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 1-18, 20-40, and 42-52 have been reviewed and are under consideration by this office action.
Notice to Applicant
The following is a Non-Final Office action. Applicant, on 07/21/2026, amended claims, cancelled claim 19 and 41, and added claim 52. Claims 1-18, 20-40, and 42-52 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The amended claims overcome the 103 Rejections for claims 1 and 30 and are therefore withdrawn. The arguments regarding claim 52 are moot in view of the new line of 103 Rejections.
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 at Step 2A-P1, that claims are analyzed at an excess level of generality. Applicant further asserts claims recite a computer implemented assessment architecture that works in coordination.
Examiner respectfully disagrees. The claims recite a plurality of additional elements addressed in Step 2A-P2 and 2B. The claims are directed towards assessing 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 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) which are commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations).
Applicant contends that the claims recite specialized processing architecture that requires a specific arrangement of computer implemented components and harmonizes files formats.
Examiner respectfully disagrees. The plurality of modules and coordination are analysed both individually as well as in combination in Step 2A-P2 and 2B. Further the harmonization of data is recited at a high level of generality and does not match the fact patterns of Example 42 (although not specifically argued).
Applicant contends at Step 2A-P2 that the claims as amended recite a practical application and not just generic use of a computer.
Examiner respectfully disagrees. The determination and output of recommendations is a part of the abstract idea itself. The use of modules in coordination 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).
Applicant contends that cost… module provides a practical application as provides metrics and contributes to the recommendations.
Examiner respectfully disagrees. The provided metrics and scoring abstract concepts capable of being performed in the human mind and further recites certain methods of organizing human activity. The cost… module is addressed similarly as the modules above (See MPEP 2106.05(f) and MPEP 2106.05(h).
Applicant contends that the schedule functionality further provides a practical application.
Examiner respectfully disagrees. Schedule analysis is an abstract concept. The integrated module use is addressed above.
Applicant contends that risk functionality, control assessment functionality, benchmark comparison and scorecard functionality provide further practical applications.
Examiner respectfully disagrees. The recited functions such as risk categorization, dynamic risk scores, planning and monitoring data with respect to standards, creating comparative features that contextualize project metrics, benchmark based recommendation, etc. are all abstract concepts applied to a general purpose computing device.
Applicant contends at Step 2B, that the claims recite meaningful limitations. Applicant points to coordinated use of modules and further asserts the claims provide an ordered combination that use computer technology to perform coordinated assessment, benchmarking, etc.
Examiner respectfully disagrees. The additional elements are analysed both individually as well as in combination 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 of the analysis.
The 101 Rejection is updated and maintained 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 1-18, 20-40, and 42-52 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 configured to receive source data from a plurality of data sources, wherein the source data includes project data comprising project cost estimate data, project scope data, project schedule data, project risk data, stage data, gate data, and project control data, wherein the source data includes digital project documents in a plurality of different file formats, wherein the project readiness assessment module is configured to extract the project data from the source data and harmonize the extracted project data for processing by the computer-implemented system,
wherein the project readiness assessment module is configured to categorize the harmonized project data into a plurality of project categories including one or more of project objectives, project scope, project schedule, project cost, project risk, project controls, and project resources, wherein each of the plurality of project categories includes a plurality of project subcategories, generate category data, generate a subcategory assessment score for each project subcategory, generate a category assessment score for each project category based on associated subcategory assessment scores, generate the project assessment score based on the category assessment scores, and determine a project readiness of the project based on the project assessment score,
wherein the project readiness assessment module is further configured to process the stage data and gate data and determine, based on the project assessment score and a project gate associated with the project, whether the project is ready to proceed to a next project stage,
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 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,
wherein the integrated project assessment data comprises the project assessment score, the project cost accuracy score, the project schedule score, the inherent risk score, the project control score, the stage data, and the gate data,
wherein the processor generates benchmark project comparison data by comparing at least one of the project assessment score, the project cost accuracy score, the project schedule score, the inherent risk score, or the project control score against benchmark data associated with an industry, client, project profile, or project type,
wherein the processor generates one or more project remediation recommendations based on the integrated project assessment data and the benchmark project comparison data, and
a reporting module that 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, wherein the one or more reports include at least one comparative scorecard identifying at least one trend, outlier, or potential project challenge, and wherein the one or more reports display the one or more project remediation recommendations.
