><li>The discussion of how to compare records from different sports recalls a saying from childhood: </li></ul>APPLES A...
<ul><li>The discussion of how to compare records from different sports recalls a saying from childhood: </li></ul><ul><li>...
<ul><li>The discussion of how to compare records from different sports recalls a saying from childhood: </li></ul><ul><li>...
APPLES AND ORANGES <ul><li>The discussion of how to compare records from different sports recalls a saying from childhood:...
<ul><li>What criteria might  you  use when comparing apples and oranges? </li></ul><ul><li>There are a vast set of criteri...
<ul><li>The point is that people are often confronted with the choice between apples and oranges.  </li></ul><ul><li>Their...
CAR PURCHASE EXAMPLE <ul><li>We now consider a motivating example.  </li></ul><ul><li>After completing this example, you w...
CAR PURCHASE EXAMPLE <ul><li>The couple is considering three criteria: cost, safety, and appearance. </li></ul><ul><li>The...
<ul><li>Select the  F ile,  N ew  option and enter a file name such as CARS.EC1.  (You must use the EC1 file extension.) <...
<ul><li>To enter the criteria, use the  E dit,  I nsert  command.  Use the Esc key when finished entering the criteria. </...
<ul><li>To include the same alternatives under the other criteria nodes, first highlight the cost node, then select  E dit...
ANALYZING THE HIERARCHY <ul><li>1. Determine the weights of the alternatives for each criterion. </li></ul><ul><li>2. Dete...
HYPOTHETICAL DATA FOR CAR PURCHASE EXAMPLE Car   Cost   Safety* Appearance Honda $22,000 28 Sporty Mazda    28,500 39 Slic...
DETERMINING PRIORITIES <ul><li>The couple begins by making  pairwise comparison judgments  between each pair of cars for t...
STANDARD 1 - 9 MEASUREMENT SCALE <ul><li>Intensity of Importance   Definition   Explanation </li></ul><ul><li>1 Equal impo...
COST PAIRWISE COMPARISONS <ul><li>The pairwise comparisons are represented in the form of pairwise comparison matrices.  <...
<ul><li>If we compare the Honda to the Honda, obviously they are equal.  </li></ul><ul><li>Therefore, a 1 (equal preferred...
<ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX  </li></ul><ul><li>  Honda  Mazda  Volvo  </li></ul><ul><li>22K Honda ...
<ul><li>The other entries along the main diagonal of the matrix are also 1.  </li></ul><ul><li>This simply means that ever...
<ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX  </li></ul><ul><li>  Honda  Mazda  Volvo  </li></ul><ul><li>22K Honda ...
<ul><li>Suppose we believe the Honda ($22000) is equally to moderately preferred to the Mazda ($28500).  Place a 2 in the ...
<ul><li>Do you agree? </li></ul><ul><li>It depends!  </li></ul><ul><li>For some, $28,500 is significantly greater than $22...
<ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX  </li></ul><ul><li>  Honda  Mazda  Volvo  </li></ul><ul><li>22K Honda ...
<ul><li>If the Honda is 2 times better than the Mazda, this implies that the Mazda ($28500) is one half as good as the Hon...
<ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX  </li></ul><ul><li>  Honda  Mazda  Volvo  </li></ul><ul><li>22K Honda ...
<ul><li>Suppose that we judge the Mazda ($28500) to be equally to moderately preferred to the Volvo ($33000).  </li></ul><...
<ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX  </li></ul><ul><li>  Honda  Mazda  Volvo  </li></ul><ul><li>22K Honda ...
<ul><li>Assuming perfect consistency of judgments, we would expect that the Honda ($22000) is 4 times (that is, moderately...
<ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX  </li></ul><ul><li>  Honda  Mazda  Volvo  </li></ul><ul><li>22K Honda ...
<ul><li>The matrix is now complete and the weights for each car (for the cost criterion) can be computed. </li></ul><ul><l...
<ul><li>A simple three step procedure can be used to approximate the weights for each alternative. </li></ul><ul><li>Essen...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGIN...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGIN...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGIN...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2 . DIVIDE EACH ELEMENT IN THE ORIGI...
<ul><li>Notice that no variation is seen across the rows because the judgments are perfectly consistent. </li></ul><ul><li...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGIN...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGIN...
<ul><li>Expert Choice offers a variety of modes for entering the judgments.  </li></ul><ul><li>Highlight the cost node, se...
<ul><li>The  D ata  option allows the user to enter data items for each alternative, for example, costs, miles per gallon,...
<ul><li>To enter our cost judgments choose  P airwise. </li></ul><ul><li>When comparing alternatives select  P reference  ...
INCONSISTENCY OF JUDGMENTS <ul><li>Since our pairwise comparisons were perfectly consistent, Expert Choice reports INCONSI...
INCONSISTENCY OF JUDGMENTS <ul><li>Inconsistency of judgments may result from: </li></ul><ul><li>problems of estimation; <...
INCONSISTENCY OF JUDGMENTS <ul><li>One example of natural inconsistency is in a sporting contest.  </li></ul><ul><li>If te...
INCONSISTENCY OF JUDGMENTS <ul><li>The point is not to stop inconsistency from occurring.  </li></ul><ul><li>Make sure tha...
INCONSISTENCY OF JUDGMENTS <ul><li>How does a judgment change affect the car weights? </li></ul><ul><li>Suppose the Mazda ...
<ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX  </li></ul><ul><li>  Honda  Mazda  Volvo  </li></ul><ul><li>22K Honda ...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGIN...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2 . DIVIDE EACH ELEMENT IN THE ORIGI...
<ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX.  </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGIN...
INCONSISTENCY OF JUDGMENTS <ul><li>The new weights are: 0.557, 0.320, and 0.123.  The inconsistency resulted in some chang...
<ul><li>Highlight cost node, select  A ssessment,  P airwise. </li></ul><ul><li>Enter a 3 in the Mazda to Volvo cell then ...
INCONSISTENCY OF JUDGMENTS <ul><li>The weights can also be used to measure the effectiveness of the alternatives.  </li></...
REMAINING COMPUTATIONS <ul><li>Next, the cars must be pairwise compared for the safety criterion and then for the appearan...
SAFETY & APPEARANCE JUDGMENTS <ul><li>Safety Pairwise Comparison Matrix  </li></ul><ul><li>Honda Mazda Volvo  </li></ul><u...
REMAINING COMPUTATIONS <ul><li>Next, the criteria must be pairwise compared.  </li></ul><ul><li>These judgments are shown ...
CRITERIA JUDGMENTS <ul><li>Original Criteria Pairwise Comparison Matrix </li></ul><ul><li>Cost Safety Appearance </li></ul...
REMAINING COMPUTATIONS <ul><li>The last stage computes the final weights for each car.  </li></ul><ul><li>Multiply the cri...
FINAL CAR WEIGHTS <ul><li>  CRITERIA WEIGHTS   </li></ul><ul><li>COST  SAFETY  APPEARANCE   </li></ul><ul><li>0.309  0.582...
FINAL CAR WEIGHTS <ul><li>  CRITERIA WEIGHTS   </li></ul><ul><li>COST  SAFETY  APPEARANCE   </li></ul><ul><li>0.309  0.582...
