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 .
DETAILED ACTION
This non-final Office action is in response to applicant’s communication received on November 03, 2025, wherein claims 1, 3-4, 7-10, 12-13, and 16-19 (filed October 06, 2025) are currently pending.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 November 03, 2025 has been entered.
Response to Arguments
Applicant's arguments have been fully considered but they are geared towards the newly amended claims with newly added limitations. The newly amended claims are considered for the first time in the rejection below.
35 USC §101 discussion:
Applicant’s newly amended and added limitations do not help overcome the §101 rejection set forth in the previous Office action.
The claimed limitations are directed to optimizing scheduling strategy by using known abstract information (e.g. customer information (accounts information, etc.,), staff/employee/personnel information, historical information, etc., and where a lot of this information is also mathematical in nature (e.g. numbers, percentages, maximums/minimums, amounts, time, prediction/forecasting , etc.,); and then using that information for scheduling and making contact with customers (human activities). The models used by the claims are mathematical in nature. The limitations in the independent claims (1, 10, 19) and dependent claims (3-9, 12-18), under its broadest reasonable interpretation, covers the performance of the limitations as organizing human activities (commercial interactions (obligations; advertising, marketing or sales activities or behaviors; business relations) and clearly managing personal behavior and interactions between people (scheduling and following rules or instructions)) and also mathematical relationships, mathematical formulas or equations, mathematical calculations. (MPEP 2106.04; and also See 2019 Revised Patent Subject Matter Eligibility Guidance - Federal Register, Vol. 84, Vol. 4, January 07, 2019, pages 50-57). These amended and added limitation do not recite any technology or technical elements and neither show any improvement to any technology or technical environment. The technical terms recited in the claims are generic and general-purpose computers and/or computing elements/components/devices/etc., (for example, processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in Independent claim 1 and its dependent claims 3-9); computing apparatus, processors, memories, communication interface (using generic/general-purpose communication devices/components), machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in independent claim 10 and its dependent claims 12-18); and non-transitory computer readable storage medium, executable code (software), processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (independent claim 19)). As discussed below in the rejection the claimed abstract idea (claims) is not integrated into a practical applicant (see rejection below). The claims also do not recite any additional elements that are sufficient to amount to significantly more than the judicial exception (see rejection below). The generic/general- purpose computers and network/computing elements/components/devices/etc., are stated in an “apply-it” fashion to the abstract idea to only analyze/manipulate known type of abstract information and for abstract output (scheduling) and/or strategy/decision-making (optimizing scheduling and scheduling contacting customers). That is, the generic/general-purpose computers and network/computing elements/components/devices/etc., limitations/terms/elements are no more than mere instructions to apply the judicial exception (organizing human activities (commercial interactions (obligations; advertising, marketing or sales activities or behaviors; business relations) and clearly managing personal behavior and interactions between people (scheduling and following rules or instructions)) and also mathematical relationships, mathematical formulas or equations, mathematical calculations) using generic/general-purpose computer/computing components. It is not enough, however, to merely improve abstract processes by invoking a computer merely as a tool. Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1364 (Fed. Cir. 2020). The focus of the claims is simply to use computers and a familiar network as a tool to perform abstract processes (organizing human activities (commercial interactions (obligations; advertising, marketing or sales activities or behaviors; business relations) and clearly managing personal behavior and interactions between people (scheduling and following rules or instructions)) and also mathematical relationships, mathematical formulas or equations, mathematical calculations) involving simple information exchange. Accordingly, the additional elements in the claimed limitations do not integrate the abstract idea in to a practical application because it does not impose any meaningful limits on practicing the abstract idea — i.e. they are just post-solution/extra-solution activities.