Regarding Claim(s) 30. A computer-implemented method for assessing a project, comprising receiving, by a processor executing computer-executable instructions stored in a memory, source data from a plurality of data sources, wherein the source data includes project data comprising project cost data including project cost estimate data, project scope data, project schedule data, project risk data, and project control data, stage data, and gate data, and wherein the source data includes digital project documents in a plurality of different file formats, extracting project data from the source data and harmonizing the extracted project data for processing by the processor;
assessing a project readiness using the computer-executable instructions stored in the memory and executed by the processor implementing a project readiness assessment module, the assessing including categorizing the harmonized project data into a plurality of project categories including two or more of project objectives, project scope, project schedule, project cost, project risk, project controls, and project resources, wherein each of the plurality of project categories includes a plurality of project subcategories, generating category data, generating a subcategory assessment score for each project subcategory, generating a category assessment score for each project category based on associated subcategory assessment scores, generating the project assessment score based on the category assessment scores, and determining a project readiness of the project based on the project assessment score,
processing the stage data and gate data and determining, based on the project assessment score and a project gate associated with the project, whether the project is ready to proceed to a next project stage,
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 project schedule data using computer-executable instructions stored in the memory and executed by the processor implementing 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 the 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,
wherein the integrated project assessment data comprises the project assessment score, the project cost accuracy score, the project schedule score, the inherent risk score, the project control score, the stage data, and the gate data,
generating benchmark project comparison data by comparing at least one of the project assessment score, the project cost accuracy score, the project schedule score, the inherent risk score, or the project control score against benchmark data associated with an industry, client, project profile, or project type,
generating one or more project remediation recommendations based on the integrated project assessment data and the benchmark project comparison 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, wherein the one or more reports include a comparative scorecard generated from the benchmark project comparison data and identifying at least one project trend, project outlier, or project challenge, and wherein the one or more reports display the one or more project remediation recommendations.
Regarding Claim 52, A computer-implemented method for assessing a project, comprising:
receiving, by a processor executing computer-executable instructions stored in a memory, source data associated with a project from a plurality of data sources, wherein the source data includes project-related information maintained in a plurality of different digital file formats;
extracting project data from the source data;
harmonizing the extracted project data by converting project information from the plurality of different digital file formats into a common project-data structure configured for processing by a project assessment system;
processing the harmonized project data using a plurality of assessment modules including a project readiness assessment module, a project diagnostic and cost assessment module, a project schedule assessment module, a project risk assessment module, and a project control assessment module;
generating, by the plurality of assessment modules, integrated project assessment data having a plurality of project assessment outputs associated with the project;
generating benchmark project comparison data by comparing one or more portions of the integrated project assessment data with benchmark data associated with projects, project profiles, clients, or industries, or combinations thereof;
generating one or more project remediation recommendations based upon the integrated project assessment data and the benchmark project comparison data; and
displaying, on a display device, one or more reports based on the integrated project assessment data, wherein the one or more reports include a comparative project assessment identifying at least one project trend, project outlier, project challenge, or project remediation recommendation.
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, 31-40, and 42-51 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) 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) 52 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), and Prieto et al. (US 20140052489 A1).
Regarding Claim 52, A computer-implemented method for assessing a project, comprising: receiving, by a processor executing computer-executable instructions stored in a memory, source data associated with a project from a plurality of data sources, (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, [co. 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, [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.
extracting project data from the source data; (Fleiss, [co. 10-11, l. 62-3]; The numbering system used in FIG. 2 indicates an exemplary arrangement for replicating users as need by the organizations projects, labeled from A through Z. The actual number of replicated roles created may be determined based on the size of the organization. However the number of roles may be greater or less than Z; certain roles may not be filled, such as the Business Analyst and 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).
processing the harmonized project data using a plurality of assessment modules including a project readiness assessment module, a project diagnostic and cost assessment module, a project schedule assessment module, a project risk assessment module, and a project control assessment module; (Fleiss, [co. 4, l. 30-33]; describes a plurality of modules and Fleiss, [col. 14, l. 50-55]; project readiness assessment module; Fleiss, [co. 22, l. 15-26]; describes risk assessment module and Fleiss, [co. 16, l. 16-25]; project diagnostic and cost assessment module and Fleiss, [co. 15-16, l. 55-5 and co. 16, l. 16-25]; project schedule assessment module and Fleiss, [co. 13, l. 55-61]; project control assessment module).
