PPA 670 POLICY ANALYSIS

DECISION RULES and

DISPLAYING ALTERNATIVES

Decision Rules
Paired comparisons
Satisficing
Grading Method
Lexicographic Ordering
Non-Dominated Alternative
Equivalent Alternatives
Weighted Decision Criteria
Groller Scorecard
 

DECISION RULES

    Policy assessment techniques do not determine which policy should be adopted. Policy analysis presents the benefits and drawbacks of each alternative, but in addition one or more decision rules are needed in order to determine which policy is the "best."
There are many problems in trying to determine which policy to adopt.
1) Many problems in the public sector have multiple facets. Policies are designed with multiple goals or objectives. There may be no dominant objective, or several objectives may be in conflict.
2) there are multiple criteria to take into account--technical, economic, political, and administrative--but who decides which is the most important?
3) not all important considerations can be converted into comparable units, such as dollar values.
4) which is the proper criterion to use, greatest net present value? greatest internal rate of return? largest benefit-cost ratio?
5) there is often a lack of agreement beforehand on decision rules, or which rules to apply
6) even if each decision criterion is optimized separately, there may still be a sub-optimal choice at the end (a camel is a horse designed by a committee).
    The policy analyst is often faced with trying to present multiple policy alternatives which have been assessed in terms of multiple decision criteria. There are various methods which can be used to display this information in a way that facilitates decision-making.
 

PAIRED COMPARISONS

    If there are 5 different ways of collecting the city's garbage, then the analyst can compare method 1 with method 2 and determine which is superior. The better of the two is then compared with method 3, and again one of them is determined to be superior. The winner of each contest is then compared with another of the remaining alternatives until all have been evaluated and the winner of the last contest is the overall winner.

    This method presents a simple, step-by-step comparison that is relatively easy to follow, if somewhat tedious. The problem with this method is that the outcome may be influenced by the order in which the alternatives were considered.
 

SATISFICING

    The analyst presents all the alternatives that meet the minimum threshold levels on all criteria. The minimum threshold is then increased on each criterion, and those alternatives which do not meet the new levels are dropped. This process continues until only one alternative is left.

    For example, say there are 6 alternatives to solve the parking problems on campus and three criteria: net revenues, number of permits sold, and student satisfaction. The minimum levels are $50,000 in revenues, 10% increase in permits sold, and at least 50% students satisfaction. Two alternatives are dropped because they do not meet one or more of these minimum levels.

    The levels are then raised to $75,000 in revenues, 20% increase in parking, and 65% student satisfaction. Another two alternatives drop out. Finally, raising the minimums to $100,000 in revenues, 25% increase in parking, and 75% student satisfaction eliminates one alternative and the only remaining alternative that meets all these minimums is the winner.

    This method assures that the minimum "needs" for the policy will be met, and, in addition, offers the prospect of meeting higher than minimum needs ("desires"). The problem is that it changes the definition of acceptable after the analysis has been completed.
 

GRADING METHOD

    The consequences of each alternative on each criterion are considered. A grade of "Pass" or "Fail" is assigned to each alternative on each criterion. Only those alternatives which "Pass" on all criteria are retained; those which have any "Fails" are rejected. The retained criteria are then compared further. This is comparable to the satisficing method discussed above.
 

LEXICOGRAPHIC ORDERING

    The analyst lists all those alternatives that ranked most highly on the one most important criterion. These alternatives are all considered to be roughly equal. The alternatives are then compared on the second most important criterion. Those alternatives which rank most highly are retained, and they are then compared on the third most important criterion. This process is repeated until the alternative that is most highly ranked on all the criteria is found.

    For example, say there are 5 alternatives for economic development for the downtown area, and there are three criteria: increased revenues, increased jobs, and citizen satisfaction. Three alternatives rank highly on the most important criterion of increased jobs. These three are then compared on the second criterion, citizen satisfaction. Only two are highly ranked. These last two are compared on the third criterion of increased revenues, and the most highly ranked is the winner.

    This is a rather straightforward process of comparison. However, it assumes there is agreement on which is the first most important criterion, the second most important, and so on. For situations with multiple objectives (criteria) or multiple decision makers, this may be difficult.
 