Additionally, the additional elements recited in the claims (for example, processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in Independent claim 1 and its dependent claims 3-9); computing apparatus, processors, memories, communication interface (using generic/general-purpose communication devices/components), machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in independent claim 10 and its dependent claims 12-18); and non-transitory computer readable storage medium, executable code (software), processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (independent claim 19)) are insufficient to amount to significantly more than the judicial exception because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. The limitation recites using known and/or generic computing devices and software. For the role of a computer in a computer implemented invention to be deemed meaningful in the context of this analysis, it must involve more than performance of "well-understood, routine, [and] conventional activities previously known to the industry." Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (U.S. 2014), at 2359 (quoting Mayo, 132 S. Ct. at 1294 (internal quotation marks and brackets omitted)). These activities as claimed by the Applicant are all well-known and routine tasks in the field of art (see specification of Applicant’s application (for example, see Applicant’s specification at, for example, Figs. 1-2 [general-purpose/generic computers/processors/etc., and generic/general-purpose computing components/devices/etc.,], and ¶¶ 0036-0046 [general-purpose/generic computers/processors/etc., and generic/general-purpose computing components/devices/etc.,], 0050-0055 [general-purpose/generic computers/processors/etc., and generic/general-purpose computing components/devices/etc.,]) and/or the specification of the below cited art (in the rejection and PTO-892) and/or also as noted in the court cases in §2106.05 in the MPEP.). It should be noted that "the mere recitation of a generic computer cannot transform a patent ineligible abstract idea into a patent-eligible invention." Alice, at 2358. In Applicant’s newly added limitation the additional elements are generic/general-purpose and do not transform a patent ineligible abstract idea into a patent-eligible invention. None of the hardware offers a meaningful limitation beyond generally linking the system to a particular technological environment, that is, implementation via computers. Adding generic computer components to perform generic functions that are well-understood, routine and conventional, such as gathering data, performing calculations, and outputting a result would not transform the claim into eligible subject matter. Hence the claims do not amount to significantly more than the judicial exception.
Also see detailed §101 rejection below.
Prior art discussion:
Applicant argues that Pachauri does not explicitly state "analyzing ... the first data set to determine at least one proposed schedule for an attempt to contact the customer" (no disclosure of a proposed schedule because the schedule is already set). Examiner respectfully disagrees.
A proposed schedule is an already made schedule that can be implemented and/or that is modifiable – i.e. it is a created schedule that exists. This can be seen in Applicant’s specification where gathered information is analyzed and clearly a schedule is created but just called a “proposed” schedule (which is clearly an implementable schedule and can be implemented and modified if needed). Also, “attempting” to contact the customer is just taking an action to contact the customer (i.e. an action taken to contact the customer). Pachauri clearly shows actions being taken to contact the customer (attempting to contact the customer) and modifiable schedules (proposed and remain as “proposed” as they can be modified while the schedule is created with forecasting and predictions) which have been created using gathered and analyzed information. This can be seen where Pachauri states on paragraphs 0024-0026 “enhanced CRM system...goal dashboard that summarizes the number of calls...scheduled to make (proposed schedule not yet acted upon)...goal dashboard...predicted number of hours that will be spent (prediction means proposed)...using machine learning algorithms that create the prediction...goal dashboard may also present a summary...measure might be derived using a number and priority of tickets to be resolved within a time period (e.g., day, week, etc.).” Here the information is analyzed to create a schedule that can be used that when used make the staff/employees/etc., attempt to contact customers. Paragraphs 0075-0077 of Pachauri states “provide scheduling guidance...goal setting...call preparation” where it is clear that the scheduling guidance and goal setting is the proposed schedule (where the goal may not be being met) and that call preparation is part of “attempting” to contact (see with paragraph 0028 “(proposed scheduling by) prediction of the best time to contact the debtor/customer...prediction of the best time to contact the debtor/customer...by machine learning algorithm...determine time to contact debtor that results in the highest probability to actually make contact”).
Therefore, Pachauri indeed discloses Applicant limitation in its entirety of “analyzing, by the at least one processor, the first data set to determine at least one proposed schedule for an attempt to contact the customer; and generating, by the at least one processor based on a result of the analysis, a report that includes the proposed schedule.”
As per claim 5 arguments presented by the Applicant, Applicant’s arguments are geared towards a newly amended claims with newly added limitations. This newly amended claims with newly added limitations (changing the claim) is considered for the first time in the rejection below.
In regards to claim 6, Applicant argues that Pachauri fails to disclose the limitation "the proposed schedule includes at least five schedule items that indicate respective dates and respective times for making the attempt to contact the customer." Examiner respectfully disagrees.
