Project failure reduction through generation, structuring, and/or assessment of a critical event objectt

Abstract

Disclosed is a method, a device, and/or a system of project failure reduction through generation, structuring, and/or assessment of a critical event object. In one embodiment, a device for reducing project failure includes a processor, a session initiation routine, an object generation engine, an object initiation routine, a categorization subroutine, and a risk assessment routine. The session initiation routine initiates a session including a session UID, provisions computing resources, and associates a user profile with the session UID. The object generation engine receives a critical event criterion data. The object initiation routine generates a critical event object including the critical event criterion data and a unique identifier, and stores the critical event object in an evaluation queue. The categorization subroutine associates a category value with the critical event object, and the risk assessment routine includes generates and/or receives a risk value to be associated with the critical event object.

1 . A system for building a failure evaluation data structure, the system comprising:
 an orchestration server, comprising:
 a processor of the orchestration server; 
 a memory of the orchestration server; 
 a session initiation routine comprising computer readable instructions that when executed on the processor of the orchestration server:
 initiate a session comprising generating a session UID and provisioning computing resources comprising a computing memory and a processing power, and 
 associate a unique identifier of a first user profile with the session UID, 
 
 an object generation engine comprising computer readable instructions that when executed on the processor of the orchestration server:
 receive a failure criterion data comprising an alphanumeric string specifying a failure event; 
 
 an object initiation routine comprising computer readable instructions that when executed on the processor of the orchestration server:
 generate a failure event object in the computing memory comprising the failure criterion data, and 
 store the failure event object in an evaluation queue; 
 
 a categorization subroutine comprising computer readable instructions that when executed on the processor of the orchestration server:
 associate a category value with the failure event object; 
 
 a risk assessment routine comprising computer readable instructions that when executed on the processor of the orchestration server:
 at least one of generate and receive a risk value, and 
 store the risk value in association with the failure event object; 
 
 a user assignment routine comprising computer readable instructions that when executed on the processor of the orchestration server:
 associate the first user profile with the failure event object to assign responsibility to a first user of the first user profile for preventing the failure event; and 
 
   a network communicatively coupled to the orchestration server.   
     
     
         2 . The system of  claim 1 ,
 wherein the orchestration server further comprising:
 a dependency routine comprising computer readable instructions that when executed on the processor of the orchestration server store in a referential attribute of the failure event object a unique identifier of a second failure event object to define a failure dependency of a failure dependency hierarchy; and 
   wherein the system further comprising an object server comprising:
 a processor of the object server; 
 a memory of the object server; 
 a critical hierarchy generation engine comprising computer readable instructions that when executed on the processor of the orchestration server:
 query the session UID as a root of the failure dependency hierarchy, 
 
   determine a set of failure event objects at least one of directly and indirectly connected to the root through one or more failure dependency references of a data structure, and   assemble a failure dependency hierarchy data in the computer memory.   
     
     
         3 . The system of  claim 2 ,
 wherein the risk assessment routine further comprising computer readable instructions that when executed:
 store at least one of a probability data, an impact data, and the risk value in association with the failure event object; and 
   wherein the orchestration server further comprising a hierarchy analysis routine comprising computer readable instructions that when executed on the processor of the object server:
 determine that each of a subset of the set of failure event objects within the failure dependency hierarchy data comprise a data value in common; and 
 return to a client device associated with a second user profile registered with administrative privilege with respect to the session a set of session unique identifiers of the subset of the set of failure event objects. 
   
     
     
         4 . The system of  claim 3 , wherein the data value in common comprising at least one of: (i) the unique identifier of the first user profile of the first user; (ii) a word of the alphanumeric string; (iii) the risk value; (iv) a failure averted value; (v) an event status value; and (vi) the unique identifier of the second failure event object specified in the referential attribute. 
     
     
         5 . The system of  claim 1 , wherein at least one of the orchestration server and the object server further comprising:
 a critical event log routine comprising computer readable instructions that when executed on the processor of the orchestration server:
 store a failure averted value in an occurrence status attribute of the failure event object, 
 generate a critical event log, and 
 designate the critical event log for reporting to at least one of the first user profile and a second user profile registered with administrative privilege with respect to the session. 
   
