DETAILED ACTION
This FINAL office action is in response to Applicant’s amendment filed August 3, 2026. Applicant’s August 3, 2026 amendment amended claims 1 and 2 and canceled claims 3-5 and added new claims 9 and 10. Currently Claims 1, 2 and 6-10 are pending. Claims 1 and 2 are the independent claims.
The instant application is a continuation of application no. 17683148, now abandoned, which is a continuation of application no. 16616257 now abandoned.
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 .
Response to Amendment
The 35 U.S.C. 101 rejection of Claims 1, 2 and 6-8 in the previous office action is maintained.
Applicant’s amendments to the claims necessitated the new grounds of rejection.
Response to Arguments
Applicant's arguments filed August 3, 2026 have been fully considered but they are not persuasive. Specifically, Applicant argues that the claims are patent eligible under 35 U.S.C. 101 as the claims are not directed to an abstract idea/cannot be performed mentally (e.g. specific feedback driven mechanism for modifying weighted hierarchal structure and updating a plurality of rules associated with comparative learning; automatically setting safety stock quantity; requires specific analytics engine; Specification: Paragraphs 83, 85; Remarks: Last Paragraph, Page 9; Last Two Paragraphs, Page 10); the provides a computing improvement (e.g. improves processing speed by providing hierarchical model structure comprising risk categories, attributes and weights; Specification: Paragraphs 114, 118, 119; Remarks: Paragraph 1, Page 10), the claims are similar to the recent Dejardins et al. decision (Remarks: Paragraph 1, Page 10); and the claims recite significantly more than the abstract idea (Remarks: Paragraph 2, Page 11).
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims are not directed to an abstract idea and/or the claims cannot be performed mentally, the examiner respectfully disagrees.
The claims are directed to a well-known economic business practice – supply chain planning – more specifically displaying comparative risk of insufficient supply (supply imbalance) within a supply chain and setting a new safety stock quantity (Title: Systems and Methods for Risk Processing of Supply Chain Management System Data; representative claim 1: calculating a comparative opportunity value….generating a plurality of data outputs associated with the comparative value comprising the risk to the supply chain of the imbalance…displaying an interactive data visualization interface….displaying a drill-down window…automatically set the new safety stock quantity….) utilizing generic computing elements for the old, well-known, conventional and routine purpose (merely a tool/conduit for the abstract idea; i.e. without significantly more, see detailed discussion below).
Supply chain planning, more specifically the analysis of the risk of insufficient supply in a supply chain in order to set a safety stock quantity (i.e. supply chain planning - inventory/replenishment management), is a fundamental economic practice that falls into the abstract idea subcategories of sales activities and/or commercial interactions. The intended purpose of independent claim appears to be to enable a human user to view data (comparative values) displayed as bubbles having relative sizes and determine/set a new safety stock quantity for at least one component.
While the claims may represent an improvement to the fundamental economic process of analyzing and visualizing supply chain imbalance risks in order to set a safety stock quantity (i.e. an improvement in the abstract idea itself – supply chain planning), the claims in no way either claimed or disclosed provide a technical solution to a technical problem; improve any of the underlying technology or improve another technology or technical field (supply chain planning is not a technology nor a technical field).
Further, the claims are directed to a mental processing practically capable of being performed in the human mind via observation, evaluation, judgement and opinion. Representative claim 1: The step of receiving first data from a plurality of supply chain noes may be performed in the human mind using observation of data. The step of receiving social media data from one or more networked social media feeds may be performed in the human mind using observation of data. The step of producing tertiary data based on a plurality of rules may be performed in the human mind via judgement and opinion. The step of calculating a comparative opportunity value from the tertiary data may be performed in the human mind using judgement. This step is also directed to a mathematical operation/concept. The step of generating a plurality of data outputs, using a comparative learning algorithm, may be performed in the human mind via judgement and opinion. The step of displaying an interactive data visualization interface directed to insignificant extra-solution activity (i.e. data output), further a human via pen and paper is practically capable of drawing a visualization of graphical bubble icons. The step of receiving a selection of one of the bubble icons may be performed in the human mind via observation of data. The step of displaying an analytics window is directed to insignificant extra-solution activity (i.e. data output), further a human via pen and paper is practically capable of drawing a window comprising graphical component icons. The step of receiving a selection of a component icon may be performed in the human mind via observation. The step of displaying a drill down window directed to insignificant extra-solution activity (i.e. data output), further a human via pen and paper is practically capable of drawing of drill-down window overlaid on the analytics window. The step of receiving accumulation data may be performed in the human mind via observation. The step of determine a correlation between at least one supply chain attribute and the actual risk outcome may be performed in the human mind via judgement and opinion. The step of modify the weighted hierarchical structure by modifying assigned weighting may be performed in the human mind via judgement and opinion. The step of update the plurality of rules associated with the comparative learning algorithm may be performed in the human mind via judgement. The step of using the updated plurality of rules to determine a new safety stock quantity may be performed in the human mind via judgement. The step of set the new safety stock quantity may be performed in the human mind by observation. Additionally setting the safety stock quantity is directed to insignificant post/extra solution activity (mere data output) and may at best be an insignificant application of the abstract idea (apply it; see at least MPEP § 2106.05(f), MPEP 2106.05(g) - Insignificant application: i. Cutting hair after first determining the hair style, In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016)).
Other than the recitation of an analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display nothing in the claimed steps precludes the step from practically being performed in the mind. The claims do not recite additional elements that are sufficient to amount to significantly more than the abstract idea. The limitations directed to analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display are each recited at a high level of generality and amount to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f).
Further the mere nominal recitation of a generic computer does not take the claim limitation out of the mental processes grouping. The claims use “conventional or generic technology in a nascent but well-known environment” to implement the abstract idea of business analytics.