FINAL CAR WEIGHTS <ul><li>  CRITERIA WEIGHTS   </li></ul><ul><li>COST  SAFETY  APPEARANCE   </li></ul><ul><li>0.309  0.582...
FINAL CAR WEIGHTS <ul><li>  CRITERIA WEIGHTS   </li></ul><ul><li>COST  SAFETY  APPEARANCE   </li></ul><ul><li>0.309  0.582...
LOCAL VS GLOBAL WEIGHTS <ul><li>For cost, the local weights for the cars are 0.558, 0.320, and 0.122 and sum to 1.000. </l...
<ul><li>To compute the final weights select  S ynthesis  ( from  G OAL ). </li></ul><ul><li>Choose  Dis t ributive  Mode a...
<ul><li>The Print icon can be used to select certain options.  </li></ul><ul><li>The recommended print options are:  E nti...
INTERPRETING THE RESULTS <ul><li>The final weights provide a measure of the relative performance of each alternative.  </l...
INTERPRETING THE RESULTS <ul><li>Should we buy the Volvo? </li></ul><ul><li>The output is a decision-making aid and cannot...
SENSITIVITY ANALYSIS <ul><li>Sensitivity analysis is an important aspect of any decision-making process. </li></ul><ul><li...
EXPERT CHOICE: Sensitivity Analysis <ul><li>In Expert Choice sensitivity analysis from the GOAL shows how the weights and ...
<ul><li>The last two show how the alternatives perform with respect to any two criteria. </li></ul><ul><li>Performance : p...
<ul><li>Gradient : a line graph that shows how the weights of the alternatives vary according to the weight assigned to a ...
<ul><li>An important use of sensitivity analysis is to determine how much a given criterion weight must change before ther...
<ul><li>Choose  D ynamic  from the  Sensitivity- G raphs  option. </li></ul><ul><li>Drag the cost criterion bar 30.9% to a...
NEW PRODUCT INTRODUCTION <ul><li>CHOCK-FUL-O-CHIPS developed the following hierarchy and data that can be used to help dec...
RECIPE DATA <ul><li>Taste  Fat Content </li></ul><ul><li>Recipe  Cost*  Rating**  (Grams)* </li></ul><ul><li>1   $0.166 54...
TASTE PAIRWISE COMPARISON MATRIX <ul><li>  54%  24%  20%  43% </li></ul><ul><li>Recipe 1  Recipe 2  Recipe 3  Recipe 4 </l...
COST PAIRWISE COMPARISON MATRIX <ul><li>  0.166  0.099  0.265  0.224 </li></ul><ul><li>Recipe 1  Recipe 2  Recipe 3  Recip...
FAT CONTENT PAIRWISE COMPARISON MATRIX <ul><li>  8.0  7.0  3.5  6.0 </li></ul><ul><li>Recipe 1  Recipe 2  Recipe 3  Recipe...
CRITERIA PAIRWISE COMPARISON MATRIX <ul><li>  Taste Cost Fat Content </li></ul><ul><li>Taste   1 </li></ul><ul><li>Cost   ...
FINAL WEIGHTS FROM EXPERT CHOICE <ul><li>Criteria Weights   </li></ul><ul><li>Taste  Cost  Fat Content </li></ul><ul><li> ...
SUMMARY <ul><li>In this chapter: </li></ul><ul><li>we provided an overview of operations management; and </li></ul><ul><li...
SUMMARY <ul><li>AHP benefits include: </li></ul><ul><li>natural way to elicit judgments; </li></ul><ul><li>measure degree ...
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Mazda Omintro

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Experience Mazda Zoom Zoom Lifestyle and Culture by Visiting and joining the Official Mazda Community at http://www.MazdaCommunity.org for additional insight into the Zoom Zoom Lifestyle and special offers for Mazda Community Members. If you live in Arizona, check out CardinaleWay Mazda's eCommerce website at http://www.Cardinale-Way-Mazda.com

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  • Transcript of "Mazda Omintro"

    1. 1. DIT 1141: OPERATIONS MANAGEMENT DEPARTMENT OF DECISION AND INFORMATION TECHNOLOGIES COLLEGE OF COMMERCE AND FINANCE VILLANOVA UNIVERSITY
    2. 2. INTRODUCTION
    3. 3. INTRODUCTION <ul><li>Operations management is the process of obtaining and utilizing resources to produce useful goods and services so as to meet the goals of the organization. </li></ul>
    4. 4. INTRODUCTION <ul><li>Production management is concerned with the manufacturing of goods: </li></ul><ul><li>Examples of goods: </li></ul><ul><li>cars </li></ul><ul><li>books </li></ul><ul><li>chairs </li></ul><ul><li>computers </li></ul><ul><li>houses </li></ul><ul><li>etc. </li></ul>
    5. 5. INTRODUCTION <ul><li>Operations management is also concerned with the management of service industries as well as the manufacturing of goods. </li></ul>
    6. 6. INTRODUCTION <ul><li>Examples of services: </li></ul><ul><li>retailing/food </li></ul><ul><li>banking </li></ul><ul><li>education </li></ul><ul><li>health care </li></ul><ul><li>utilities </li></ul><ul><li>insurance </li></ul><ul><li>government agencies </li></ul><ul><li>etc. </li></ul>
    7. 7. OVERVIEW OF OPERATIONS MANAGEMENT MODEL Transformation Process Output Goods or Services Control Input: resources raw materials machines personnel capital land/buildings utilities information etc.