     
     
         6 . The system of  claim 5 , wherein at least one of the orchestration server and the object server further comprising:
 a factor retrieval routine comprising computer readable instructions that when executed on the processor of the orchestration server:
 receive the probability data, 
 receive the impact data, query a probability data source,
 wherein the probability data source comprising a first database comprising a first plurality of failure event objects from a plurality of sessions associated with one or more accounts, 
 
 receive the probability data, 
 query an impact data source,
 wherein the impact data source comprising a second database comprising failure event objects from the plurality of sessions associated with one or more accounts, and 
 
 receive the impact data. 
   
     
     
         7 . The system of  claim 6 , wherein the orchestration server further comprising:
 a session spawning subroutine comprising computer readable instructions that when executed:
 generate a new session based on the failure event object, 
 determine that the first user profile is associated with the failure event object, and 
 generate a call to register the first user profile associated with the failure event object with administrative privileges with respect to the new session. 
   
     
     
         8 . The system of  claim 7 , further comprising:
 a machine learning server comprising:   a processor of the machine learning server,   a memory of the machine learning server,   a first risk model engine comprising computer readable instructions that when executed on the processor of the machine learning server:
 input values of at least two data attributes of each of a second plurality of failure event objects into a first machine learning algorithm as independent variables of the first machine learning algorithm, 
 input a value of an occurrence status of each of the second plurality of failure event objects into the first machine learning algorithm as a first dependent variable of the first machine learning algorithm, and 
 generate a first predictive model outputting a second risk value based on inputting of the at least two data attributes of the second plurality of failure event objects; 
   a second risk model engine comprising computer readable instructions that when executed on the processor of the machine learning server:
 input values of at least two data attributes of a plurality of session files into a second machine learning algorithm as independent variables of the second machine learning algorithm, 
 input a session status value of each of the plurality of session files into the second machine learning algorithm as a second dependent variable of the second machine learning algorithm, and 
 generate a second predictive model outputting at least one of a probability for success and a probability for failure of the session based on inputting the values of at least the at least two data attributes of the plurality of session files; 
   a critical criteria recommendation engine comprising computer readable instructions that when executed on the processor of the machine learning server:
 parse the failure criterion data to result in one or more words of the alphanumeric string, 
 input one or more of the one or more words into a third predictive model built with a third machine learning algorithm and trained with a set of failure criterion data extracted from each of a third plurality of failure event objects across two or more sessions, 
 output a second failure criterion data most likely to be associated with the failure criterion data across the two or more sessions to increase a likelihood for consideration of critical events related to the session, and 
 generate the failure event object from the second failure criterion data and add the failure event object to the evaluation queue. 
   
     
     
         9 . The system of  claim 8 , wherein at least one of the orchestration server and the object server further comprising:
 an authentication system comprising computer readable instructions that when executed on the processor of the orchestration server:
 authenticate at least one of the first user and a device of the first user; 
   a timer subroutine comprising computer readable instructions that when executed on the processor of the orchestration server:
 initiate a timer for receipt of the failure criterion data, and 
 determine expiration of the timer; 
   a realtime communication module comprising computer readable instructions that when executed on the processor of the orchestration server:
 initiate a realtime communication channel; 
   a grouping subroutine comprising computer readable instructions that when executed on the processor of the orchestration server:
 associate a first failure event object with a different failure event object through a grouping reference; 
   an object sorting subroutine comprising computer readable instructions that when executed on the processor of the orchestration server:
 sort a fourth plurality of failure event objects based on a risk value of each failure event object within the fourth plurality of failure event objects,
 wherein the probability data and the impact data are received from the first user; 
 
   a factor adjustment subroutine comprising computer readable instructions that when executed on the processor of the orchestration server:
 generate an adjusted probability data that is at least one of an averaged probability data and a weighted probability data generated from a first probability data and a second probability data, and 
 generate at least one of an adjusted impact data that is at least one of an averaged impact data and a weighted impact data from a first impact data and a second impact data,
 wherein the first probability data and the first impact data are received from the first user and the second probability data and the second impact data are received from a second user, 
 wherein the weighted impact data based on a first weight factor associated with the first user profile of the first user and further based on a second weight factor associated with the second user profile of the second user, and 
 
 generate the risk value by inputting at least one of the adjusted probability data and the adjusted impact data into a risk assessment function; and 
   a project object creation module comprising computer readable instructions that when executed on the processor of the orchestration server:
 generate a project data object from the failure event object. 
   