NON-DOMINATED ALTERNATIVES

    All alternatives are measured on all criteria, and their rank order on each criterion is displayed. Every alternative that is ranked the most highly on any criterion is retained; any alternative that is not ranked #1 on at least one criterion is discarded. The result is only "non-dominated" alternatives, that is, alternatives that are clearly superior on at least one criterion. These alternatives can then be compared further by another method.
 
Criterion 1 Criterion 2 Criterion 3
Alternative A Rank #4 Rank #5 Rank #6
Alternative B Rank #2 Rank #1 Rank #3
Alternative C Rank #3 Rank #4 Rank #1
Alternative D Rank #1 Rank #3 Rank #2
Alternative E Rank #6 Rank #6 Rank #5
Alternative F Rank #5 Rank #2 Rank #4
    In this example, only Alternatives B, C, and D were ranked #1 in at least one category. Alternative B is not dominated by any other alternative on Criterion 2; Alternative C is not dominated by any other alternative on Criterion 3; and Alternative D is not dominated by any other alternative on Criterion 1. Alternatives B, C, and D must now be considered further.

    Say there are five designs for a new community building, and the designs are ranked in terms of their suitability for athletics, as well as their suitability for arts and crafts. Only one design will be ranked #1 in each category. These two designs are the only non-dominated alternatives. Since they are each ranked #1 on one category, and they are each ranked #2 in the other category, they are considered equal.

    A third criterion may be added as a "tie-breaker." For example, the two alternatives might be ranked in terms of their suitability for meetings. The higher ranking of the two will be the winner.

    This method is straightforward and relatively easy to follow. However, it brings in additional criteria (tie-breakers) after the analysis has been completed and some alternatives have been eliminated.
 

EQUIVALENT ALTERNATIVES

    When at least one of the criteria can be measured in quantitative units, for example, dollars, this method can be used to compare two alternatives. It involves converting other units of measurement to dollars as well and then comparing the two alternatives again.

    For example, you have been offered two possible jobs. You assess these jobs in terms of five criteria: salary (measured in dollars), climate (measured in days of sunshine per year), commute time (measured in minutes), nature of job (interesting or uninteresting), and potential for advancement (measured as good or poor).
 
Salary Climate Commute Nature Advance
Job A $36,000 240 20 I G
Job B $42,000 200 30 U P
    Since the two jobs are both measured on at least one criterion--salary--in a quantitative form (dollars), the next step is to convert the value of the other criteria to dollars as well.

    For example, how much of the $42,000 salary would you be willing to give up to have more days of sunshine per year? Say that the extra 40 days of sunshine per year are worth $1,600 (you would be willing to take Job B at $1,600 less in pay if it had 40 more days of sunshine). Show these calculations in a revised chart.
 
Salary Climate Commute Nature Advance
Job A $36,000 240 30 I G
Job B $40,400 240 20 U P
    Now, how much of the remaining salary of Job B would you be willing to give up to have a shorter commute? Say that cutting commute time by 10 minutes per day is worth $1,000 (you would be willing to take Job B at $1,000 less in pay if it had 10 minutes less of commuting). Show these calculations in a revised chart.
 
Salary Climate Commute Nature Advance
Job A $36,000 240 20 I G
Job B $39,400 240 20 U P
    Now, how much of the remaining salary of Job B would you be willing to give up to have a more interesting job? Say that it is worth $1,400 (you would be willing to take Job B at $1,400 less in pay if it was more interesting). Show these calculations in a revised chart.
 
Salary Climate Commute Nature Advance
Job A $36,000 240 20 I G
Job B $38,000 240 20 I P
    Now, how much of the remaining salary of Job B would you be willing to give up to have greater potential for advancement? Say that it is worth $2,500 (you would be willing to take Job B at $2,500 less if there was greater advancement potential). Show these calculations in a revised chart.
 
Salary Climate Commute Nature Advance
Job A $36,000 240 20 I G
Job B $35,500 240 20 I G
    Now the two jobs are "equalized" on all criteria except the quantitative on (salary). Since the two jobs are equal except for salary, then the job with the higher salary (Job A) is the winner.

