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The U.S. Navy s Rating Identification Engine RIDE 46th IMTA, Brussels October 28, 2004

2. Facilitating Classification With Fleet-RIDE. Fleet-RIDE uses the RIDE (Rating IDentification Engine) processes and technologies for in-service re-classifications. CREO1. IT 12. MA 13. CM 14. SW 1 . 3. Fleet-RIDE Overview. Rating Identification Engine (RIDE): Stage I: Screen for fully qualified available ratingsMental-ASVABMoral/LegalMedical/PhysicalStage II: Rank order for best fitNavy NeedAptitudeInterestStage III: Job SelectionProgram/Ratin31890

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The U.S. Navy s Rating Identification Engine RIDE 46th IMTA, Brussels October 28, 2004

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    2. 2 Facilitating Classification With Fleet-RIDE

    3. 3 Fleet-RIDE Overview Rating Identification Engine (RIDE): Stage I: Screen for fully qualified available ratings Mental-ASVAB Moral/Legal Medical/Physical Stage II: Rank order for best fit Navy Need Aptitude Interest Stage III: Job Selection Program/Rating information Availability Processing/Forms/Submission Accession RIDE targeted for production for use by MEPS and PSD-RTC classifiers for initial classification Provides best match for the recruits based on their qualifications and stated interest to Navy requirements reflected in critical list and other available training seats

    4. 4 Fleet RIDE Overview (cont.) Fleet-RIDE transforms the proven and accepted RIDE processes and technologies for Fleet use in support of Perform to Serve (PTS) Developed with NPRST and EDS; operational deployment scheduled Q1 2005 For use by Fleet Career Counselors, ECMs, Detailers and individual Sailors for reclassification and career guidance Provides best match of Fleet Sailor’s qualifications and interests to meet Navy requirements for rating assignment/conversions Fleet-RIDE in the conversion process (e.g., PTS) will contribute to the balance of Navy Rating skill mix and help to improve: Community Management Career opportunities for Sailors Fleet readiness Conversion process (reduces time and errors) Command CDB/PDBs process Sailor-NC career counseling Fleet-RIDE demo

    5. 5 Fleet-RIDE Early Pilot Test Results Fleet-RIDE Early Pilot Test Decrease in “unqualified” conversion packages Fleet average errors = 30% of all PTS conversion packages Fleet RIDE assisted applications = 0 errors Enabled decrease in transfer time for Submarine School, Groton Reclassification shortened from 6 months to 1 month on average Several enhancements/functionality changes made to Fleet-RIDE interface based on feedback from test sites As a result of our rapid prototyping approach and early and frequent user involvement, both RIDE prototypes have demonstrated early returns on investment and enthusiastic user acceptance. MOEs include lower DEP attrition, higher training pass rates, and quicker Sailor transfer times to their new jobs. The user acceptance has been unsolicited and remarkable: West Coast “I really appreciate this program and my ship appreciates it more. . . especially with the numerous rate mergers and changes being required via PTS and Navy restructuring.  Please, Please, Please never take this program away from us.” NCCS Pollyanna Neely Career Counselor USS BELLEAU WOOD (LHA-3) East Coast “We are using FLEET RIDE and LOVE IT!  I have also demoed it for the command and it has received great praises.  Quoting one of the CPOs, "This is what I have been looking for!” Demetrius J. C. Carter NC1(SW)            USN Career Counselor Naval Submarine School New London As a result of our rapid prototyping approach and early and frequent user involvement, both RIDE prototypes have demonstrated early returns on investment and enthusiastic user acceptance. MOEs include lower DEP attrition, higher training pass rates, and quicker Sailor transfer times to their new jobs. The user acceptance has been unsolicited and remarkable: West Coast “I really appreciate this program and my ship appreciates it more. . . especially with the numerous rate mergers and changes being required via PTS and Navy restructuring.  Please, Please, Please never take this program away from us.” NCCS Pollyanna Neely Career Counselor USS BELLEAU WOOD (LHA-3) East Coast “We are using FLEET RIDE and LOVE IT!  I have also demoed it for the command and it has received great praises.  Quoting one of the CPOs, "This is what I have been looking for!” Demetrius J. C. Carter NC1(SW)            USN Career Counselor Naval Submarine School New London

    6. 6 Early Pilot Test Acceptance West Coast “I really appreciate this program and my ship appreciates it more. . . especially with the numerous rate mergers and changes being required via PTS and Navy restructuring.  Please, Please, Please never take this program away from us.” NCCS Pollyanna Neely Career Counselor USS BELLEAU WOOD (LHA-3) East Coast “We are using FLEET RIDE and LOVE IT!  I have also demoed it for the command and it has received great praises.  Quoting one of the CPOs, "This is what I have been looking for!” Demetrius J. C. Carter NC1(SW)             Career Counselor Naval Submarine School New London

    7. 7 RIDE Ability Model: Efficient Resource Allocation

    8. 8 RIDE

    9. 9 YERKES-DODSON

    10. 10 RIDE Ability Function

    11. 11 As shown in our research to refine and improve the RIDE algorithm, EDS, in partnership with NPRST, ensured the exploration of a new classification algorithm to improve retention (lower attrition). The data on the chart above shows actual First Pass Pipeline Success measured by the RIDE ranking of the job the applicants were classified. Applicants classified to jobs within the top 10 they were ranked by RIDE had over a 91% FPPS, while applicants classified to jobs at the lower end of their RIDE ranking only had an 84% FPPS. In addition, EDS is collaborating with NPRST to enhance Sailor job satisfaction using a pictorial vocational interest instrument call Jobs and Occupational Interests in the Navy (JOIN). In 2004, EDS will be exploring new methods to refine the JOIN interest matching using the Analytical Hierarchy Process (AHP) technique. As shown in our research to refine and improve the RIDE algorithm, EDS, in partnership with NPRST, ensured the exploration of a new classification algorithm to improve retention (lower attrition). The data on the chart above shows actual First Pass Pipeline Success measured by the RIDE ranking of the job the applicants were classified. Applicants classified to jobs within the top 10 they were ranked by RIDE had over a 91% FPPS, while applicants classified to jobs at the lower end of their RIDE ranking only had an 84% FPPS. In addition, EDS is collaborating with NPRST to enhance Sailor job satisfaction using a pictorial vocational interest instrument call Jobs and Occupational Interests in the Navy (JOIN). In 2004, EDS will be exploring new methods to refine the JOIN interest matching using the Analytical Hierarchy Process (AHP) technique.

    12. 12 RIDE Model: Efficient Resource Allocation Considers first pass pipeline success (FPPS) as the training success measure FPPS: pass entire training pipeline, no setbacks Reduces exaggerated “best” test score Developed plateau relationship between training success and cut score, vice simple linear relationship Modified utility score by a factor reflecting the degree of difficulty of a job Penalizes for “over-qualification” of applicant AFQT based for a given program/rating, to minimize resource “wastage” Increases number of ratings applicant “optimally” qualified for Increases number of ratings “tied” for the top of the list Increases opportunity for interest based vocational guidance RIDE Rank is the rank order value of the Rating fit for the individual. Ratings on the “plateau” are the best fit, and have the best (lowest number) RIDE rank. Ratings on the “slope” are either over-qualified or under-qualified and have worse (higher number) RIDE ranks

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