Nothing in Applicant’s disclosures suggests that the Applicant intended to accomplish any of the steps recited in the claims through anything other than well understood technology used in a routine and conventional manner. Therefore, the claims lack an inventive concept.
Reevaluating the steps of receiving first data, receiving social media data, displaying an interactive data visualization interface, receiving a selection, displaying an analytics window, receiving a selection, displaying a drill-down window, receiving accumulation data and setting a safety stock quantity which are considered insignificant extra solution activity, these limitations are mere data gathering and/or data output recited at a high level of generality and amount to nothing more than which are both well-understood, routine and conventional activities. The limitations remain insignificant extra solution activity even upon reconsideration. Even when considered in combination the additional elements represent mere instructions to apply an exception and insignificant extra solution activity which cannot provide an inventive concept.
As for Applicant’s argument the claims require a specific computer, specifically an analytics engine, the examiner respectfully disagrees. The recited hardware and software, of which the analytics engine is at best comprised of, elements recited in the claims were specifically considered and were determined to be nothing more than recitations of a generic computer or other machinery used a tool/conduit for the abstract idea.
As described in MPEP § 2106.05(f), additional elements that invoke computers or other machinery merely as a tool to perform an existing process will generally not amount to significantly more than a judicial exception. See, e.g., Versata Development Group v. SAP America, 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015) (explaining that in order for a machine to add significantly more, it must “play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly”).
(2) Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field.
Further as discussed in MPEP 2106.05(I)(A): "It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2B. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception is not in itself an inventive concept and does not guarantee eligibility: The fact that a computer "necessarily exist[s] in the physical, rather than purely conceptual, realm," is beside the point. There is no dispute that a computer is a tangible system (in § 101 terms, a "machine"), or that many computer-implemented claims are formally addressed to patent-eligible subject matter. But if that were the end of the § 101 inquiry, an applicant could claim any principle of the physical or social sciences by reciting a computer system configured to implement the relevant concept. Such a result would make the determination of patent eligibility "depend simply on the draftsman’s art," Flook, supra, at 593, 98 S. Ct. 2522, 57 L. Ed. 2d 451, thereby eviscerating the rule that "‘[l]aws of nature, natural phenomena, and abstract ideas are not patentable,’" Myriad, 133 S. Ct. 1289, 186 L. Ed. 2d 124, 133).
As for the recited comparative learning algorithm for generating a plurality of data outputs associated with the comparative opportunity value comprising the risk to the supply chain imbalance, updating the plurality of rules associated with the comparative learning algorithm, using the updated plurality of rules in applying the comparative learning to determine/set a safety stock, the comparative learning algorithm is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic comparative learning algorithm on a generic computer, also recited at a high level of generality. Only Specification Paragraph 118, as published, tangentially mentions that risk modeling or recommendations may comprising one or more learning algorithms and that the learnings may cause modification to automated weightings assigned by the analytics engine. The comparative learning algorithm is used to generally apply the abstract idea without limiting how the comparative learning algorithm functions. The comparative learning algorithm is described at a high level such that it amounts to using a generic computer with a generic comparative learning algorithm to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Nothing in Applicant’s disclosures suggests that the Applicant intended to accomplish any of the steps recited in independent claims 1 and 2 through anything other than well understood technology used in a routine and conventional manner. Therefore, the claims lack an inventive concept. See also, e.g., Elec. Power Grp., 830 F.3d at 1355 (holding claims lacked inventive concept where “[n]othing in the claims, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information”); Content Extraction, 776 F.3d at 1348 (holding claims lacked an inventive concept where the claims recited the use of “existing scanning and processing technology”).
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s arguments that the claims are patent eligible under 35 U.S.C. 101 as the claims provide a computing improvement, the examiner respectfully disagrees.
As discussed above claims are directed to a well-known business practice – supply chain planning – more specifically displaying comparative risk of insufficient supply (supply imbalance) within a supply chain and the automatically setting a safety stock quantity. While the claims may represent an improvement to the business process of supply chain planning – specifically supply imbalance risk analysis (i.e. improvement lies in the abstract idea itself – supply chain planning), they in no way either claimed or disclosed or inherent in the recited method steps provide a technical solution to a technical problem; improve any of the underlying technology, or represent a practical application of the abstaract idea or represent an improvement to other technology or technical field (i.e. supply chain planning/analysis is not a technical field or a technology or a technical problem– it is a well-known business problem).
The instant application provides an interactive data visualization interface (aka. a user interface) comprising selectable bubble icons associated with a comparative opportunity value (data) that when selected (by a human) display an analytics window which when selected displays a drill-down window (overlaid) which enable a human user to input data and then performs a series of data manipulation/calculation steps in order to determine and set a safety stock quantity. Neither the displayed data, in the form of one or more interactive/selectable bubbles/windows/icons, nor the ability to enter data via a window nor the launching of one or more windows in response to a user’s selection (a core requirement for any/all graphical user interfaces) nor setting a safety stock quantity in any way improves the underlying computer or improves another technical field or solves a technical problem in the realm of computers or computer networks. The interactive/actuatable/selectable bubbles/icons/windows simply data output on a screen and enable a human user to input data into a computer via a window/interactive data visualization interface wherein such data visualization and data input are a conventional, well-known and extremely common (if not inherent) use of a user interface and represent insignificant extra solution activity. Figure 8B provided for Applicant’s convenience.
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The claimed windows, icons, bubbles and the like do not represent a technical solution to a technical problem nor do the claims improve the functioning of the underlying computer/technology nor do the claims recite an improvement to other technology (none identified in Applicant’s remarks) or technical field (supply chain management is not a technical field, supply chain management is a well-known, well-understood, conventional and routine business solution to a business planning problem) nor do the claims integrate the abstract idea into a practical application.