    This method is rather complex and has many steps. It is also very subjective and best suited to situations where there are only individual decision makers rather than groups. It does help the decision maker to clarify their personal preferences, however, and may provide useful insight into the most important facets of the problem.
 

WEIGHTED DECISION CRITERIA

    When there are multiple decision criteria, a ranking or weighting system can be developed to reflect the relative importance of each criterion in the decision making process. These are sometimes referred to as "importance weights."

    Say that the state wants to adopt a plan to give grants to the elderly to defray their utility expenses. The decision criteria are number of elderly reached, speed at delivering the grants, and controls on fraud. Each alternative is measured on each criterion and a raw score is assigned.

Elderly Reached: 5 = 80% - 100%; 4 = 60% - 80%; 3 = 40% - 60%; 2 = 20% - 40%; 1 = 0% - 20%
Speed of Delivery: 5 = 0-5 days; 4 = 6-10 days; 3 = 11-15 days; 2 = 16-20 days; 1 = 21+ days
Curbs on Fraud: 5 = Very strong; 4 = Strong; 3 = Moderate; 2 = Weak; 1 = Very Weak
 
RAW SCORES Elderly Reached Speed of Delivery Fraud Curbs
Alternative A 5 4 3
Alternative B 4 4 4
Alternative C 4 3 3
Alternative D 2 3 5
    The decision criteria have been weighted by the decision makers, so that the number of elderly reached is worth 50% of the decision, the speed at delivering grants is worth 30%, and controls on fraud is worth 20%.

    The raw score for each alternative on each criterion is then multiplied by the importance weight for each criterion. The result is a weighted score. The weighted scores for each alternative on all the criteria are then added for the total weighted score.
 
WEIGHTED SCORES Elderly Reached  
(50%)		 Speed of Delivery  
(30%)		 Fraud Curbs  
(20%)		 Total  
Score
Alternative A 5 x .5 = 2.5 4 x .3 = 1.2 3 x .2 = 0.6 4.3
Alternative B 4 x .5 = 2.0 4 x .3 = 1.2 4 x .2 = 0.8 4.0
Alternative C 4 x .5 = 2.0 3 x .3 = 0.9 3 x .2 = 0.6 3.5
Alternative D 2 x .5 = 1.0 3 x .3 = 0.9 5 x .2 = 1.0 2.9
    The alternative which scores the highest on the number of elderly reached (Alternative A) is the alternative with the highest total score. An alternative which has very good controls on fraud, but does not do as well in the areas of reaching the elderly or speed, has the lowest total score.

    The advantages of this method are that arriving at the superior alternative is straightforward and relatively easy. Rather than considering alternatives one at a time, or considering criteria one at a time, this method considers all alternatives on all criteria simultaneously. The disadvantages are that many criteria are not measurable in quantitative form and there may be disagreement over the importance weights of the criteria.
 

GROLLER SCORECARD

    The matrix (or "scorecard") is a way of displaying the impacts of each alternative in terms of each criterion in "natural" units of measure, such as reduction in fatality rate, political acceptability, administrative ease, effectiveness, impact on need for additional landfills, etc. The scorecard indicates the extent to which each alternative attains the objectives specified by each criterion.

    This approach the viewer(s) to grasp a complex analysis by summarizing it in a chart. It can help a group to come to a decision without the need to impose quantitative measurement or assign importance weights to criteria.
 
REDUCE  
PERMIT  
PRICE		 STRONGER PARKING  
ENFORCEMENT		 EDUCATIONAL CAMPAIGN
COST TO THE  
UNIVERSITY		 More students buy permits; no net loss or gain Higher costs in enforcement Moderate costs for materials
SOLVES PARKING  
PROBLEM		 Cuts illegal parking by 25% Cuts illegal parking by 40% Cuts illegal parking by 10%
ACCEPTABILITY  
TO STUDENTS		 Highly acceptable Highly unacceptable Moderately acceptable
ACCEPTABILITY  
TO COMMUNITY		 Moderately acceptable Highly acceptable Unacceptable
 
Best option
 
Worst option