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 . 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 (i.e., changing from AIA to pre-AIA ) 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.
DETAILED ACTION
The following NON-FINAL Office Action is in response to communication filed on 5/18/2025.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 05/18/2026 has been entered.
Information Disclosure Statement (IDS)
The information disclosure statements filed on 6/18/2024 and 11/11/2025 comply with the provisions 37 CFR 1.97, 1.98, and MPEP 609 and is considered by the Examiner.
Status of Claims
Claims 1-20 are currently pending.
Claims 1, 11, 19 are currently amended.
Claims 1-20 are currently under examination and have been rejected as follows.
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Response to Amendment
The previously pending rejections under 35 USC 101 will be maintained. The 101 rejection is updated in view of the amendments.
The previously pending rejections under 35 USC 103 will be maintained. The 103 rejection is updated in view of the amendments.
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Response to Arguments
Regarding Applicant’s remarks pertaining to 35 USC 101:
Step 2A Prong 1:
Applicant submits on page 13 of remarks 5/18/2025:
“Inasmuch as the Office alleges that the claim recitations pertain to mitigating risk, the Applicant respectfully notes that claim 1 does not recite "risk" anywhere.
“With regard to commercial or legal interactions, claim 1 does not recite a contract, a legal
obligation, advertising, marketing or sales activities, or business relations.
“Further, claim 1 does not recite any of the types activities recognized in the MPEP as managing personal behavior.
“For at least the foregoing reasons, the Applicant respectfully submits that claim 1 is not directed to a certain method of organizing human activity.
Examiner respectfully disagrees. While the literal word “risk” is not currently present in the claims or specification, the concept of optimizing shift scheduling based on demand forecasting to minimize operational costs (see Applicant Specification ¶ [0002, 0096, 0108]) is present throughout the whole of the claims (receive a staffing requirement forecast, receive a service level override value indicative of an allowed change in a service level, wherein the change is indicative of an adjustment to a key performance indicator goal of the contact center, generate an optimized contact center agent shift schedule, restrict a set of candidate alternative shifts to satisfy the service level override value, etc.) and clearly represents a method of mitigating financial risk for an enterprise.
Regarding commercial or legal interactions, the concept of customer relations or customer service goals is clearly analogous to “business relations”, and optimally scheduling agent shifts based on service goals is present throughout the claims and the specification.
Regarding managing personal behavior or relationships or interactions between people, Examiner interprets managing employee shift scheduling, including managing requests for shift changes, e.g. receive a request to replace an individual shift of the optimized contact center agent shift schedule with an alternative shift, etc., as managing personal behavior or relationships or interactions between people (see Applicant Specification ¶ [0134, 0139]).
Step 2A Prong 2:
Applicant submits on page 15 of remarks 5/18/2025:
“The Applicant respectfully submits that the claims also indicate integration of the alleged
abstract idea into a practical application at least because the claims include specific recitations that place meaningful limits on the alleged judicial exception.
“The features of claim 1 are recited with specificity and impose meaningful limits. In the example of Parker v. Flook, discussed above, the claims at issue were not supported with any specific details of how the claimed operations were accomplished. However, unlike the claims in Parker v. Flook, claim 1 expressly recites specific details on how the system identifies an alternative shift from a plurality of shifts by restricting a set of candidate alternative shifts to satisfy a service level override value that is indicative of an acceptable change in a service level to be provided by a contact center, in which the change is indicative of an adjustment to a key performance indicator goal of the contact center and wherein identifying the alternative shift further includes presenting the restricted set of candidate alternative shifts in a graphical user interface to enable selection of the alternative shift, as described in more detail with respect to the rejections under 35 U.S.C. § 103.
Examiner respectfully disagrees. Specific details such as identifying an alternative shift by restricting a set of candidate shifts to satisfy an acceptable service level override value provided by a contact center, and where the change is indicative of a KPI goal adjustment of the contact center, appear specific to an abstract method as opposed to specific technological improvements. Further, the newly amended claim limitations do not appear to provide any computer-based elements additional to the original system, processor, memory, non-transitory machine-readable storage media, and contact center system, let alone for such additional computer-based elements to integrate the abstract idea into practical application.
Step 2B:
Applicant submits on page 17 of remarks 5/18/2025:
“The prior art of record does not teach or suggest each of the features recited in any of the pending claims, as described in more detail with reference to the rejections under § 103. The
Applicant further submits that the amended features of the claims likewise recite "additional features" that are not taught by the prior art of record when each claim is interpreted as a whole.
The Applicant respectfully submits that at least those features not taught, when read in view of the claim as a whole, constitute significantly more than the alleged abstract idea.
Examiner respectfully disagrees.
First, Examiner submits with regard to Applicant’s argument above alleging that the references do not disclose a limitation in the claim: this argument is not persuasive because the test under Alice is not a matter of evidence but rather a test of law, the nonobviousness or novelty of those limitations would not provide an indication that those limitations are 'something more'. In other words, nonobviousness or novelty is not an indicium of eligibility - it is not an indicium that limitations provide "something more. However, arguendo, the 103 rejection has been updated in view of the amended claim limitations, detailed below. As above, the claimed features appear specific to an abstract method as opposed to specific technological improvements, and the newly amended claim limitations do not appear to provide any computer-based elements additional to the original system, processor, memory, non-transitory machine-readable storage media, and contact center system, let alone for such additional computer-based elements to provide significantly more than the judicial exception. The claim limitations that attempt to cover an entrepreneurial and thus abstract solution to an entrepreneurial problem with insufficient technological details on how the technological result is accomplished.
Applicant submits on page 17 of remarks 5/18/2025:
“…The claims at issue in Ex Parte Desjardins were directed to a complex algorithm and were rejected by the Examiner and PTAB as allegedly being directed to an abstract idea. However, in his written opinion, the Director of the USPTO was unequivocal in his disagreement and, instead, alleged that the claims were directed to patentable subject matter. In doing so, the Director of the USPTO set forth the reminder that "Examiners and panels should not evaluate claims at such a high level of generality." (See Decision, p. 9). As such, in evaluating the claims of the subject application, the Applicant respectfully requests that such directive be followed.”
