DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-51 have been reviewed and are under consideration by this office action.
Notice to Applicant
The following is a Final Office action. Applicant, on 02/10/2026, amended claims. Claims 1-51 are pending in this application and have been rejected below.
Response to Amendment
Applicant’s amendments are received and acknowledged.
The amended claims overcome the 102 Rejections; however a new 103 Rejection is facilitated by the new amendments. The need for 112(f) Interpretation is overcome by the amended claims.
Response to Arguments - 35 USC § 101
Applicant’s arguments with respect to the 35 USC 101 rejections have been fully considered, but they are not persuasive.
Applicant contends that the claims require a comprise memory storing instruction and implement specialized modules and as such do not recite an abstract idea.
Examiner respectfully disagrees. The additional elements are identified and separated from the abstract idea. The abstract idea of assessing a project readiness of a project based on plurality of data sources, utilizing project cost data and various other data, receive project cost data, receive and process control data, and generating a project score all of which are concepts capable of being performed in the human mind (i.e. via pen and paper) and further directed towards certain methods of organizing human activity.
Applicant contends that the abstract idea is integrated into a practical application as they require specific technical analyses and are not mere computer components.
Examiner respectfully disagrees. The additional elements are each identified and determined to be performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) and as such do not integrate the abstract idea into a practical application.
Applicant contends that the claims amount to significantly more and not well-understood, routine, or conventional activities.
Examiner respectfully disagrees. The additional elements are each identified and determined to be performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) in Step 2B. Further the Examiner notes the claims are not identified as WURC activities.
The 101 Rejection is updated and maintained below.
Response to Arguments - 35 USC § 103
Applicant’s arguments with respect to the 35 USC 103 rejections have been fully considered, but are moot in view of the 103 Rejections below.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-51 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step One - First, pursuant to step 1 in the January 2019 Guidance on 84 Fed. Reg. 53, the claim(s) is/are directed to statutory categories.
Step 2A, Prong One – The claims are found to recite limitations that set forth the abstract idea(s), namely in independent claims recite a series of steps for the abstract idea recited below.
Regarding independent claims, (additional elements bolded)
Regarding Claim(s) 1. A computer-implemented system for assessing a project, comprising a memory for storing computer executable instructions, and a processor configured to execute the computer executable instructions stored in the memory to implement:
a project readiness assessment module for assessing a project readiness of a project based on source data from a plurality of data sources and for generating a project assessment score,
wherein the source data includes project data and wherein the project data includes project cost data including project cost estimate data, project scope data, project risk data, and project control data,
a project diagnostic and cost assessment module for receiving the project cost data including the project cost estimate data and for applying a cost accuracy determination process to determine an accuracy of a cost associated with the project based on the project cost data and the project cost estimate data and for generating a project cost accuracy score,
a project schedule assessment module for applying one or more predetermined schedule analysis and assessment techniques selected from critical path analysis, float time analysis, and baseline execution analysis to project schedule data to assess a quality and an accuracy of a project schedule and for generating a project schedule score,
a project risk assessment module for processing the project risk data using a risk categorization process and for determining an inherent risk score associated with the project,
a project control assessment module for receiving and processing the project control data and for generating a project control score,
wherein the project readiness assessment module, project diagnostic and cost assessment module, project schedule assessment module, project risk assessment module, and project control assessment module operate in coordination to generate integrated project assessment data, and
a reporting module that can includes a user interface generator for generating one or more user interfaces for displaying on a display device one or more reports based on the integrated project assessment data..
Regarding Claim(s) 30. A computer-implemented method for assessing a project, comprising assessing a project readiness using computer-executable instructions stored in a non- transient memory and executed by a processor implementing a project readiness assessment, the project readiness based on source data from a plurality of data sources and for generating a project assessment score, wherein the source data includes project data and wherein the project data includes project cost data including project cost estimate data, project scope data, project risk data, and project control data,
determining an accuracy of a cost associated with the project using computer-executable instructions stored in the memory and executed by the processor implementing a project diagnostic and cost assessment module, the accuracy of the cost based on the project cost data and the project cost estimate data and generating in response a project cost accuracy score,
applying one or more schedule analysis and assessment techniques selected from critical path analysis, float time analysis, and baseline execution analysis to the project schedule data using computer-executable instructions stored in the memory and executed by the processor implementing with a project schedule assessment module for assessing a quality of a project schedule and an accuracy of the project schedule and for generating a project schedule score,
determining an inherent risk score associated with the project using computer-executable instructions stored in the memory and executed by the processor implementing a project risk assessment module based on the project risk data,
assessing one or more project controls associated with the project using computer-executable instructions stored in the memory and executed by the processor implementing a project control assessment module based on project control data and in response generating a project control score,
wherein the project readiness assessment module, project diagnostic and cost assessment module, project schedule assessment module, project risk assessment module, and project control assessment module operate in coordination to generate integrated project assessment data, and
displaying on a display device one or more reports based on the integrated project assessment data using computer-executable instructions stored in the memory and executed by the processor implementing a reporting module including a user interface generator for generating a user interface.
As drafted, this is, under its broadest reasonable interpretation, within the Abstract idea groupings of “Mental processes—concepts performed in the human mind” (observation, evaluation, judgment, opinion) as the claims are directed towards assessing a project readiness of a project based on plurality of data sources, utilizing project cost data and various other data, receive project cost data, receive and process control data, and generating a project score all of which are concepts capable of being performed in the human mind (i.e. via pen and paper).
Further the claims are directed towards the abstract idea grouping of “Certain methods of organizing human activity” — commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) and/or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as the claims are directed towards evaluating a project at any point in the project lifecycle (See Specification, [P.2, PARA. 2].
Step 2A, Prong Two - This judicial exception is not integrated into a practical application. The independent claims utilize at least the additional elements bolded above. The additional elements are performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h).
Step 2B - The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are just “apply it” on a computer. (See MPEP 2106.05(f) – Mere Instructions to Apply an Exception – “Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” Alice Corp., 134 S. Ct. at 235) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h).
Regarding Claim(s) 3-9, 11-18, 20-23, 25-26, 28-29, and 31-51 the claim further narrows the abstract idea or recite additional elements previously addressed (i.e. processors, modules.)in the independent claims.
Regarding Claim(s) 2, the claim further recite the additional element(s) of a categorization module and a project readiness scoring module. This element(s) is performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) in Steps 2A-Prong 2 and 2B.
Regarding Claim(s) 10, the claim further recite the additional element(s) of a cost classification module and project cost accuracy determination module . This element(s) is performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) in Steps 2A-Prong 2 and 2B.
Regarding Claim(s) 19, the claim further recite the additional element(s) of a project schedule assessment module and a project schedule scoring module. This element(s) is performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) in Steps 2A-Prong 2 and 2B.
Regarding Claim(s) 24, the claim further recite the additional element(s) of a risk categorization module and a risk scoring module. This element(s) is performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) in Steps 2A-Prong 2 and 2B.
Regarding Claim(s) 27, the claim further recite the additional element(s) of a control categorization module and a control scoring module. This element(s) is performing the steps would be no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f) and/or amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h) in Steps 2A-Prong 2 and 2B.
Accordingly, the claim fails to recite any improvements to another technology or technical field, improvements to the functioning of the computer itself, use of a particular machine, effecting a transformation or reduction of a particular article to a different state or thing, adding unconventional steps that confine the claim to a particular useful application, and/or meaningful limitations beyond generally linking the use of an abstract idea to a particular environment. See 84 Fed. Reg. 55. Viewed individually or as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1 and 30 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fleiss et al. (US 8543438 B1), in view of Dooley et al. (US 20220129804 A1).