    8. 8. OVERVIEW OF OPERATIONS MANAGEMENT MODEL <ul><li>Operations management considers how the input are transformed into goods or services. </li></ul><ul><li>Control is when something is learned about the goods or services that is used to more effectively transform future goods or services. </li></ul>
    9. 9. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input </li></ul>
    10. 10. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input </li></ul><ul><li>steel, plastic </li></ul><ul><li>glass, paint </li></ul><ul><li>tools </li></ul><ul><li>equipment </li></ul><ul><li>machines </li></ul><ul><li>personnel, buildings </li></ul><ul><li>utilities, etc. </li></ul>
    11. 11. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input </li></ul><ul><li>steel, plastic </li></ul><ul><li>glass, paint </li></ul><ul><li>tools Transformation </li></ul><ul><li>equipment process </li></ul><ul><li>machines </li></ul><ul><li>personnel, buildings </li></ul><ul><li>utilities, etc. </li></ul>
    12. 12. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input Output </li></ul><ul><li>steel, plastic </li></ul><ul><li>glass, paint </li></ul><ul><li>tools Transformation </li></ul><ul><li>equipment process </li></ul><ul><li>machines </li></ul><ul><li>personnel, buildings </li></ul><ul><li>utilities, etc. </li></ul>
    13. 13. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Automobile factory </li></ul><ul><li>Input Output </li></ul><ul><li>steel, plastic Car </li></ul><ul><li>glass, paint </li></ul><ul><li>tools Transformation </li></ul><ul><li>equipment process </li></ul><ul><li>machines </li></ul><ul><li>personnel, buildings </li></ul><ul><li>utilities, etc. </li></ul>
    14. 14. OPERATIONS MANAGEMENT QUESTIONS <ul><li>1. How many items will be demanded next month? </li></ul><ul><li>2. How many items should be produced next month? </li></ul><ul><li>3. How many workers are needed to satisfy the proposed production level? </li></ul>
    15. 15. OPERATIONS MANAGEMENT QUESTIONS <ul><li>4. If a plant is built, how should the activities be scheduled so that the project is completed on time, within budget, and with acceptable quality? </li></ul><ul><li>5. How is the quality of our output measured and how is it improved? </li></ul><ul><li>6. If tires are needed, how many should be ordered? </li></ul>
    16. 16. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input </li></ul>
    17. 17. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input </li></ul><ul><li>patients, doctors </li></ul><ul><li>nurses, drugs </li></ul><ul><li>beds </li></ul><ul><li>building </li></ul><ul><li>medical equipment </li></ul><ul><li>support staff, computers </li></ul><ul><li>utilities, etc. </li></ul>
    18. 18. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input </li></ul><ul><li>patients, doctors </li></ul><ul><li>nurses, drugs Transformation </li></ul><ul><li>beds Process </li></ul><ul><li>building </li></ul><ul><li>medical equipment </li></ul><ul><li>support staff, computers </li></ul><ul><li>utilities, etc. </li></ul>
    19. 19. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input Output </li></ul><ul><li>patients, doctors </li></ul><ul><li>nurses, drugs Transformation </li></ul><ul><li>beds Process </li></ul><ul><li>building </li></ul><ul><li>medical equipment </li></ul><ul><li>support staff, computers </li></ul><ul><li>utilities, etc. </li></ul>
    20. 20. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>Hospital </li></ul><ul><li>Input Output </li></ul><ul><li>patients, doctors A treated patient </li></ul><ul><li>nurses, drugs Transformation </li></ul><ul><li>beds Process </li></ul><ul><li>building </li></ul><ul><li>medical equipment </li></ul><ul><li>support staff, computers </li></ul><ul><li>utilities, etc. </li></ul>
    21. 21. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul>
    22. 22. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors </li></ul><ul><li>secretaries </li></ul>
    23. 23. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors </li></ul><ul><li>secretaries, drugs </li></ul>
    24. 24. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors </li></ul><ul><li>secretaries, drugs </li></ul>
    25. 25. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors </li></ul><ul><li>secretaries, lab equipment </li></ul><ul><li>dormitories </li></ul><ul><li>staff, computers </li></ul><ul><li>buildings </li></ul><ul><li>etc. </li></ul>
    26. 26. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input </li></ul><ul><li>students, professors </li></ul><ul><li>secretaries, lab equipment </li></ul><ul><li>dormitories </li></ul><ul><li>staff, computers Transformation </li></ul><ul><li>buildings process </li></ul><ul><li>etc. </li></ul>
    27. 27. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input Output </li></ul><ul><li>students, professors </li></ul><ul><li>secretaries, lab equipment </li></ul><ul><li>dormitories </li></ul><ul><li>staff, computers Transformation </li></ul><ul><li>buildings process </li></ul><ul><li>etc. </li></ul>
    28. 28. EXAMPLE OF OPERATIONS MANAGEMENT PROCESS <ul><li>University </li></ul><ul><li>Input Output </li></ul><ul><li>students, professors A more highly </li></ul><ul><li>secretaries, lab equipment educated </li></ul><ul><li>dormitories student </li></ul><ul><li>staff, computers Transformation </li></ul><ul><li>buildings process </li></ul><ul><li>etc. </li></ul>
    29. 29. DECISION MAKING IN OPERATIONS: THE ANALYTIC HIERARCHY PROCESS
    30. 30. <ul><li>What is the Analytic Hierarchy Process (AHP)? </li></ul><ul><li>The AHP, developed by Tom Saaty, is a decision-making method for prioritizing alternatives when multi-criteria must be considered. </li></ul><ul><li>An approach for structuring a problem as a hierarchy or set of integrated levels. </li></ul>INTRODUCTION
    31. 31. <ul><li>AHP problems are structured in at least three levels: </li></ul><ul><li>The goal , such as selecting the best car to purchase, </li></ul><ul><li>The criteria , such as cost, safety, and appearance, </li></ul><ul><li>The alternatives , namely the cars themselves. </li></ul>INTRODUCTION
    32. 32. <ul><li>The decision-maker: </li></ul><ul><li>measures the extent to which each alternative achieves each criterion, and </li></ul><ul><li>determines the relative importance of the criteria in meeting the goal, and </li></ul><ul><li>synthesizes the results to determine the relative importance of the alternatives in meeting the goal. </li></ul>INTRODUCTION
    33. 33. APPROACH <ul><li>How does AHP capture human judgments? </li></ul><ul><li>AHP never requires you to make an absolute judgment or assessment. You would never be asked to directly estimate the weight of a stone in kilograms. </li></ul><ul><li>AHP does require you to make a relative assessment between two items at a time. AHP uses a ratio scale of measurement. </li></ul>
    34. 34. APPROACH <ul><li>Suppose the weights of two stones are being assessed. AHP would ask: How much heavier (or lighter) is stone A compared to stone B? </li></ul><ul><li>AHP might tell us that, of the total weight of stones A and B, stone A has 65% of the total weight, whereas, stone B has 35% of the total weight. </li></ul>
    35. 35. APPROACH <ul><li>Individual AHP judgments are called pairwise comparisons . </li></ul><ul><li>These judgments can be based on objective or subjective information. </li></ul><ul><li>For example, smoothness might be a subjective criterion used to compare two stones. Pairwise comparisons could be based on touch. </li></ul>
    36. 36. APPROACH <ul><li>However, suppose stone A is a diamond worth $1,000.00 and stone B is a ruby worth $300.00. </li></ul><ul><li>This objective information could be used as a basis for a pairwise comparison based on the value of the stones. </li></ul>
    37. 37. APPROACH <ul><li>Consistency of judgments can also be measured. Consistency is important when three or more items are being compared. </li></ul><ul><li>Suppose we judge a basketball to be twice as large as a soccer ball and a soccer ball to be three times as large as a softball. </li></ul><ul><li>To be perfectly consistent, a basketball must be six times as large as a softball. </li></ul>