While the claims may improve the ability of a human user to visualize supply chain imbalances and perform a series of calculations/data operations to determine/set a safety stock quantity neither utilizing well-known bubble charts/graphs nor data manipulations/calculations are directed to a technical solution to a technical problem, the claims do not recite an improvement in the underlying computer technology, the claims do not recite an improvement in another technology or technical field. The claimed invention does not improve any of the generic/conventional technological components claimed.
At best the claims recite an improvement to the abstract idea itself, wherein the abstract idea is merely applied and performed using generic computers performing generic computer processing.
In view of the MPEP 2106.05, one must consider whether there are additional elements set forth in the claims that integrate the judicial exception into a practical application. The identified additional non-abstract elements recited in the independent claims are the generic analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display. These generic computer hardware merely performs generic computer functions of receiving, processing and displaying data and represent a purely conventional implementation of applicant’s supply chain risk analysis in the general field of business analytics and do not represent significantly more than the abstract idea. See at least MPEP § 2106.05(a) ("Improvements to the Functioning of a Computer or to Any Other Technology or Technical Field").
These recited additional elements are merely generic computer components. The claims do present any other issues as set forth in MPEP 2106.05 regarding a determination of whether the additional generic elements integrate the judicial exception into a practical application. Rather, the claims merely use instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea.
There is a fundamental difference between computer functionality improvements, on the one hand, and uses of existing computers as tools to perform a particular task, on the other — a distinction that the Federal Circuit applied in Enfish, in rejecting a § 101 challenge at the first stage of the Mayo/Alice framework because the claims at issue focused on a specific type of data structure, i.e., a self-referential table, designed to improve the way a computer stores and retrieves data in memory, and not merely on asserted advances in uses to which existing computer capabilities could be put. See Enfish, 822 F.3d at 1335-36. Here the claims simply use a computer as a tool and nothing more.
For the reasons outlined above, the claims are directed to a method of organizing human activity, i.e., an abstract idea, and that the additional element recited in the claim beyond the abstract idea (e.g., computer, data visualization interface, etc.) is no more than a generic computer component used as a tool to perform the recited abstract idea. As such, it does not integrate the abstract idea into a practical application. See Alice Corp., 573 U.S. at 223-24 (“[Wholly generic computer implementation is not generally the sort of ‘additional featur[e]’ that provides any ‘practical assurance that the process is more than a drafting effort designed to monopolize the [abstract idea] itself.’” (quoting Mayo, 566 U.S. at 77)).
Under step two of the Mayo/Alice framework, the elements of each claim are considered both individually and “as an ordered combination” to determine whether the additional elements, i.e., the elements other than the abstract idea itself, “transform the nature of the claim” into a patent-eligible application. Alice Corp., 573 U.S. at 217 (citation omitted); see Mayo, 566 U.S. at 72-73 (requiring that “a process that focuses upon the use of a natural law also contain other elements or a combination of elements, sometimes referred to as an ‘inventive concept,’ sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the natural law itself’ (emphasis added) (citation omitted)).
Here the only additional element recited in claims 1, 2, and 6-10 beyond the abstract idea are the analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display i.e., generic computer component. See Alice, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). Applicant has not identified any additional elements recited in the claim that, individually or in combination, provides significantly more than the abstract idea.
As for Applicant’s that the claimed invention improves processing speed by providing hierarchical model structure comprising risk categories, attributes and weights, the examiner respectfully disagrees.
In order to successfully argue that the claims invention results in an improvement in a technology or another technical field Applicant must claim the argued improvement and clearly disclose that the improvement as discussed in detail in McRO, McRO, 837 F.3d at 1316, 120 USPQ2d at 1103. The basis for the McRO court's decision was that the claims were directed to an improvement in computer animation. The court relied on the specification's explanation of how the claimed rules enabled the automation of specific animation tasks that previously could not be automated. 837 F.3d at 1313, 120 USPQ2d at 1101. The McRO court found that the claims clearly improved the functioning of the claimed computer and that the claims directed to recite improvement (e.g. rules). Further the court found that the specification clearly disclosed that the claimed improvement improved the functioning of the computer. Neither Applicant’s disclosure nor the pending claims recite or disclose an improvement to the functioning of any of the underlying technology/technological components.
With regards to argued Specification Paragraph 114, see below, Applicant’s disclosure discusses at a very high level that due to voluminous accessible data to which rules-based risk modeling/risk analysis may be applied comparative risk model algorithms maybe employed which may employ a hierarchal model structure to improve processing speed and capabilities. This single sentence fails to discuss in any level of detail how the hierarchical models function such that they result in improved processing speed. At best this represents a wished for improvement. Further, as discussed below – see rejection under 35 U.S.C. 112a – Applicant’s disclosure fails to provide sufficient support for the newly claimed features, including the hierarchical model structure argued to provide a computing improvement.
[0114] The analytics engine 1703 may employ the voluminous accessible data 1711 to apply rules-based risk modelling to allow for extensive risk management of risk in supply chain operation and supply chain design. The comparative risk model algorithms 1709 that may be employed by the analytics engine 1703 additional improve computing processing speed and capabilities by providing a hierarchical model structure. That is, categories in which risk may occur in a supply chain design, such as five (5) risk categories, may be hierarchically treated and provided within the comparative algorithms 1709. Within each category, one or more attributes may be provided that contribute to a scoring within the category. Of note, each category may be scored, as may be each attribute within each category to contribute to the category score, and these scores may be weighted, such as in relation to the stated goals and objectives of a user, as referenced further below. This weighted scoring system may then provide a total risk score for the factor, part, supplier, or the like for which the risk model was applied.
With regards to argued Specification Paragraph 118, discloses that risk modeling a recommendations may comprise one or more learning algorithms which may cause modification of weightings recommended/assigned by the analytics engines. This paragraph fails to disclose or discuss at any level of detail improving the functioning of a computer or other technology and as such does not a represent a technical solution to a specific technical problem inherent in computers or computer networks and does not improve any of the underlying technology or represent an improvement to another technical field.