Regarding Claim(s) 1. Fleiss teaches: A computer-implemented system for assessing a project, comprising a memory for storing computer executable instructions, and a processor configured to execute the computer executable instructions stored in the memory to implement: (Fleiss, [col. 6, l. 6-15]; methods described herein may be implemented in software running on a programmable microprocessor, or implemented in hardware utilizing either a combination of microprocessors or other specially designed application specific integrated circuits, programmable logic devices, or various combinations thereof. The methods described herein may be implemented by a series of computer-executable instructions residing on a storage medium such as a disk drive, or other computer-readable medium).
a project readiness assessment module for assessing a project readiness of a project based on source data from a plurality of data sources and for generating a project assessment score, wherein the source data includes project data and wherein the project data includes project cost data including project cost estimate data, project scope data, project risk data, and project control data, (Fleiss, [co. 6, l. 12-15]; The methods described herein may be implemented by a series of computer-executable instructions residing on a storage medium such as a disk drive, or other computer-readable medium and Fleiss, [col. 14, l. 50-55]; The data processing for realizing project schedules may involve executing analyzer module facilities configured to examine the quality of project requirements and schedules entered into the system. The arrangement may support the examination of data sourced from multiple concurrent proposed and active projects and Fleiss, [co. 4, l. 30-33]; The system provides facilities and modules for executing the resource allocation algorithms and functions. The processing and execution environment maps each project requirement to a set of tasks and Fleiss, [co. 7, l. 41-45]; Duties may involve creating requirements and schedules, estimating total project cost, allocating resources, managing changes in project scope, and measuring project metrics for evaluating overall performance and Fleiss, [15, l. 30-32]; In the situation where the analyzer modules indicate or `mark` all project content as accepted, the project data is ready for Project Portfolio Manager approval and Fleiss, [co. 16, l. 15-25]; Additional reports may be added and configured for presenting, including but not limited to, performance metrics measuring and tracking project quality. One report metric for tracking performance is total productive capacity, measured in hours, for an organization's labor resources. Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated. An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs and Fleiss, [co. 22, l. 15-26]; The present design may involve continuously examining project selection criteria to detect changes to criterion or scores at point 443. The process flow arrangement may route projects with detected changes for consideration and review to the appropriate evaluators at point 449. Criterion evaluators may examine the project for any changes, where the change may occur as a result from inside and/or outside influences, relative to their criterion. Criterion evaluators may adjust their scores for each of their organization's projects to reflect the effect of the influence. For example, a project with a major "Technical Risk" score may diminish significantly as the project proceeds towards completion). Examiner interprets the modules of Fleiss to be the “modules” described.
a project diagnostic and cost assessment module for receiving the project cost data including the project cost estimate data and for applying a cost accuracy determination process to determine an accuracy of a cost associated with the project based on the project cost data and the project cost estimate data and for generating a project cost accuracy score, (Fleiss, [co. 16, l. 16-25]; performance metrics measuring and tracking project quality. One report metric for tracking performance is total productive capacity, measured in hours, for an organization's labor resources. Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated. An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs). Examiner interprets the metrics as scores, further the Examiner notes that the cost accuracy determination process is recited at a high level of generality and the comparison of data is interpreted as the process.
a project schedule assessment module for applying one or more predetermined schedule analysis and assessment techniques selected from critical path analysis, float time analysis, and baseline execution analysis to project schedule data to assess a quality and an accuracy of a project schedule and for generating a project schedule score, (Fleiss, [co. 15-16, l. 55-5 and co. 16, l. 16-25]; Baseline processor 337 may generate and store sequential project baselines for multiple concurrent projects. The resultant baseline quality metrics may indicate incremental measures for determining a project's progress at any point in time and comparisons with past estimates. A new project baseline may be created in response to requirements changes and/or updates to schedule items that may arise during the project development activities. Previously generated baselines may be used as a historical basis for determining project impacts. In one embodiment, the present design may generate a projects baseline based on potential changes entered into the projects database…. For example, the simulation may include determining changes to the project plan tasks existing, or considered, on the critical path…. performance metrics measuring and tracking project quality. One report metric for tracking performance is total productive capacity, measured in hours, for an organization's labor resources. Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated. An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs and Fleiss, [co. 29, l. 41-50]; The allocation algorithm, illustrated in FIG. 6A, may calculate the project's critical path by assigning a productivity factor of one (1.0) for each low-level task assigned to a labor category. The present design may compute the project's critical path by calculating total float for each low-level task. The total float time may be obtained by subtracting the earliest time task can start from the latest time task can start without causing a delay in the project's completion….). Examiner interprets the metrics as scores.
a project risk assessment module for processing the project risk data…. and for determining an inherent risk score associated with the project, (Fleiss, [co. 22, l. 15-26]; The present design may involve continuously examining project selection criteria to detect changes to criterion or scores at point 443. The process flow arrangement may route projects with detected changes for consideration and review to the appropriate evaluators at point 449. Criterion evaluators may examine the project for any changes, where the change may occur as a result from inside and/or outside influences, relative to their criterion. Criterion evaluators may adjust their scores for each of their organization's projects to reflect the effect of the influence. For example, a project with a major "Technical Risk" score may diminish significantly as the project proceeds towards completion).
a project control assessment module for receiving and processing the project control data and for generating a project control score, and (Fleiss, [co. 13, l. 55-61]; Scoring processor 316 may process a score for each individual project criterion stored by the designated criterion evaluators. The module configuration may involve a formula for calculating a sum total of the individual scores generated by scoring processor 316 to determine a total project ranking score. Scoring processor 316 may store the total project score in the project's ranking database 318).
a reporting module that can includes a user interface generator for generating one or more user interfaces for displaying on a display device one or more reports based on the integrated project assessment data. (Fleiss, [co. 13, l. 21-29]; In FIGS. 3A-3E, each process may involve executing similar operations for user/system interaction functions, such as accessing and modifying data, requesting project reports, and like operational procedures, initiated from a graphical user interface. The graphical user interface may enable rendering of page views generated by the system. The server may enable access to project content stored in the project database).
While Fleiss teaches an inherent risk score, Fleiss does not appear to teach using a risk categorization process. However, Fleiss in view of the analogous art of Dooley (i.e. project management) does teach the entirety of the limitation: (Dooley, [45]; an input to a rule-set or trained model (and hence a possible factor in determining a risk evaluation metric) used in assessing an overall organizational risk may be the number of projects being undertaken that have a specific source of risk associated with them or are in a specified category of risk and Dooley, [53]; The risk vector may be used to generate a scalar risk value for the total organizational risk arising from the risk associated with each category by using a specific formula for generating a single value from the components of a vector).
While Fleiss teaches a plurality of modules to perform the functions above and generating integrated project assessment data (Fleiss, [co. 34, l. 53-65]), Fleiss does not appear to explicitly teach a coordination of modules. However, Fleiss in view of the analogous art of Dooley (i.e. project management) does teach: wherein the project readiness assessment module, project diagnostic and cost assessment module, project schedule assessment module, project risk assessment module, and project control assessment module operate in coordination to generate integrated project assessment data, and (Dooley, [126]; In a complex application or system such instructions are typically arranged into “modules” with each such module typically performing a specific task, process, function, or operation. The entire set of modules may be controlled or coordinated in their operation by an operating system (OS) or other form of organizational platform).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including an inherent risk score, with the teachings of Dooley including a risk categorization process in order to determine what category of risk are highest contributors to risk and determine if mitigation is needed. (Dooley, [09]; Embodiments are also directed to determining if an additional or modified mitigation process or technique should be used for a task, project, or organization. This determination may be based at least in part on considering whether a risk metric for the task, project, or organization exceeds a threshold or trigger value. In some embodiments, a risk metric may take the form of a risk vector that comprises risk contributions from multiple categories or types of risk (such as regulatory, credit, IP, political, reputation, etc.). The individual risk contributions may be combined into a single metric or value based on a set of weights, a form of a norm or distance measure, etc).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including a plurality of modules to perform the functions above and generating integrated project assessment data with the teachings of Dooley including coordinated modules in order to provide a system that works in unison to provide metrics and benchmarks against similar industries and locations (Dooley, [155]; Project or Task Factual Information Module 406 may contain instructions that when executed by a processor or processors cause a system or device to perform a process to access, obtain or generate information and data regarding a specific task or project, such as that indicated by the questions and factors described herein (as suggested by steps or stages 112 and 113 of FIG. 1). Risk Mitigation Procedures and Protocols Module 407 may contain instructions that when executed by a processor or processors cause a system or device to perform a process to access, obtain or generate information and data regarding the risk mitigation processes or protocols available and/or being applied to a specific task, project, or organization (i.e., those at a task, project, or organizational level, depending on the rule-set, model, or logic being applied, as suggested by step or stage 114 of FIG. 1). Benchmark Data Module 408 may contain instructions that when executed by a processor or processors cause a system or device to perform a process to access or obtain information regarding industry, project specific, location, or other benchmarks (as suggested by step or stage 114 of FIG. 1). These benchmarks may be in the form of a risk score or metric for an industry, location, organization and/or project having sufficient similarity to the organization or project being evaluated for risk).