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: generating, by the plurality of assessment modules, integrated project assessment data having a plurality of project assessment outputs associated with the project; (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).
generating benchmark project comparison data by comparing one or more portions of the integrated project assessment data with benchmark data associated with projects, project profiles, clients, or industries, or combinations thereof; (Fleiss, [co. 14-15, l. 60-2]; Project Managers, Business Analysts, and Project Portfolio Managers may modify and update project content and/or incorporate changes to the project prior to establishing a baseline. As used herein, the term "baseline" represents a point in time and the status of the various components--requirements, schedule, labor, etc.--at that point in time. Server 304 may provide an execution environment to generate sequential project baselines, i.e. multiple baselines occurring one after another. Modules may communicate, interact, and operate with the database system and Fleiss, [co. 15, l. 40-50]; In one embodiment, the architecture 300 may determine that a new project baseline needs to be established. Baseline processor 337 may establish baselines for multiple projects, synchronously, in accordance with the architecture illustrated in FIG. 3B. The generated baseline comprises available project requirements and schedules so comparison can be made against previous dates and costs. A baseline may provide a complete project implementation plan defining and depicting project milestones and relevant project deliverables. At the time a baseline is established, baseline processor 337 functions may involve accessing the currently available contents from project database 306).
displaying, on a display device, one or more reports based on the integrated project assessment data, wherein the one or more reports include a comparative project assessment identifying at least one project trend, project outlier, project challenge, or project remediation recommendation. (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 and Fleiss, [co. 14, l. 40-52]; FIG. 3B is a logical architectural representation for the modules and databases involved in establishing a project schedule. Architecture 300 may establish project schedules for multiple projects. Each project schedule may include but is not limited to details for scheduled milestones, tasks including an assigned generic labor categories, durations, and dependencies. 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 and Fleiss, [co. 15, l. 44-48]; The generated baseline comprises available project requirements and schedules so comparison can be made against previous dates and costs. A baseline may provide a complete project implementation plan defining and depicting project milestones and relevant project deliverables).
While Fleiss/Dooley teach a plurality of modules with integrated data analysis receiving a plurality of data, neither appears to explicitly teach different file formats. However, Fleiss/Dooley in view of the analogous art of Prieto (i.e. project management) does teach: wherein the source data includes project-related information maintained in a plurality of different digital file formats; (Prieto, [44]; In response, the program analysis engine 120 can send a message to the program team to allocate additional man-hours (resources) to a particular activity that caused the disruption to prevent further issues. The message can be sent through multiple formats such as an email, SMS, automatic voice, sensor activation, among others, wherein the message can indicate further information relating to what the additional resources are intended to do, what their respective targets would be, time when they need to be allocated, what would be the impact of such allocation of resources on other parallel activities, additional cost impact through allocation of resources, or other suggestions).
harmonizing the extracted project data by converting project information from the plurality of different digital file formats into a common project-data structure configured for processing by a project assessment system; (Prieto, [74]; The system 100 can further be configured to generate signatures based on certain trends, types, or magnitudes of disruptions, efficiencies, or inefficiencies and store such signatures in program database 110. Such signatures can be generated based on experience of subject matter experts on anticipated disruptions or efficiencies, previous signatures in same or other programs, or common types of jerks or snaps that are generated in a particular type of project. The signatures can either be stored in the database 110 in an encoded format or any other known format, which can help their efficient retrieval or processing by the program analysis engine 120. The signatures can also be updated or new signatures can be formed as the program proceeds over a period time, wherein such update or formation can be based on earlier disruptions detected in the same program, new learning from other parts of the program or from other projects in the same program).
generating one or more project remediation recommendations based upon the integrated project assessment data and the benchmark project comparison data; and (Prieto, [66]; Project analysis engine 120 can be configured to generate recommendations to a project manager to manage disruption metric 122 in a program based on comparison between projected curve 210 and an actual curve 215, wherein the recommendations can comprise actions to minimize disruptions or maximize snaps in the program. The project analysis engine 120 can also help in optimizing disruption metric 122 of one or more project metrics 112 based on needs of the program manager. In some embodiments, analysis engine 120 can compare characteristics of disruption or efficiency indices (e.g., jerk and snap respectively) to known event signatures. When the characteristics suitably match such signatures, analysis engine 120 can construct a notification or recommendation on corrective actions as derived from information stored within or associated with the known event signatures).
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/Dooley including a plurality of modules with integrated data analysis receiving a plurality of data with the teachings of Prieto including multiple formats and harmonizing data in order to allow for a plurality of data types to be analyzed and further to aid in efficient retrieval and processing of data (Prieto, [74]; The signatures can either be stored in the database 110 in an encoded format or any other known format, which can help their efficient retrieval or processing by the program analysis engine 120. The signatures can also be updated or new signatures can be formed as the program proceeds over a period time, wherein such update or formation can be based on earlier disruptions detected in the same program, new learning from other parts of the program or from other projects in the same program. The signatures can be configured to store disruption or efficiency characteristics along with their possible reasons and resolutions).