    38. 38. APPROACH <ul><li>AHP does not require perfect consistency, however, it does provide a measure of consistency. </li></ul><ul><li>We will discuss consistency in more detail later. </li></ul>
    39. 39. AHP APPLICATIONS <ul><li>AHP has been successfully applied to a variety of problems. </li></ul><ul><li>1. R&D projects and research papers; </li></ul><ul><li>2. vendors, transport carriers, and site locations; </li></ul><ul><li>3. employee appraisal and salary increases; </li></ul><ul><li>4. product formulation and pharmaceutical licensing; </li></ul><ul><li>5. capital budgeting and strategic planning; </li></ul><ul><li>6. surgical residents, medical treatment, and diagnostic testing. </li></ul>
    40. 40. AHP APPLICATIONS <ul><li>The product and service evaluations prepared by consumer testing services is another potential application. </li></ul><ul><li>Products and services, such as self propelled lawn mowers are evaluated. </li></ul><ul><li>Factors include: bagging, mulching, discharging, handling, and ease of use. </li></ul><ul><li>An overall score for each mower is determined. </li></ul>
    41. 41. AHP APPLICATIONS <ul><li>Would you make your purchasing decision based solely on this score? </li></ul><ul><li>Probably not! Some of the information will be helpful. </li></ul><ul><li>Some additional questions are: </li></ul><ul><li>How important is each criterion? </li></ul><ul><li>Would you weigh the criteria the same way? </li></ul><ul><li>Are all of the criteria considered important to you? </li></ul><ul><li>Are there other criteria that are important to you? </li></ul><ul><li>Have you ever thought about these issues? </li></ul>
    42. 42. RANKING SPORTS RECORDS <ul><li>The AHP has been used to rank outstanding season, career, and single event records across sports. </li></ul><ul><li>Season </li></ul><ul><li>1. Babe Ruth, 1920: .847 slugging average </li></ul><ul><li>2. Joe DiMaggio, 1944: 56 game hitting streak </li></ul><ul><li>3. Wilt Chamberlain, 1961-62: 50.4 points per game scoring average </li></ul>
    43. 43. RANKING SPORTS RECORDS <ul><li>Career </li></ul><ul><li>1. Johnny Unitas, 1956-70: touchdown passes in 47 consecutive games </li></ul><ul><li>2. Babe Ruth, 1914-35: .690 slugging average </li></ul><ul><li>3. Walter Payton, 1975-86: 16,193 rushing yardage </li></ul><ul><li>Single event </li></ul><ul><li>1. Wilt Chamberlain, 1962: 100 points scored </li></ul><ul><li>2. Norm Van Brocklin, 1951: 554 passing yards </li></ul><ul><li>3. Bob Beamon, 1968: 29' 2.5&quot; long jump </li></ul>
    44. 44. RANKING SPORTS RECORDS <ul><li>How do we compare records from different sports? </li></ul><ul><li>It all depends on the criteria that you select! </li></ul><ul><li>Golden and Wasil (1987) used the following criteria: </li></ul><ul><li>1. Duration of record - years record has stood, years expected to stand </li></ul><ul><li>2. Incremental improvement - % better than previous record </li></ul><ul><li>3. Other record characteristics - glamour, purity (single person vs. team) </li></ul>
    45. 45. RANKING SPORTS RECORDS <ul><li>Did this article end all arguments about sports records? </li></ul><ul><li>Absolutely not! </li></ul><ul><li>In bars and living rooms across the country, people still argue about sports. </li></ul><ul><li>AHP provides a methodology to structure the debate. </li></ul><ul><li>Different criteria and different judgments could produce different results. </li></ul>
    46. 46. A FINAL POINT ABOUT SPORTS <ul><li>In reading the sports pages we often see discussion of how well teams match up across different positions. </li></ul><ul><li>These match-ups are often used to predict a winner. </li></ul><ul><li>Match-ups is a pairwise comparison concept! </li></ul>
    47. 47. AHP APPLICATIONS <ul><li>Our culture is obsessed with quantitative rankings of all sorts of things. </li></ul><ul><li>There are many measurement problems associated with rankings of products, sports teams, universities, and the like. </li></ul><ul><li>Many of these issues are discussed on a web site at: </li></ul><ul><li>http://www.expertchoice.com/annie.person . </li></ul>
    48. 48. <ul><li>The discussion of how to compare records from different sports recalls a saying from childhood: </li></ul>APPLES AND ORANGES
    49. 49. <ul><li>The discussion of how to compare records from different sports recalls a saying from childhood: </li></ul><ul><li>You can’t compare apples and oranges. All you get is mixed fruit! </li></ul>APPLES AND ORANGES
    50. 50. <ul><li>The discussion of how to compare records from different sports recalls a saying from childhood: </li></ul><ul><li>You can’t compare apples and oranges. All you get is mixed fruit! </li></ul><ul><li>After the discussion about sports, do you still believe this statement? </li></ul>APPLES AND ORANGES
    51. 51. APPLES AND ORANGES <ul><li>The discussion of how to compare records from different sports recalls a saying from childhood: </li></ul><ul><li>You can’t compare apples and oranges. All you get is mixed fruit! </li></ul><ul><li>After the discussion about sports, do you still believe this statement? </li></ul><ul><li>We hope not!!! </li></ul>
    52. 52. <ul><li>What criteria might you use when comparing apples and oranges? </li></ul><ul><li>There are a vast set of criteria that may change depending upon time of day or season of year: </li></ul><ul><li>taste, texture, smell, </li></ul><ul><li>ripeness, juiciness, nutrition, </li></ul><ul><li>shape, weight, color, and </li></ul><ul><li>cost. </li></ul><ul><li>Can you think of others? </li></ul>APPLES AND ORANGES
    53. 53. <ul><li>The point is that people are often confronted with the choice between apples and oranges. </li></ul><ul><li>Their choice is based on some psychological assessment of: </li></ul><ul><li>relevant criteria, </li></ul><ul><li>their importance, and </li></ul><ul><li>how well the alternatives achieve the criteria. </li></ul>APPLES AND ORANGES
    54. 54. CAR PURCHASE EXAMPLE <ul><li>We now consider a motivating example. </li></ul><ul><li>After completing this example, you will have an understanding of the basics of AHP and its application through Expert Choice (www.expertchoice.com). </li></ul><ul><li>We want to apply the AHP to help a couple decide which car they should purchase. </li></ul>
    55. 55. CAR PURCHASE EXAMPLE <ul><li>The couple is considering three criteria: cost, safety, and appearance. </li></ul><ul><li>They have narrowed their alternatives to three specific cars: Honda, Mazda, and Volvo. </li></ul><ul><li>We demonstrate how to build the AHP hierarchy in Expert Choice. </li></ul>
    56. 56. <ul><li>Select the F ile, N ew option and enter a file name such as CARS.EC1. (You must use the EC1 file extension.) </li></ul><ul><li>Choose the D irect option to create the model. Next, specify the description of the goal, such as, “Select the best car.” </li></ul>EXPERT CHOICE: FILE SETUP
    57. 57. <ul><li>To enter the criteria, use the E dit, I nsert command. Use the Esc key when finished entering the criteria. </li></ul><ul><li>To add the alternative cars under the cost node, simply highlight the cost node and again use the E dit, I nsert command. Use the Esc key when finished. </li></ul>EXPERT CHOICE: FILE SETUP
    58. 58. <ul><li>To include the same alternatives under the other criteria nodes, first highlight the cost node, then select E dit, R eplicate children of current node, To P eers, Y es . </li></ul><ul><li>Double-click on the goal node to display the complete hierarchy. </li></ul><ul><li>Additional details can be found in the Expert Choice tutorial provided with the software. </li></ul>EXPERT CHOICE: FILE SETUP
    59. 59. ANALYZING THE HIERARCHY <ul><li>1. Determine the weights of the alternatives for each criterion. </li></ul><ul><li>2. Determine the priorities or weights of the criteria in achieving the goal. </li></ul><ul><li>3. Determine the overall weight of each alternative in achieving the goal. This is accomplished by combining the results of the first two stages and is called synthesis. </li></ul>
    60. 60. HYPOTHETICAL DATA FOR CAR PURCHASE EXAMPLE Car Cost Safety* Appearance Honda $22,000 28 Sporty Mazda 28,500 39 Slick Volvo 33,000 52 Dull * Safety Rating from a consumer testing service - the higher the number, the safer the car.