Regarding Claim(s) 30. Fleiss teaches:. A computer-implemented method for assessing a project, comprising assessing a project readiness using computer-executable instructions stored in a non- transient memory and executed by a processor implementing a project readiness assessment(Fleiss, [col. 6, l. 6-15]; methods described herein may be implemented in software running on a programmable microprocessor, or implemented in hardware utilizing either a combination of microprocessors or other specially designed application specific integrated circuits, programmable logic devices, or various combinations thereof. The methods described herein may be implemented by a series of computer-executable instructions residing on a storage medium such as a disk drive, or other computer-readable medium and Fleiss, [col. 14, l. 50-55]; The data processing for realizing project schedules may involve executing analyzer module facilities configured to examine the quality of project requirements and schedules entered into the system. The arrangement may support the examination of data sourced from multiple concurrent proposed and active projects and Fleiss, [co. 4, l. 30-33]; The system provides facilities and modules for executing the resource allocation algorithms and functions. The processing and execution environment maps each project requirement to a set of tasks and Fleiss, [co. 7, l. 41-45]; Duties may involve creating requirements and schedules, estimating total project cost, allocating resources, managing changes in project scope, and measuring project metrics for evaluating overall performance and Fleiss, [co. 16, l. 15-25]; Additional reports may be added and configured for presenting, including but not limited to, performance metrics measuring and tracking project quality. One report metric for tracking performance is total productive capacity, measured in hours, for an organization's labor resources. Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated. An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs and Fleiss, [co. 22, l. 15-26]; The present design may involve continuously examining project selection criteria to detect changes to criterion or scores at point 443. The process flow arrangement may route projects with detected changes for consideration and review to the appropriate evaluators at point 449. Criterion evaluators may examine the project for any changes, where the change may occur as a result from inside and/or outside influences, relative to their criterion. Criterion evaluators may adjust their scores for each of their organization's projects to reflect the effect of the influence. For example, a project with a major "Technical Risk" score may diminish significantly as the project proceeds towards completion). Examiner interprets the modules of Fleiss to be the “modules” described.
determining an accuracy of a cost associated with the project using computer-executable instructions stored in the memory and executed by the processor implementing a project diagnostic and cost assessment module, the accuracy of the cost based on the project cost data and the project cost estimate data and generating in response a project cost accuracy score, (Fleiss, [co. 16, l. 16-25]; performance metrics measuring and tracking project quality. One report metric for tracking performance is total productive capacity, measured in hours, for an organization's labor resources. Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated. An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs). Examiner interprets the metrics as scores, further the Examiner notes that the cost accuracy determination process is recited at a high level of generality and the comparison of data is interpreted as the process.
applying one or more schedule analysis and assessment techniques selected from critical path analysis, float time analysis, and baseline execution analysis to the project schedule data using computer-executable instructions stored in the memory and executed by the processor implementing with a project schedule assessment module for assessing a quality of a project schedule and an accuracy of the project schedule and for generating a project schedule score, (Fleiss, [co. 15-16, l. 55-5 and co. 16, l. 16-25]; Baseline processor 337 may generate and store sequential project baselines for multiple concurrent projects. The resultant baseline quality metrics may indicate incremental measures for determining a project's progress at any point in time and comparisons with past estimates. A new project baseline may be created in response to requirements changes and/or updates to schedule items that may arise during the project development activities. Previously generated baselines may be used as a historical basis for determining project impacts. In one embodiment, the present design may generate a projects baseline based on potential changes entered into the projects database…. For example, the simulation may include determining changes to the project plan tasks existing, or considered, on the critical path…. performance metrics measuring and tracking project quality. One report metric for tracking performance is total productive capacity, measured in hours, for an organization's labor resources. Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated. An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs and Fleiss, [co. 29, l. 41-50]; The allocation algorithm, illustrated in FIG. 6A, may calculate the project's critical path by assigning a productivity factor of one (1.0) for each low-level task assigned to a labor category. The present design may compute the project's critical path by calculating total float for each low-level task. The total float time may be obtained by subtracting the earliest time task can start from the latest time task can start without causing a delay in the project's completion….). Examiner interprets the metrics as scores.
determining an inherent risk score associated with the project using computer-executable instructions stored in the memory and executed by the processor implementing a project risk assessment module based on the project risk data, (Fleiss, [co. 22, l. 15-26]; The present design may involve continuously examining project selection criteria to detect changes to criterion or scores at point 443. The process flow arrangement may route projects with detected changes for consideration and review to the appropriate evaluators at point 449. Criterion evaluators may examine the project for any changes, where the change may occur as a result from inside and/or outside influences, relative to their criterion. Criterion evaluators may adjust their scores for each of their organization's projects to reflect the effect of the influence. For example, a project with a major "Technical Risk" score may diminish significantly as the project proceeds towards completion.
assessing one or more project controls associated with the project using computer-executable instructions stored in the memory and executed by the processor implementing a project control assessment module based on project control data and in response generating a project control score, (Fleiss, [co. 13, l. 55-61]; Scoring processor 316 may process a score for each individual project criterion stored by the designated criterion evaluators. The module configuration may involve a formula for calculating a sum total of the individual scores generated by scoring processor 316 to determine a total project ranking score. Scoring processor 316 may store the total project score in the project's ranking database 318).
displaying on a display device one or more reports based on the integrated project assessment data using computer-executable instructions stored in the memory and executed by the processor implementing a reporting module including a user interface generator for generating a user interface. (Fleiss, [co. 13, l. 21-29]; In FIGS. 3A-3E, each process may involve executing similar operations for user/system interaction functions, such as accessing and modifying data, requesting project reports, and like operational procedures, initiated from a graphical user interface. The graphical user interface may enable rendering of page views generated by the system. The server may enable access to project content stored in the project database).
While Fleiss teaches a plurality of modules to perform the functions above and generating integrated project assessment data (Fleiss, [co. 34, l. 53-65]), Fleiss does not appear to explicitly teach a coordination of modules. However, Fleiss in view of the analogous art of Dooley (i.e. project management) does teach: wherein the project readiness assessment module, project diagnostic and cost assessment module, project schedule assessment module, project risk assessment module, and project control assessment module operate in coordination to generate integrated project assessment data, and (Dooley, [126]; In a complex application or system such instructions are typically arranged into “modules” with each such module typically performing a specific task, process, function, or operation. The entire set of modules may be controlled or coordinated in their operation by an operating system (OS) or other form of organizational platform).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including a plurality of modules to perform the functions above and generating integrated project assessment data with the teachings of Dooley including coordinated modules in order to provide a system that works in unison to provide metrics and benchmarks against similar industries and locations (Dooley, [155]; Project or Task Factual Information Module 406 may contain instructions that when executed by a processor or processors cause a system or device to perform a process to access, obtain or generate information and data regarding a specific task or project, such as that indicated by the questions and factors described herein (as suggested by steps or stages 112 and 113 of FIG. 1). Risk Mitigation Procedures and Protocols Module 407 may contain instructions that when executed by a processor or processors cause a system or device to perform a process to access, obtain or generate information and data regarding the risk mitigation processes or protocols available and/or being applied to a specific task, project, or organization (i.e., those at a task, project, or organizational level, depending on the rule-set, model, or logic being applied, as suggested by step or stage 114 of FIG. 1). Benchmark Data Module 408 may contain instructions that when executed by a processor or processors cause a system or device to perform a process to access or obtain information regarding industry, project specific, location, or other benchmarks (as suggested by step or stage 114 of FIG. 1). These benchmarks may be in the form of a risk score or metric for an industry, location, organization and/or project having sufficient similarity to the organization or project being evaluated for risk).
Claim(s) 2-13, 19-23, 29, 31-35, and 41-45 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fleiss et al. (US 8543438 B1), in view of Dooley et al. (US 20220129804 A1), Leehman et al. (US 20050043976 A1).
Regarding Claim(s) 2 and 31. Fleiss teaches: a project readiness scoring module for receiving and processing the category data and for generating the project assessment score. (Fleiss, [co. 5, l. 42-52]; The first module assigns labor resources to a prioritized list of project tasks from the entire portfolio of projects with the highest skilled individual for the required labor category. The second module identifies and matches a generic labor category to each scheduled task to generate a current, up to date set of schedules for multiple concurrent projects. The resulting schedule tasks may be assembled to form a prioritized list, accounting for complexity and risk. The third module ranks multiple projects based on assessment criterion evaluation scores and adjusts the prioritized task list order according to project ranking and Fleiss, [co. 20, l. 45-52]; The process flow arrangement may add the generated scores and sum each measured project criteria for each project. The scores generated may provide input to the mechanized facility, illustrated in FIG. 4A, to determine an ordered ranking of proposed projects. One example of ordering is ordering from highest total project score down to the lowest generated score and Fleiss, [co.13, l. 9-13]; In another example, EOB processing provides automated reporting of previously scanned and examined project's data to identify potential issues that may impact project cost, schedule, or the quality of deliverable materials (i.e. project objectives) and Fleiss, [co. 24, l. 5-15]; FIG. 4E represents a general layout for criteria update page-view 480 report when activated. In this view, at point 482, the criteria name, selected from the scoring screen, is presented along with the currently assigned weight, or importance, at point 484. The responsibilities 486 may be submitted by a Project Portfolio Manager who may input a new or revised description at point 486 specifying duties with regards to the criteria being scored. A member/user may submit a change for a named criteria weight by selecting weight 484 from a pull-down menu, provided to the left of the currently assign value, and choose a different weight for assignment to update the criteria). Examiner notes the criteria further exemplifies categories.
a categorization module for categorizing the source data into a plurality of project categories, wherein the plurality of project categories includes project objectives, project scope, project schedule, project cost, project risk, project controls, and project resources; (Fleiss, co. 5, l. 44-49]; The first module assigns labor resources to a prioritized list of project tasks from the entire portfolio of projects with the highest skilled individual for the required labor category (i.e. resources). The second module identifies and matches a generic labor category to each scheduled task to generate a current, up to date set of schedules for multiple concurrent projects and Fleiss, [co. 9, l. 54-60]; A Sponsor is not typically a system member type supported in the personnel database. In this arrangement, the Project Portfolio Manager is able to assign access rights for a project Sponsor. The system may notify the project Sponsor in the case of critical events that might affect the project's schedule, cost, scope or quality (i.e. project controls). Examiner notes that Dooley is relied upon to teach risk categories.