     
     
         10 . The system of  claim 9 , wherein at least one of the orchestration server and the object server further comprising:
 a templating module comprising computer readable instructions that when executed:
 select a template data for the session, the template data comprising one or more category values, 
 determine one or more failure criterion data associated with the template data, 
 generate one or more new failure event objects from the one or more failure criterion data associated with the template data, and 
 add the one or more new failure event objects to the evaluation queue; 
   an auxiliary session data routine comprising computer readable instructions that when executed on the processor of the orchestration server:
 determine a third failure event object is associated with a project failure of an account profile, 
 extract a failure criterion data of the third failure event object and optionally a probability data of the third failure event object, an impact data of the third failure event object, and a risk value of the third failure event object, 
 generate a fourth failure event object comprising the failure criterion data of the third failure event object and associate the fourth failure event object with the session, and 
 add the fourth failure event object to the evaluation queue; 
   a risk threshold routine comprising computer readable instructions that when executed on the processor of the orchestration server:
 determine a subset of a fifth plurality the failure event objects that are above of a risk threshold value calculated by a risk threshold function; 
   a visualization module comprising computer readable instructions that when executed on the processor of the orchestration server:
 generate a visualization of one or more UI elements each representing one or more failure event objects relative to the risk threshold value; 
   a report subroutine comprising computer readable instructions that when executed on the processor of the orchestration server:
 generate a report comprising a name of the first user profile and one or more failure event objects assigned to the first user profile; 
   an event evaluation engine comprising computer readable instructions that when executed on the processor of the orchestration server:
 store at least one of a failure condition data specifying a failure condition and a failure detection script that when executed on a computer processor evaluates an input to the failure detection script to determine the failure condition as an output of the failure detection script, and 
 determine occurrence of the failure condition; 
   a set of computer readable instructions that when executed on the processor of the orchestration server:
 store a session file comprising the session UID and unique identifiers of a sixth plurality of failure event objects, 
 restore the session from the session file, 
 re-initiate the realtime communication channel, 
 update an attribute of the failure event object, 
 re-generate the risk value of the failure event object, and 
 re-evaluate the subset of the sixth plurality of the failure event objects above the risk threshold value of the risk threshold function; 
   a status tracking engine comprising computer readable instructions that when executed on the processor of the orchestration server:
 store an object check condition of the failure event object, 
 generate a status check request of the failure event object upon occurrence of the object check condition, and 
 store a status check value received from a client device associated with a user profile associated with the failure event object; and 
   the user assignment routine further comprising computer readable instructions that when executed on the processor of the orchestration server:
 receive a selection of the unique identifier of the first user profile, and 
 overwrite the unique identifier of the first user profile of the first user assigned responsibility for preventing the failure event with a second unique identifier of the second user profile of a second user newly assigned responsibility for preventing the failure. 
   
     
     
         11 . A device for reducing project failure, the device comprising:
 a processor;   a memory;   a session initiation routine comprising computer readable instructions that when executed on the processor:
 initiate a session comprising generating a session UID and provisioning computing resources comprising a computing memory and a processing power, and 
 generate a user addition request to associate a unique identifier of a first user profile with the session UID; 
   an object generation engine comprising computer readable instructions that when executed on the processor:
 receive a critical event criterion data comprising an alphanumeric string specifying a critical event; 
   an object initiation routine comprising computer readable instructions that when executed on the processor:
 generate a critical event object in the computing memory comprising the critical event criterion data and a unique identifier of the critical event object, and 
 store the critical event object in an evaluation queue; 
   a categorization subroutine comprising computer readable instructions that when executed on the processor:
 associate a category value with the critical event object; and 
   a risk assessment routine comprising computer readable instructions that when executed on the processor:
 at least one of generate and receive a risk value, and 
 store the risk value in association with the critical event object. 
   
     
     
         12 . The device of  claim 11 , further comprising:
 a dependency routine comprising computer readable instructions that when executed on the processor:
 store in a referential attribute of the critical event object a unique identifier of a second critical event object to define a critical event dependency of a critical event hierarchy, 
   a critical hierarchy generation engine comprising computer readable instructions that when executed on the processor:
 query the session UID as a root of the critical event hierarchy, 
 determine a set of critical event objects at least one of directly and indirectly connected to the root through one or more critical event dependency references of a data structure, and 
 assemble a critical event hierarchy data in the computer memory, 
   a hierarchy analysis routine comprising computer readable instructions that when executed on the processor:
 determine that each of a subset of the set of critical event objects within the critical event hierarchy data comprise a data value in common, and 
 returns to a client device associated with a second user profile registered with an administrative privilege with respect to the session a set of session unique identifiers of the subset of the set of critical event objects. 
   
