US 11,657,344 B2
Automated scheduling assistant for a workforce management system
Nicholas Duane Martin, McKinney, TX (US); Brent Allen Haferkamp, Garland, TX (US); Oren Gerstner, Plano, TX (US); Chetan Prajapati, Richardson, TX (US); and Juan Claudio Serviere Morales, Allen, TX (US)
Assigned to NICE LTD., Ra'anana (IL)
Filed by NICE LTD., Ra'anana (IL)
Filed on Apr. 8, 2022, as Appl. No. 17/716,798.
Application 17/716,798 is a continuation of application No. 16/400,226, filed on May 1, 2019, granted, now 11,315,050.
Prior Publication US 2022/0230126 A1, Jul. 21, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 10/06 (2023.01); G06Q 10/0631 (2023.01); G06Q 10/1093 (2023.01)
CPC G06Q 10/063116 (2013.01) [G06Q 10/1093 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A workforce management system adapted to perform automated scheduling operations based on one or more scheduling rules and parameters, the workforce management system comprising:
a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform the automated scheduling operations which comprise:
automatically generating a survey comprising queries having at least a first dimension and a second dimension based on the one or more scheduling rules and the parameters;
distributing the survey to one or more users via one or more interfaces of the workforce management system, wherein the distributing comprises:
providing, on a web portal of the workforce management system using web nodes connected to service nodes for computing services of the workforce management system, an availability of the survey via the one or more interfaces, wherein the web nodes comprise a web application and an application programming interface (API) service;
monitoring, via the web nodes, user inputs associated with the queries over a time period;
detecting, via the web nodes based on the monitoring, one or more responses to the survey during the time period, wherein the one or more responses comprise inputs by the one or more users to a gamified version of the survey accessible through the web portal;
analyzing, using a deep learning model of the workforce management system, the one or more responses to the survey;
generating, using executable rule logic of a schedule rules generator based on outputs of the deep learning model from the analyzing, one or more recommendations for the one or more users based on analyzing the one or more responses using the deep learning model, wherein the schedule rules generator comprises an automated computing component of the workforce management system that executes the executable rule logic for generating a schedule of the one or more users;
detecting, from the computing services via the service nodes, one or more feedbacks to the survey;
adjusting, using the deep learning model and based on the one or more feedbacks to the one or more recommendations, one or more of the parameters for the survey;
detecting, via the web nodes based on the monitoring, one or more additional responses to the survey having the adjusted one or more of the parameters; and
applying, using the web nodes, the one or more additional responses to the schedule of the one or more users with the workforce management system; and
after an expiration of the time period, reconfiguring, on the web portal, the survey based on the one or more recommendations, the adjusted one or more of the parameters, and the schedule, wherein the reconfigured survey is further available via the web nodes.