While Fleiss/Dooley teach project risk, project resources, project scores and a plurality of categories that generate category data, Fleiss does not appear to teach subcategories. However, Fleiss in view of the analogous art of Leehman (i.e. project planning) does teach: The computer-implemented system of claim 1, wherein the project readiness assessment module comprises: a categorization module for categorizing the source data into a plurality of project categories, wherein each of the plurality of project categories includes a plurality of project subcategories, wherein the categorization module generates category data, and (Leehman, [20-21]; Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service (i.e. due diligence). The associated KPI, KPI-8, can be measured as downtime per service call. A threshold for KPI-8 can be, for example, four hours per incident… Cost subcategory C2 may be preventative measures, such as inspections and routine maintenance. The associated business processes, P10-P12, may be vehicle inspection, routine maintenance, and product selection, respectively. The operations needed for each one of these processes are detailed in an operations manual. The associated KPI, KPI-9, for all of processes P10-P12 can be measured as number of service calls. A threshold for KPI-9 can be, for example, four calls per year and Leehman, [27]; The updated subcategory and major category costs are calculated. This procedure is repeated for each process until the most cost effective process map 100 is prepared (step 280).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including project scores and a plurality of categories that generate category data with the teachings of Leehman including subcategories in order to have a better understanding of cost factors such as services, products, shipping costs, etc. and allow for thresholds on each value (Leehman, [20]; For an additional example, assume that the business entity includes a shipping division with a fleet of trucks. Further assume that major cost category C is emergency road service for the trucks of the fleet. Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. The associated KPI, KPI-8, can be measured as downtime per service call.
Regarding Claim(s) 3 and 32. Fleiss/Leehman teaches: The computer-implemented system of claim 2, wherein the project readiness scoring module generates the project assessment score by summing together a category assessment score generated for each of the plurality of project categories, and (Fleiss, [co. 20, li. 39-50]; The present method may multiply individual evaluation score for each project by the weight assigned for the criterion, thus generating an evaluation score. If, for example, a user wishes to allocate greater weight to cost of an individual project than return on investment during the first year of the individual project than is provided by default, such a difference may be reflected in a user defined weighting for specified criterion. The process flow arrangement may add the generated scores and sum each measured project criteria for each project. The scores generated may provide input to the mechanized facility, illustrated in FIG. 4A, to determine an ordered ranking of proposed projects. One example of ordering is ordering from highest total project score down to the lowest generated score). Examiner notes that Leehman is relied upon to teach the subcategories.
wherein the project assessment score is indicative of a readiness of the project to be undertaken. (Fleiss, [co. 20, l. 19-32]; The process flow may access and retrieve scores entered from the evaluators, apply entered scores to pre-established criterion and weighting factors for each project, total the resulting criterion scores for each project, in a portfolio containing multiple projects, and order the projects based on the total scores. The highest score becomes the most important project, the next highest becomes the next most important project and so forth. The ordering of generated scores establishes the ranking for multiple proposed projects and may be used to determine which projects are to be funded. Project selection criteria entries may include a weighting (importance) factor. The weighting factor may be represented by a numerical value indicating the relative level of importance with respect to the overall project criterion).
While Fleiss/Leehman teach categories, subcategories, and scores; neither appear to teach summing scores. However, Fleiss/Dooley/Leehman does teach: wherein each of the category assessment scores are determined by summing together a subcategory assessment score for each of the plurality of project subcategories associated with each of the plurality of project categories, and (Dooley, [107]; The combination of the set of individual task or project metrics may be performed on risk vectors which contain multiple risk category components and scores for each category, or on a single risk measure. Thus, the combining process may generate a result for each component, an overall single risk value, or both. The combining operation may be the result of calculating a weighted sum, applying a rule, fitting values to a curve, applying a filter to remove or level certain components or values, calculating a norm or distance measure from the vector components, or other suitable operation. The combining method or operations may include adjustable values or parameters, which may be set by a user, determined by separate logic, or by another suitable method, as suggested by step or stage 123).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of as Fleiss/Leehman teach categories, subcategories, and scores with the teachings of Dooley including summing scores in order to generate weighted score to generate an overall value. (Dooley, [107]; The combination of the set of individual task or project metrics may be performed on risk vectors which contain multiple risk category components and scores for each category, or on a single risk measure. Thus, the combining process may generate a result for each component, an overall single risk value, or both. The combining operation may be the result of calculating a weighted sum, applying a rule, fitting values to a curve, applying a filter to remove or level certain components or values, calculating a norm or distance measure from the vector components, or other suitable operation. The combining method or operations may include adjustable values or parameters, which may be set by a user, determined by separate logic, or by another suitable method, as suggested by step or stage 123).
Regarding Claim(s) 4. Fleiss/Leehman/Heckman teaches: The computer-implemented system of claim 3, wherein the plurality of project categories comprises one or more of a project characteristics category, a project execution strategy category, a basis of design category, and an operations category. (Fleiss, [Fig. 1C]; provides examples of a plurality of criteria (i.e. categories) such as alignment product, financial risks, schedule risks (i.e. both project characteristics)).
Regarding Claim(s) 5. Fleiss/Leehman/Heckman teaches: The computer-implemented system of claim 4, wherein the project characteristics category comprises a plurality of project subcategories including two or more of a project objective subcategory, a due diligence subcategory, a funding model subcategory, a schedule definition subcategory, and a development rights subcategory. (Leehman, [2021]; Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service (i.e. due diligence). The associated KPI, KPI-8, can be measured as downtime per service call. A threshold for KPI-8 can be, for example, four hours per incident… Cost subcategory C2 may be preventative measures, such as inspections and routine maintenance. The associated business processes, P10-P12, may be vehicle inspection, routine maintenance, and product selection, respectively. The operations needed for each one of these processes are detailed in an operations manual. The associated KPI, KPI-9, for all of processes P10-P12 can be measured as number of service calls. A threshold for KPI-9 can be, for example, four calls per year and Leehman, [27]; The updated subcategory and major category costs are calculated. This procedure is repeated for each process until the most cost effective process map 100 is prepared (step 280).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including project scores and a plurality of categories that generate category data with the teachings of Leehman including subcategories in order to have a better understanding of cost factors such as services, products, shipping costs, etc. and allow for thresholds on each value (Leehman, [20]; For an additional example, assume that the business entity includes a shipping division with a fleet of trucks. Further assume that major cost category C is emergency road service for the trucks of the fleet. Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. The associated KPI, KPI-8, can be measured as downtime per service call.
Regarding Claim(s) 6 and 33. Fleiss/Leehman/Heckman teaches: The computer-implemented system of claim 3, wherein the category scores for each of the plurality of project categories or the subcategory scores for each of the plurality of project subcategories are weighted relative to each other based on one or more project factors. (Fleiss, [co. 21, l. 1-21]; The weight assigned may indicate the relative level of importance for the inputted selection criteria. Members may directly influence the project funding selection process results by adjusting the relative weight of a criterion compared to the entire set of selection criteria available in the system. Increasing and decreasing the assigned weight adjusts the relative importance of the criteria being influenced as compared against importance of each of the criterion in the set).
Regarding Claim(s) 7 and 34. Fleiss/Leehman/Heckman teaches: The computer-implemented system of claim 3, wherein the project assessment score associated with each of the plurality of project categories is compared with a corresponding threshold assessment score, and (Fleiss, [co. 9, l. 60-64]; The system may monitor project data, based on a set of predefined metrics, to detect and indicate when data values fall outside of the desired range. Event processing may involve detecting, generating, and transmitting information regarding the occurrence).