The terms “items” is used very broadly in the claims and point to information that “indicate” dates and times (Applicant also provides nothing in the claims or the specification that defines what “indicate” means and as per the claims this just means the information has link/reference to/connection to date or time). Pachauri in paragraphs 0024-0025 states various information with connection/reference to (and include) dates and times used in making schedule where Pachauri states “daily goals, debt to collect daily, number of calls, money collected in a time period, (things to be done within a time period (e.g. day, week, etc.,)), credit profile, behavior information, account balance, etc., (all this information is used in scheduling when making the schedule and times plans for making calls to the debtor).” Paragraphs 0021-0029 (including paragraphs 0033-0034, 0037, 0041) shows even more other information used in planning schedules/scheduling (best time to contact) that also indicate dates and times, for example “time delays, hours per month, time researching, time non-productive, payment history, breakdown of the time the current total owed, a time where the debtor/customer may be relaxed and willing,” etc. Additionally, as explained above and repeated here, “attempting” to contact the customer is just taking an action to contact the customer (i.e. an action taken to contact the customer). Pachauri clearly shows actions being taken to contact the customer (attempting to contact the customer) and modifiable schedules (proposed and remain as “proposed” as they can be modified while the schedule is created with forecasting and predictions) which have been created using gathered and analyzed information. This can be seen where Pachauri states on paragraphs 0024-0026 “enhanced CRM system...goal dashboard that summarizes the number of calls...scheduled to make (proposed schedule not yet acted upon)...goal dashboard...predicted number of hours that will be spent (prediction means proposed)...using machine learning algorithms that create the prediction...goal dashboard may also present a summary...measure might be derived using a number and priority of tickets to be resolved within a time period (e.g., day, week, etc.).” Here the information is analyzed to create a schedule that can be used that when used make the staff/employees/etc., attempt to contact customers. Paragraphs 0075-0077 of Pachauri states “provide scheduling guidance...goal setting...call preparation” where it is clear that the scheduling guidance and goal setting is the proposed schedule (where the goal may not be being met) and that call preparation is part of “attempting” to contact (see with paragraph 0028 “(proposed scheduling by) prediction of the best time to contact the debtor/customer...prediction of the best time to contact the debtor/customer...by machine learning algorithm...determine time to contact debtor that results in the highest probability to actually make contact”). Also see explanation provided by examiner above for the independent claims argued limitation.
Therefore, Pachauri indeed discloses Applicant’s claim 6 limitation "the proposed schedule includes at least five schedule items that indicate respective dates and respective times for making the attempt to contact the customer" in its entirety.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 3-4, 7-10, 12-13, and 16-19 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claims contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Independent claims 1, 10, 19 state “reducing energy consumption.” However, neither the specification nor the previous set of claims discloses " reducing energy consumption." Therefore, the limitation "call capping operation that reduces energy consumption" constitutes new subject matter not disclosed in the specification or the claims when the application was filed and amendments cannot include new matter. 35 USC §132; MPEP §§ 706.03(o), 608.04, 706.03(c) 702, 702.02. Also, in amended cases, subject matter not disclosed in the original application is sometimes added and a claim directed thereto. Such a claim is rejected on the ground that it recites elements without support in the original disclosure under 35 U.S.C. 112, first paragraph, Waldemar Link, GmbH & Co. v. Osteonics Corp. 32 F.3d 556, 559, 31 USPQ2d 1855, 1857 (Fed. Cir. 1994); In re Rasmussen, 650 F.2d 1212, 211 USPQ 323 (CCPA 1981). Also See MPEP § 2163.06 - § 2163.07(b).
Dependent claims 3-4, 7-9, 12-13, 16-18 are rejected due their dependency on the independent claims as the dependent claims incorporate the limitations of the independent claims.
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, 3-4, 7-10, 12-13, and 16-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Regarding Step 1 (MPEP 2106.03) of the subject matter eligibility test per MPEP 2106.03, Claims 1, 3-4, 7-9 are directed to a method (i.e., process), claims 10, 12-13, 16-18 are directed to a computing apparatus (i.e. machine), and claims 19 are directed to non-transitory computer readable medium (i.e. product or article of manufacture). Accordingly, all claims are directed to one of the four statutory categories of invention.
(Under Step 2) The claimed invention is directed to an abstract idea without significantly more.