    61. 61. DETERMINING PRIORITIES <ul><li>The couple begins by making pairwise comparison judgments between each pair of cars for the cost criterion. </li></ul><ul><li>In our example, three judgments are needed: Honda to Mazda, Mazda to Volvo, and Honda to Volvo. </li></ul>
    62. 62. STANDARD 1 - 9 MEASUREMENT SCALE <ul><li>Intensity of Importance Definition Explanation </li></ul><ul><li>1 Equal importance Two activities contribute equally </li></ul><ul><li>3 Moderate importance Experience and judgment slightly favor one </li></ul><ul><li>activity over another </li></ul><ul><li>5 Strong importance Experience and judgment strongly favor one </li></ul><ul><li>activity over another </li></ul><ul><li>7 Very strong An activity is favored very strongly over </li></ul><ul><li>another </li></ul><ul><li>9 Extreme importance The evidence favoring one activity over </li></ul><ul><li>another is of the highest possible order </li></ul><ul><li>of affirmation </li></ul><ul><li> 2, 4, 6, 8 For compromise Sometimes one needs to interpolate a </li></ul><ul><li>values compromise between the above judgment </li></ul><ul><li>numerically because there is no good </li></ul><ul><li>word to describe it </li></ul><ul><li> 1.1 - 1.9 For tied activities When elements are close and nearly </li></ul><ul><li>indistinguishable; moderate is 1.3 and </li></ul><ul><li>extreme is 1.9 </li></ul><ul><li>Reciprocals of above If activity A has For example, if the pairwise comparison of </li></ul><ul><li>one of the above A to B is 3.0, then the pairwise comparison </li></ul><ul><li>numbers assigned of B to A is 1/3 </li></ul><ul><li>to it when compared </li></ul><ul><li>with activity B, </li></ul><ul><li>then B has the </li></ul><ul><li>reciprocal value </li></ul><ul><li>when compared to A. </li></ul>
    63. 63. COST PAIRWISE COMPARISONS <ul><li>The pairwise comparisons are represented in the form of pairwise comparison matrices. </li></ul><ul><li>The computation of the weights are also shown. </li></ul><ul><li>Consider the pairwise comparison matrix to compare the cars for the cost criterion. </li></ul><ul><li>Remember that the costs of the three cars are: $22000, $28500, and $33000, respectively. </li></ul>
    64. 64. <ul><li>If we compare the Honda to the Honda, obviously they are equal. </li></ul><ul><li>Therefore, a 1 (equal preferred) is placed in the first row, first column entry of the matrix. </li></ul>COST PAIRWISE COMPARISONS
    65. 65. <ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 </li></ul><ul><li>28.5K Mazda </li></ul><ul><li>33K Volvo </li></ul>COST PAIRWISE COMPARISONS
    66. 66. <ul><li>The other entries along the main diagonal of the matrix are also 1. </li></ul><ul><li>This simply means that everything is equally preferred to itself. </li></ul>COST PAIRWISE COMPARISONS
    67. 67. <ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 </li></ul><ul><li>28.5K Mazda 1 </li></ul><ul><li>33K Volvo 1 </li></ul>COST PAIRWISE COMPARISONS
    68. 68. <ul><li>Suppose we believe the Honda ($22000) is equally to moderately preferred to the Mazda ($28500). Place a 2 in the row 1, column 2 entry. </li></ul><ul><li>Some might argue that the Honda should be 1.295 times better than the Mazda (28,500/22,000). </li></ul>COST PAIRWISE COMPARISONS
    69. 69. <ul><li>Do you agree? </li></ul><ul><li>It depends! </li></ul><ul><li>For some, $28,500 is significantly greater than $22,000, implying a judgments greater than 1.295. </li></ul><ul><li>Others with a lot of money may perceive virtually no difference between the two costs, implying a judgment somewhere between 1 and 1.295. </li></ul>COST PAIRWISE COMPARISONS
    70. 70. <ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 </li></ul><ul><li>28.5K Mazda 1 </li></ul><ul><li>33K Volvo 1 </li></ul>COST PAIRWISE COMPARISONS
    71. 71. <ul><li>If the Honda is 2 times better than the Mazda, this implies that the Mazda ($28500) is one half as good as the Honda ($22000). </li></ul><ul><li>The reciprocal judgment, (1/2), should be placed in the row 2, column 1 entry of the matrix. </li></ul>COST PAIRWISE COMPARISONS
    72. 72. <ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 </li></ul><ul><li>28.5K Mazda 1/2 1 </li></ul><ul><li>33K Volvo 1 </li></ul>COST PAIRWISE COMPARISONS
    73. 73. <ul><li>Suppose that we judge the Mazda ($28500) to be equally to moderately preferred to the Volvo ($33000). </li></ul><ul><li>The following judgments would be entered in the matrix. </li></ul>COST PAIRWISE COMPARISONS
    74. 74. <ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 </li></ul><ul><li>28.5K Mazda 1/2 1 2 </li></ul><ul><li>33K Volvo 1/2 1 </li></ul>COST PAIRWISE COMPARISONS
    75. 75. <ul><li>Assuming perfect consistency of judgments, we would expect that the Honda ($22000) is 4 times (that is, moderately to strongly) preferred to the Volvo ($33000). </li></ul><ul><li>We will relax this assumption later. </li></ul>COST PAIRWISE COMPARISONS
    76. 76. <ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 2 </li></ul><ul><li>33K Volvo 1/4 1/2 1 </li></ul>COST PAIRWISE COMPARISONS
    77. 77. <ul><li>The matrix is now complete and the weights for each car (for the cost criterion) can be computed. </li></ul><ul><li>The exact computational procedure is implemented in Expert Choice. For details see Expert Choice homepage and download AHPDEMO.EXE. </li></ul>COST PAIRWISE COMPARISONS
    78. 78. <ul><li>A simple three step procedure can be used to approximate the weights for each alternative. </li></ul><ul><li>Essentially, this procedure normalizes the ratios of the judgments between any pair of alternatives. </li></ul>COST PAIRWISE COMPARISONS
    79. 79. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 2 </li></ul><ul><li>33K Volvo 1/4 1/2 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS </li></ul>COST PAIRWISE COMPARISONS
    80. 80. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 2 </li></ul><ul><li>33K Volvo 1/4 1/2 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS 7/4 7/2 7 </li></ul>COST PAIRWISE COMPARISONS
    81. 81. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 2 </li></ul><ul><li>33K Volvo 1/4 1/2 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS 7/4 7/2 7 </li></ul>COST PAIRWISE COMPARISONS