While Fleiss teaches a threshold value compared to category data, Fleiss does not appear to teach a responsive action. However, Fleiss/Leehman does teach: if the project assessment score is less than the threshold assessment score, perform one or more project related actions. (Leehman, [28]; For example, processes resulting in the greatest savings (i.e., above a predetermined savings threshold) would all be placed in savings category 1, processes resulting in less savings (i.e., above a lower savings threshold) would all be placed in savings category 2, and so on and Leehman, [24]; The new process may optionally be tailored to the individual needs of the business entity by considering existing "situational factors" and adjusting for overall business entity guidelines. For example, fleet truck tires that are slated for repair may be handled differently depending on the remaining life of the tire, (e.g., tread depth and uniformity), which is a situational factor. KPIs are established that fit the new process (step 260), including recommended compliance levels and audit guidelines. The new costs associated with each new process are estimated (step 270) based on cost analysis performed using all available information, including information contained in the best practice database). Examiner notes that is the tire tread is within a threshold value the system recommends a different adjustment of entity guidelines such as servicing trucks.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including a threshold value compared to category data with the teachings of Leehman including a responsive action in order to establish a new process with compliance levels and audit guidelines (Leehman, [24]; adjusting for overall business entity guidelines. For example, fleet truck tires that are slated for repair may be handled differently depending on the remaining life of the tire, (e.g., tread depth and uniformity), which is a situational factor. KPIs are established that fit the new process (step 260), including recommended compliance levels and audit guidelines. The new costs associated with each new process are estimated (step 270) based on cost analysis performed using all available information, including information contained in the best practice database).
Regarding Claim(s) 8. Fleiss/Leehman/Heckman teaches: The computer-implemented system of claim 7, wherein the one or more project related actions comprises one or more of delaying or holding the project, recommend that additional project design work be performed to reduce uncertainty associated with the project, correct any identified project scheduling issues, adjust a budget associated with the project, and recommend the addition of one or more project resources. (Leehman, [28]; For example, processes resulting in the greatest savings (i.e., above a predetermined savings threshold) would all be placed in savings category 1, processes resulting in less savings (i.e., above a lower savings threshold) would all be placed in savings category 2, and so on and Leehman, [24]; The new process may optionally be tailored to the individual needs of the business entity by considering existing "situational factors" and adjusting for overall business entity guidelines. For example, fleet truck tires that are slated for repair may be handled differently depending on the remaining life of the tire, (e.g., tread depth and uniformity), which is a situational factor). Examiner notes that is the tire tread is within a threshold value the system recommends a different adjustment of entity guidelines such as servicing trucks.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including a threshold value compared to category data with the teachings of Leehman including a responsive action in order to establish a new process with compliance levels and audit guidelines (Leehman, [24]; adjusting for overall business entity guidelines. For example, fleet truck tires that are slated for repair may be handled differently depending on the remaining life of the tire, (e.g., tread depth and uniformity), which is a situational factor. KPIs are established that fit the new process (step 260), including recommended compliance levels and audit guidelines. The new costs associated with each new process are estimated (step 270) based on cost analysis performed using all available information, including information contained in the best practice database).
Regarding Claim(s) 9. Fleiss/Leehman teaches:. The computer-implemented system of claim 6, wherein the project data includes stage data and gate data, (Fleiss, [co. 9, l. 3-6]; The Project Manager role may include responsibility for modifying project tasks, reporting project's task attributes such as percentage of task completed, monitoring progress for assigned tasks, and monitoring team member performance and Fleiss, [co. 9, l. 11-19]; The Project Manager 150 may input scheduled task attributes, for example, inputting a numerical value for each task based on measured progress to indicate the amount, or percentage, of progress completed against or relative to task completion. An exemplary chart, illustrated in FIG. 1E, provides a list for the major database structures. The list may relate a specific database structure and provide a description for each structure listed and Fleiss, [co. 24, l. 20-24]; FIG. 5A illustrates a process flow method for establishing multiple concurrent projects' baseline for establishing key metrics after completion of a major milestone (such as a phase within a project) that can be used later in comparison with the current status of a project and Fleiss, [co. 34, l. 44-52]; the project schedule of each project based on available labor resources and tasks for each of the plurality of projects, periodically monitoring progress of tasks of each of the plurality of projects using the server, thereby establishing a current project status, by collecting task progress information for each project and comparing task progress information against established project completion criteria, and reallocating selected available labor resources to different tasks based on the project status.). Examiner interprets stage/gate in light of the specification wherein stages include “distinct phases or steps in the project lifecycle” and gates include “review or decision points or gates that occur at the end of each project stage and hence can function or act as go/no-go checkpoints” (Spec, page. 19)
wherein the project readiness assessment module processes the stage data and the gate data to determine a progress of the project. (Fleiss, [co. 9, l. 11-19]; The Project Manager 150 may input scheduled task attributes, for example, inputting a numerical value for each task based on measured progress to indicate the amount, or percentage, of progress completed against or relative to task completion. An exemplary chart, illustrated in FIG. 1E, provides a list for the major database structures. The list may relate a specific database structure and provide a description for each structure listed).
Regarding Claim(s) 10 and 35. Fleiss/Leehman teaches: a project cost accuracy determination module for determining, based on the cost classification data, a project cost accuracy score indicative of an accuracy of a cost associated with the project. (Fleiss. [co. 16, l. 19-26]; Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated. An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs and Fleiss, [co. 33, l. 11-17]; FIG. 8A illustrates a process flow for a project costing method for determining project element costs in accordance with one embodiment of the present design. Project element costs may include, but is not limited to, cost of a project requirement, cost-expended-to-date, cost-to-complete, and the total project cost.
The computer-implemented system of claim 2, wherein the project diagnostic and cost assessment module comprises a cost classification module for classifying the project cost data into one or more of a plurality of cost classifications, wherein each of the plurality of cost classifications includes a plurality of cost subclassifications, wherein the cost classification module generates cost classification data, and (Leehman, [20-21]; Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service (i.e. due diligence). The associated KPI, KPI-8, can be measured as downtime per service call. A threshold for KPI-8 can be, for example, four hours per incident… Cost subcategory C2 may be preventative measures, such as inspections and routine maintenance. The associated business processes, P10-P12, may be vehicle inspection, routine maintenance, and product selection, respectively. The operations needed for each one of these processes are detailed in an operations manual. The associated KPI, KPI-9, for all of processes P10-P12 can be measured as number of service calls. A threshold for KPI-9 can be, for example, four calls per year and Leehman, [27]; The updated subcategory and major category costs are calculated. This procedure is repeated for each process until the most cost effective process map 100 is prepared (step 280).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including project scores and a plurality of categories that generate category data with the teachings of Leehman including subcategories in order to have a better understanding of cost factors such as services, products, shipping costs, etc. and allow for thresholds on each value (Leehman, [20]; For an additional example, assume that the business entity includes a shipping division with a fleet of trucks. Further assume that major cost category C is emergency road service for the trucks of the fleet. Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. The associated KPI, KPI-8, can be measured as downtime per service call).
Regarding Claim(s) 11. Fleiss/Leehman teaches: The computer-implemented system of claim 10, wherein the plurality of cost classifications comprises a process industry cost classification and a general building cost classification. (Leehman, [20-21]; Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. (i.e. general business)… Cost subcategory C2 may be preventative measures, such as inspections and routine maintenance. The associated business processes, P10-P12, may be vehicle inspection, routine maintenance, and product selection, respectively. (i.e. process industry cost) The operations needed for each one of these processes are detailed in an operations manual. The associated KPI, KPI-9, for all of processes P10-P12 can be measured as number of service calls.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including project scores and a plurality of categories that generate category data with the teachings of Leehman including subcategories in order to have a better understanding of cost factors such as services, products, shipping costs, etc. and allow for thresholds on each value (Leehman, [20]; For an additional example, assume that the business entity includes a shipping division with a fleet of trucks. Further assume that major cost category C is emergency road service for the trucks of the fleet. Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. The associated KPI, KPI-8, can be measured as downtime per service call).