With regards to argued Specification Paragraph 119, discloses that attribute interrelationships may occur and the some risk factors may be more important than others which may be factored into the decision making process/risk modeling/analysis. Further this paragraph discloses that rules maybe modified as learning occurs based on feedback. This paragraph fails to disclose or discuss at any level of detail improving the functioning of a computer or other technology and as such does not a represent a technical solution to a specific technical problem inherent in computers or computer networks and does not improve any of the underlying technology or represent an improvement to another technical field.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims are similar to the recent Appeals Review Panel review of Ex parte Desjardins et al., related to U.S. Patent Application No. 16/319,040, assigned to DeepMind Technologies Limited, the examiner respectfully disagrees.
While the Desjardins decision cautions against overbroad application of 35 U.S.C. 101 to artificial intelligence inventions, such inventions not categorically excluded from patentability, the thrust of the decision made clear that improvements to an AI model itself can be sufficient for the purpose of patent eligibility, even when the claims recite, on their face, an ostensibly “abstract idea.” Specifically, the Appeals Review Panel found that the claims under review provided a technical improvement in the functioning of comparative learning algorithm/models by enabling continual learning, reducing storage requirements, and preserving performance across tasks. In particular, the decision emphasized that the claimed invention addresses a technical problem ("catastrophic forgetting") and improves the operation of AI systems, not just through generic computer implementation but by a specific training strategy. To support this determination, the Appeals Review Panel looked to the specification which, on its own, disclosed how the invention would improve functioning of an AI model--in particular, the specification explained how the proposed invention would use less “storage capacity” and lead to “reduced system complexity." These improvements, which the Appeals Review Panel found were incorporated into the claims as a whole, constituted an “improvement to how the comparative learning algorithm/model itself operates”.
None of Applicant’s arguments, disclosure or claims discusses at any level that the generically applied/utilization of comparative learning algorithm represents or provides an improvement in machine learning itself.
While independent claims 1 and 2, comparative learning algorithm for generating a plurality of data outputs associated with the comparative opportunity value comprising the risk to the supply chain imbalance, updating the plurality of rules associated with the comparative learning algorithm, using the updated plurality of rules in applying the comparative learning to determine/set a safety stock, the comparative learning algorithm is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic comparative learning algorithm on a generic computer, also recited at a high level of generality. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished. Further nowhere in Applicant’s disclosure is there any discussion at any level that the utilization of a generic comparative learning algorithm/model to identify/classify items improve the general field of machine learning or addresses a technical problem in the field of machine learning or provides an improvement to a specific comparative learning algorithm/model, algorithm, technique or the like.
Accordingly, the claims are nothing like those in the Desjardins decision and are therefore not patent eligible under 35 U.S.C. 101.
In response to Applicant’s argument that the claims are patent eligible under 35 U.S.C. 101 as the claims recite significantly more than the abstract idea, the examiner respectfully disagrees.
The claims use “conventional or generic technology in a nascent but well-known environment” to implement the abstract idea of business analytics. In re TLI Commc’ns LLC Pat. Litig., 823 F.3d 607, 612 (Fed. Cir. 2016). The recited technology (processor, memory, device, platform, etc.), are used as a “conduit for the abstract idea,” not to provide a technological solution to a specific technological problem. Id.; see also id. at 611–13 (holding claims reciting the use of a cellular telephone and a network server to classify an image and store the image based on its classification to be abstract because the patent did “not describe a new telephone, a new server, or a new physical combination of the two” and did not address “how to combine a camera with a cellular telephone, how to transmit images via a cellular network, or even how to append classification information to that data”).
Nothing in Applicant’s disclosures suggests that the Applicant intended to accomplish any of the steps recited in independent claims 1 and 2 through anything other than well understood technology used in a routine and conventional manner. Therefore, the claims lack an inventive concept. See also, e.g., Elec. Power Grp., 830 F.3d at 1355 (holding claims lacked inventive concept where “[n]othing in the claims, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information”); Content Extraction, 776 F.3d at 1348 (holding claims lacked an inventive concept where the claims recited the use of “existing scanning and processing technology”).
Additionally, it is noted that displaying text or other data as part of an interactive computer user interface (e.g., window) wherein the textual data comprises one or more items such that upon actuation/selection a second or third window is launched to provide additional data/information is old, very-well-known, routine and conventional in user interfaces (e.g. nearly all websites contain textual links which launch new websites many times in a new browser window). Such actuation/selection of textual data displayed as part of a user interface (e.g. URL links) does not represent an improvement to the user interface nor an improvement to the underlying technology (e.g. computer). Support for this old and well-known fact can be found in at least the following references: Hansen, U.S. Patent No. 9412117 (Claims 43, 63, 69); Rubin et al. U.S. Patent No. 11816619 (DETX 187, Claims 1, 14); Tawil et al. U.S. Patent Publication No. 20150248536 Paragraph 158, Claim 19; Huang U.S. Patent No. 9547409 Claims 7, 17; Jose, U.S. Patent No. 9489417 (Claim 19).
As discussed in Uniloc USA, Inc. v. LG Electronics USA, Appeal No. 19-1835 (Fed. Cir. Apr. 30, 2020), the Federal Circuit reaffirmed that software inventions are patentable in the U.S. with a bright-line statement: “Our precedent is clear that software can make patent-eligible improvements to computer technology, and related claims are eligible as long as they are directed to non-abstract improvements to the functionality of a computer or network platform itself.” Nothing in Applicant’s disclosure or the pending claims (e.g. a bubble chart that is selectable and capable of launching an analytics window and the analytics window itself is capable of nesting information and generating another window) makes patent eligible improvements to the functioning of the claimed processor, memory (platform) or another technical field similar to those discussed in Uniloc.