Examiner considers the comparison but respectfully disagrees. Every application is examined for subject matter eligibility on a case-by-case basis. That said, the Ex Parte Desjardins decision to acknowledge eligibility rested on technological improvements in machine learning including learning new tasks in succession while protecting knowledge about previous tasks, reducing required storage capacity, and reducing system complexity. Examiner submits the cases are not analogous. As above, the present claimed features appear specific to an abstract method as opposed to specific technological improvements, and the newly amended claim limitations do not appear to provide any computer-based elements additional to the originals, nor for such additional computer-based elements to provide significantly more.
Accordingly, the previously pending rejections under 35 USC 101 will be maintained. The 101 rejection is updated in view of the amendments.
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Regarding Applicant’s remarks pertaining to 35 USC 103:
Applicant submits on page 20 of remarks 5/18/2025:
“That is, claim 1 has been amended to clarify that the system receives a service level override value that is indicative of an allowed change in service level to be provided by a contact
center and more specifically that the change is indicative of an adjustment to a key performance indicator (KPI) goal of the contact center. Further, the amendments clarify that in identifying the alternative shift, the system restricts a set of candidate alternative shifts from the plurality of shifts that were identified from the column generation process and does so by restricting the set based on the service level override value, which is indicative of the adjustment to the key performance indicator goal of the contact center and further by presenting those candidate shifts (i.e., that satisfy the adjustment to the key performance indicator goal of the contact center) in a graphical user interface for selection of the alternative shift therefrom.
Examiner respectfully disagrees based on additional support from primary reference D’Attilio which discloses a process of filtering all possible shifts down to a subset of shifts for end-user selection based on adjustable KPIs of the contact center. Disclosure can be found to teach the above amended claim limitations in with secondary reference Suryawanshi, inter alia, at D’Attilio ¶ [0083], [0087], and specifically at mid-¶ [0058]: “A workload forecasting model may be defined as the best method to apply given time series data and a set of optimal parameters that yield optimal key performance indicator (KPI) metrics used to validate the accuracy of the forecast. ¶ [0107]: It should be appreciated that the master problem formulation may minimize (or reduce) shift cost and under staffing, given parameters for labor cost and a penalty for missing requirement. In other embodiments, an objective [EN: KPI] may be substituted with the appropriate changes to the lower bound. Therefore, it should be appreciated that this approach can support any number of custom objectives or multi-objective optimizations (e.g., minimize shift cost while maximizing service level and agent preferences). Multi-objective scheduling optimization allows the system to provide several, similarly "optimal," [EN: restricted set of] shift schedule solutions and allow the end users [to] choose depending on the objectives that are more important for their contact center.”
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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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-10 are directed to a system or machine which is a statutory category.
Claims 11-18 are directed to one or more non-transitory machine-readable storage media or articles of manufacture which is a statutory category.
Claims 19-20 are directed to a method or process which is a statutory category.
Step 2A Prong One: The claims recite, describe, or set forth a judicial exception of an abstract idea (see MPEP 2106.04(a)). Specifically, the claims recite, describe or set forth mental processes, including observation, evaluation, and judgement; mitigating risk; agreements in the form of contracts; legal obligations; business relations; and managing personal relationships or interactions between people, including: “receive a staffing requirement forecast indicative of a number of agents required”, “receive agent data [which] comprises agent working rules”, “receive a service level override value indicative of an allowed change in a service level to be provided by a contact center, wherein the change is indicative of an adjustment to a key performance indicator goal of the contact center”, “identify a plurality of shifts for the plurality of agents based on the staffing requirement forecast, the agent working rules, and one or more work plan constraints”, “generate an optimized contact center agent shift schedule for the plurality of agents”, “receive a request to replace an individual shift of the optimized contact center agent shift schedule with an alternative shift”, “identify the alternative shift from the plurality of shifts based on the service level override value, wherein to identify the alternative shift includes to restrict a set of candidate alternative shifts from the plurality of shifts identified from the column generation to satisfy the service level override value indicative of the adjustment to the key performance indicator goal of the contact center and present the restricted set of candidate alternative shifts in a graphical user interface to enable selection of the alternative shift”, “replace the individual shift with the identified alternative shift”. Optimally scheduling agent shifts based on forecasted workforce need, service level goals, agent working rules, and other constraints to minimize operational costs; and managing shift replacements subject thereto fall within mitigating risk as it pertains to fundamental economic principles; agreements in the form of contracts, legal obligations, business relations as they pertain to commercial or legal interactions; and managing personal behavior or relationships or interactions between people, all under the larger abstract grouping of Certain Methods of Organizing Human Activity Certain Methods of Organizing Human Activity (MPEP 2106.04(a)(2) II). These functions also fall within concepts performed in the human mind, including observation, evaluation, and judgement, under the abstract grouping Mental Processes (MPEP 2106.04(a)(2) III). Accordingly, the claims recite an abstract idea.
Step 2A Prong Two: Independent claims 1, 11, 19 recite the following additional elements: system, processor, memory, non-transitory machine-readable storage media, and contact center system. The functions of these additional elements include examples such as receive a forecast, receive agent data, receive a service level override value, restrict a set of candidate alternative shifts to satisfy the service level override value, perform column generation, generate an optimized contact center agent shift schedule, receive a request to replace an individual shift, and identify the alternative shift. The additional elements are recited at a high level of generality (i.e. as a generic computer performing functions of receiving and collecting data, organizing data, mathematical optimization, etc.) such that they amount to no more than mere instructions to apply the exception using generic computer components. Therefore, these functions can be viewed as not meaningfully different than a business method or mathematical algorithm being applied on a general-purpose computer as tested per MPEP 2106.05(f)(2)(i). The claims are directed to an abstract idea and the judicial exception does not integrate the abstract idea into a practical application.