Regarding Claim(s) 12. Fleiss/Leehman teaches: The computer-implemented system of claim 11, wherein the plurality of cost subclassifications comprise two or more of a project scope description subclassification, a plant production capacity subclassification, a plant location subclassification, a soil and hydrology subclassification, an integrated project plan subclassification, a project master schedule subclassification, an escalation strategy subclassification, a work breakdown structure subclassification, an escalation strategy subclassification, a project code of accounts subclassification, a contracting strategy subclassification, a diagrams subclassification, a plot plans subclassification, a process flow diagrams subclassification, a utility flow diagrams subclassification, an instrument diagrams subclassification, a heating material balances subclassification, a process equipment list subclassification, a utility equipment list subclassification, an electrical drawing subclassification, a specification and data sheet subclassification, a general equipment arrangement subclassification, a spare parts subclassification, a mechanical discipline drawings subclassification, an electrical discipline drawings subclassification, an instrumentation and control system subclassification, and a civil and structural site discipline subclassification. (Leehman, [21]; Cost subcategory C2 may be preventative measures, such as inspections and routine maintenance. The associated business processes, P10-P12, may be vehicle inspection, routine maintenance, and product selection, respectively. (i.e. process flow/process equipment) The operations needed for each one of these processes are detailed in an operations manual. The associated KPI, KPI-9, for all of processes P10-P12 can be measured as number of service calls and Leehman, [46]; Other: Miscellaneous parts and tools supplied by an outside vendor for use in the normal course of a fleet's tire program implementation and management (i.e. general equipment arrangement).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including project scores and a plurality of categories that generate category data with the teachings of Leehman including subcategories in order to have a better understanding of cost factors such as services, products, shipping costs, etc. and allow for thresholds on each value (Leehman, [20]; For an additional example, assume that the business entity includes a shipping division with a fleet of trucks. Further assume that major cost category C is emergency road service for the trucks of the fleet. Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. The associated KPI, KPI-8, can be measured as downtime per service call).
Regarding Claim(s) 13. Fleiss/Dooley/Leehman teaches: The computer-implemented system of claim 12, wherein the general building cost classification comprises a plurality of cost subclassifications including two or more of an assessment area subclassification, a project general scope description subclassification, a project location subclassification, a building area subclassification, a functional space requirements subclassification, a building specific subclassification, an exterior closure description subclassification, a finishes description and requirements subclassification, a building code or standards requirement subclassification, a mechanical systems and total capacity subclassification, an electrical capacity subclassification, a communication system subclassification, a fire protection and life safety requirements subclassification, a security system subclassification, an antiterrorism force protection requirements subclassification, a LEED certification level subclassification, a soil and hydrology subclassification, an integrated project plan subclassification, a project master schedule subclassification, a work breakdown structure subclassification, a project code of accounts subclassification, a contracting strategy subclassification, an escalation strategy and basis subclassification, a building codes and standards subclassification, a site plan subclassification, a demolition plan and drawing subclassification, a utility plan and drawing subclassification, a site electrical plan and drawings subclassification, a site lighting plan and drawing subclassification, a site communications plan and drawing subclassification, an erosion control plan subclassification, a stormwater plan subclassification, a landscape plan subclassification drama and exterior elevations subclassification, an interior elevations subclassification, an interior section views subclassification, a partition or wall type subclassification, a fender schedule subclassification, a door schedule subclassification, a window schedule subclassification, a restroom schedule subclassification, a furniture plan subclassification, a signage subclassification, a fire protection plan subclassification, a room layout plan subclassification, a foundation plan subclassification, a foundation section subclassification, a structural plan subclassification, a roof plan subclassification, a building envelope subclassification, material and equipment subclassification, a mechanical and HVAC subclassification, a flow control subclassification, a plumbing subclassification, and electrical subclassification, a lighting subclassification, and an information systems and telecommunications subclassification. (Leehman, [20]; Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. The associated KPI, KPI-8, can be measured as downtime per service call (i.e. flow control) and Leehman, [51]; Miscellaneous Parts: Complementary parts (such as wheels, automatic air inflation systems, and more) supplied in an effort to ensure the continued mobility of a fleet as it relates to the normal or planned aspects of tire program management (i.e. material and equipment).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including project scores and a plurality of categories that generate category data with the teachings of Leehman including subcategories in order to have a better understanding of cost factors such as services, products, shipping costs, etc. and allow for thresholds on each value (Leehman, [20]; For an additional example, assume that the business entity includes a shipping division with a fleet of trucks. Further assume that major cost category C is emergency road service for the trucks of the fleet. Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. The associated KPI, KPI-8, can be measured as downtime per service call).
Regarding Claim(s) 19 and 41. Fleiss/Leehman teaches: The computer-implemented system of claim 10, wherein the project schedule assessment module comprises: a project schedule assessment module for applying the one or more schedule analysis and assessment techniques to the project schedule data to assess the quality and the accuracy of the project schedule and for generating project schedule assessment data, and a project schedule scoring module for determining the project schedule score based on one or more of the project schedule assessment data and a third party project schedule score. (Fleiss, [co. 16, l. 16-22]; One report metric for tracking performance is total productive capacity, measured in hours, for an organization's labor resources. Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated and Fleiss, [co. 11, l. 57-62]; Example labor categories may include software architect, software engineer, level-one programmer, level two-programmer, test engineer, configuration and release engineer, contractor, electrician, and so forth. Each labor category within the team member role structure may include as many levels of division as needed and Fleiss, [co. 18, l. 14-18]; Status processor 366 may mark tasks reported completed, sum the completed task estimated hours and calculate the needed hours to complete the task for each labor category. The status processor 366 may calculate the labor category and individual resource productivity factors and compute the associated cost effectiveness).
Regarding Claim(s) 20 and 42. Fleiss/Leehman teaches: The computer-implemented system of claim 19, wherein the schedule analysis and assessment technique analyzes the project schedule data and evaluates the quality and the accuracy of the project schedule data based on a set of predetermined project criteria. (Fleiss, [co. 14, l. 46-53]; The information contained in the established schedule generated may identify a suite of quality metrics, for measuring and tracking quality, available for use during the development effort or comparing against the present project data. The data processing for realizing project schedules may involve executing analyzer module facilities configured to examine the quality of project requirements and schedules entered into the system).
Regarding Claim(s) 21 and 43. Fleiss/Leehman teaches: The computer-implemented system of claim 20, wherein the project criteria comprises two or more of a project logic criteria, project lead criteria, project lag criteria, project relationship criteria, project hard restraint criteria, high float criteria, a negative float criteria, high duration task, invalid dates criteria, resources criteria, missed tasks criteria, critical path test criteria, a critical path length index (CPLI) criteria, and a baseline execution index (BEI). (Fleiss, [co. 29 l. 45-55]; The present design may compute the project's critical path by calculating total float for each low-level task. The total float time may be obtained by subtracting the earliest time task can start from the latest time task can start without causing a delay in the project's completion. For purposes of disclosure, the "total float time" for a task is defined as the longest possible delay (i.e. high float) in the completion of the task that will not cause a delay in the completion of the project. The allocation process flow may involve computing a total float time value equal to zero for low-level tasks placed on the critical path and Fleiss, [co. 29, l. 55-62]; By identifying the critical path tasks, the system may provide for refining the relative importance for each critical path task relative to the remaining tasks (i.e. critical path test). The present designs allocation algorithm may involve generating an ordered list of all tasks to be performed during the allocation period and sort the ordered list for ranking the tasks based on ranking. Allocate resources 620 mechanisms may build a table containing prioritized tasks, at point 625).
Regarding Claim(s) 22 and 44. teaches: The computer-implemented system of claim 20, wherein the project schedule scoring module determines a project score for each of the predetermined project criteria, and the project schedule scoring module determines a total project schedule score by summing together the project scores associated with each of the project criteria. (Fleiss, [co. 18, l. 14-18]; Status processor 366 may mark tasks reported completed, sum the completed task estimated hours and calculate the needed hours to complete the task for each labor category. The status processor 366 may calculate the labor category and individual resource productivity factors and compute the associated cost effectiveness and Fleiss, [co. 16, l. 18-22]; One report metric for tracking performance is total productive capacity, measured in hours, for an organization's labor resources. Such a utilization metric may entail a calculation of the total hours allocated Project Team Members that are actually performing scheduled tasks versus the total number of resource hours that remain unallocated).
Regarding Claim(s) 23 and 45. teaches: The computer-implemented system of claim 22, wherein each of the project scores associated with each of the project criteria are weighted differently relative to each other based on one or more predetermined project weighting factors. (Fleiss, [co. 21, l. 1-21]; The weight assigned may indicate the relative level of importance for the inputted selection criteria. Members may directly influence the project funding selection process results by adjusting the relative weight of a criterion compared to the entire set of selection criteria available in the system. Increasing and decreasing the assigned weight adjusts the relative importance of the criteria being influenced as compared against importance of each of the criterion in the set and Fleiss, [co. 20, l. 34-38]; The present method may assign a default value for each weighting factor signifying the importance relative to the initial system populated default criterion. The criteria weighting table may support the entry for user defined names for criteria and custom weighting factors).