    82. 82. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2 . DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 2 </li></ul><ul><li>33K Volvo 1/4 1/2 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS 7/4 7/2 7 </li></ul><ul><li>B. ADJUSTED COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>Honda 4/7* 4/7 4/7 </li></ul><ul><li>Mazda 2/7 2/7 2/7 </li></ul><ul><li>Volvo 1/7 1/7 1/7 </li></ul><ul><li>* This entry is obtained by dividing the Honda entry in the original matrix (1) by the Honda column total (7/4). </li></ul>COST PAIRWISE COMPARISONS
    83. 83. <ul><li>Notice that no variation is seen across the rows because the judgments are perfectly consistent. </li></ul><ul><li>For the third column, judgments totaling 7 were awarded. The Honda received 4 of 7 (57.1%), the Mazda 2 of 7 (28.6%), and the Volvo 1 of 7 (14.3%) of the weight. </li></ul><ul><li>Similar comparisons can be made for the other two columns. </li></ul>COST PAIRWISE COMPARISONS
    84. 84. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 2 </li></ul><ul><li>33K Volvo 1/4 1/2 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS 7/4 7/2 7 </li></ul><ul><li>B. ADJUSTED COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>Honda 4/7* 4/7 4/7 </li></ul><ul><li>Mazda 2/7 2/7 2/7 </li></ul><ul><li>Volvo 1/7 1/7 1/7 </li></ul><ul><li>* This entry is obtained by dividing the Honda entry in the original matrix (1) by the Honda column total (7/4). </li></ul>COST PAIRWISE COMPARISONS
    85. 85. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 2 </li></ul><ul><li>33K Volvo 1/4 1/2 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS 7/4 7/2 7 </li></ul><ul><li>B. ADJUSTED COST PAIRWISE COMPARISON MATRIX WEIGHTS </li></ul><ul><li> Honda Mazda Volvo (ROW AVG.) </li></ul><ul><li>Honda 4/7* 4/7 4/7 0.571 </li></ul><ul><li>Mazda 2/7 2/7 2/7 0.286 </li></ul><ul><li>Volvo 1/7 1/7 1/7 0.143 </li></ul><ul><li> --------- </li></ul><ul><li> TOTAL 1.000 </li></ul><ul><li>* This entry is obtained by dividing the Honda entry in the original matrix (1) by the Honda column total (7/4). </li></ul>COST PAIRWISE COMPARISONS
    86. 86. <ul><li>Expert Choice offers a variety of modes for entering the judgments. </li></ul><ul><li>Highlight the cost node, select A ssessment. </li></ul><ul><li>There are three options: P airwise, D ata , and R atings . </li></ul><ul><li>Ratings will be discussed later. </li></ul>EXPERT CHOICE: Entering Judgments
    87. 87. <ul><li>The D ata option allows the user to enter data items for each alternative, for example, costs, miles per gallon, and number of defects. </li></ul><ul><li>Expert Choice takes the ratio of these data items and converts them into pairwise comparisons. </li></ul><ul><li>What assumption are you making if you use the Data option? </li></ul><ul><li>The data items have a linear preference scale, that is, a $20,000 car is twice as good as a $40,000 car. </li></ul>EXPERT CHOICE: Entering Judgments
    88. 88. <ul><li>To enter our cost judgments choose P airwise. </li></ul><ul><li>When comparing alternatives select P reference for T ype ; for criteria select I mportance . </li></ul><ul><li>Modes options are: V erbal, M atrix (numerical), Q uestionnaire, and G raphic . </li></ul><ul><li>A ssessment, P airwise, M atrix is demonstrated. </li></ul><ul><li>Enter judgments, C alculate and R ecord . </li></ul>EXPERT CHOICE: Entering Judgments
    89. 89. INCONSISTENCY OF JUDGMENTS <ul><li>Since our pairwise comparisons were perfectly consistent, Expert Choice reports INCONSISTENCY RATIO = 0.0. </li></ul><ul><li>If this ratio is greater than 0.1 some revision of judgments is required. </li></ul><ul><li>Select Inconsis t ency (within A ssessment , P airwise ) to identify the most inconsistent judgments. </li></ul>
    90. 90. INCONSISTENCY OF JUDGMENTS <ul><li>Inconsistency of judgments may result from: </li></ul><ul><li>problems of estimation; </li></ul><ul><li>errors between the comparisons; </li></ul><ul><li>or, the comparisons may be naturally inconsistent. </li></ul>
    91. 91. INCONSISTENCY OF JUDGMENTS <ul><li>One example of natural inconsistency is in a sporting contest. </li></ul><ul><li>If team A is twice as likely to beat team B, and if team B is three times as likely to beat team C, this does not necessarily imply that team A is six times as likely to beat team C. </li></ul><ul><li>This inconsistency may result because of the way that the teams “match-up” overall. </li></ul>
    92. 92. INCONSISTENCY OF JUDGMENTS <ul><li>The point is not to stop inconsistency from occurring. </li></ul><ul><li>Make sure that the level of inconsistency remains within some reasonable limit. </li></ul>
    93. 93. INCONSISTENCY OF JUDGMENTS <ul><li>How does a judgment change affect the car weights? </li></ul><ul><li>Suppose the Mazda to Volvo changes from 2 to 3. </li></ul><ul><li>This obviously changes the comparison for Volvo to Mazda from (1/2) to (1/3). </li></ul><ul><li>The judgments are now somewhat inconsistent. </li></ul>
    94. 94. <ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 3 </li></ul><ul><li>33K Volvo 1/4 1/3 1 </li></ul>COST PAIRWISE COMPARISONS
    95. 95. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 3 </li></ul><ul><li>33K Volvo 1/4 1/3 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS 7/4 10/3 8 </li></ul>COST PAIRWISE COMPARISONS
    96. 96. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2 . DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 3 </li></ul><ul><li>33K Volvo 1/4 1/3 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS 7/4 10/3 8 </li></ul><ul><li>B. ADJUSTED COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>Honda 4/7* 6/10 4/8 </li></ul><ul><li>Mazda 2/7 3/10 3/8 </li></ul><ul><li>Volvo 1/7 1/10 1/8 </li></ul><ul><li>* This entry is obtained by dividing the Honda entry in the original matrix (1) by the Honda column total (7/4). </li></ul>COST PAIRWISE COMPARISONS