(Under Step 2A, Prong 1 (MPEP 2106.04)) The claims recite obtaining information/data (where the information itself is abstract in nature), data analysis and manipulation to determine more abstract information (optimizing scheduling – and using mathematical based concepts (discussed in the claims, including dependent claims, and specification) to determine schedules), and providing/displaying this determined data – for further decision-making. The claimed invention further uses mathematical steps to analyze and determine further data (see, for example dependent claims (statistical concepts, maximum determinations, and percentages; metrics, probabilities, etc.,) and specification (provides further mathematical details used to get data used in determining schedules)). The limitations of independent claims (1, 10, 19) and dependent claims (3-4, 7-9, 12-13, 16-18), under the broadest reasonable interpretation, covers methods of organizing human activity (managing personal behavior or relationships or interactions between people – scheduling and following rules or instructions; and commercial and/or legal interactions (activities or behaviors including obligations and contracts) in a call-center debt collection/recovery environment) and mathematical concepts (see, for example dependent claims (statistical concepts, maximum determinations, and percentages; metrics, probabilities, etc.,) and specification (provides further mathematical details used to get data used in determining schedules)). If a claims limitation, under its broadest reasonable interpretation, covers the performance of the limitation as fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including scheduling, social activities, teaching, and following rules or instructions), then it falls within the “organizing human activities” grouping of abstract ideas. (MPEP 2106.04; and also see 2019 Revised Patent Subject Matter Eligibility Guidance – Federal Register, Vol. 84, Vol. 4, January 07, 2019, pages 50-57). If a claims limitation, under its broadest reasonable interpretation, covers the performance of the limitation as mathematical relationships, mathematical formulas or equations, mathematical calculations then it falls within the Mathematical concepts grouping of abstract ideas. (MPEP 2106.04; and also see 2019 Revised Patent Subject Matter Eligibility Guidance - Federal Register, Vol. 84, Vol. 4, January 07, 2019, pages 50-57). Accordingly, since Applicant's claims fall under organizing human activities grouping and mathematical concepts grouping, the claims recite an abstract idea.
(Under Step 2A, prong 2 (MPEP 2106.04(d))) This judicial exception is not integrated into a practical application because but for the recitation of generic/general-purpose computers and/or computing components/elements/etc., for example, processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in Independent claim 1 and its dependent claims 3-4, 7-9); computing apparatus, processors, memories, communication interface (using generic/general-purpose communication devices/components), machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in independent claim 10 and its dependent claims 12-13, 16-18); and non-transitory computer readable storage medium, executable code (software), processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (independent claim 19) in the context of the claims, the claim encompasses the above stated abstract idea of organizing human activity (managing personal behavior or relationships or interactions between people – scheduling and following rules or instructions; and commercial and/or legal interactions (activities or behaviors including obligations and contracts) in a call-center debt collection/recovery environment) and mathematical concepts (see, for example dependent claims (statistical concepts, maximum determinations, and percentages; metrics, probabilities, etc.,) and specification (provides further mathematical details used to get data used in determining schedules)). As shown above, the claims and specification recite computers and/or computing components/elements/etc., which are recited at a high level of generality performing generic computer/system/network functions. (MPEP 2106.04; and also see 2019 Revised Patent Subject Matter Eligibility Guidance – Federal Register, Vol. 84, Vol. 4, January 07, 2019, page 53-55). The generic/general-purpose computer/computing elements/terms/limitations are no more than mere instructions to apply the judicial exception (the above abstract idea) in an apply-it fashion using generic/general-purpose computers, processors, and/or computer components/elements/ devices, etc., (as shown above). The CAFC has stated that it is not enough, however, to merely improve abstract processes by invoking a computer merely as a tool.. Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1364 (Fed. Cir. 2020). The focus of the claims is simply to use computers and a familiar network as a tool to perform abstract processes (organizing human activity (managing personal behavior or relationships or interactions between people – scheduling and following rules or instructions; and commercial and/or legal interactions (activities or behaviors including obligations and contracts) in a call-center debt collection/recovery environment) and mathematical concepts (see, for example dependent claims (statistical concepts, maximum determinations, and percentages; metrics, probabilities, etc.,) and specification (provides further mathematical details used to get data used in determining schedules))) involving simple information exchange. Carrying out abstract processes (as shown and discussed above) involving information exchange is an abstract idea. See, e.g., BSG, 899 F.3d at 1286; SAP America, 898 F.3d at 1167-68; Affinity Labs of Tex., LLC v. DIRECTV, LLC, 838 F.3d 1253, 1261-62 (Fed. Cir. 2016). And use of standard computers and networks to carry out those functions—more speedily, more efficiently, more reliably—does not make the claims any less directed to that abstract idea. See Alice Corp., 573 U.S. at 222-25; Customedia, 951 F.3d at 1364; Trading Techs. Int'l, Inc. v. IBG LLC, 921 F.3d 1084, 1092-93 (Fed. Cir. 2019); SAP America, 898 F.3d at 1167; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1314 (Fed. Cir. 2016); Electric Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1353, 1355 (Fed. Cir. 2016); Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 1370 (Fed. Cir. 2015); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014). Accordingly, the additional elements do not integrate the abstract idea in to a practical application because it does not impose any meaningful limits on practicing the abstract idea – i.e. they are just post-solution activities.