Regarding Claim(s) 29. Fleiss teaches: The computer-implemented system of claim 1, wherein the reporting unit module generates one or more reports based on the project assessment score, the project cost accuracy score, the project cost accuracy score, the project schedule score, the inherent risk score, and the project control score. (Fleiss, [co. 13, l. 21-29]; In FIGS. 3A-3E, each process may involve executing similar operations for user/system interaction functions, such as accessing and modifying data, requesting project reports, and like operational procedures, initiated from a graphical user interface. The graphical user interface may enable rendering of page views generated by the system. The server may enable access to project content stored in the project database).
Claim(s) 14-15, 17-18, 24-27, 36-37, 39-40, and 46-49 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fleiss et al. (US 8543438 B1), in view of Dooley et al. (US 20220129804 A1), Leehman et al. (US 20050043976 A1), and Heckman et al. (US 20190207968 A1).
Regarding Claim(s) 14 and 36. While Fleiss/Dooley/Leehman teach classifications, subclassifications, summing scores, and project accuracy cost scores; neither appear to teach summing classification scores. However, Fleiss/Lehman in view of the analogous art of Heckman (i.e. project planning) does teach: The computer-implemented system of claim 10, wherein the cost accuracy determination module generates the project cost accuracy score by summing together a classification score generated for each of the plurality of cost classifications, and wherein the classification scores are determined by summing together a subclassification score for each of the plurality of cost subclassifications associated with each of the plurality of classifications. (Heckman, [115]; Specifically, the target maturity level values for all of the subcategories of a particular category may be combined to generate the target risk management level value for that category. In block 448, the enterprise system may calculate a target maturity level for each core or special activity area based on the maturity levels determined in block 446 and Heckman, [128]; the processor may determine or compute an overall to-be CS&P framework profile or risk level for the CS&P program based on a weighted sum/average of values given with each of a plurality of risk management categories).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of as Fleiss/Leehman teach categories, subcategories, and scores with the teachings of Heckman including summing subcategory scores in order to generate target levels for each category (Heckman, [115]; Specifically, the target maturity level values for all of the subcategories of a particular category may be combined to generate the target risk management level value for that category. In block 448, the enterprise system may calculate a target maturity level for each core or special activity area based on the maturity levels determined in block 446).
Regarding Claim(s) 15. Fleiss/Leehman teaches: The computer-implemented system of claim 14, wherein the cost accuracy determination module generates the project cost accuracy score by employing one or more project cost measurement techniques. (Fleiss, [co. 33, l. 11-16 ]; FIG. 8A illustrates a process flow for a project costing method for determining project element costs in accordance with one embodiment of the present design. Project element costs may include, but is not limited to, cost of a project requirement, cost-expended-to-date, cost-to-complete, and the total project cost).
Regarding Claim(s) 17. teaches: The computer-implemented system of claim 14, wherein the project cost accuracy determination module generates the project cost accuracy score by employing one or more project cost comparative analysis techniques. (Fleiss, [co. 16, l. 23-26]; An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs and Fleiss, [co. 33, l. 11-16 ]; FIG. 8A illustrates a process flow for a project costing method for determining project element costs in accordance with one embodiment of the present design. Project element costs may include, but is not limited to, cost of a project requirement, cost-expended-to-date, cost-to-complete, and the total project cost). Examiner notes the system compares actual cost to estimated and further use cost expended to date
Regarding Claim(s) 18 and 40. teaches: The computer-implemented system of claim 17, wherein the one or more project cost comparative analysis techniques comprise one or more of an analogous estimation technique, a bottom-up estimation technique, a three-point estimation technique, a parametric estimation technique, an expert judgment estimation technique, and a reserve analysis estimation technique. (Fleiss, [co. 15, l. 60-64]; Baseline processor 337 may generate and store sequential project baselines for multiple concurrent projects. The resultant baseline quality metrics may indicate incremental measures for determining a project's progress at any point in time and comparisons with past estimates… A new project baseline may be created in response to requirements changes and/or updates to schedule items that may arise during the project development activities. Previously generated baselines may be used as a historical basis for determining project impacts). Examiner interprets the above citation to be an analogous estimation technique.1
Regarding Claim(s) 24 and 46. While Fleiss/Leehman teach risk categories, and sub-categories; Fleiss/Leehman in view of Heckman more explicitly teaches: The computer-implemented system of claim 19, wherein the project risk assessment module comprises: a risk categorization module for categorizing the project risk data into a plurality of project risk categories, wherein each of the plurality of project risk categories includes a plurality of project risk subcategories, (Heckman, [29]; To develop a framework profile, an organization can review all of the categories and subcategories and, based on business drivers and a risk assessment, determine which are most important. They can also add categories and subcategories as needed to address specific organization's risks and Heckman, [108]; the identification of applicable categories and subcategories may be based on input from the program and technical review phase (i.e., from block 402), the current and/or target risk framework profile score(s) (i.e., from blocks 414 and/or 428), and any identified cybersecurity/privacy risk gaps or issues (i.e., from block 430).
wherein the categorization module generates risk category data, and (Heckman, [115]; Specifically, the target maturity level values for all of the subcategories of a particular category may be combined to generate the target risk management level value for that category. In block 448, the enterprise system may calculate a target maturity level for each core or special activity area based on the maturity levels determined in block 446).
a risk scoring module for receiving and processing the risk category data and for generating the inherent risk score. (Heckman, [115]; Specifically, the target maturity level values for all of the subcategories of a particular category may be combined to generate the target risk management level value for that category. In block 448, the enterprise system may calculate a target maturity level for each core or special activity area based on the maturity levels determined in block 446).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of as Fleiss/Leehman teach categories, subcategories, and scores with the teachings of Heckman including summing subcategory scores in order to generate target levels for each category (Heckman, [115]; Specifically, the target maturity level values for all of the subcategories of a particular category may be combined to generate the target risk management level value for that category. In block 448, the enterprise system may calculate a target maturity level for each core or special activity area based on the maturity levels determined in block 446).
Regarding Claim(s) 25 and 47. Fleiss/Leehman/Heckman teaches: The computer-implemented system of claim 24, wherein the risk scoring module determines the inherent risk score by summing together a category risk score generated for each of the plurality of project risk categories, and wherein the category risk scores are determined by summing together a subcategory risk score for each of the plurality of project risk subcategories associated with each of the plurality of project risk categories, and wherein the inherent risk score is determined by summing together the category risk scores. (Heckman, [115]; Specifically, the target maturity level values for all of the subcategories of a particular category may be combined to generate the target risk management level value for that category. In block 448, the enterprise system may calculate a target maturity level for each core or special activity area based on the maturity levels determined in block 446).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of as Fleiss/Leehman teach categories, subcategories, and scores with the teachings of Heckman including summing subcategory scores in order to generate target levels for each category (Heckman, [115]; Specifically, the target maturity level values for all of the subcategories of a particular category may be combined to generate the target risk management level value for that category. In block 448, the enterprise system may calculate a target maturity level for each core or special activity area based on the maturity levels determined in block 446).
Regarding Claim(s) 26 and 48. While Fleiss/Heckman teaches risk scores and thresholds, neither appear to teach recommending an action. However, Fleiss/Heckman in view of the analogous art of Dooley does teach: The computer-implemented system of claim 25, wherein the risk scoring module compares one or more of the category risk score, the subcategory risk score, or the inherent risk score with a threshold risk score, and if the risk score is above the threshold risk score, then the project risk assessment module recommends a project risk action. (Dooley, [35-36]; As another example, if when the benchmark data (internal or external) is considered, a threshold value for additional mitigation is 7 as opposed to 10 datasets, then in response, the threshold value for the number of datasets to trigger this mitigation action may be changed from 10 to 7. Similarly, the risk models may consider the benchmark data and revise their predictions or classifications in evaluating similar “high risk” or “higher risk” projects and Dooley, [49]; in some embodiments, a form of decision process may be used to determine if a task risk assessment that exceeds a threshold value is sufficient to cause the system to recommend or require an additional (or modified) mitigation procedure).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including an inherent risk score, with the teachings of Dooley including a risk categorization process in order to determine what category of risk are highest contributors to risk and determine if mitigation is needed. (Dooley, [09]; Embodiments are also directed to determining if an additional or modified mitigation process or technique should be used for a task, project, or organization. This determination may be based at least in part on considering whether a risk metric for the task, project, or organization exceeds a threshold or trigger value. In some embodiments, a risk metric may take the form of a risk vector that comprises risk contributions from multiple categories or types of risk (such as regulatory, credit, IP, political, reputation, etc.). The individual risk contributions may be combined into a single metric or value based on a set of weights, a form of a norm or distance measure, etc).