Applicant has not demonstrated that a special purpose machine/computer is required to carry out the claimed invention. A special purpose machine is now evaluated as part of the significantly more analysis established by the Alice decision and current 35 U.S.C. 101 guidelines. It involves/requires more than a machine only broadly applying the abstract idea and/or performing conventional functions.
Applicant’s claimed features directed to a system and components do not represent custom or specific computer hardware circuits, instead the term system merely refers to commercially available software and/or hardware.
As discussed above and as described in MPEP § 2106.05(f), the recited analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display must “play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly” in order to add significantly more than the abstract idea. The claims merely invoke computers or other machinery merely as a tool to perform an existing process and use of a computer or other machinery in its ordinary capacity for economic or other tasks and as such do not recite significantly more than an abstract idea.
As discussed above the additional elements in the claims amount to no more than a mere instruction to apply the abstract idea using generic computing components or other machinery, wherein mere instructions to apply an judicial exception using generic computer components or other machinery do not provide an inventive concept.
Accordingly, the claims are not patent eligible under 35 U.S.C. 101.
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, 2 and 6-10 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 claim(s) 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 pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding independent 1 and 2, the claims recite “modify the weighted hierarchical structure of the tertiary data based on the received accumulation data by automatically modifying the automated weighting assigned to the at least one supply chain attribute based on the determined correlation” wherein Applicant’s specification does not provide a sufficient description to show possession of the invention. Specifically, Applicant’s specification fails to provide a specific algorithm, models, flow-charts, steps, processes or the like for at least the step of modify the weighted hierarchical structure of the tertiary data based on the received accumulation data by automatically modifying the automated weighting assigned to the at least one supply chain attribute based on the determined correlation as claimed. Applicant’s specification only describes an indication of a result that one might achieve. This is insufficient to show possession or enablement under 35 U.S.C. 112.
Only Specification Paragraph 114, see above, tangentially mentions that hat each (risk) category may be scored and that these scores maybe weighted - weighted scoring system - to provide a total risk score for a factor – this brief discussion of a weighted scoring system is insufficient to show possession of the invention as claimed. This paragraph, like the remainder of Applicant’s disclosure fails to discuss at any level modifying a weighted hierarchical structure much along automatically modifying weighting assigned to supply chain attributes as part of a weighted hierarchical structure as claimed.
Accordingly, Applicant's specification fails to provide adequate written support to show possession as well as lacks written disclosure to enable one to use the invention without undue experimentation as claimed. Applicant's disclosure fails to disclose any specific method, algorithm, approach, process or working example for the step “modify the weighted hierarchical structure of the tertiary data based on the received accumulation data by automatically modifying the automated weighting assigned to the at least one supply chain attribute based on the determined correlation” as claimed nor the claimed embodiment as a whole.
The Federal Circuit explained that “[t]he test for the sufficiency of the written description ‘is whether the disclosure of the application relied upon reasonably conveys to those skilled in the art that the inventor had possession of the claimed subject matter as of the filing date.’” Id. at 682 (quoting Ariad, 598 F.3d at 1351). The Federal Circuit emphasized that “[t]he written description requirement is not met if the specification merely describes a ‘desired result.’” Vasudevan, 782 F.3d at 682 (quoting Ariad, 598 F.3d at 1349). Thus, in applying this standard to the computer implemented functional claim at issue, the Federal Circuit stated that “[t]he more telling question is whether the specification shows possession by the inventor of how [the claimed function] is achieved.” Vasudevan, 782 F.3d at 683.
It is noted that the written description requirement under 112(a) is not satisfied by stating that one of ordinary skill in the art could devise an algorithm to perform the specialized programmed functions. For written description, the specification as filed must describe the claimed invention in sufficient detail so that one of ordinary skill in the art can reasonably conclude that the inventor had possession of the claimed invention. An original claim may lack written description when the claim defines the invention in functional language specifying a desired result but the specification does not sufficiently identify how the inventor has devised the function to be performed or result achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient).
Further, the structure corresponding to claim limitations that are computer-implemented specialized functions must include a general-purpose computer or computer component along with the algorithms that the computer uses to perform each claimed specialized function.
It is not enough that one skilled in the art could theoretically write a program to achieve the claimed function, rather the specification itself must explain how the claimed function is achieved to demonstrate that the applicant had possession of it. See, e.g., Vasudevan, 782 F.3d at 682-83.
Applicant’s specification does not provide a disclosure of the computer and algorithms in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention that achieves the claimed result.
Accordingly, Applicant's specification fails to provide adequate written support to show possession as well as lacks written disclosure to enable one to use the invention without undue experimentation as claimed. Applicant's disclosure fails to disclose any specific method, algorithm, approach, process or working example for the step of “modify the weighted hierarchical structure of the tertiary data based on the received accumulation data by automatically modifying the automated weighting assigned to the at least one supply chain attribute based on the determined correlation” as claimed.
Further regarding independent 1 and 2, the claims recite “update the plurality of rules associated with the comparative learning algorithm based on the modified automated weighting for subsequent generation of the plurality of data outputs” and “use the updated plurality of rules in a subsequent application of the comparative learning algorithm to determine a new safety stock quantity for the at least one component” wherein Applicant’s specification does not provide a sufficient description to show possession of the invention. Specifically, Applicant’s specification fails to provide a specific algorithm, models, flow-charts, steps, processes or the like for at least the step of updating a plurality of rules using a comparative learning algorithm based on automated weighting or using the plurality of updated rules in a subsequent application of the comparative learning algorithm to determine a safety stock quantity as claimed. Applicant’s specification only describes an indication of a result that one might achieve. This is insufficient to show possession or enablement under 35 U.S.C. 112.
Initially it is noted that neither comparative learning algorithm nor comparative learning appear anywhere in Applicant’s disclosure. The phrase comparative learning is recited in only Specification Paragraphs 110 and 114 (see discussion below), while the phrase comparative and cascading analytics is mentioned in Specification Paragraph 111. Additionally, the phrase comparative rule set is mentioned in Specification Paragraph 118 (see discussion below).