Step 2B: According to MPEP 2106.05(f)(1), considering whether the claim recites only the idea of a solution or outcome i.e., the claims fail to recite the technological details of how the actual technological solution to the actual technological problem is accomplished. The recitation of claim limitations that attempt to cover an entrepreneurial and thus abstract solution to an entrepreneurial problem with no technological details on how the technological result is accomplished and no description of the mechanism for accomplishing the result do not provide significantly more than the judicial exception.
The dependent claims do not appear to provide any additional computer-based elements, let alone for such additional computer-based elements to integrate the abstract idea into practical application (Step 2A prong two) or providing significantly more (Step 2B).
Further, dependent claims 2-10, 12-18, 20 merely incorporate the additional elements recited in claims 1, 11, 19 along with further narrowing of the abstract idea of claims 1, 11, 19 and their execution of the abstract idea. Specifically, the dependent claims narrow the system, processor, memory, non-transitory machine-readable storage media, and contact center system to capabilities such as generate, comprise, determine, evaluate, approve, deny, receive, search, and replace various forms of data such as forecasts, demand, planning periods, time series data, staffing requirements, shifts, durations, starting times, finishing times, columns, criteria, agent capabilities, working rules, constraints, service goals, requests, etc. which, when evaluated per MPEP 2106.05(f)(2) represent mere invocation of computers to perform existing processes. Therefore, the additional elements recited in the claimed invention individually and in combination fail to integrate a judicial exception into a practical application (Step 2A prong two) and for the same reasons they also fail to provide significantly more (Step 2B). Thus, claims 1-20 are reasoned to be patent ineligible.
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REJECTIONS BASED ON PRIOR ART
Examiner Note: Some rejections will contain bracketed comments preceded by an “EN” that will denote an examiner note. This will be placed to further explain a rejection.
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Claim Rejections - 35 USC § 103
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 of this title, 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
The factual inquiries 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.
Claims 1-6, 9-16, 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over:
D’Attilio US 20220027837 A1, hereinafter D’Attilio in view of
Suryawanshi US 20240428153 A1, hereinafter Suryawanshi. As per,
Regarding claims 1, 11: D’Attilio teaches:
A system for generating alternative shifts for contact center agent scheduling, the system comprising: at least one processor; and at least one memory (claim 1) / One or more non-transitory machine-readable storage media (claim 11) comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor (D’Attilio ¶ [0006]: According to an embodiment, a system for performing contact center agent scheduling may include at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to…), causes the system to:
receive a staffing requirement forecast indicative of a number of agents required to handle a workload forecast based on the workload forecast, one or more service goals, and a staffing requirement model (See D’Attilio Fig. 8 step 802: Receive list of agents and staffing requirement forecasts. ¶ [0006]: …generate a workload forecast indicative of a demand that will be introduced into the contact center in a future planning period based on a workload forecast model and time series data, generate a staffing requirement forecast indicative of a number of agents required to handle the workload forecast based on the workload forecast, one or more service goals, and a staffing requirement model….);
receive agent data for a plurality of agents, the agent data comprises agent working rules for each agent of the plurality of agents (D’Attilio mid-¶ [0126]: …the storage device 1220 may store agent data in an agent database. Agent data maintained by the contact center system 1200 may include, for example, agent availability and agent profiles, schedules, skills, handle time, and/or other relevant data. Mid-¶ [0083]: It should be appreciated that the list of agents may include, for example, working rules associated with the agents (e.g., work hours, regulatory requirements, etc.), capabilities of the respective agents (e.g., specializations in various areas, etc.));
[..] wherein the change is indicative of an adjustment to a key performance indicator goal of the contact center (D’Attilio mid-¶ [0058]: A workload forecasting model may be defined as the best method to apply given time series data and a set of optimal parameters that yield optimal key performance indicator (KPI) metrics used to validate the accuracy of the forecast. ¶ [0107]: It should be appreciated that the master problem formulation may minimize (or reduce) shift cost and under staffing, given parameters for labor cost and a penalty for missing requirement. In other embodiments, an objective [EN: KPI] may be substituted with the appropriate changes to the lower bound. Therefore, it should be appreciated that this approach can support any number of custom objectives or multi-objective optimizations (e.g., minimize shift cost while maximizing service level and agent preferences));
perform column generation to identify a plurality of shifts for the plurality of agents based on the staffing requirement forecast, the agent working rules, and one or more work plan constraints, wherein each shift of the plurality of shifts corresponds to a column added by the column generation (D’Attilio ¶ [0087]: In order to utilize column generation for scheduling, the system must have both a restricted version of the problem and a way to find columns. In the illustrative embodiment, a column is defined as the set of shifts assigned to an agent (i.e., a "shift schedule"). The master problem ensures that the shift schedules selected meet the requirements
for each planning group, and the sub-problem finds shift schedules that meet the scheduling constraints. According to this technical arrangement, the system can use column generation to iteratively identify good candidate shift schedules for covering requirements (e.g., without having to enumerate all possibilities));
select a subset of the shifts to generate an optimized contact center agent shift schedule for the plurality of agents (D’Attilio ¶ [0087]: According, in block 804, the system executes a column generation algorithm in order to determine the optimized shift schedules. It should be appreciate that column generation involves solving a restricted problem (i.e., a problem with a subset of all potential solutions to choose from), and iteratively finding candidate columns to add to the potential solutions in the restricted problem until some criteria is met. ¶ [0108]: Accordingly,
in other embodiments, aggregation and clustering of planning groups may be performed to decrease or reduce the dimensionality of the problem, which allows for potential splitting or decomposition of the problem into independent subnetworks of agents and planning groups ( e.g., for scheduling in parallel using the column generation algorithm described above));
[..]