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/Dooley including a plurality of modules with integrated data analysis receiving a plurality of data with the teachings of Prieto including generating recommendations in order to minimize disruptions in projects (Prieto, [66]; the recommendations can comprise actions to minimize disruptions or maximize snaps in the program. The project analysis engine 120 can also help in optimizing disruption metric 122 of one or more project metrics 112 based on needs of the program manager. In some embodiments, analysis engine 120 can compare characteristics of disruption or efficiency indices (e.g., jerk and snap respectively) to known event signatures. When the characteristics suitably match such signatures, analysis engine 120 can construct a notification or recommendation on corrective actions as derived from information stored within or associated with the known event signatures).
Examining Claims with Respect to Prior Art
Claims 1-18, 20-40, and 42-51, though directed to non-statutory subject matter, are deemed to define over the currently known prior art under 35 USC 102 and 103. Examiner interprets based upon the claim limitations that there is no currently known prior art that discloses the features relating to: “a project readiness assessment module configured to receive for assessing a project readiness of a project based on source data from a plurality of data sources; comprising project cost estimate data, project scope data, project schedule data, project risk data, stage data, gate data, and project control data, wherein the source data includes digital project documents in a plurality of different file formats, wherein the project readiness assessment module is configured to extract the project data from the source data and harmonize the extracted project data for processing by the computer-implemented system, wherein the project readiness assessment module is configured to categorize the harmonized project data into a plurality of project categories including one or more of project objectives, project scope, project schedule, project cost, project risk, project controls, and project resources, wherein each of the plurality of project categories includes a plurality of project subcategories, generate category data, generate a subcategory assessment score for each project subcategory, generate a category assessment score for each project category based on associated subcategory assessment scores, generate the project assessment score based on the category assessment scores, and determine a project readiness of the project based on the project assessment score, wherein the project readiness assessment module is further configured to process the stage data and gate data and determine, based on the project assessment score and a project gate associated with the project, whether the project is ready to proceed to a next project stage, 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, wherein the integrated project assessment data comprises the project assessment score, the project cost accuracy score, the project schedule score, the inherent risk score, the project control score, the stage data, and the gate data, wherein the processor generates benchmark project comparison data by comparing at least one of the project assessment score, the project cost accuracy score, the project schedule score, the inherent risk score, or the project control score against benchmark data associated with an industry, client, project profile, or project type, wherein the processor generates one or more project remediation recommendations based on the integrated project assessment data and the benchmark project comparison data, and a reporting module that 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, wherein the one or more reports include at least one comparative scorecard identifying at least one trend, outlier, or potential project challenge, and wherein the one or more reports display the one or more project remediation recommendations.”
The reason to withdraw the 35 USC 103 rejection of claims 1-20 in the instant application is because the prior art of record fails to teach the overall combination as claimed. Therefore, it would not have been obvious to one of ordinary skill in the art to modify the prior art to meet the combination above without unequivocal hindsight and one of ordinary skill would have no reason to do so. Upon further searching the examiner could not identify any prior art to teach these limitations. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, not renders obvious the Applicant’s claimed invention.
The closest prior arts of record are as follows:
Known Prior Art (patent)
US 8543438 B1
Labor resource utilization method and apparatus
US 20220129804 A1
Systems and Methods for Integrated Technology Risk Management
US 20050043976 A1
Method for improving business performance through analysis
US 20140052489 A1
TIME DERIVATIVE-BASED PROGRAM MANAGEMENT SYSTEMS AND METHODS
US 20050043976 A1
Method for improving business performance through analysis
US 20190207968 A1
Methods and Systems for Providing an Integrated Assessment of Risk Management and Maturity for an Organizational Cybersecurity/Privacy Program
US 20200081933 A1
PRE-COMPUTED SERVICE METRIC LOOKUP FOR A NETWORK-BASED SERVICE
US 20240192993 A1
SYSTEM AND METHOD FOR ESG REPORTNG BASED OPTIMIZED RESOURCE ALLOCATION ACROSS ESG DIMENSIONS
US 20070106599 A1
Method and apparatus for dynamic risk assessment
Known Prior Art (NPL)
Corsiglia, Frederic Anthony, Haidar, Hani, and Andrew Duncan Frost. "Risk Informed Work Selection." Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, November 2021
Known Prior Art (foreign)
AU2010200158B2
Methods and systems for assessing project management offices
Conclusion
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/JEREMY L GUNN/ Primary Examiner, Art Unit 3624
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