Regarding Claim(s) 27 and 49. Fleiss teaches: a control scoring module for receiving and processing the control category data and for generating the project control score. (Fleiss, [co. 20, li. 39-50]; The present method may multiply individual evaluation score for each project by the weight assigned for the criterion, thus generating an evaluation score. If, for example, a user wishes to allocate greater weight to cost of an individual project than return on investment during the first year of the individual project than is provided by default, such a difference may be reflected in a user defined weighting for specified criterion. The process flow arrangement may add the generated scores and sum each measured project criteria for each project. The scores generated may provide input to the mechanized facility, illustrated in FIG. 4A, to determine an ordered ranking of proposed projects. One example of ordering is ordering from highest total project score down to the lowest generated score).
While Fleiss teaches control data and scores, Fleiss does not appear to teach subcategories. Fleiss/Leehman teaches: The computer-implemented system of claim 24, wherein the project control assessment module comprises: a control categorization module for categorizing the project control data into a plurality of project control categories, wherein each of the plurality of project control categories includes a plurality of project control subcategories, wherein the control categorization module generates control category data, and (Leehman, [44]; Cost Sub-Categories 510 and Leehman, [54]; Administration: The cost of labor supplied via internal staffing dedicated to information capture and analysis, to include data entry and reporting and Leehman, [55]; Management: The cost of labor supplied via internal staffing dedicated to the supervision and decision making function of the tire management program).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss including project scores and a plurality of categories that generate category data with the teachings of Leehman including subcategories in order to have a better understanding of cost factors such as services, products, shipping costs, etc. and allow for thresholds on each value (Leehman, [20]; For an additional example, assume that the business entity includes a shipping division with a fleet of trucks. Further assume that major cost category C is emergency road service for the trucks of the fleet. Cost subcategory C1 may be service, which would represent the accumulated cost of servicing the trucks when breakdowns occur. The associated business process, P9, is road service, which details the operations needed to perform emergency road service. The associated KPI, KPI-8, can be measured as downtime per service call).
Regarding Claim(s) 37. Fleiss teaches: The computer-implemented method of claim 36, further comprising generating the project cost accuracy score by applying one or more project cost measurement techniques to the cost classification data. (Fleiss, [co. 33, l. 11-16 ]; FIG. 8A illustrates a process flow for a project costing method for determining project element costs in accordance with one embodiment of the present design. Project element costs may include, but is not limited to, cost of a project requirement, cost-expended-to-date, cost-to-complete, and the total project cost).
Regarding Claim(s) 39. Fleiss teaches: The computer-implemented method of claim 36, further comprising generating the project cost accuracy score by applying one or more project cost comparative analysis techniques to the cost classification data. (Fleiss, [co. 16, l. 23-26]; An actual cost metric compares actual cost incurred to date versus projected, or estimated, budget funding breakouts mapped to baseline deliverable items, and may track and sum project, and portfolio costs and Fleiss, [co. 33, l. 11-16 ]; FIG. 8A illustrates a process flow for a project costing method for determining project element costs in accordance with one embodiment of the present design. Project element costs may include, but is not limited to, cost of a project requirement, cost-expended-to-date, cost-to-complete, and the total project cost). Examiner notes the system compares actual cost to estimated and further use cost expended to date.
Claim(s) 16, 28, 38, and 50 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fleiss et al. (US 8543438 B1), in view of Dooley et al. (US 20220129804 A1), Leehman et al. (US 20050043976 A1), Heckman et al. (US 20190207968 A1), and Jiang et al. (US 20200081933 A1).
Regarding Claim(s) 16 and 38. While Fleiss teaches cost measurement techniques, Fleiss does not appear to explicitly teach: The computer-implemented system of claim 15, wherein the one or more project cost measurement techniques comprises one or more of a percentage deviation technique, a root mean square error (RMSE) technique, a mean absolute error (MAE) technique, and a standard deviation technique. However, Fleiss in view of the analogous art of Jiang (i.e. project management) does teach the entirety of the limitation: (Jiang, [15]; in this example, in times of peak demand (e.g., during rush hour) where dynamically-determined costs are typically high, users can expect to pay no more than the 80% percentile value for this service. Other statistical measures can be utilized. For instance, the mean value or a value corresponding to a number of standard deviations from the mean value can also be used. In addition, different statistical measures may be used for different geographic regions or even for different subregion cluster pairs within the same geographic region).
It would have been obvious to try by one of ordinary skill in the art at the time the invention was made, to use a standard deviation cost technique of Jiang and incorporate it into the system of Fleiss since the system performs a plurality of cost techniques and the system would have performed the same regardless of the type of cost technique used and one of ordinary skill in the art could have pursued the known potential solutions with reasonable expectation of success (calculating cost techniques). (See MPEP2143(E) – Obvious to try rationale).
Regarding Claim(s) 28 and 50. While Fleiss/Leehman teach a plurality of assessments and subcategories provided to users, neither appear to explicitly teach a query for the assessments. However, Fleiss/Leehman in view of the analogous art of Jiang (i.e. project management) does teach: The computer-implemented system of claim 27, wherein the each of the plurality of project control subcategories has a plurality of assessment queries associated therewith. (Jiang, [19]; In addition, the two-step translation process to translate geographic locations (e.g., geographic coordinates) to database search keys (e.g., cluster identifiers) provides ensures that not only can the query for service metrics be performed in real-time in response to session data from users, but that the translation process is flexible enough such that the clusters can be redefined in response to altered usage or demand patterns).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the disclosed invention to have combined the teachings of Fleiss/Leehman including a plurality of assessments and subcategories provided to users with the teachings of Jiang including assessment queries in order to real time responses and reduce computing resources (Jiang, [19]; pre-computing the service metrics can significantly reduce the amount of computing power needed to maintain a steady and acceptable user experience (e.g., delays due to computational latencies). In addition, the two-step translation process to translate geographic locations (e.g., geographic coordinates) to database search keys (e.g., cluster identifiers) provides ensures that not only can the query for service metrics be performed in real-time in response to session data from users, but that the translation process is flexible enough such that the clusters can be redefined in response to altered usage or demand patterns).
Claim(s) 51 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fleiss et al. (US 8543438 B1), in view of Dooley et al. (US 20220129804 A1), Leehman et al. (US 20050043976 A1), and Jiang et al. (US 20200081933 A1), Heckman et al. (US 20190207968 A1), and Misra et al. (US 20240192993 A1).
Regarding Claim 51, While Fleiss/Leehman/Jiang teach categorizing data, categories, and subcategories; they do not appear to teach ESG values. However, Fleiss/Leehman/Jiang in view of the analogous art of Misra (i.e. project reporting) teaches The computer-implemented method of claim 49, further comprising: categorizing ESG data forming part of the project data into a plurality of ESG categories, wherein each of the plurality of ESG categories includes a plurality of ESG subcategories, and generating ESG category data, and (Misra, [07]; In some implementations computing a dimension indicator score for the ESG dimension comprises: processing a respective knowledge element using a first machine learning classifier to classify the knowledge element as belonging to one of multiple categories, the categories comprising ESG categories and one non-ESG category; determining whether the knowledge element is classified as belonging to an ESG category; in response to determining that the knowledge element is classified as belonging to an ESG category).
receiving and processing the ESG category data and generating an ESG control score indicative of a performance of the enterprise in attaining ESG related goals. (Misra, [04]; wherein the ESG disclosures relate to one or more ESG dimensions; computing, using the obtained data, a vulnerability indicator score for each of the ESG dimensions, wherein a vulnerability indicator score for an ESG dimension represents a measure of latent vulnerability with respect to the ESG dimension; computing, using the obtained data, a descriptive distribution score for each of the ESG dimensions, wherein the descriptive distribution scores represent a distribution of descriptions of the ESG dimensions within the knowledge source; determining, using the vulnerability indicator scores and the descriptive distribution scores).
It would have been obvious to try by one of ordinary skill in the art at the time the invention was made, to use ESG data of Misra and incorporate it into the system of Fleiss/Leehman since the system performs categorizing a plurality of data and the system would have performed the same regardless of the type of cost technique used and one of ordinary skill in the art could have pursued the known potential solutions with reasonable expectation of success (categorizing data). (See MPEP2143(E) – Obvious to try rationale).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/JEREMY L GUNN/ Examiner, Art Module 3624
1 Analogous estimation technique - Baseline processor 337 may generate and store sequential project baselines for multiple concurrent projects. The resultant baseline quality metrics may indicate incremental measures for determining a project's progress at any point in time and comparisons with past estimates. < https://www.google.com/search?q=analogous+estimation+technique >
Prosecution Insights