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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on Sep. 8, 2026 has been entered.
Status of the Claims
Claims 1-4, 6-10, 12-15 and 17-20 are all the claims pending in the application.
Claims 21-23 are cancelled.
Claims 1-4, 9, 10, and 20 are amended.
Claims 1-4, 6-10, 12-15 and 17-20 are rejected.
The following is a Non-Final Office Action in response to amendments and remarks filed Sep. 8, 2026.
Response to Arguments
Regarding the 101 rejections, the rejections are maintained for the following reasons. First, Step 2A Prong 1, Applicant assert the claims do not recite an abstract idea. Examiner respectfully does not find this assertion persuasive because the present claims and Specification make clear the invention involves analyzing dimensions of affecting compensation (i.e., salaries), see ¶¶[0002], [0018] of the Specification as filed.
Second, under Step 2A Prong 2, Applicant asserts the claims reflect an improvement because the claims solve problems related disparate system sharing information. Examiner respectfully does not find this assertion persuasive because showing an improvement involves showing a technical solution to a technical problem and failing to share information is not a technical problem, it is a business or administrative problem. Further, Examiner finds the use of a neural network in solving this problem, even with the newly amended limitations including the input data and the recalculation, is still recited too broadly and generally to be more than mere instructions to apply the exception.
Third, under Step 2B, Applicant asserts the claims reflect a technology based solution rather than mere instructions to apply an exception. Again, Examiner respectfully does not find this assertion persuasive because showing an improvement involves showing a technical solution to a technical problem and failing to share information is not a technical problem, it is a business or administrative problem.
Regarding the 103 rejections, the rejections are withdrawn at least because the cited references do not teach incorporating economic indicators and job market dynamics to adjust compensation estimates as claimed in the newly amended limitations.
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 1-4, 6-10, 12-15 and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Under Step 1 of the patent eligibility analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention. Applying Step 1 to the claims it is determined that: claims 1, 4, and 6-9 are directed to a process; and claims 2, 3, 12-15, and 17-20 are directed to a machine. Therefore, we proceed to Step 2.
Independent Claims
Under Step 2A Prong 1 of the patent eligibility analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories or “buckets” of patent ineligible subject matter that amount to a judicial exception to patentability.
The independent claims recite an abstract idea. Specifically, the independent claims recite an abstract idea in the limitations (emphasized):
…receiving, via a user interface, a selection of criteria to generate a scheme for a dimension of an entity according to a level of granularity;
obtaining, using the cloud computing architecture configured to aggregate data associated with computing resources provided to devices in accordance with a plurality of models, a benchmark for the dimension by:
executing a function configured for the cloud computing architecture to access, based on the plurality of disparate systems, criteria of a second dimension similar to the dimension of the entity, the plurality of disparate systems including a human resource database, a payroll database, and a benefits system database; and
generating, using a neural network function operated by a workforce compensation module that processes information obtained from a data warehouse module and a market pay database, the benchmark for the second dimension according to the criteria of the second dimension and the level of granularity, wherein the neural network incorporates geographic and economic development indicators and job market dynamics to generate an adjusted compensation estimate that mitigates for potential biases in the data aggregated from the plurality of disparate systems;
obtaining a metric based on information of employees for the dimension of the entity;
identifying a score for data aggregated from the disparate systems, the score indicating a candidate benchmark for the dimension of the entity;
generating, responsive to the metric not satisfying the score, the scheme with a portion of the data aggregated from the plurality of disparate systems to adjust the metric to satisfy the score;
responsive to the metric satisfying the score, identifying that the metric does not satisfy the benchmark by comparing the benchmark for the second dimension against the metric;
generating responsive to the metric not satisfying the benchmark, the scheme with a second portion of the data aggregated from the disparate systems to adjust the metric to satisfy the benchmark based on the selection of criteria for the dimension of the entity, wherein the second portion of the data aggregated includes the portion of data aggregated from the disparate systems;
generating a plurality of filters with the user interface comprising at least two of: a first filter configured with a first interactive graphical user element corresponding to a slide rule; a second filter configured with a second interactive graphical user element capable of adjusting a level of granularity with which to compare benchmarks, a third filter configured with a third graphical user interface element configured to select a record associated with the dimension of the entity and a fourth graphical user interface element capable of providing a display including the benchmark for the dimension of the entity;
generating responsive to the generation of the scheme, a second user interface within the user interface to display the plurality of filters indicating the generated scheme and to adjust the metric associated with the entity at the level of granularity, wherein the second user interface includes a graphical user element that is configured to adjust a geographic level of the level of granularity for the benchmark at the dimension of the entity, the geographic level including at least one of national, state, or regional;
receiving a selection of at least one of the plurality of filters and the geographic level of granularity for the benchmark;
updating, by the computer system, responsive to the selection via the second user interface, the benchmark based on execution of the neural network with an input corresponding to the selection of the at least one of the plurality of filters and the geographic level of granularity;
generating, by the computer system, a graphical representation of benchmarks by geographic location at multiple levels of granularity, wherein the graphical representation is dynamically updated in real time based on user selection of at least two filters, and wherein values of the benchmark displayed are recalculated by the neural network responsive to changes in both the geographic level of granularity and the selection of the at least two filters; and
transmitting for display on a display device coupled with the computer system, the generated second user interface with the plurality of filters.