Specification Paragraph 110, see below, discloses that the invention may apply comparative algorithms to large volume of supply chain data. This paragraph fails to provide any specific discussion of what the comparative algorithms are much alone how they are applied to the voluminous supply chain data. More specifically, this paragraph like the remainder of Applicant’s disclosure fails to discuss updating a plurality of rules using a comparative learning algorithm or more specification updating a plurality of rules using a comparative learning algorithm based on automated weighting or using the plurality of updated rules in a subsequent application of the comparative learning algorithm to determine a safety stock quantity as claimed.
[0110] ……The analytics engine 1703 may include a risk attribute module 1705 that may perform the functionality described in the Figures herein, and such as may apply rules indicated for an risk attribute analysis by a rules engine 1707 that applies at least a comparator 1709 having therein comparative algorithms, such as those discussed herein, to the large volume data 1711 from other supply chains, such as may include similar product verticals and dissimilar verticals that integrate similar parts, and from the nodes of the supply chain of interest.
Specification Paragraph 111 discloses a diagnostic and analytics engine applied node-by-node, line-by-line to a particular supply chain such that a variety of comparative and cascading analytics may be assessed. This paragraph fails to discuss updating a plurality of rules using a comparative learning algorithm or more specification updating a plurality of rules using a comparative learning algorithm based on automated weighting or using the plurality of updated rules in a subsequent application of the comparative learning algorithm to determine a safety stock quantity as claimed
Specification Paragraph 114, see above, similarly discloses applying rules-based risk modeling to voluminous supply chain data as well as the use of comparative risk model algorithms which employ a hierarchical model structure. This paragraph like the remainder of Applicant’s disclosure fails to discuss updating a plurality of rules using a comparative learning algorithm or more specification updating a plurality of rules using a comparative learning algorithm based on automated weighting or using the plurality of updated rules in a subsequent application of the comparative learning algorithm to determine a safety stock quantity as claimed
Specification Paragraph 118, discloses that risk modeling and recommendations may comprise one or more learning algorithms and that the learning algorithms may cause the modification to automated weights assigned by the analytics engine. While this single paragraph discloses automatically updating weights by the analytics engine, this brief disclosure fails to provide any details as to how those modifications are actually implemented. This paragraph merely recites wished for outcomes/results without any discussion as to how without any discussion as to how that result is actually implemented or achieved. More specifically, this paragraph like the remainder of Applicant’s disclosure fails to discuss updating a plurality of rules using a comparative learning algorithm or more specification updating a plurality of rules using a comparative learning algorithm based on automated weighting or using the plurality of updated rules in a subsequent application of the comparative learning algorithm to determine a safety stock quantity as claimed.
Accordingly, Applicant's specification fails to provide adequate written support to show possession as well as lacks written disclosure to enable one to use the invention without undue experimentation as claimed. Applicant's disclosure fails to disclose any specific method, algorithm, approach, process or working example for the step recite “in response to detecting the one or more stopping criteria, generating a supply chain plan” as claimed nor the claimed embodiment as a whole.
While Applicant’s specification appears to suggest some potential capabilities of the claimed system/method, the Specification merely lists potential features and fails to disclose any specific method, mechanism, process, algorithm, or example for how to perform any of the claimed steps much alone the combination of the steps as claimed. Applicant’s specification simply represents a wish list of potential system/device capabilities without any disclosure as to HOW those wished for capabilities are actually performed or implemented.
Further, the structure corresponding to claim limitations that are computer-implemented specialized functions must include a general-purpose computer or computer component along with the algorithms that the computer uses to perform each claimed specialized function.
It is not enough that one skilled in the art could theoretically write a program to achieve the claimed function, rather the specification itself must explain how the claimed function is achieved to demonstrate that the applicant had possession of it. See, e.g., Vasudevan, 782 F.3d at 682-83.
Applicant’s specification does not provide a disclosure of the computer and algorithms in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention that achieves the claimed result.
Accordingly, Applicant's specification fails to provide adequate written support to show possession as well as lacks written disclosure to enable one to use the invention without undue experimentation as claimed. Applicant's disclosure fails to disclose any specific method, algorithm, approach, process or working example for the steps of “update the plurality of rules associated with the comparative learning algorithm based on the modified automated weighting for subsequent generation of the plurality of data outputs” and “use the updated plurality of rules in a subsequent application of the comparative learning algorithm to determine a new safety stock quantity for the at least one component” as claimed.
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, 2 and 6-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Regarding independent Claims 1 and 2, the claims are directed to the abstract idea of business analytics. This is a process (i.e. a series of steps) which (Statutory Category – Yes –process).
The claims recite a judicial exception, a method for organizing human activity, business analytics (data visualization) (Judicial Exception – Yes – organizing human activity). Specifically, the claims are directed to displaying comparative risk of insufficient supply (supply imbalance) within a supply chain, wherein business analytics is a fundamental economic practice that falls into the abstract idea subcategories of sales activities and/or commercial interactions. Further all of the steps of “receiving”, “receiving”, “producing”, “calculating”, “generating”, “displaying”, “receiving”, “displaying”, “receiving”, “displaying”, “receiving”, “determining”, “modifying”, “updating”, “using”, “automatically setting” (Claim 1) recite functions of the business analytics; the steps of “receive”, “produce”, “calculate”, “generate”, “display”, “receive”, “display”, “receive”, “display”, “receive”, “determine”, “modify”, “update”, “use”, and “automatically set” (Claim2) recite function of business analytics. The intended purpose of independent Claims 1, 2 and 6-10 appears to be to provide a human user with visualization of data – supply chain imbalances - utilizing well-known bubble charts/graphs wherein the displayed data is associated with the risk of supply chain imbalance (insufficient supply/inventory) a supply chain and to set a safety stock quantity. Supply chain planning, more specifically the analysis of the risk of insufficient supply in a supply chain, is a fundamental economic practice that falls into the abstract idea subcategories of sales activities and/or commercial interactions. The intended purpose of independent claim appears to be to enable a human user to view data (comparative values) displayed as bubbles having relative sizes and to set a safety stock for a component.