     
     
         13 . The device of  claim 12 , wherein the data value in common comprising at least one of: (i) the unique identifier of the first user profile of a first user; (ii) a word of the alphanumeric string; (iii) the risk value; (iv) an occurrence value; (v) an event status value; and (vi) the unique identifier of the second critical event object specified in the referential attribute. 
     
     
         14 . The device of  claim 13 , further comprising:
 a user assignment routine comprising computer readable instructions that when executed on the processor:
 receive a selection of the unique identifier of the first user profile, and 
 associate the unique identifier of the first user profile with the unique identifier of the critical event object to assign responsibility to the first user of the first user profile for preventing the critical event; 
   a factor retrieval routine comprising computer readable instructions that when executed on the processor:
 receive a probability data, and 
 receive an impact data,
 wherein the risk value is generated by inputting the probability data and the impact data into a risk assessment function. 
 
   
     
     
         15 . The device of  claim 14 , further comprising:
 a critical event log routine comprising computer readable instructions that when executed on the processor:
 store an occurrence value in an occurrence status attribute of the critical event object, 
 generate a critical event log, and 
 designate the critical event log for reporting to at least one of the first user profile and the second user profile registered with the administrative privilege with respect to the session; 
   the factor retrieval routine further comprising computer readable instructions that when executed on the processor:
 query a probability data source,
 wherein the probability data source comprising a first database comprising a first plurality of critical event objects from a plurality of sessions associated with one or more accounts, 
 
 receive the probability data, 
 query an impact data source,
 wherein the impact data source comprising a second database comprising critical event objects from the plurality of sessions associated with one or more accounts, and 
 
 receives the impact data; 
   a first risk model engine comprising computer readable instructions that when executed on the processor:
 input values of at least two data attributes of each of a second plurality of critical event objects into a first machine learning algorithm as independent variables of the first machine learning algorithm, 
 input a value of an occurrence status of each of the second plurality of critical event objects into the first machine learning algorithm as a first dependent variable of the first machine learning algorithm, and 
 generate a first predictive model outputting a second risk value based on inputting of the at least two data attributes of the second plurality of critical event objects; 
   a second a second risk model engine comprising computer readable instructions that when executed on the processor:
 input values of at least two data attributes of a plurality of session files into a second machine learning algorithm as independent variables of the second machine learning algorithm, 
 input a session status value of each of the plurality of session files into the second machine learning algorithm as a second dependent variable of the second machine learning algorithm, and 
 generate a second predictive model outputting at least one of a probability for success and a probability for failure of the session based on inputting the values of at least the at least two data attributes of the plurality of session files; 
   a critical criteria recommendation engine comprising computer readable instructions that when executed on the processor:
 parse the critical event criterion data to result in one or more words of the alphanumeric string, 
 input one or more of the one or more words into a third predictive model built with a third machine learning algorithm and trained with a set of critical event criterion data extracted from each of a third plurality of critical event objects across two or more sessions, 
 output a second critical event criterion data most likely to be associated with the critical event criterion data across the two or more sessions to increase a likelihood for consideration of critical events related to the session, and 
 generate the critical event object from the second critical event criterion data and add the critical event object to the evaluation queue; 
   a project object creation module comprising computer readable instructions that when executed on the processor:
 generate a project data object from the critical event object; and 
   an event evaluation engine comprising computer readable instructions that when executed on the processor:
 store at least one of an event occurrence condition specifying an occurrence condition and an event detection script that when executed on a computer processor evaluates an input to the event detection script to determine the occurrence condition as an output of the event detection script, and 
 determine occurrence of the occurrence condition; 
 store an object check condition of the critical event object, 
 generate a status check request of the critical event object upon occurrence of the object check condition, and 
 store a status check value received from the client device associated with a user profile associated with the critical event object. 
   
     
     
         16 . A method for reducing probability of failure implemented by executing computer readable instructions, the method comprising:
 initiating a session comprising generating a session UID and provisioning computing resources comprising a computing memory and a processing power;   associating a unique identifier of a first user profile with the session UID;   receiving a failure criterion data comprising an alphanumeric string specifying a failure event;   generating a failure event object in the computing memory comprising the failure criterion data;   storing the failure event object in an evaluation queue;   associating a category value with the failure event object;   associating the failure event object with a different failure event object through a grouping reference;   receiving a risk value;   storing the risk value in association with the failure event object; and   associating the first user profile with the failure event object to assign responsibility to a first user of the first user profile for preventing the failure event.   
     