(Under Step 2B (MPEP 2106.05)) The independent claims and dependent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. The independent claims and dependent claims recite using known and/or generic/general-purpose computers and generic/general-purpose computing devices/components/elements/etc., and software (for example, processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in Independent claim 1 and its dependent claims 3-4, 7-9); computing apparatus, processors, memories, communication interface (using generic/general-purpose communication devices/components), machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in independent claim 10 and its dependent claims 12-13, 16-18); and non-transitory computer readable storage medium, executable code (software), processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (independent claim 19)). For the role of a computer in a computer implemented invention to be deemed meaningful in the context of this analysis, it must involve more than performance of "well-understood, routine, [and] conventional activities previously known to the industry." Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (U.S. 2014), at 2359 (quoting Mayo, 132 S. Ct. at 1294 (internal quotation marks and brackets omitted)). These activities as claimed by the Applicant are all well-known and routine tasks in the field of art – as can been seen in the specification of Applicant’s application (for example, see Applicant’s specification at, for example, Figs. 1-2 [general-purpose/generic computers/processors/etc., and generic/general-purpose computing components/devices/etc.,], and ¶¶ 0036-0046 [general-purpose/generic computers/processors/etc., and generic/general-purpose computing components/devices/etc.,], 0050-0055 [general-purpose/generic computers/processors/etc., and generic/general-purpose computing components/devices/etc.,]) and/or the specification of the below cited art (used in the rejection below and on the PTO-892) and/or also as noted in the court cases in §2106.05 in the MPEP. Further, "the mere recitation of a generic computer cannot transform a patent ineligible abstract idea into a patent-eligible invention." Alice, at 2358. None of the hardware offers a meaningful limitation beyond generally linking the system to a particular technological environment, that is, implementation via computers. Adding generic computer components to perform generic functions that are well‐understood, routine and conventional, such as gathering data, performing calculations, and outputting a result would not transform the claim into eligible subject matter. Abstract ideas are excluded from patent eligibility based on a concern that monopolization of the basic tools of scientific and technological work might impede innovation more than it would promote it. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims require no more than a generic computer to perform generic computer functions. The additional element(s) or combination of elements in the claim(s) other than the abstract idea per se amount(s) to no more than: (i) mere instructions to implement the idea on a computer, and/or (ii) recitation of generic computer structure that serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Applicant is directed to the following citations and references: Digitech Image., LLC v. Electronics for Imaging, Inc.(U.S. Patent No. 6,128,415); and (2) Federal register/Vol. 79, No 241 issued on December 16, 2014, page 74629, column 2, Gottschalk v. Benson. Viewed as a whole, the claims do not purport to improve the functioning of the computer itself, or to improve any other technology or technical field. Use of an unspecified, generic computer does not transform an abstract idea into a patent-eligible invention. Thus, the claim does not amount to significantly more than the abstract idea itself. See Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (U.S. 2014).
