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Release: Australia · Updated: 2026-06-08 · Official documentation · View source

Configure resource profiling score

Configure the resource profiling score to adjust how the AI Resource Finder ranks candidates by modifying attribute weights in the CandidateProfileScoringConfigSNC script include.

Before you begin

Role required: admin

Procedure

Navigate to All > System Definition > Script Includes.
Locate and open the CandidateProfileScoringConfigSNC script include record.
To edit the record change the scope of the application to SPM Planning Attributes.

Use the Script field to view and understand the current allocation logic using the getWeights function.

Following is the default code.

var CandidateProfileScoringConfigCustom = Class.create();
    CandidateProfileScoringConfigCustom.prototype = Object.extendsObject(
        CandidateProfileScoringConfigSNC, {

        getWeights: function() {
            return {
                availabilityCoverage: 0.40,
                attrExpScore:         0.20,
                prjExpScore:          0.20,
                adjacentAttrExp:      0.15,
                generalExp:           0.05
            };
        },

        type: 'CandidateProfileScoringConfigCustom'
    });

Attributes	Definition
availabilityCoverage	Scoring attribute indicating resource's as capacity during the assignment period.This is the dominant factor. A resource with perfect skills but no availability scores lower than a less experienced resource who is free when needed.
attrExpScore	Whether the resource has worked with the same planning attributes \(such as role or skills group\) that the assignment requires.
prjExpScore	Scoring indicating if resource has worked on similar projects before.
adjacentAttrExp	Whether the resource has experience with related planning attributes, but not identical ones. For example, a Developer considered for a Senior Developer assignment.
generalExp	The resource's overall organizational tenure and breadth of work history.

Edit the allocation of the existing attributes to match with your organization requirements.
Verify that the five values add up to 1.0, indicating 100%.
Select Submit.

Result

The AI Resource Finder uses the custom weights for subsequent fit score calculations. Resources are re-ranked according to the new weight distribution the next time a user opens the Resource Finder modal.

Parent Topic:Configure Resource Management Workspace