Embodiments of the invention are directed to a computer-implemented system and method of performing quality assurance. The method may include receiving, by a processor, a quality plan comprising an expected number of evaluation tasks, wherein each evaluation task is distributed to an evaluator of a plurality of evaluators to be completed. For each evaluator, the processor computes an expected number of evaluation tasks to be completed per period, wherein the expected number of evaluation tasks completed per period is based on the expected number of evaluation tasks averaged over a set time period. The processor receives, for each evaluator, a number of actual evaluation tasks completed during the set time period and reassigns one or more evaluation tasks from the evaluator if the actual evaluation tasks completed during the set time period for said evaluator does not meet a predetermined threshold.

Methods, systems, and computer programs are presented for scheduling user notifications to maximize short-term and long-term benefits from sending the notifications. One method includes an operation for identifying features of a state used for reinforcement learning. The state is associated with an action to decide if a notification to a user is to be sent and a reward for sending the notification to the user. Further, the method includes capturing user responses to notifications sent to users to obtain training data and training a machine-learning (ML) algorithm with reinforcement learning based on the features and the training data to obtain an ML model. Additionally, the method includes receiving a request to send a notification to the user, and deciding, by the ML model, whether to send the notification based on a current state. The notification is sent to the user based on the decision.

A customer who is contacting customer care via a support session regarding a problem is classified into a customer category of multiple customer categories based at least on customer account information of the customer. A customer care topic in a predetermined set of multiple customer care topics that correspond to the problem is then identified via machine learning. A topic script that corresponds to the customer category of the customer for the customer care topic in the predetermined set of customer care topics is further retrieved or generated, in which the topic script includes one or more topic issues related to the customer care topics. The topic script is provided for presentation to a customer service representative (CSR) to prompt the CSR to discuss the one or more topic issues related to the customer care topic with the customer.

Systems and methods for enabling controls at a user computing device for delegating tasks include providing information to an intermediary regarding the likelihood that a user associated with the user computing device will delegate a particular task. The intermediary may then selectively activate a delegation control at the user computing device that, when activated, results in delegation of the task for completion by a task facilitation service.

Systems and methods for predicting the likelihood that a member of a task facilitation service will delegate a given task for completion by the task facilitation service include providing data to a delegation likelihood model. The data may include, among other things, data collected about the member and past tasks of the member including whether the member delegated those tasks. The data may further include data for other members and tasks other than those associated with the task being analyzed. The task facilitation service may transmit an indication regarding the likelihood of delegation to an intermediary who may then decide whether to enable a delegation control for the task at a user interface of the member.

Techniques described herein relate to computer-implemented systems and methods for generating an insurance business plan. The method includes receiving an identification of an agent associated with the insurance business plan and a selection of a future time period for the insurance business plan. A business plan objective graphical user interface (GUI) is displayed, presenting for selection a plurality of insurance business plan objectives, wherein one of the objectives is to grow or maintain insurance policy counts for one or more insurance lines of business. The business plan objective GUI receives a selection of the objective to grow or maintain insurance policy counts for one or more lines of business. Based on a determination that the objective to grow or maintain insurance policy counts for one or more lines of business has been selected, a plurality of insurance lines of business is displayed. The business plan objective GUI receives a selection of an insurance line of business of the plurality of insurance lines of business. Insurance policy information for insurance policies assigned to the agent in the selected line of business is retrieved from an insurance policy database over a network. Additionally, displayed is a goal setting GUI for the selected line of business, the goal setting GUI being populated based on the retrieved insurance policy information and including a policy count chart showing a number of insurance policies assigned to the agent having a selected status, among a plurality of statuses, during a historical period of time through the present and showing a number of polices projected to have the selected status during the selected future time period of the business plan.

An apparatus, method and computer program is described comprising: receiving interaction information via at least one user device, wherein the interaction information is related to at least one user using at least one user device in relation to a first content creation task; receiving sensor data relating to the at least one user from one or more sensors; and determining data, using a first model, the data comprising content creation performance data and user state data, wherein: the content creation performance data indicates performance of the at least one user in relation to the first content creation task, based, at least in part, on the interaction information and a first content created when the at least one user performs the first content creation task; and the user state data is based, at least in part, on the received sensor data in relation to the first content creation task.

Methods, apparatuses, and systems for scheduling tasks to field professionals include: storing, in a database, a plurality of records reflecting characteristics associated with completing a set of technical services, wherein information in each record is derived from historical experience of completing each of the technical services; receiving a request for a new technical service associated with a location; and assigning a field professional to perform the new service having determined from information in the database a likelihood that the field professional will complete the new technical service in a single on-site visit at the location.

A liquid product distribution network includes a liquid product distribution monitoring and reporting apparatus for operation in association with a tap handle flow monitoring and reporting apparatus. The liquid product distribution monitoring and reporting apparatus includes a radio transmitter device and sensing circuitry for sensing and communicating physical properties associating with the keg. A tap handle flow monitoring and reporting apparatus senses flow of a liquid through a tap includes a tap handle radio transmitter device for fitting within and protected by a tap handle and a low-energy consumption tap handle radio/processing module. A mobile communications device with geographic position sensing device and/or said tap handle flow monitoring and reporting apparatus passively and without user interaction within the liquid product distribution network, without using network uplink/gateway circuit devices for sensing and reporting fluid storage, flow, and financial operations relating to the distribution of said liquid product throughout the liquid product distribution network.

Regardless of the production method applied, it is possible for a user to estimate a factor that causes trouble in one of the resources belonging to a resource type. A supporting system refers to management information indicating a production past record of the production system, and displays an overlay chart in which a diagram chart is relatively superimposed on a Gantt chart. The Gantt chart is a chart for a first resource type and has a resource axis and a time axis. The diagram chart is for a second resource type. In the overlay chart, a polygonal line connecting a plurality of points corresponding to a second resource, belonging to the second resource type, is on the Gantt chart, and each point is plotted at a position corresponding to an execution time of a step and a first resource, belonging to the first resource type, related to the step.