identify the alternative shift from [..] from the plurality of shifts identified from the column generation [..] indicative of the adjustment to the key performance indicator goal of the contact center and present the restricted set of candidate alternative shifts in a graphical user interface to enable selection of the alternative shift (D’Attilio mid-¶ [0058]: A workload forecasting model may be defined as the best method to apply given time series data and a set of optimal parameters that yield optimal key performance indicator (KPI) metrics used to validate the accuracy of the forecast. ¶ [0107]: It should be appreciated that the master problem formulation may minimize (or reduce) shift cost and under staffing, given parameters for labor cost and a penalty for missing requirement. In other embodiments, an objective [EN: KPI] may be substituted with the appropriate changes to the lower bound. Therefore, it should be appreciated that this approach can support any number of custom objectives or multi-objective optimizations (e.g., minimize shift cost while maximizing service level and agent preferences). Multi-objective scheduling optimization allows the system to provide several, similarly "optimal," [EN: restricted set of] shift schedule solutions and allow the end users [to] choose depending on the objectives that are more important for their contact center).
Although D’Attilio teaches applying column generation to optimize a contact center agent schedule based on staffing forecasts, agent data, and service goals, D’Attilio does not specifically teach receiving a service level override value or modifying the optimized schedule upon requests for alternative individual agent shifts.
However, Suryawanshi in analogous art of contact center scheduling teaches or suggests:
receive a service level override value indicative of an allowed change in a service level to be provided by a contact center [..] (Suryawanshi ¶ [0025]: In several embodiments, trade index score calculations are used for automatic approvals of trade requests. In some embodiments, the manager configures the upper and lower threshold limits [EN: override values] of the trade index score [EN: service level]. Once the automatic approval is "ON" at the tenant level, trade requests can be automatically approved, which can save a lot of time for managers. mid-¶ [0029]: Some agents may not be suited to long shifts, and the system can be pre-configured to decline trades that might result in such a target agent having too long a shift to remain at a desirable level of performance…. another important aspect being checked is if there were no-shows in the past by the target agent, which will help avoid any non-adherence activities in the future. Use of the trade index score reduces the number of no-shows and hence reduces the impact on staffing levels in the contact center. End-¶ [0057]: WFM system 105 determines that the trade index score is greater than or equal to the upper threshold [EN: service level override] value for the trade index score and WFM system 105 automatically approves the shift trade request… WFM system 105 determines that the trade index score is lower than or equal to the lower threshold [EN: service level override] value for the trade index score and WFM system 105 automatically rejects or declines the shift trade request);
receive a request to replace an individual shift of the optimized contact center agent shift schedule with an alternative shift (Suryawanshi ¶ [0025]: Referring now to FIG. 7, a method 700 according to various embodiments of the present disclosure is described. At step 702, WFM system 105 receives a shift trade request from a source agent. The shift trade request includes a shift day and a shift time. ¶ [0049]: At step 704, WFM system 105 matches the shift trade request with a plurality of target agents that are available on the shift day and the shift time);
identify the alternative shift from the plurality of shifts based on the service level override value, wherein to identify the alternative shift includes to restrict a set of candidate alternative shifts [..] to satisfy the service level override value [..]; (Suryawanshi ¶ [0050]: At step 706, trade target agent ranking engine 110 calculates a trade index score for each target agent from the plurality of target agents [EN: set of candidates w/ alternative shifts]. The trade index score is based on a trade history success index score, a matching skill index score, a skill proficiency index score, and a trade interval index score. In certain embodiments, the trade index score is further based on an adherence index score. ¶ [0052]: At step 708, trade target agent ranking engine 110 ranks [EN: restricts] the plurality of target agents [EN: with alternate shifts] from highest to lowest trade index score. ¶ [0053]: At step 710, agent user interface 120 displays the ranked plurality of target agents with the target agent having the highest trade index score at the top of the list [EN: thus identifying the alternate shift]. End-¶ [0057]: WFM system 105 determines that the trade index score is greater than or equal to the upper threshold [EN: service level override] value for the trade index score and WFM system 105 automatically approves the shift trade request… WFM system 105 determines that the trade index score is lower than or equal to the lower threshold [EN: service level override] value for the trade index score and WFM system 105 automatically rejects or declines the shift trade request); and
modify the optimized contact center agent shift schedule to replace the individual shift with the identified alternative shift (Suryawanshi ¶ [0050]: …WFM system 105 changes the schedule of the source agent and the selected target agent according to the shift trade request).
Suryawanshi and D’Attilio are found as analogous art of contact center scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified D’Attilio’s scalable contact center agent scheduling utilizing automated ai modeling and multi-objective optimization system and method to have included Suryawanshi’s teachings around receiving a service level override value or modifying the optimized schedule upon requests for alternative individual agent shifts. The benefit of these additional features would have provided an improved experience to customers, sustained desirable levels of performance and reduced the impact on staffing levels when allowing agents to change shifts (Suryawanshi ¶ [0028-0029]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by D’Attilio in view of Suryawanshi (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of contact center scheduling. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by D’Attilio in view of Suryawanshi above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claims 2, 12: D’Attilio / Suryawanshi teaches all the limitations of claims 1, 11 above.
D’Attilio further teaches:
wherein the plurality of instructions further causes the system to:
generate a workload forecast indicative of a demand that will be introduced into the contact center in a future planning period based on a workload forecast model and time series data; and generate the staffing requirement (D’Attilio ¶ [0006]: …a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to generate a workload forecast indicative of a demand that will be introduced into the contact center in a future planning period based on a workload forecast model and time series data, generate a staffing requirement forecast indicative of a number of agents required to handle the workload forecast based on the workload forecast, one or more service goals, and a staffing requirement model ….).
Regarding claims 3, 13: D’Attilio / Suryawanshi teaches all the limitations of claims 1, 11 above.