These limitations recites an abstract idea because these limitation encompass commercial or legal interactions. These limitations encompass commercial or legal interactions because these limitations encompass marketing or sales activities or behaviors; business relations (i.e., market research). That is, these limitations encompass assessing salaries of employees to determine their relative levels of pay (e.g., relative to comparable employees in the same city), and adjusting the relative levels based on various factors, to determine appropriate salaries (e.g., for new employees). Claims that encompass commercial or legal interactions fall within the “Certain Methods of Organizing Human Activity”. Claims 1-3 recite an abstract idea.
Under Step 2A Prong 2 of the patent eligibility analysis, it must be determined whether the identified, recited abstract idea includes additional elements that integrate the abstract idea into a practical application.
The additional elements of the independent claims do not integrate the abstract idea into a practical application. The independent claims recite the additional elements (emphasized):
…receiving, via a user interface, a selection of criteria to generate a scheme for a dimension of an entity according to a level of granularity;
obtaining, using the cloud computing architecture configured to aggregate data associated with computing resources provided to devices in accordance with a plurality of models, a benchmark for the dimension by:
executing a function configured for the cloud computing architecture to access, based on the plurality of disparate systems, criteria of a second dimension similar to the dimension of the entity, the plurality of disparate systems including a human resource database, a payroll database, and a benefits system database; and
generating, using a neural network function operated by a workforce compensation module that processes information obtained from a data warehouse module and a market pay database, the benchmark for the second dimension according to the criteria of the second dimension and the level of granularity, wherein the neural network incorporates geographic and economic development indicators and job market dynamics to generate an adjusted compensation estimate that mitigates for potential biases in the data aggregated from the plurality of disparate systems;
obtaining a metric based on information of employees for the dimension of the entity;
identifying a score for data aggregated from the disparate systems, the score indicating a candidate benchmark for the dimension of the entity;
generating, responsive to the metric not satisfying the score, the scheme with a portion of the data aggregated from the plurality of disparate systems to adjust the metric to satisfy the score;
responsive to the metric satisfying the score, identifying that the metric does not satisfy the benchmark by comparing the benchmark for the second dimension against the metric;
generating responsive to the metric not satisfying the benchmark, the scheme with a second portion of the data aggregated from the disparate systems to adjust the metric to satisfy the benchmark based on the selection of criteria for the dimension of the entity, wherein the second portion of the data aggregated includes the portion of data aggregated from the disparate systems;
generating a plurality of filters with the user interface comprising at least two of: a first filter configured with a first interactive graphical user element corresponding to a slide rule; a second filter configured with a second interactive graphical user element capable of adjusting a level of granularity with which to compare benchmarks, a third filter configured with a third graphical user interface element configured to select a record associated with the dimension of the entity and a fourth graphical user interface element capable of providing a display including the benchmark for the dimension of the entity;
generating responsive to the generation of the scheme, a second user interface within the user interface to display the plurality of filters indicating the generated scheme and to adjust the metric associated with the entity at the level of granularity, wherein the second user interface includes a graphical user element that is configured to adjust a geographic level of the level of granularity for the benchmark at the dimension of the entity, the geographic level including at least one of national, state, or regional;
receiving a selection of at least one of the plurality of filters and the geographic level of granularity for the benchmark;
updating, by the computer system, responsive to the selection via the second user interface, the benchmark based on execution of the neural network with an input corresponding to the selection of the at least one of the plurality of filters and the geographic level of granularity;
generating, by the computer system, a graphical representation of benchmarks by geographic location at multiple levels of granularity, wherein the graphical representation is dynamically updated in real time based on user selection of at least two filters, and wherein values of the benchmark displayed are recalculated by the neural network responsive to changes in both the geographic level of granularity and the selection of the at least two filters; and
transmitting for display on a display device coupled with the computer system, the generated second user interface with the plurality of filters.