    97. 97. <ul><li>1. SUM THE ELEMENTS IN EACH COLUMN OF THE ORIGINAL MATRIX. </li></ul><ul><li>2. DIVIDE EACH ELEMENT IN THE ORIGINAL MATRIX BY ITS COLUMN SUM. </li></ul><ul><li>THIS RESULTS IN THE ADJUSTED MATRIX. </li></ul><ul><li>3. COMPUTE THE ROW AVERAGES - THESE ARE THE WEIGHTS. </li></ul><ul><li>A. ORIGINAL COST PAIRWISE COMPARISON MATRIX </li></ul><ul><li> Honda Mazda Volvo </li></ul><ul><li>22K Honda 1 2 4 </li></ul><ul><li>28.5K Mazda 1/2 1 3 </li></ul><ul><li>33K Volvo 1/4 1/3 1 </li></ul><ul><li> ------- ------- ------- </li></ul><ul><li>COLUMN TOTALS 7/4 10/3 8 </li></ul><ul><li>B. ADJUSTED COST PAIRWISE COMPARISON MATRIX WEIGHTS </li></ul><ul><li> Honda Mazda Volvo (ROW AVG.) </li></ul><ul><li>Honda 4/7* 6/10 4/8 0.557 </li></ul><ul><li>Mazda 2/7 3/10 3/8 0.320 </li></ul><ul><li>Volvo 1/7 1/10 1/8 0.123 </li></ul><ul><li>-------- </li></ul><ul><li>TOTAL 1.000 </li></ul><ul><li>* This entry is obtained by dividing the Honda entry in the original matrix (1) by the Honda column total (7/4). </li></ul>COST PAIRWISE COMPARISONS
    98. 98. INCONSISTENCY OF JUDGMENTS <ul><li>The new weights are: 0.557, 0.320, and 0.123. The inconsistency resulted in some change in the original weights of 0.571, 0.286, and 0.143. </li></ul><ul><li>As expected, the weight for the Mazda increased while the weight for the Volvo decreased. </li></ul><ul><li>The weights now vary across each row. Essentially, inconsistency measures the degree of variation across the rows. </li></ul>
    99. 99. <ul><li>Highlight cost node, select A ssessment, P airwise. </li></ul><ul><li>Enter a 3 in the Mazda to Volvo cell then C alculate . </li></ul><ul><li>The weights of 0.558, 0.320, and 0.122 are slightly different from the three-step procedure weights. </li></ul><ul><li>This is not due to rounding -- Expert Choice gives the exact results. </li></ul><ul><li>The INCONSISTENCY RATIO is now 0.02. </li></ul>EXPERT CHOICE: Revising Judgments
    100. 100. INCONSISTENCY OF JUDGMENTS <ul><li>The weights can also be used to measure the effectiveness of the alternatives. </li></ul><ul><li>For example, based on all pairwise comparisons, we determined that the Honda is 1.74 (0.558/0.320) times better than the Mazda. </li></ul><ul><li>Why is this ratio 1.74 and not the pairwise comparison of 2? </li></ul><ul><li>Inconsistency in the judgments! </li></ul>
    101. 101. REMAINING COMPUTATIONS <ul><li>Next, the cars must be pairwise compared for the safety criterion and then for the appearance criterion. </li></ul><ul><li>These judgments are shown on the next page. </li></ul><ul><li>Since the Mazda to Honda safety comparison is 2, highlight the Honda to Mazda cell, click I nvert , and enter 2. </li></ul><ul><li>This judgment now appears in red. </li></ul>
    102. 102. SAFETY & APPEARANCE JUDGMENTS <ul><li>Safety Pairwise Comparison Matrix </li></ul><ul><li>Honda Mazda Volvo </li></ul><ul><li>28 Honda 1 1/2 1/5 </li></ul><ul><li>39 Mazda 2 1 1/4 </li></ul><ul><li>52 Volvo 5 4 1 </li></ul><ul><li>Appearance Pairwise Comparison Matrix </li></ul><ul><li>Honda Mazda Volvo </li></ul><ul><li>Sporty Honda 1 5 9 </li></ul><ul><li>Slick Mazda 1/5 1 2 </li></ul><ul><li>Dull Volvo 1/9 1/2 1 </li></ul>
    103. 103. REMAINING COMPUTATIONS <ul><li>Next, the criteria must be pairwise compared. </li></ul><ul><li>These judgments are shown on the next page. </li></ul><ul><li>There are no data to support these judgments since they are purely a reflection of your preferences. </li></ul>
    104. 104. CRITERIA JUDGMENTS <ul><li>Original Criteria Pairwise Comparison Matrix </li></ul><ul><li>Cost Safety Appearance </li></ul><ul><li>Cost 1 1/2 3 </li></ul><ul><li>Safety 2 1 5 </li></ul><ul><li>Appearance 1/3 1/5 1 </li></ul>
    105. 105. REMAINING COMPUTATIONS <ul><li>The last stage computes the final weights for each car. </li></ul><ul><li>Multiply the criteria weight by the car weight for each criterion and then sum over all criteria. </li></ul><ul><li>This is nothing more than a weighted average. </li></ul><ul><li>The computational results are shown next. </li></ul>
    106. 106. FINAL CAR WEIGHTS <ul><li> CRITERIA WEIGHTS </li></ul><ul><li>COST SAFETY APPEARANCE </li></ul><ul><li>0.309 0.582 0.109 </li></ul><ul><li>CARS FINAL WEIGHTS </li></ul><ul><li>Honda 0.558 0.117 0.761 </li></ul><ul><li>Mazda 0.320 0.200 0.158 </li></ul><ul><li>Volvo 0.122 0.683 0.082 </li></ul>
    107. 107. FINAL CAR WEIGHTS <ul><li> CRITERIA WEIGHTS </li></ul><ul><li>COST SAFETY APPEARANCE </li></ul><ul><li>0.309 0.582 0.109 </li></ul><ul><li>CARS FINAL WEIGHTS </li></ul><ul><li>Honda 0.558 0.117 0.761 0.324 </li></ul><ul><li>Mazda 0.320 0.200 0.158 </li></ul><ul><li>Volvo 0.122 0.683 0.082 </li></ul><ul><li>Honda: (0.558)(0.309) + (0.117)(0.582) + (0.761)(0.109) = 0.324 </li></ul><ul><li> 0.173 0.068 0.083 </li></ul>
    108. 108. FINAL CAR WEIGHTS <ul><li> CRITERIA WEIGHTS </li></ul><ul><li>COST SAFETY APPEARANCE </li></ul><ul><li>0.309 0.582 0.109 </li></ul><ul><li>CARS FINAL WEIGHTS </li></ul><ul><li>Honda 0.558 0.117 0.761 0.324 </li></ul><ul><li>Mazda 0.320 0.200 0.158 0.232 </li></ul><ul><li>Volvo 0.122 0.683 0.082 </li></ul><ul><li>Honda: (0.558)(0.309) + (0.117)(0.582) + (0.761)(0.109) = 0.324 </li></ul><ul><li> 0.173 0.068 0.083 </li></ul><ul><li>Mazda: (0.320)(0.309) + (0.200)(0.582) + (0.158)(0.109) = 0.232 </li></ul><ul><li> 0.099 0.116 0.017 </li></ul>
    109. 109. FINAL CAR WEIGHTS <ul><li> CRITERIA WEIGHTS </li></ul><ul><li>COST SAFETY APPEARANCE </li></ul><ul><li>0.309 0.582 0.109 </li></ul><ul><li>CARS FINAL WEIGHTS </li></ul><ul><li>Honda 0.558 0.117 0.761 0.324 </li></ul><ul><li>Mazda 0.320 0.200 0.158 0.232 </li></ul><ul><li>Volvo 0.122 0.683 0.082 0.444 </li></ul><ul><li>Honda: (0.558)(0.309) + (0.117)(0.582) + (0.761)(0.109) = 0.324 </li></ul><ul><li> 0.173 0.068 0.083 </li></ul><ul><li>Mazda: (0.320)(0.309) + (0.200)(0.582) + (0.158)(0.109) = 0.232 </li></ul><ul><li> 0.099 0.116 0.017 </li></ul><ul><li>Volvo: (0.122)(0.309) + (0.683)(0.582) + (0.082)(0.109) = 0.444 </li></ul><ul><li> 0.038 0.397 0.009 </li></ul>
    110. 110. LOCAL VS GLOBAL WEIGHTS <ul><li>For cost, the local weights for the cars are 0.558, 0.320, and 0.122 and sum to 1.000. </li></ul><ul><li>The global weights are computed by multiplying the cost criterion weight by the local car weights. </li></ul><ul><li>The global weights are 0.173, 0.099, and 0.038 and sum to the cost criterion weight of 0.309. </li></ul>
    111. 111. <ul><li>To compute the final weights select S ynthesis ( from G OAL ). </li></ul><ul><li>Choose Dis t ributive Mode and Display S ummary . </li></ul><ul><li>D etails provides the global weights. </li></ul><ul><li>The output can also be exported to a spreadsheet using the U tilities , Export Model(s) to Spreadsheet commands. </li></ul>EXPERT CHOICE: Synthesis
