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The Optsee® Pro Prioritizer Form

Form Overview

Use this form to set the parameters to run a Monte Carlo simulation prioritization on an open portfolio (over-writing the current SMART Score data) or to create a new portfolio. The Monte Carlo prioritization involves creating thousands of models with random attribute rankings (in sequential or random order), testing the portfolio project set in each model a Cumulative Percentage Chart, and a Statistics Summary List form to show the statistical value rankings of each individual project.

Opening the Prioritization Form

The Optsee® Pro Prioritizer Form is opened by clicking the [Prioritizer] button on an open Portfolio form.

This button is visible only if the [Track Uncertainty In Attributes] checkbox has been selected in the Portfolio Preferences form.

If the portfolio has NOT been prioritized using Simulation-Prioritization before, the following dialog appears:

If the portfolio HAS been prioritized previously using Simulation-Prioritization before, the following dialog appears:

In both cases, you are being asked to overwrite the current SMART Score data with the Simulation-Prioritization results or save the data in a new portfolio.

Optsee® Pro Prioritizer Form Name Field:

If you are creating a new portfolio, enter the name for the new prioritization here. The name must be unique and not exceed 48 characters, including spaces. Otherwise, the name of the portfolio is listed here.

Prioritization Type Radio Buttons:

These buttons let you select which type of prioritization to perform:

[Variable Weights] radio button: Two types of Variable Weights prioritizations can be executed. In the first type, the attribute rank order of preference is kept constant, i.e. highest-to-lowest weight, but the relative weights of the attributes are randomly varied. This is called a Fixed Sequential Order prioritization. In the second type, both the attribute rank order and the weights of the attributes are varied. This is called a Random Order prioritization. A Ranked Attribute Order prioritization will provide a statistical ranking of the projects based on how the projects were ranked in up to 100,000 portfolios that maintained the same attribute rank order as the original portfolio. This allows you to see which projects are statistically most attractive with a particular rank order. A Random Attribute Order prioritization will provide a statistical ranking of the projects in up to 100,000 portfolios that have randomly ranked the order of attribute weights. This allows you to see which projects are statistically most attractive when the attributes are randomly ranked.

[Variable Projects] radio button: A Variable Projects prioritization involves generating multiple portfolios using the portfolio where the project attribute values are modified within the % uncertainty of each individual project. For example, if a project has an attribute value of "500" and a % uncertainty of "5" for that attribute, the Variable Portfolio prioritization would create portfolios where that project attribute would randomly vary between "475" and "525" or between 95% and 105% of the attribute value. The random variation can be distributed over a normal Gaussian distribution (bell curve) or a uniform distribution (equally distributed between the maximum and minimum values). Maximum and minimum values outside of the portfolio best and worst attribute outcome constraints are not used in the prioritization.

[Combined] radio button: A Combined prioritization combines the Variable Decision Model prioritization with the Variable Projects prioritization such that the portfolios weights and the portfolio project attribute values are varied simultaneously within the constraints described above.

Attribute Order Radio Buttons:

[Ranked Attribute Order] radio button: Select this button to automatically perform the prioritization with all of the attributes in the same ranked order as the portfolio. For example, if the attributes A, B, and C are weighted 900, 500, and 100, respectively in the portfolio, the random models will retain the same order (attribute A will always be the highest, attribute B will always be second highest, and attribute C will always be third highest). The random models will only vary the interval between each attribute weights.

[Random Attribute Order] radio button: Select this button to automatically perform the prioritization with all of the attributes in random ranked order, regardless of the portfolio weightings. Therefore, the random models will vary both the order of and the interval between each attribute weight.

The Drop-Down Menus:

Number of Simulations drop-down menu: Use this menu to select the number of simulations (1,000 to 100,000) that you want to generate.

Weight Range drop-down menu: Use this menu to select the maximum spread between the attribute weightings (1000 to 10,000). For example, if the Weight Range was set to 1,000, the highest possible weight for an attribute would be 1,000, which is 1,000 times greater than the lowest weight. Note that this number represents the maximum spread between the highest and lowest weight, but this spread is varied in the random models. This menu is disabled if the Variable Projects prioritization has been selected.

Weight Bias drop-down menus: Use these menus to bias the prioritization towards your top attributes. For example, if you have six non-zero weight attributes in a ranked attribute order prioritization, the top three attribute weights will always account for at least 51% of the total normalized attribute weights (i.e. they will always provide at least 51% of the influence into the project rankings in a single portfolio). However, if you would like to have the top three attributes always having at least 70% of the normalized attribute weight (i.e. 70% of the influence into your project ranking), you would set the Weight Bias to "Bias top three attributes by 70%." All of the prioritization portfolios would then use weight sets in which the top three attribute weights would always sum to at least 70% of the total weight. Note that you cannot set a bias below the minimum possible percentage of the rankings. (For example, if you want to bias three of six non-zero weight attributes, the minimum bias that you could set is 55%.) After you run a prioritization using an attribute bias, the average bias of the specified attributes is displayed in the Statistics Summary List form.

The Bias Top drop-down menu displays n-1 non-zero weight attributes. For example, if you have ten attributes and two attributes have weights of "0", then you can bias up to seven attributes (eight non-zero weight attributes minus one).

The Bias Percentage drop-down menu lets you bias the selected number of top attributes from 10% to 95% in increments of 5%. The Bias Percentage drop-down menu will set to the minimum value that you can select for a selected number of attributes. For example, if you want to bias three of six non-zero weight attributes, the minimum bias that you could set is 55%.

The Weight Bias drop-down menus are disabled for Random Order weight prioritizations.

Optsee® Pro Prioritizer Form Buttons:

[Run Prioritization]: Click on this button to run the prioritization, save and display the new prioritization chart. This button is disabled until a name has been added to the Prioritization Chart Name field.

[Cancel]: Click on this button to cancel and close the form.