These additional elements do not integrate the abstract idea into an practical application for the following reasons. First, the additional elements of receiving selection criteria, obtaining and aggregating data according to models, transmitting and displaying the various user interfaces, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass a generic computer function of receiving and displaying data (e.g. receiving user input and outputting results of an analysis), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
Second, the additional elements of the various steps being performed using cloud computing architecture to execute a function based on disparate systems, as claimed, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only a general link to a field of use or technological environment, see MPEP 2106.05(h) (discussing Affinity Labs). That is, although these additional elements do limit the use of the abstract idea, this type of limitation merely confines the use of the abstract idea to a particular technological environment (cloud computing) and does not integrate the abstract idea into a practical application or add an inventive concept to the claims.
Third, the additional elements of using a neural network to process information and perform the claimed calculations, when considered individually or in combination, do not integrate the abstract idea into a practical application because the use of the neural network is recited sufficiently broadly and generally such that it amounts to no more than mere instructions to apply the exception, see MPEP 2106.05(f).
Fourth, the additional elements of generating the filters with an interactive graphical user element corresponding to a slide rule, the second interactive graphical user element capable of adjusting a level of granularity, the third filter to select a record, and a fourth graphical user interface element displaying the bench mark for the dimension, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are only using software to tailor information and provide it to a user, which is no more than mere instructions to apply the exception, see MPEP 2106.05(f) (discussing Intellectual Ventures I LLC v. Capital One Bank (USA)).
Fifth, the additional elements of receiving a selection and generating and updating the graphical representation of benchmarks, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass a generic computer function of receiving and sending data (e.g. receiving user input and displaying outputs), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
The independent claims further recite “by a computer system comprising one or more processors coupled with memory”, a “non-transitory computer readable storage media including instructions” and “one or more processors coupled with memory, the one or more processors”. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components. Claims 1-3 are directed to an abstract idea.
Under Step 2B of the patent eligibility analysis, the additional elements are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea (i.e., an innovative concept).
The independent claims do 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 amount to no more than mere instructions to apply the exception and a general link to a field of use. Mere instructions to apply an exception using generic computer components cannot and a general link to a field of use provide an inventive concept. Claims 1-3 are not patent eligible.
Dependent Claims
The dependent claims are rejected under 35 USC 101 as directed to an abstract idea for the following reasons.
Claims 4, 10, and 15 recite the additional elements of providing a notification via text or email. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass a generic computer function of sending data (e.g. sending data using communication software), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
Claims 6, 12, and 17 recite the additional elements of filtering based on a menu selection. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional element are no more than using software to tailor information and provide it to a user, which is not more than mere instructions to apply the exception, see MPEP 2106.05(f) (discussing Intellectual Ventures I LLC v. Capital One Bank (USA)).
Claims 7, 13, and 18 recite the same abstract idea as the independent claims because providing alerts in response to an update of a benchmark is a part of performing market research (e.g., notifying changes in the research).
Claims 8, 14, and 19 recite the same abstract idea as the independent claims because determining a benchmark or a second dimension is a part of performing market research (e.g., identifying multiple, relevant metrics like salaries and bonuses).
Claims 9 and 20 further recite the additional elements of generating a third user interface to display a second report. These additional elements, when considered individually or in combination, do not integrate the abstract idea into a practical application because the additional elements encompass a generic computer function of sending data (e.g. sending data for display), see MPEP 2106.05(f)(2) (noting the use of computers in their ordinary capacity to receive, store, or transmit data does not integrate a judicial exception into a practical application).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRENDAN S O'SHEA whose telephone number is (571)270-1064. The examiner can normally be reached Monday to Friday 11-7.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan Uber can be reached at (571) 270-3923. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BRENDAN S O'SHEA/ Examiner, Art Unit 3626
Prosecution Insights