Accordingly, the claims recite an abstract idea – fundamental economic practice, specifically in the abstract idea subcategories of sales activities and/or commercial interactions. The exceptions are the additional limitations of generic analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display.
Accordingly, the claims recite an abstract idea under Step 2A, Prong One, we proceed to Step 2A, Prong Two. Considering whether the additional elements set forth in the claim integrate the abstract idea into a practical application, the previously identified non-abstract elements directed to generic computing components include: analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display. These generic computing components are merely used to receive, process and display data as described extensively in Applicant’s specification (Specification: Figures 1, 2). Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. Moreover, when viewed as a whole with such additional elements considered as an ordered combination, the claim modified by adding a generic computer would be nothing more than a purely conventional computerized implementation of applicant's business analytics in the general field of business management and would not provide significantly more than the judicial exception itself. Note McRo, Inc. v. Bandai Namco Games America Inc. (837 F.3d 1299 (Fed. Cir. 2016)), guides: "[t]he abstract idea exception prevents patenting a result where 'it matters not by what process or machinery the result is accomplished."' 837 F.3d at 1312 (quoting O'Reilly v. Morse, 56 U.S. 62, 113 (1854)) (emphasis added). The claims are not directed to a particular machine nor do they recite a particular transformation (MPEP § 2106.05(b)).
Additionally, the claims do not recite any specific claim limitations that would provide a meaningful limitation beyond generally linking the use of the judicial exception to a particular technological environment. Nor do the claims present any other issues regarding a determination of whether the additional generic elements integrate the judicial exception into a practical application. See Revised Guidance, 84 Fed. Reg. at 55. Rather, the claim merely uses instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea. Thus, under Step 2A, Prong Two (MPEP §§ 2106.05(a)-(c) and (e)- (h)), claim 1 does not integrate the judicial exception into a practical application. Regarding the use of the generic (known, conventional) analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display the Supreme Court has held "the mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention." Alice, 573 U.S. 208, 223. Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. The claim as a whole do not recite more than what was well-known, routine and conventional in the field (see MPEP § 2106.05(d)). In light of the foregoing, that each of the claims, considered as a whole, is directed to a patent-ineligible abstract idea that is not integrated into a practical application and does not include an inventive concept.
As for the recited comparative learning algorithm for generating a plurality of data outputs associated with the comparative opportunity value comprising the risk to the supply chain imbalance, updating the plurality of rules associated with the comparative learning algorithm, using the updated plurality of rules in applying the comparative learning to determine/set a safety stock, the comparative learning algorithm is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic comparative learning algorithm on a generic computer, also recited at a high level of generality. Only Specification Paragraph 118, as published, tangentially mentions that risk modeling or recommendations may comprising one or more learning algorithms and that the learnings may cause modification to automated weightings assigned by the analytics engine (see discussion above). The comparative learning algorithm is used to generally apply the abstract idea without limiting how the comparative learning algorithm functions. The comparative learning algorithm is described at a high level such that it amounts to using a generic computer with a generic comparative learning algorithm to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished.
Accordingly, the claim is not patent eligible under 35 U.S.C. 101.
Additionally, the claims recite a judicial exception, a mental processes, which can be performed in the human mind or via pen and paper (Judicial Exception – Yes – mental process).
The claimed steps of producing tertiary data, calculating a comparative opportunity value, determining a correlation between at least one supply chain attribute and actual risk outcome, modifying the weighted hierarchical structure, updating the plurality of rules, using the updated rules in a subsequent application all describe the abstract idea. These limitations as drafted are directed to a process that under its reasonable interpretation covers performance of the steps in the mind but for the recitation of the generic computer components. Other than the recitation of an analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display nothing in the claimed steps precludes the step from practically being performed in the mind. The claims do not recite additional elements that are sufficient to amount to significantly more than the abstract idea because the receiving first data, receiving social media data, generating of data outputs, receiving a selection of one of the graphical bubble icons, receiving a selection of a component icon, displaying an analytics window, receiving a selection of a component icon, displaying a drill-down window, receiving accumulation data and automatically setting a safety stock quantity, are directed to insignificant extra solution activity (i.e. data input/output). The mere nominal recitation of a generic processor/computer does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process. (Judicial Exception recited – Yes – mental process).
The claims do not integrate the abstract idea into a practical application. The generic primary device, platform, memory, processor, network, software and display are recited at a high level of generality merely performs generic computer functions of receiving, processing and outputting/displaying data. The generic processor/computer merely applies the abstract idea using generic computer components. The elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims do not recite improvements to the functioning of a computer or any other technology field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition, the claims to do apply the abstract idea with a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (e.g. data remains data even after processing; MPEP 2106.05(c)), the claims no not apply or use the abstract idea in some other meaningful way beyond generally linking the user of the abstract idea to a particular technological environment (i.e. a generic computer) such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea (MPEP 2106.05(e)). The recited generic computing elements are no more than mere instructions to apply the exception using a generic computer component.