The dependent claims further define the independent claims and merely narrow the described abstract idea, but not adding significantly more than the abstract idea. The above rejection includes and details the discussion of dependent claims and the above rejection applies to all the dependent claim limitations. In summary, the dependent claims further state using obtained data/information (where the information itself is abstract in nature), data analysis and manipulation to determine more abstract information (optimizing scheduling – and using mathematical based concepts (discussed in the claims, including dependent claims, and specification) to determine schedules), and providing/displaying this determined data – for further decision-making. The claimed invention further uses mathematical steps to analyze and determine further data (see, for example dependent claims (statistical concepts, maximum determinations, and percentages; metrics, probabilities, etc.,) and specification (provides further mathematical details used to get data used in determining schedules)). These claims are directed towards organizing human activity (managing personal behavior or relationships or interactions between people – scheduling and following rules or instructions; and commercial and/or legal interactions (activities or behaviors including obligations and contracts) in a call-center debt collection/recovery environment) and mathematical concepts (see, for example dependent claims (statistical concepts, maximum determinations, and percentages; metrics, probabilities, etc.,) and specification (provides further mathematical details used to get data used in determining schedules)). This judicial exception is not integrated into a practical application because the claims and specification recite generic components (for example, processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in Independent claim 1 and its dependent claims 3-4, 7-9); computing apparatus, processors, memories, communication interface (using generic/general-purpose communication devices/components), machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (in independent claim 10 and its dependent claims 12-13, 16-18); and non-transitory computer readable storage medium, executable code (software), processors, machine learning (ML) model (no specifics provided and only stated use of some ML – also ML models are mathematical in nature), etc., (independent claim 19)) which are recited at a high level of generality performing generic computer functions. The dependent claims also merely recites post-solution/extra-solution activities (with generic/general-purpose computers and/or computing components/devices/etc.,). The additional elements do not integrate the abstract idea in to a practical application because it does not impose any meaningful limits on practicing the abstract idea – i.e. they are just post-solution/extra-solution activities. The dependent claims merely use the same general technological environment and instructions to implement the abstract idea without adding any new additional elements. Also, the dependent claims also do not include additional elements that are sufficient to amount to significantly more than the juridical exception because the additional elements either individually or in combination are merely an extension of 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.
Claims 1, 3-4, 7-8, 10, 12-13, 16-17, and 19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Pachauri et al., (US 2020/0265485) in view of Lombard et al., (US 11,233,905), further in view of Busbee et al., (US 2023/0031855).
As per claim 1, Pachauri discloses a method for optimizing a scheduling strategy for contacting a customer ((Applicant’s concept is also geared to debt collection) Abstract [CRM… artificial intelligence and machine learning…CRM provides…scheduling assistance…customer contact…call…target customer…schedules…dynamically adjusted…goals]; ¶¶ 0002 [customers…debt collection…customers owing money]), the method being implemented by at least one processor, the method comprising:
receiving, by the at least one processor, a first data set that relates to a customer account (¶¶ 0021-0022 [debtor’s (customer) account], 0026 [summary information…a credit profile of the debtor, a) historical payment behavior of the debtor, historical payment promises made by the debtor, b) a debtor's account balance summary that may include a breakdown of the time the current total owed has been outstanding], 0037 [debtor’s account…debtor’s records]; see also 0048 [data consolidation module 125 may aggregate multiple data sources such as digital audio recording of calls 520, text transcripts of calls 525, debtor account history 530, and data generated from machine learning]);
analyzing, by the at least one processor, the first data set to determine at least one proposed schedule for an attempt to contact the customer; generating, by the at least one processor based on a result of the analysis, a report that includes the proposed schedule (¶¶ 0024-0026 [enhanced CRM system…goal dashboard that summarizes the number of calls…scheduled to make…goal dashboard…predicted number of hours that will be spent…using machine learning algorithms that create the prediction…goal dashboard may also present a summary…measure might be derived using a number and priority of tickets to be resolved within a time period (e.g., day, week, etc.)], 0075-0077 [provide scheduling guidance…goal setting…call preparation]; also see 0028 [(proposed scheduling by) prediction of the best time to contact the debtor/customer…prediction of the best time to contact the debtor/customer…by machine learning algorithm…determine time to contact debtor that results in the highest probability to actually make contact]); and