D’Attilio further teaches:
wherein the one or more work plan constraints comprises at least one of a maximum shift duration, an earliest shift starting time, or a latest shift finishing time (D’Attilio mid-¶ [0083]: In other words, shift scheduling balances the problem of selecting what shifts are to be worked by each employee to meet workload requirements and hit certain KPI goals with adhering to various work plan constraints and state/national labor regulations (e.g., such as maximum shift duration, earliest shift starting time, latest finishing time, etc.)).
Regarding claims 4, 14: D’Attilio / Suryawanshi teaches all the limitations of claims 1, 11 above.
D’Attilio further teaches:
wherein to perform column generation comprises to solve a relaxed master problem and add columns until at least one termination criteria has been satisfied (D’Attilio mid-¶ [0083]: In block 808, the system performs column generation to add new columns. In particular, the system may solve the relaxed master problem to finding and adding new columns until one or more termination criteria have been satisfied).
Regarding claims 5, 15: D’Attilio / Suryawanshi teaches all the limitations of claims 1, 11 above.
D’Attilio further teaches:
wherein the agent data further comprises agent capability data for each agent of the plurality of agents (D’Attilio mid-¶ [0126]: …the storage device 1220 may store agent data in an agent database. Agent data maintained by the contact center system 1200 may include, for example, agent availability and agent profiles, schedules, skills, handle time, and/or other relevant data. Mid-¶ [0083]: It should be appreciated that the list of agents may include, for example, working rules associated with the agents (e.g., work hours, regulatory requirements, etc.), capabilities of the respective agents (e.g., specializations in various areas, etc.)); and
wherein to perform column generation to identify a plurality of shifts for the plurality of agents comprises to perform column generation to identify a plurality of shifts for the plurality of agents based on the staffing requirement forecast, the agent working rules, the one or more work plan constraints, and the agent capability data (D’Attilio mid-¶ [0006]: …a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to generate a workload forecast indicative of a demand that will be introduced into the contact center in a future planning period based on a workload forecast model and time series data, generate a staffing requirement forecast indicative of a number of agents required to handle the workload forecast based on the workload forecast, one or more service goals, and a staffing requirement model, and perform schedule optimization using column generation to generate an optimized contact center agent shift schedule for a plurality of agents based on the staffing requirement forecast and one or more constraints [EN: constraints enumerated previously including working rules, work plan constraints, and agent capability data]).
Regarding claims 6, 16: D’Attilio / Suryawanshi teaches all the limitations of claims 1, 11 above.
Although D’Attilio teaches applying column generation to optimize a contact center agent schedule based on staffing forecasts, agent data, and service goals, D’Attilio does not specifically teach replacing shifts based on determining a service goal impact.
However, Suryawanshi in analogous art of contact center scheduling teaches or suggests:
wherein the plurality of instructions further causes the system to determine a service goal impact of replacing the individual shift with the identified alternative shift (Suryawanshi end-¶ [0029]: Use of the trade index score [EN: service goal impact] reduces the number of no-shows and hence reduces the impact on staffing levels in the contact center. End-[0030]: Excellent customer experience is maintained even after agents have traded their shifts since the target agents have the same skills with similar proficiency levels); and
wherein to replace the individual shift with the identified alternative shift comprises to replace the individual shift with the identified alternative shift based on the determined service goal impact (Suryawanshi end-¶ [0057]: WFM system 105 determines that the trade index score [EN: service goal impact] is greater than or equal to the upper threshold value for the trade index score and WFM system 105 automatically approves the shift trade request).
Suryawanshi and D’Attilio are found as analogous art of contact center scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified D’Attilio’s scalable contact center agent scheduling utilizing automated ai modeling and multi-objective optimization system and method to have included Suryawanshi’s teachings around replacing shifts based on determining a service goal impact. The benefit of these additional features would have provided an improved experience to customers, sustained desirable levels of performance and reduced the impact on staffing levels when allowing agents to change shifts (Suryawanshi ¶ [0028-0029]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by D’Attilio in view of Suryawanshi (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of contact center scheduling. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by D’Attilio in view of Suryawanshi above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claim 9: D’Attilio / Suryawanshi teaches all the limitations of claims 1 above.
Although D’Attilio teaches applying column generation to optimize a contact center agent schedule based on staffing forecasts, agent data, and service goals, D’Attilio does not specifically teach modifying the optimized schedule upon requests for alternative individual agent shifts.
However, Suryawanshi in analogous art of contact center scheduling teaches or suggests:
wherein the alternative shift comprises a first alternative shift; wherein the plurality of instructions further causes the system to:
receive alternative shift search criteria comprising shift preferences of an agent of the plurality of agents, perform a search for alternative shifts based on the alternative shift search criteria (Suryawanshi ¶ mid-[0021]: In one or more embodiments, when a source agent requests a trade, after entering his/her preferences of days and times, the source agent gets a list of matching target agents), and
identify a second alternative shift (Suryawanshi ¶ mid-[0021]: This list of target agents is displayed based on the trade index score configurations, and the best match [EN: first alternative shift] is displayed at the top of the list. Advantageously, these details are seen on the trade shift webpage before the source agent sends a trade request to any other agents [EN: with a second alternative shift] or a manager.); and
wherein to replace the individual shift with the identified alternative shift comprises to replace the individual shift with the identified second alternative shift (Suryawanshi ¶ end-¶ [0021]: This helps source agents estimate the probability of having a successful trade and to choose the best match options [EN: among multiple alternatives]).
Suryawanshi and D’Attilio are found as analogous art of contact center scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified D’Attilio’s scalable contact center agent scheduling utilizing automated ai modeling and multi-objective optimization system and method to have included Suryawanshi’s teachings around modifying the optimized schedule upon requests for alternative individual agent shifts. The benefit of these additional features would have provided an improved experience to customers, sustained desirable levels of performance and reduced the impact on staffing levels when allowing agents to change shifts (Suryawanshi ¶ [0028-0029]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by D’Attilio in view of Suryawanshi (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of contact center scheduling. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by D’Attilio in view of Suryawanshi above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claim 10: D’Attilio / Suryawanshi teaches all the limitations of claims 9 above.