    112. 112. <ul><li>The Print icon can be used to select certain options. </li></ul><ul><li>The recommended print options are: E ntire Tree, T ree Views, J udgments/Data, and S y nthesis . </li></ul>EXPERT CHOICE: Printing
    113. 113. INTERPRETING THE RESULTS <ul><li>The final weights provide a measure of the relative performance of each alternative. </li></ul><ul><li>It is important to properly interpret the meaning of these numbers. </li></ul><ul><li>The Volvo is ranked first, the Honda second, and Mazda third. </li></ul><ul><li>The Volvo is preferred 1.37 (0.444/0.324) times more than the Honda. </li></ul>
    114. 114. INTERPRETING THE RESULTS <ul><li>Should we buy the Volvo? </li></ul><ul><li>The output is a decision-making aid and cannot replace the decision-maker. </li></ul><ul><li>The results can be used to support discussion and possibly the judgments will be revised. </li></ul><ul><li>This iterative process is quite normal. </li></ul><ul><li>AHP can help to facilitate communication and generate consensus between different groups. </li></ul>
    115. 115. SENSITIVITY ANALYSIS <ul><li>Sensitivity analysis is an important aspect of any decision-making process. </li></ul><ul><li>Sensitivity analysis determines whether small changes in judgments affects the final weights and rankings of the alternatives. </li></ul><ul><li>If so, the decision-maker may want to review the sensitive judgments. </li></ul>
    116. 116. EXPERT CHOICE: Sensitivity Analysis <ul><li>In Expert Choice sensitivity analysis from the GOAL shows how the weights and the rankings of the alternatives change if some or all of the criteria weights change. </li></ul><ul><li>There are five graphical sensitivity analysis modes available: Performance, Dynamic, Gradient, Two-Dimensional, and Difference. </li></ul><ul><li>The first three show how a change in a criterion weight affects the final weights of the alternatives. </li></ul>
    117. 117. <ul><li>The last two show how the alternatives perform with respect to any two criteria. </li></ul><ul><li>Performance : places all sensitivity information on a single chart with horizontal line graphs for the alternatives linked to vertical bars for the criteria. </li></ul><ul><li>Dynamic : two sets of dynamically linked horizontal bar graphs: one for criteria and one for alternatives. </li></ul>EXPERT CHOICE: Sensitivity Analysis
    118. 118. <ul><li>Gradient : a line graph that shows how the weights of the alternatives vary according to the weight assigned to a specific criterion. (Use the X -Axis to change the selected criterion.) </li></ul><ul><li>Two-Dimensional : shows how well the alternatives perform with respect to any two criteria. </li></ul><ul><li>Difference : a graph that shows the differences between any two alternatives for any criterion. </li></ul>EXPERT CHOICE: Sensitivity Analysis
    119. 119. <ul><li>An important use of sensitivity analysis is to determine how much a given criterion weight must change before there is a change in the rankings of the two highest alternatives. </li></ul><ul><li>This type of breakeven analysis can be easily done in Expert Choice. </li></ul>EXPERT CHOICE: Sensitivity Analysis
    120. 120. <ul><li>Choose D ynamic from the Sensitivity- G raphs option. </li></ul><ul><li>Drag the cost criterion bar 30.9% to approximately 45.9%, and see that the Volvo and Honda have the same highest final weight. </li></ul><ul><li>The final rankings are relatively insensitive to a change in the cost criterion weight because the cost weight had to be increased by almost 50% to get a change in the rankings. </li></ul>EXPERT CHOICE: Sensitivity Analysis
    121. 121. NEW PRODUCT INTRODUCTION <ul><li>CHOCK-FUL-O-CHIPS developed the following hierarchy and data that can be used to help decide which chocolate chip recipe they should use. </li></ul>Select the best recipe Taste Cost Fat Content Recipe 1 Recipe 2 Recipe 3 Recipe 4 Recipe 1 Recipe 2 Recipe 3 Recipe 4 Recipe 1 Recipe 2 Recipe 3 Recipe 4
    122. 122. RECIPE DATA <ul><li>Taste Fat Content </li></ul><ul><li>Recipe Cost* Rating** (Grams)* </li></ul><ul><li>1 $0.166 54% 8.0 </li></ul><ul><li>2 0.099 24% 7.0 </li></ul><ul><li>3 0.265 20% 3.5 </li></ul><ul><li>4 0.224 43% 6.0 </li></ul><ul><li>* Per one ounce cookie </li></ul><ul><li>** Percentage of people who rated a cookie either an 8 or 9 on a 9-point scale, where 9 means extremely liked, 8 means liked very much, and down to one which means extremely disliked. </li></ul>
    123. 123. TASTE PAIRWISE COMPARISON MATRIX <ul><li> 54% 24% 20% 43% </li></ul><ul><li>Recipe 1 Recipe 2 Recipe 3 Recipe 4 </li></ul><ul><li>Recipe 1 1 </li></ul><ul><li>Recipe 2 1 </li></ul><ul><li>Recipe 3 1 </li></ul><ul><li>Recipe 4 1 </li></ul>
    124. 124. COST PAIRWISE COMPARISON MATRIX <ul><li> 0.166 0.099 0.265 0.224 </li></ul><ul><li>Recipe 1 Recipe 2 Recipe 3 Recipe 4 </li></ul><ul><li>Recipe 1 1 </li></ul><ul><li>Recipe 2 1 </li></ul><ul><li>Recipe 3 1 </li></ul><ul><li>Recipe 4 1 </li></ul>
    125. 125. FAT CONTENT PAIRWISE COMPARISON MATRIX <ul><li> 8.0 7.0 3.5 6.0 </li></ul><ul><li>Recipe 1 Recipe 2 Recipe 3 Recipe 4 </li></ul><ul><li>Recipe 1 1 </li></ul><ul><li>Recipe 2 1 </li></ul><ul><li>Recipe 3 1 </li></ul><ul><li>Recipe 4 1 </li></ul>
    126. 126. CRITERIA PAIRWISE COMPARISON MATRIX <ul><li> Taste Cost Fat Content </li></ul><ul><li>Taste 1 </li></ul><ul><li>Cost 1 </li></ul><ul><li>Fat Content 1 </li></ul>
    127. 127. FINAL WEIGHTS FROM EXPERT CHOICE <ul><li>Criteria Weights </li></ul><ul><li>Taste Cost Fat Content </li></ul><ul><li> Final </li></ul><ul><li>Weights </li></ul><ul><li>Recipe 1 </li></ul><ul><li>Recipe 2 </li></ul><ul><li>Recipe 3 </li></ul><ul><li>Recipe 4 </li></ul>
    128. 128. SUMMARY <ul><li>In this chapter: </li></ul><ul><li>we provided an overview of operations management; and </li></ul><ul><li>offered the AHP as a decision-making process with application in operations management. </li></ul>
    129. 129. SUMMARY <ul><li>AHP benefits include: </li></ul><ul><li>natural way to elicit judgments; </li></ul><ul><li>measure degree of inconsistency; </li></ul><ul><li>easy to use; </li></ul><ul><li>allows broad participation; and </li></ul><ul><li>fully supported by Expert Choice. </li></ul>
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