wherein the analyzing comprises applying, to the first data set, a first machine learning model that is trained by using historical data that relates to interactions associated with the customer (see citations above for claim 1 and also see ¶¶ 0021, 0024-0026 [using machine learning algorithms that create the prediction using data collected during historical debt collection calls…summary information…a credit profile of the debtor, a) historical payment behavior of the debtor, historical payment promises made by the debtor, b) a debtor's account balance summary that may include a breakdown of the time the current total owed has been outstanding, and c) history of communications with the debtor by any Collection Analyst], 0037-0038 [information collected during the call may be stored as a historical record of contact with the debtor…use of machine learning algorithms as a technique to create predictions]);
wherein the proposed schedule includes at least five schedule items that indicate respective dates and respective times for making the attempt to contact the customer ((Applicant has just used “items” broadly and stated five broadly – which is interpreted as at least five any type of information/data points) see citations above and also see, for example, ¶¶ 0024-0026 [(also discussed above in other claims) here Pachauri discusses many data points in scheduling that indicate dates and times and attempts – daily goals, debt to collect daily, number of calls, money collected in a time period, (things to be done within a time period (e.g. day, week, etc.,)), credit profile, behavior information, account balance, etc., (all this information is used in scheduling when making the schedule and times plans for making calls to the debtor)], 0027-0029 [shows other data taken into account in planning/scheduling calls – scheduling best time to contact using various data points (profiles, preparation information, hobbies) and…CRM…manage communications with debtor], 0032-0034).
Pachauri does not explicitly state wherein the processor is further configured to perform a call capping operation that reduces energy consumption by ensuring that a maximum number of outbound calls to be included in the proposed schedule is not exceeded.
Lombard discloses performing a call capping operation that reduces energy consumption by ensuring that a maximum number of calls to be included in the proposed schedule is not exceeded (col. 2, lines 38-41 [call network models and/or center models can be used to develop functions for finding maximum/target values for particular parameters which impact load balancing (calls); see with col. 5, lines 32-33 [solving load balancing…for calls] and col. 17, line 43 – col. 18, lines 67 [load balancing…performance…call center network…network load…conserve resources, such as power consumption]]).
Therefore, it would be obvious to one of ordinary skill in the art to include in the system/method of Pachauri performing a call capping operation that reduces energy consumption by ensuring that a maximum number of calls to be included in the proposed schedule is not exceeded as taught by analogous art Lombard in order to optimize scheduling strategy (best strategy) since doing so could be performed readily by any person of ordinary skill in the art, with neither undue experimentation, nor risk of unexpected results (KSR-G/TSM); and also since one of ordinary skill in the art at the time of the invention would have recognized that applying the known technique and concepts of Lombard would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such concepts and features into similar systems (KSR-D). (MPEP 2141; and also see (1) 2007 Examination Guidelines for Determining Obviousness Under 35 U.S.C. 103 in View of the Supreme Court Decision in KSR International Co. v. Teleflex Inc. - Federal Register, Vol. 72, No. 195, October 10, 2007, pages 57526-57535; (2) 2010 Examination Guidelines Updated Developments in the Obviousness Inquiry After KSR v. Teleflex. -Federal Register, Vol. 75, No. 169, September 01, 2010, pages 53643-53660; and (3) materials posted at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidelines-training-materials-view-ksr).
Neither Pachauri nor Lombard state outbound calls. Analogous art Busbee discloses outbound calls and also discusses energy efficiencies (¶¶ 0003-0005 [outbound calls…improve energy efficiency (i.e. power consumption)], 0126 [calls…outgoing]).
Therefore, it would be obvious to one of ordinary skill in the art to include in the system/method of Pachauri in view of Lombard outbound calls as taught by analogous art Busbee in order to optimize scheduling strategy (best strategy) since doing so could be performed readily by any person of ordinary skill in the art, with neither undue experimentation, nor risk of unexpected results (KSR-G/TSM); and also since one of ordinary skill in the art at the time of the invention would have recognized that applying the known technique and concepts of Busbee would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such concepts and features into similar systems (KSR-D). (MPEP 2141; and also see (1) 2007 Examination Guidelines for Determining Obviousness Under 35 U.S.C. 103 in View of the Supreme Court Decision in KSR International Co. v. Teleflex Inc. - Federal Register, Vol. 72, No. 195, October 10, 2007, pages 57526-57535; (2) 2010 Examination Guidelines Updated Developments in the Obviousness Inquiry After KSR v. Teleflex. -Federal Register, Vol. 75, No. 169, September 01, 2010, pages 53643-53660; and (3) materials posted at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidelines-training-materials-view-ksr).