Although D’Attilio teaches applying column generation to optimize a contact center agent schedule based on staffing forecasts, agent data, and service goals, D’Attilio does not specifically teach modifying the optimized schedule upon requests for alternative individual agent shifts based on agent preferences.
However, Suryawanshi in analogous art of contact center scheduling teaches or suggests:
wherein the shift preferences comprise one or more of a requested shift day to be changed, a preferred alternative shift day, a preferred alternative shift start time, and a preferred alternative shift end time (Suryawanshi ¶ mid-[0021]: In one or more embodiments, when a source agent requests a trade, after entering his/her preferences of days and times, the source agent gets a list of matching target agents).
Suryawanshi and D’Attilio are found as analogous art of contact center scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified D’Attilio’s scalable contact center agent scheduling utilizing automated ai modeling and multi-objective optimization system and method to have included Suryawanshi’s teachings around modifying the optimized schedule upon requests for alternative individual agent shifts based on agent preferences. The benefit of these additional features would have provided an improved experience to customers, sustained desirable levels of performance and reduced the impact on staffing levels when allowing agents to change shifts (Suryawanshi ¶ [0028-0029]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by D’Attilio in view of Suryawanshi (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of contact center scheduling. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by D’Attilio in view of Suryawanshi above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claim 19: D’Attilio teaches:
A method of generating alternative shifts for contact center agent scheduling, the method comprising:
receiving, by a contact center system, a staffing requirement forecast indicative of a number of agents required to handle a workload forecast based on the workload forecast, one or more service goals, and a staffing requirement model (See D’Attilio Fig. 8 step 802: Receive list of agents and staffing requirement forecasts. ¶ [0006]: According to an embodiment, a system for performing contact center agent scheduling may include at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to generate a workload forecast indicative of a demand that will be introduced into the contact center in a future planning period based on a workload forecast model and time series data, generate a staffing requirement forecast indicative of a number of agents required to handle the workload forecast based on the workload forecast, one or more service goals, and a staffing requirement model….);
receiving, by the contact center system, agent data for a plurality of agents, the agent data comprises agent working rules for each agent of the plurality of agents (D’Attilio mid-¶ [0126]: …the storage device 1220 may store agent data in an agent database. Agent data maintained by the contact center system 1200 may include, for example, agent availability and agent profiles, schedules, skills, handle time, and/or other relevant data. Mid-¶ [0083]: It should be appreciated that the list of agents may include, for example, working rules associated with the agents (e.g., work hours, regulatory requirements, etc.), capabilities of the respective agents (e.g., specializations in various areas, etc.));
[..] wherein the change is indicative of an adjustment to a key performance indicator goal of the contact center (D’Attilio mid-¶ [0058]: A workload forecasting model may be defined as the best method to apply given time series data and a set of optimal parameters that yield optimal key performance indicator (KPI) metrics used to validate the accuracy of the forecast. ¶ [0107]: It should be appreciated that the master problem formulation may minimize (or reduce) shift cost and under staffing, given parameters for labor cost and a penalty for missing requirement. In other embodiments, an objective [EN: KPI] may be substituted with the appropriate changes to the lower bound. Therefore, it should be appreciated that this approach can support any number of custom objectives or multi-objective optimizations (e.g., minimize shift cost while maximizing service level and agent preferences));
performing, by the contact center system, column generation to identify a plurality of shifts for the plurality of agents based on the staffing requirement forecast, the agent working rules, and one or more work plan constraints, wherein each shift of the plurality of shifts corresponds to a column added by the column generation (D’Attilio ¶ [0087]: In order to utilize column generation for scheduling, the system must have both a restricted version of the problem and a way to find columns. In the illustrative embodiment, a column is defined as the set of shifts assigned to an agent (i.e., a "shift schedule"). The master problem ensures that the shift schedules selected meet the requirements for each planning group, and the sub-problem finds shift schedules that meet the scheduling constraints. According to this technical arrangement, the system can use column generation to iteratively identify good candidate shift schedules for covering requirements (e.g., without having to enumerate all possibilities));
selecting, by the contact center system, a subset of the shifts to generate an optimized contact center agent shift schedule for the plurality of agents (D’Attilio ¶ [0087]: According, in block 804, the system executes a column generation algorithm in order to determine the optimized shift schedules. It should be appreciate that column generation involves solving a restricted problem (i.e., a problem with a subset of all potential solutions to choose from), and iteratively finding candidate columns to add to the potential solutions in the restricted problem until some criteria is met. ¶ [0108]: Accordingly, in other embodiments, aggregation and clustering of planning groups may be performed to decrease or reduce the dimensionality of the problem, which allows for potential splitting or decomposition of the problem into independent subnetworks of agents and planning groups (e.g., for scheduling in parallel using the column generation algorithm described above));
[..]
identify the alternative shift from [..] from the plurality of shifts identified from the column generation [..] indicative of the adjustment to the key performance indicator goal of the contact center and present the restricted set of candidate alternative shifts in a graphical user interface to enable selection of the alternative shift (D’Attilio mid-¶ [0058]: A workload forecasting model may be defined as the best method to apply given time series data and a set of optimal parameters that yield optimal key performance indicator (KPI) metrics used to validate the accuracy of the forecast. ¶ [0107]: It should be appreciated that the master problem formulation may minimize (or reduce) shift cost and under staffing, given parameters for labor cost and a penalty for missing requirement. In other embodiments, an objective [EN: KPI] may be substituted with the appropriate changes to the lower bound. Therefore, it should be appreciated that this approach can support any number of custom objectives or multi-objective optimizations (e.g., minimize shift cost while maximizing service level and agent preferences). Multi-objective scheduling optimization allows the system to provide several, similarly "optimal," [EN: restricted set of] shift schedule solutions and allow the end users [to] choose depending on the objectives that are more important for their contact center).
