System and Method for Analyzing and Predicting Behavior of an Organization and Personnel

Abstract

A networked computer system permits users to analyze events associated with a target entity, using primarily externally reported data. By analyzing the target entity's personnel, procedures and reports, embodiments of the invention can assess, present and predict outcomes and timings of submissions processed by the target entity/organization.

What is claimed is: 
     
         1 . A method of indirectly analyzing and predicting behavior of a target organization with a computing system, which target organization processes input submissions from third parties using a staff of human personnel in accordance with a first rule set to generate output events, the method comprising:
 causing the computing system to access a publicly accessible database of event records derived from the output events of the target organization, and which event records identify at least an event type and event date associated with processing by the target organization of the submission;   wherein the computing system does not access said event records from databases that are only accessible internally to said target organization through computing systems of such organization;   processing the event records with the computing system to identify a historical event behavior of the target organization, including a timing performance parameter and a resolution parameter associated with the events;   wherein at least one of a Bayesian model and a Hidden Markov Model is generated and maintained based on analyzing a relationship of individual ones of the output events identified in event records for a plurality of input submissions;   generating and reporting on a target prediction of additional events to be generated by the target organization for a first submission based on one or more recent events associated with said first submission and using said Bayesian model and/or Hidden Markov Model.   
     
     
         2 . The method of  claim 1  further including a step: soliciting input from a community of users through an electronic interface presented at an online website with the computing system to identify a community prediction for said additional events. 
     
     
         3 . The method of  claim 1  further including steps:
 processing a first threshold or target criteria received from a user; 
 generating an alert to one or more users with the computing system in response to detecting a change in said target prediction with the computing system exceeding said first threshold or meeting target criteria. 
 
     
     
         4 . The method of  claim 1  wherein the target organization is the United States Patent & Trademark Office. 
     
     
         5 . The method of  claim 4  wherein the events are associated with preissuance or post grant challenge proceeding. 
     
     
         6 . The method of  claim 1 , further including a step: predicting an amount of representative fees required to process said events. 
     
     
         7 . A method of indirectly analyzing and predicting behavior of a human staff personnel of a target organization with a computing system, which target organization processes input submissions from third parties using the staff of human personnel in accordance with a first rule set to generate output events, the method comprising:
 causing the computing system to access a publicly accessible database of event records derived from the output events of the target organization, and which event records identify at least an event type and event date associated with processing by the human staff personnel of the submission;   wherein the computing system does not access said event records from databases that are only accessible internally to said target organization through computing systems of such organization;   processing the event records with the computing system to identify a historical event behavior of the human staff personnel, including a timing performance parameter and a resolution parameter associated with the events;   wherein at least one of a Bayesian model and a Hidden Markov Model is generated and maintained based on analyzing a relationship of individual ones of the output events identified in event records for a plurality of input submissions;   generating and reporting on a prediction of additional events to be generated within a selectable future time window by the human staff personnel for a first submission based on a most recent event associated with said first submission and using said Bayesian model and/or Hidden Markov Model.   
     
     
         8 . The method of  claim 7  further including a step: updating a profile of said human staff personnel based on input by users of the computing system external to said target organization so that said profile includes both objective data identified from said event records and subjective data provided by outside users. 
     
     
         9 . The method of  claim 7  wherein a loading factor associated with a calculated current and/or expected case load experience by the human staff personnel is accounted for in deriving said prediction. 
     
     
         10 . The method of  claim 7  wherein the human staff personnel are with the United States Patent & Trademark Office. 
     
     
         11 . The method of  claim 9  wherein the events are associated with preissuance or post grant challenge proceeding. 
     
     
         12 . A system for indirectly analyzing and predicting behavior of a target organization, which target organization processes input submissions from third parties using a staff of human personnel in accordance with a first rule set to generate output events, the system comprising:
 a computer server computing system operatively connected to a network; a first module configured to cause said computer server computing system to access a publicly accessible database of event records derived from the output events of the target organization, and which event records identify at least an event type and event date associated with processing by the target organization of the submission;   wherein the first module is configured so that it does not access said event records from databases that are only accessible internally by computers within said target organization;   a second module configured to process the event records to identify a historical event behavior of the target organization, including a timing performance parameter and a resolution parameter associated with the events;   wherein at least one of a Bayesian model and a Hidden Markov Model is generated and maintained by said second module based on analyzing a relationship of individual ones of the output events identified in event records for a plurality of input submissions;   a third module configured to generate a target prediction of additional events to be generated by the target organization or personnel thereof for a first submission based on one or more recent events associated with said first submission and using said Bayesian model and/or Hidden Markov Model.   
     
     
         13 . The system of  claim 12  wherein said third module is configured to compute a likelihood percentage of such additional events occurring. 
     
     
         14 . The system of  claim 12  wherein said third module is configured to determine a set of cases pending with a patent Examiner, and generate a prediction of a set of outputs expected for such Examiner in such set of cases in a target time window. 
     
     
         15 . The system of  claim 12  including a fourth module configured to receive a hypothetical challenge submission including content from a target document that has not been filed with the governmental agency for such second pending proceeding; and process said hypothetical challenge submission to compare it to prior challenge submissions; and generate a prediction of an expected treatment of such hypothetical challenge submission by such agency. 
     
     
         16 . The system of  claim 15  further including a module configured to generate a set of recommendations of content changes for said hypothetical challenge submission to increase a likelihood of a preferred post-grant challenge outcome.