As per claim 10, claim 10 discloses substantially similar limitations as claim 1 above; and therefore claim 9 is rejected under the same rationale and reasoning as presented above for claim 1.
As per claim 19, claim 19 discloses substantially similar limitations as claim 1 above; and therefore claim 19 is rejected under the same rationale and reasoning as presented above for claim 1.
As per claim 3, Pachauri discloses the method of claim 1, further comprising receiving a second data set that relates to availability of personnel for initiating the attempt to contact the customer, wherein the analyzing comprises analyzing the second data set in conjunction with the analyzing of the first data set (see citations in claims 1 and 2 [note that the “first” data set is various customer information and various historical information including various historical past communication information of debtor/customer]; and also see, for example, ¶¶ 0021 [shows debtor/customer information and historical information (first data – as also shown in claim 2 rejection above) and further shows employee information including work information]; 0024-0026 [also shows analyst/employee information (second data) taken into account by the machine learning algorithm when scheduling and creating dashboards for analysts/employees], 0051-0052 [CRM…analyst logs into system…analyst activity…determine tasks…recognition of login (availability)…task item for the…analyst to address…displayed (only after login which shows availability)…when the Collection Analyst is ready to contact the debtor (analyst can be ready (available) or not ready (unavailable))…initiate (work/calls/etc.,)], 0053 [collection analyst…log in to enhanced CRM (now available)… where data is retrieved that is relevant to the logged-in (available) Collection Analyst…when the Collection Analyst is prepared (available and ready; note that while analyst is not ready/available (while reviewing or not logged in) the call is not initiated) to contact the debtor…initiate the contact/call]).
As per claim 12, claim 12 discloses substantially similar limitations as claim 3 above; and therefore claim 12 is rejected under the same rationale and reasoning as presented above for claim 3.
As per claim 4, Pachauri discloses the method of claim 3, wherein the second data set includes information that relates to a maximum capacity for outbound calls as a function of time, and wherein the analyzing of the second data set comprises determining whether a predetermined amount of the maximum capacity has been reached ( (note that Applicant does not define “capacity” or “maximum capacity” and for examination purposes this will be taken as set goals/targets/limit from which a percentage/fraction is determined) ¶¶ 0011 [goals dashboard for employee/analyst], 0024 [daily goal of how much debt to collect and goal of number of hours that will be spent by the analyst…goal…within a period of time (e.g., day, week, etc.)], 0041 [goal dashboard…goal summary…daily collection amount goal, a minimum number of calls to reach that goal, summary of the current day's progress…in a work period (e.g., day, week, by end of month, etc.)… a number of debtors the Collection Analyst is expected to call within a work period, the amount of time that may be spent on each call, a measure of “certainty” that the Collection Analyst will meet a daily collection goal, or any other predicted value], 0073-0074 [required amount of work…set…daily goal…with respect to amount of money (so daily (time) goals (maximum capacity) of amount of money to collect)…reach their goals (stay longer)]).
Pachauri does not explicitly use the term percentages (although Pachauri does state how much of a target/total).
Analogous art Lombard (call center load balancing and agent/employee and customer communication and calls) discloses percentages in a calls setting and in an agent/employee and customer communication (col. 7, line 43 – col. 9, line 10 [percentages…utilization… calculated from percentages or proportions…(percentage used and disclosed throughout reference)]).
Therefore, it would be obvious to one of ordinary skill in the art to include in the system/method of Pachauri percentages as taught by analogous art Lombard in order to calculate and represent data more efficiently get optimal data representation since doing so could be performed readily by any person of ordinary skill in the art, with neither undue experimentation, nor risk of unexpected results (KSR-G); and also since one of ordinary skill in the art at the time of the invention would have recognized that applying the known technique and concepts (data representation in percentages is very old and well-known concept and can easily be derived from fractions) of Lombard would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such concepts and features into similar systems (KSR-D); and also since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results (fractional amount in percentages) of the combination were predictable (KSR-A