Although D’Attilio teaches applying column generation to optimize a contact center agent schedule based on staffing forecasts, agent data, and service goals, D’Attilio does not specifically teach receiving a service level override value or modifying the optimized schedule upon requests for alternative individual agent shifts.
However, Suryawanshi in analogous art of contact center scheduling teaches or suggests:
receiving, by the contact service center system, a service level override value indicative of an allowed change in a service level to be provided by a contact center [..] (Suryawanshi ¶ [0025]: In several embodiments, trade index score calculations are used for automatic approvals of trade requests. In some embodiments, the manager configures the upper and lower threshold limits [EN: override values] of the trade index score [EN: service level]. Once the automatic approval is "ON" at the tenant level, trade requests can be automatically approved, which can save a lot of time for managers. End-¶ [0029]: …another important aspect being checked is if there were no-shows in the past by the target agent, which will help avoid any non-adherence activities in the future. Use of the trade index score reduces the number of no-shows and hence reduces the impact on staffing levels in the contact center);
receiving, by the contact center system, a request to replace an individual shift of the optimized contact center agent shift schedule with an alternative shift (Suryawanshi ¶ [0025]: Referring now to FIG. 7, a method 700 according to various embodiments of the present disclosure is described. At step 702, WFM system 105 receives a shift trade request from a source agent. The shift trade request includes a shift day and a shift time. ¶ [0049]: At step 704, WFM system 105 matches the shift trade request with a plurality of target agents that are available on the shift day and the shift time);
identifying, by the contact center system, the alternative shift from the plurality of shifts based on the service level override value, including restricting a set of candidate alternative shifts [..] to satisfy the service level override value [..] (Suryawanshi ¶ [0050]: At step 706, trade target agent ranking engine 110 calculates a trade index score for each target agent from the plurality of target agents. The trade index score is based on a trade history success index score, a matching skill index score, a skill proficiency index score, and a trade interval index score. In certain embodiments, the trade index score is further based on an adherence index score. ¶ [0052]: At step 708, trade target agent ranking engine 110 ranks the plurality of target agents [EN: with alternate shifts] from highest to lowest trade index score. ¶ [0053]: At step 710, agent user interface 120 displays the ranked plurality of target agents with the target agent having the highest trade index score at the top of the list [EN: thus identifying the alternate shift]); and
modifying, by the contact center system, the optimized contact center agent shift schedule to replace the individual shift with the identified alternative shift (Suryawanshi ¶ [0050]: …WFM system 105 changes the schedule of the source agent and the selected target agent according to the shift trade request).
Rationales to have modified / combined D’Attilio / Suryawanshi are above and reincorporated.
Regarding claim 20: D’Attilio / Suryawanshi teaches all the limitations of claims 19 above.
Although D’Attilio teaches applying column generation to optimize a contact center agent schedule based on staffing forecasts, agent data, and service goals, D’Attilio does not specifically teach modifying the optimized schedule upon requests for alternative individual agent shifts.
However, Suryawanshi in analogous art of contact center scheduling teaches or suggests:
wherein the alternative shift comprises a first alternative shift; and the method further comprising:
receiving, by the contact center system, alternative shift search criteria comprising shift preferences of an agent of the plurality of agents, performing, by the contact center system, a search for alternative shifts based on the alternative shift search criteria (Suryawanshi ¶ mid-[0021]: In one or more embodiments, when a source agent requests a trade, after entering his/her preferences of days and times, the source agent gets a list of matching target agents), and
identifying, by the contact center system, a second alternative shift (Suryawanshi ¶ mid-[0021]: This list of target agents is displayed based on the trade index score configurations, and the best match [EN: first alternative shift] is displayed at the top of the list. Advantageously, these details are seen on the trade shift webpage before the source agent sends a trade request to any other agents [EN: with a second alternative shift] or a manager.); and
wherein to replace the individual shift with the identified alternative shift comprises to replace the individual shift with the identified second alternative shift (Suryawanshi ¶ end-¶ [0021]: This helps source agents estimate the probability of having a successful trade and to choose the best match options [EN: among multiple alternatives]).
Rationales to have modified / combined D’Attilio / Suryawanshi are above and reincorporated.
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Claims 7-8, 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over:
D’Attilio / Suryawanshi as indicated above, and in further view of
Chobe US 20250045706 A1, hereinafter Chobe. As per,
Regarding claims 7, 17: D’Attilio / Suryawanshi teaches all the limitations of claims 1, 11 above.
Although D’Attilio teaches applying column generation to optimize a contact center agent schedule based on staffing forecasts, agent data, and service goals, D’Attilio does not specifically teach automatically approving shift change requests based on workload forecast, service goals, and staffing requirements.
However, Suryawanshi in analogous art of contact center scheduling teaches or suggests:
wherein the plurality of instructions further causes the system to:
evaluate a request to replace the individual shift of the optimized contact center agent shift schedule with the identified alternative shift (Suryawanshi ¶ [0057]: In one or more embodiments, WFM system 105 receives, from the manager, an upper threshold value and/or a lower threshold value for one or more of the trade index score, the trade history success index score, the matching skill index score, the skill proficiency index score, or the trade interval index score. In embodiments where the trade index score is also based on the adherence index score, WFM system 105 can also receive an upper threshold value and/or a lower threshold value for the adherence index score); and
automatically approve or deny the replacement request based on [..], the one or more service goals, and [..] (Suryawanshi ¶ mid-[0057]: In several embodiments, WFM system 105 determines that the trade index score is greater than or equal to the upper threshold value for the trade index score and WFM system 105 automatically approves the shift trade request. In some embodiments, WFM system 105 determines that the trade index score is lower than or equal to the lower threshold value for the trade index score and WFM system 105 automatically rejects or declines the shift trade request).
