Task management platform

Abstract

A device may receive, from a user device, a request for a recommendation identifying one or more tasks to be performed, of a set of tasks that are part of a job for an organization and associated with managing a set of applications for a product or a service. The device may generate the recommendation by using a data model that has been trained using one or more machine learning techniques to process data identifying a set of application status metrics based on application status data for the set of applications, and events data identifying real-time events associated with the group of sites. The device may provide the recommendation for display on an interface of the user device. The device may perform one or more actions associated with assisting in performance of at least one of the one or more tasks.

What is claimed is: 
     
         1 . A method, comprising:
 receiving, by a device and from a user device, a request for a recommendation identifying one or more tasks to be performed, of a set of tasks that are part of a job for an organization;   generating, by the device and by processing data associated with the set of tasks, data identifying a set of task status metrics for a group of sites associated with performance of the set of tasks;   obtaining, by the device, events data identifying real-time events associated with the group of sites,
 wherein the events data includes user workload data identifying a workload capacity for the group of sites; 
   providing, by the device, the data identifying the set of task status metrics and the events data as input to a data model to cause the data model to output a set of priority values for the set of tasks,
 wherein the data model has been trained using one or more machine learning techniques, and 
 wherein the set of priority values are based on a likelihood of the events data delaying particular tasks from being performed; 
   generating, by the device, the recommendation based on the set of priority values; and   performing, by the device, one or more actions associated with assisting in performance of at least one of the one or more tasks.   
     
     
         2 . The method of  claim 1 , wherein the at least one of one or more tasks includes sending a communication to another user or another device associated with one of the group of sites; and
 wherein the recommendation includes a recommendation to schedule the sending of the communication at a particular time.   
     
     
         3 . The method of  claim 1 , wherein the one or more actions includes an action to transfer the at least one of the one of more tasks. 
     
     
         4 . The method of  claim 1 , wherein performing the one or more actions comprises:
 providing, for display on an interface associated with the user device, data identifying the recommendation.   
     
     
         5 . The method of  claim 1 , further comprising:
 providing the user device with a prompt for feedback regarding the recommendation;   receiving, from the user device and based on the prompt, feedback data regarding the recommendation; and   retraining the data model based on the feedback data.   
     
     
         6 . The method of  claim 1 , further comprising:
 periodically updating the set of priority values; and   generating updated recommendations based on the periodic updating of the set of priority values.   
     
     
         7 . The method of  claim 6 , wherein generating an updated recommendation, of the updated recommendations, includes at least one of:
 reordering a subset of the one or more tasks, or   adding a new task to the one or more tasks.   
     
     
         8 . A device, comprising:
 one or more memories; and   one or more processors, communicatively coupled to the one or more memories, configured to:
 receive, from a user device, a request for a recommendation identifying one or more tasks to be performed, of a set of tasks that are part of a job for an organization; 
 generate, by processing data associated with the set of tasks, data identifying a set of task status metrics for a group of sites associated with performance of the set of tasks; 
 obtain events data identifying real-time events associated with the group of sites,
 wherein the events data includes user workload data identifying a workload capacity for the group of sites; 
 
 provide the data identifying the set of task status metrics and the events data as input to a data model to cause the data model to output a set of priority values for the set of tasks,
 wherein the data model has been trained using one or more machine learning techniques, and 
 wherein the set of priority values are based on a likelihood of the events data delaying particular tasks from being performed; 
 
 generate the recommendation based on the set of priority values; and 
 perform one or more actions associated with assisting in performance of at least one of the one or more tasks. 
   
     
     
         9 . The device of  claim 8 , wherein the at least one of one or more tasks includes sending a communication to another user or another device associated with one of the group of sites; and
 wherein the recommendation includes a recommendation to schedule the sending of the communication at a particular time.   
     
     
         10 . The device of  claim 8 , wherein the one or more actions includes an action to transfer the at least one of the one of more tasks. 
     
     
         11 . The device of  claim 8 , wherein the one or more processors, when performing the one or more actions, are configured to:
 provide, for display on an interface associated with the user device, data identifying the recommendation.   
     
     
         12 . The device of  claim 8 , wherein the one or more processors are further configured to:
 provide the user device with a prompt for feedback regarding the recommendation;   receive, from the user device and based on the prompt, feedback data regarding the recommendation; and   retrain the data model based on the feedback data.   
     
     
         13 . The device of  claim 8 , wherein the one or more processors are further configured to:
 periodically update the set of priority values; and   generate updated recommendations based on the periodic updating of the set of priority values.   
     
     
         14 . The device of  claim 13 , wherein the one or more processors, when generating an updated recommendation, of the updated recommendations, are configured to:
 reorder a subset of the one or more tasks, or   add a new task to the one or more tasks.   
     
     
         15 . A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:
 one or more instructions that, when executed by one or more processors of a device, cause the device to:
 receive, from a user device, a request for a recommendation identifying one or more tasks to be performed, of a set of tasks that are part of a job for an organization; 
 generate, by processing data associated with the set of tasks, data identifying a set of task status metrics for a group of sites associated with performance of the set of tasks; 
 obtain events data identifying real-time events associated with the group of sites,
 wherein the events data includes user workload data identifying a workload capacity for the group of sites; 
 
 provide the data identifying the set of task status metrics and the events data as input to a data model to cause the data model to output a set of priority values for the set of tasks,
 wherein the data model has been trained using one or more machine learning techniques, and 
 wherein the set of priority values are based on a likelihood of the events data delaying particular tasks from being performed; 
 
 generate the recommendation based on the set of priority values; and 
 perform one or more actions associated with assisting in performance of at least one of the one or more tasks. 
   
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to send a communication to another user or another device associated with one of the group of sites; and
 wherein the recommendation includes a recommendation to schedule the sending of the communication at a particular time.   
     
     
         17 . The non-transitory computer-readable medium of  claim 15 , wherein the one or more actions includes an action to transfer the at least one of the one of more tasks. 
     
     
         18 . The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions, that cause the device to perform the one or more actions, cause the device to:
 provide, for display on an interface associated with the user device, data identifying the recommendation.   
     
     
         19 . The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to:
 provide the user device with a prompt for feedback regarding the recommendation;   receive, from the user device and based on the prompt, feedback data regarding the recommendation; and   retrain the data model based on the feedback data.   
     
     
         20 . The non-transitory computer-readable medium of  claim 15 , wherein the one or more instructions further cause the device to:
 periodically update the set of priority values; and   generate updated recommendations based on the periodic updating of the set of priority values.