With regards to the recited comparative learning algorithm for generating a plurality of data outputs associated with the comparative opportunity value comprising the risk to the supply chain imbalance, updating the plurality of rules associated with the comparative learning algorithm, using the updated plurality of rules in applying the comparative learning to determine/set a safety stock, the comparative learning algorithm is recited at a high level of generality and amounts to no more than mere instructions to apply the abstract idea using a generic comparative learning algorithm on a generic computer, also recited at a high level of generality. Only Specification Paragraph 118, as published, tangentially mentions that risk modeling or recommendations may comprising one or more learning algorithms and that the learnings may cause modification to automated weightings assigned by the analytics engine. The comparative learning algorithm is used to generally apply the abstract idea without limiting how the comparative learning algorithm functions. The comparative learning algorithm is described at a high level such that it amounts to using a generic computer with a generic comparative learning algorithm to apply the abstract idea. These limitations only recite outcomes/results of the steps without any details about how the outcomes are accomplished. The recitation of a comparative learning algorithm in this claim does not negate the mental nature of these limitations because the comparative learning algorithm is merely used at a tool to perform an otherwise mental process.
Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. (Integrated into a Practical Application – No).
As discussed above the additional elements in the claims amount to no more than a mere instruction to apply the abstract idea using generic computing components, wherein mere instructions to apply a judicial exception using generic computer components cannot integrate a judicial exception into a practical application or provide an inventive concept. For the receiving and displaying steps that were considered extra-solution activity, this has been re-evaluated and determined to be well-understood, routine, conventional activity in the field.
Applicant’s specification does not provide any indication that the computer/processor is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions (MPEP 2106.05(d)(II)) indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). For these reasons, there is no inventive concept. The claim is ineligible (Provide Inventive Concept – No).
The claims are ineligible under 35 U.S.C. 101 as being directed to an abstract idea without significantly more.
Regarding dependent claims 6-10, the claims are directed to the abstract idea of business analytics and merely further limit the abstract idea claimed in independent claims 1 and 2.
Claim 6 further limits the abstract idea by limiting the comparative opportunity value being calculated based upon at least a difference between a future and current total cost (a more detailed abstract idea remains an abstract idea, non-functional descriptive material). Claim 7 further limits the abstract idea by limiting the comparative opportunity value to being rendered on the analytics window (a more detailed abstract idea remains an abstract idea, non-functional descriptive material). Claim 8 further limits the abstract idea by rendering the comparative opportunity value as a plot (a more detailed abstract idea remains an abstract idea, non-functional descriptive material). Claim 9 further limits the abstract idea by updating the plurality of rules comprising a comparative rule set generated by combining statistical analysis with performance feedback (a more detailed abstract idea remains an abstract idea, non-functional descriptive material). Claim 10 further limits the abstract idea by adjusting a forecast demand value to a sale being recorded (a more detailed abstract idea remains an abstract idea, non-functional descriptive material).
None of the limitations considered as an ordered combination provide eligibility because taken as a whole the claims simply instruct the practitioner to apply the abstract idea to a generic computer.
Further regarding Claims 1, 2 and 6-10 Applicant’s specification discloses that the claimed elements directed to a analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display at best merely comprise generic computer hardware which is commercially available (Figures 1, 2). More specifically Applicant’s claimed features directed to a system do not represent custom or specific computer hardware circuits, instead the terms merely refer to commercially available software and/or hardware. Thus, as to the system recited, "the system claims are no different from the method claims in substance. The method claims recite the abstract idea implemented on a generic computer; the system claims recite a handful of generic computer components configured to implement the same idea." See Alice Corp. Pry. Ltd., 134 S.Ct. at 2360.
Accordingly, the claims merely recite manipulating data utilizing generic computer hardware (e.g. analytics engine (software per se), processor, memory, network, primary/second nodes (software per se), computer readable storage medium comprising instructions, interactive data visualization interface (software per se), computing display). Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. Further the lack of detail of the claimed embodiment in Applicant’s disclosure is an indication that the claims are directed to an abstract idea and not a specific improvement to a machine.
Accordingly given the broadest reasonable interpretation and in light of the specification the claims are interpreted to include the process steps being performed by a human mind or via pen and paper. The claim limitations which recite a computer implemented method is at best recite generic, well-known hardware. However, the recited generic hardware simply performs generic computer function of storing, accessing, displaying or processing data. Generic computers performing generic, well known computer functions, alone, do not amount to significantly more than the abstract idea. Further the recited memories are part of every conventional general-purpose computer.
Applicant has not demonstrated that a special purpose machine/computer is required to carry out the claimed invention. A special purpose machine is now evaluated as part of the significantly more analysis established by the Alice decision and current 35 U.S.C. 101 guidelines. It involves/requires more than a machine only broadly applying the abstract idea and/or performing conventional functions.
Applicant’s specification discloses that the claimed elements directed to a system and software modules (analytics engine (software per se), primary/second nodes (software per se), interactive data visualization interface (software per se)) merely comprise generic computer hardware which is commercially available (Specification: Figures 1, 2). More specifically Applicant’s claimed features directed to a system and components do not represent custom or specific computer hardware circuits, instead the term system merely refers to commercially available software and/or hardware. Thus, as to the system recited, "the system claims are no different from the method claims in substance. The method claims recite the abstract idea implemented on a generic computer; the system claims recite a handful of generic computer components configured to implement the same idea." See Alice Corp. Pry. Ltd., 134 S.Ct. at 2360.
Accordingly, the claims merely recite manipulating data utilizing generic computer hardware (e.g. system, software, network, display, etc.). Generic computers performing generic computer functions, alone, do not amount to significantly more than the abstract idea. Further the lack of detail of the claimed embodiment in Applicant’s disclosure is an indication that the claims are directed to an abstract idea and not a specific improvement to a machine.
The claims are not patent eligible under 35 U.S.C. 101.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Smith et al., U.S. Patent No. 11521143 discloses a supply chain planning/analysis system and method for managing supply chain risks/disruptions.
Perry, U.S. Patent Publication No. 20090164599 discloses a supply chain analysis and visualization system and method.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SCOTT L JARRETT whose telephone number is (571)272-7033. The examiner can normally be reached M-TH 6am-4:30PM.
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SCOTT L. JARRETT
Primary Examiner
Art Unit 3625
/SCOTT L JARRETT/Primary Examiner, Art Unit 3625
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