     
         17 . The method of  claim 16 , further comprising:
 storing in a referential attribute of the failure event object a unique identifier of a second failure event object to define a failure dependency of a failure dependency hierarchy;   querying the session UID as a root of the failure dependency hierarchy;   determining a set of failure event objects at least one of directly and indirectly connected to the root through one or more failure dependency references of a data structure;   assembling a failure dependency hierarchy data in the computer memory;   storing at least one of a probability data, an impact data, and the risk value in association with the failure event object;   determining that each of a subset of the set of failure event objects within the failure dependency hierarchy data comprise a data value in common; and   returning to a client device associated with a second user profile registered with administrative privilege with respect to the session a set of session unique identifiers of the subset of the set of failure event objects,
 wherein the data value in common comprising at least one of: (i) the unique identifier of the first user profile of the first user; (ii) a word of the alphanumeric string; (iii) the risk value; (iv) a failure averted value; (v) an event status value; and (vi) the unique identifier of the second failure event object specified in the referential attribute. 
   
     
     
         18 . The method of  claim 17 , further comprising:
 storing a failure averted value in an occurrence status attribute of the failure event object;   generating a critical event log;   designating the critical event log for reporting to at least one of the first user profile and a second user profile registered with administrative privilege with respect to the session;   receiving the probability data;   receiving the impact data;   querying a probability data source,
 wherein the probability data source comprising a first database comprising a first plurality of failure event objects from a plurality of sessions associated with one or more accounts; 
   receiving the probability data;   querying an impact data source,
 wherein the impact data source comprising a second database comprising failure event objects from the plurality of sessions associated with one or more accounts; and 
   receiving the impact data.   
     
     
         19 . The method of  claim 18 , further comprising:
 generating a new session based on the failure event object;   determining that the first user profile is associated with the failure event object;   generating a call to register the first user profile associated with the failure event object with administrative privileges with respect to the new session;   inputting values of at least two data attributes of each of a second plurality of failure event objects into a first machine learning algorithm as independent variables of the first machine learning algorithm;   inputting a value of an occurrence status of each of the second plurality of failure event objects into the first machine learning algorithm as a first dependent variable of the first machine learning algorithm;   generating a first predictive model outputting a second risk value based on inputting of the at least two data attributes of the second plurality of failure event objects;   inputting values of at least two data attributes of a plurality of session files into a second machine learning algorithm as independent variables of the second machine learning algorithm;   inputting a session status value of each of the plurality of session files into the second machine learning algorithm as a second dependent variable of the second machine learning algorithm; and   generating a second predictive model outputting at least one of a probability for success and a probability for failure of the session based on inputting the values of at least the at least two data attributes of the plurality of session files;   parsing the failure criterion data to result in one or more words of the alphanumeric string;   inputting one or more of the one or more words into a third predictive model built with a third machine learning algorithm and trained with a set of failure criterion data extracted from each of a third plurality of failure event objects across two or more sessions;   outputting a second failure criterion data most likely to be associated with the failure criterion data across the two or more sessions to increase a likelihood for consideration of critical events related to the session; and   generating the failure event object from the second failure criterion data and add the failure event object to the evaluation queue.   
     
     
         20 . The method of  claim 19 , further comprising:
 authenticating at least one of the first user and a device of the first user;   determining expiration of the timer;   initiating a realtime communication channel;   sorting a fourth plurality of failure event objects based on a risk value of each failure event object within the fourth plurality of failure event objects,
 wherein the probability data and the impact data are received from the first user; 
   generating an adjusted probability data that is at least one of an averaged probability data and a weighted probability data generated from a first probability data and a second probability data;   generating at least one of an adjusted impact data that is at least one of an averaged impact data and a weighted impact data from a first impact data and a second impact data,
 wherein the first probability data and the first impact data from the first user and the second probability data and the second impact data received from a second user, and 
 wherein the weighted impact data based on a first weight factor associated with the first user profile of the first user and a further based on a second weight factor associated with the second user profile of the second user; and 
   generating the risk value by inputting at least one of the adjusted probability data and the adjusted impact data into a risk assessment function;   generating a project data object from the failure event object;   determining one or more failure criterion data associated with the template data;   generating one or more new failure event objects from the one or more failure criterion data associated with the template data; and   adding the one or more new failure event objects to the evaluation queue.