Suryawanshi and D’Attilio are found as analogous art of contact center scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified D’Attilio’s scalable contact center agent scheduling utilizing automated ai modeling and multi-objective optimization system and method to have included Suryawanshi’s teachings around automatically approving shift change requests based on workload forecast, service goals, and staffing requirements. The benefit of these additional features would have provided an improved experience to customers, sustained desirable levels of performance and reduced the impact on staffing levels when allowing agents to change shifts (Suryawanshi ¶ [0028-0029]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by D’Attilio in view of Suryawanshi (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of contact center scheduling. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by D’Attilio in view of Suryawanshi above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Furthermore, Chobe in analogous art of contact center scheduling teaches or suggests:
automatically approve or deny the replacement request based on the workload forecast, [..], and the staffing requirement model (Chobe ¶ [0040]: … WFM involves effectively forecasting staffing requirements and creating and managing staff schedules to accomplish a particular task on a day-to-day and hour-to-hour basis. ¶ [0041]: As used herein, "Staffing Requirements" may refer to the required amount of personnel (e.g. agents) needed at a contact center to handle expected/forecasted contacts in accordance with quality-of-service metrics. ¶ [0096]: FIG. 4C shows an example flow according to some embodiments of the invention. The example flow shows how embodiments of the invention can automatically approve and automatically adjust the schedules of the agents once a target agent accepts the trade request. [Also see Fig. 4C and related text]).
Chobe, Suryawanshi and D’Attilio are found as analogous art of contact center scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified D’Attilio / Suryawanshi’s scalable contact center agent scheduling utilizing automated ai modeling and multi-objective optimization system and method to have included Chobe’s teachings around automatically approving shift change requests based on workload forecast, service goals, and staffing requirements. The benefit of these additional features would have efficiently automated shift trading for contact center agents (Chobe ¶ [0004-0006]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by D’Attilio in view of Suryawanshi and Chobe (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of contact center scheduling. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by D’Attilio in view of Suryawanshi and Chobe above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding claims 8, 18: D’Attilio / Suryawanshi teaches all the limitations of claims 1, 11 above.
Although D’Attilio in combination with Suryawanshi teaches evaluating alternative shift requests, D’Attilio in combination with Suryawanshi does not specifically teach evaluating the alternative shift requests based on minimum lead time before the shift or a minimum staffing requirement.
However, Chobe in analogous art of contact center scheduling teaches or suggests:
wherein to evaluate the request to replace the individual shift of the optimized contact center agent shift schedule with the alternative shift comprises to evaluate the request based on a threshold amount of time between the evaluation and a start time of the alternative shift and a minimum staffing requirement (Chobe ¶ [0009]: According to some embodiments, the validation criteria for a given date includes a check that: the source agent has a shift on the given date; a pending multi-day trade request does not include the given date [EN: must be requested at least the day before]; and the given date includes a shift with a tradeable activity. Mid-¶ [0041]: Embodiments of the invention may ensure that staffing requirements are met by, for example, only allowing shift trades where both agents have a common skill such that the required staffing for that skill is preserved for the time periods of the traded shifts).
Chobe, Suryawanshi and D’Attilio are found as analogous art of contact center scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified D’Attilio / Suryawanshi’s scalable contact center agent scheduling utilizing automated ai modeling and multi-objective optimization system and method to have included Chobe’s teachings around evaluating the alternative shift requests based on minimum lead time before the shift or a minimum staffing requirement. The benefit of these additional features would have efficiently automated shift trading for contact center agents (Chobe ¶ [0004-0006]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by D’Attilio in view of Suryawanshi and Chobe (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of contact center scheduling. In such combination each element would have merely performed the same function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by D’Attilio in view of Suryawanshi and Chobe above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
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Conclusion
The following art is made of record and considered pertinent to Applicant’s disclosure:
Sun; Xiaoqing et al. US 20230222410 A1, Systems and methods for decomposition in workforce optimization with search sub-problems.
deSilva, Anura H. et al. US 20050004828 A1, System and method for preference scheduling of staffing resources.
Mishra; Sanyog et al. US 20250148387 A1, System and method for auto-approving pending requests of agents based in a dynamic environment.
Bergman; Ophira et al. US 20190304595 A1, Methods and apparatus for healthcare team performance optimization and management.
Ambekar; Harshad et al. US 20240242143 A1, Computerized-method and computerized-system for identifying high impacted schedules, in a contact center.
Fama; Jason et al. US 20190130329 A1, Systems and methods for automatic scheduling of a workforce.
Pati; Sunil et al. US 20180365624 A1, Anonymized allocations-based workforce management system.
Wayne; David Henry et al. US 20240020756 A1, Apparatus and methods for enabling workers to compete for currently upcoming shifts.
BELL; CLIFF W. et al. US 20250148385 A1, Automated incentivizing tool for contact center agents.
Narasimhan, Sundar et al. US 20050096962 A1, Methods and systems for assigning workshifts.
Vasnani; Kanchan et al. US 20250094933 A1, System and method of digital schedule processing.
Aykin; Turgut US 7725339 B1, Contact center scheduling using integer programming.
Flockhart; Andrew D. et al. US 8234141 B1, Dynamic work assignment strategies based on multiple aspects of agent proficiency.
O'Brien; Kenneth US 6587831 B1, System and method for online scheduling and shift management.
Bagade N et al. US 20230196228 A1, Method for predicting target-agents for shift-trade request e.g. Date based on trading trends of agents in contact center, involves sending notification with details of first scheduled-shift for each computerized-device of pre-configured number of top predicted-probability target-agents.
Tewari, Swati et al. CA 2567368 A1, Systems and methods of partial shift swapping.
Taylor, James W. "Density forecasting of intraday call center arrivals using models based on exponential smoothing." Management Science 58.3 (2012): 534-549.
https://www.jstor.org/stable/pdf/41431669
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/REED M. BOND/Examiner, Art Unit 3624
August 4, 2026
/HAMZEH OBAID/Primary Examiner, Art Unit 3624 August 5, 2026
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