Expert matching through workload intelligence

Client Ref. No.: 2111933WO P+S Ref. No.: INTU/0437PC Aspects of the present disclosure provide techniques for expert matching though workload intelligence. Embodiments include receiving a request for a support engagement. Embodiments include receiving workload data of a plurality of experts. Embodim...

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Bibliographic Details
Main Authors BROWN, Steven James, YUCHEN, Neo, Nguyen, Quang, LI, Yunqi, BEERAM, Divya
Format Patent
LanguageEnglish
Published 07.07.2022
Subjects
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Summary:Client Ref. No.: 2111933WO P+S Ref. No.: INTU/0437PC Aspects of the present disclosure provide techniques for expert matching though workload intelligence. Embodiments include receiving a request for a support engagement. Embodiments include receiving workload data of a plurality of experts. Embodiments include 5 determining a workload capacity of each respective expert based on the respective workload data for the respective expert. Embodiments include determining a respective estimated completion time for the support engagement for each of the plurality of experts using a machine learning model. Embodiments include determining match scores for the support engagement and each of the plurality of experts based on the estimated completion times and the workload 10 capacities. Embodiments include selecting a given expert of the plurality of experts to handle the support engagement based on the match scores.
Bibliography:Application Number: AU20210390061