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 .
Specification
The disclosure is objected to because of the following informalities: paragraph 0008 of the specification ends in the middle of a sentence and ending in a comma.
Appropriate correction is required.
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.
Claim(s) 1-20 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim(s) 1-20 is/are directed to a method, system, and computer program product. Thus, all the claims are within the four potentially eligible categories of invention (a process, a machine and an article of manufacture, respectively), satisfying Step 1 of the Subject Matter Eligibility (SME) test.
As per Prong One of Step 2A of the §101 eligibility analysis set forth in MPEP 2106, the Examiner notes that the claims recite generating a forecast based upon a plurality of supply nodes and an input parameter which is certain methods of organizing human activity.
But for the computer implementation in claim 1 and the system in claim 19, the claims recite data analysis steps to generate a forecast for a product. This type of analysis is certain methods of organizing human activity as it relates to advertising/marketing, sales behaviors, etc. The nominal recitation of a computing system, one or more server computers and one or more memory devices having programs stored thereon for instructing server computers does not necessarily preclude the claim from reciting an abstract idea as evidenced by the analysis at Prong 2 of Step 2A.
Regarding Prong Two of Step 2A, a claim reciting an abstract idea must be analyzed to determine whether any additional elements in the claim integrate the judicial exception into a practical application. Limitations that are indicative of integration into a practical application include: Improvements to the functioning of a computer, or to any other technology or technical field, as discussed in MPEP 2106.05(a); Applying or using a judicial exception to effect a particular treatment or prophylaxis for disease or medical condition – see Vanda Memo; Applying the judicial exception with, or by use of, a particular machine, as discussed in MPEP 2106.05(b); Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP 2106.05(c); and Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP 2106.05(e) and the Vanda Memo issued in June 2018.
In this case, the independent claims do not include limitations that meet the criteria listed above, thus the abstract idea is not integrated into a practical application. Independent claim 1 is implemented by a computing system which amounts to using a computer as a tool to perform the abstract idea. Independent claim 19 recites one or more server computers and one or more memory devices having one or more programs stored thereon for instructing server computers. In both claim 1 and claim 19, these limitations amount to using a computer as a tool to perform the abstract idea. There is no integration into a practical application.
The dependent claims recite additional abstract ideas and/or additional details of the abstract idea identified above and some recite additional elements that do not integrate the abstract idea into a practical application.
Dependent claim 2 specifies the parameters of claim 1 are associated with at least one of the listed node types which part of the abstract idea identified in claim 1. There is no integration into a practical application.
Dependent claim 3 specifies the output parameters and the second selected node being upstream relative to the first selected node which is part of the abstract idea identified in claim 1. There is no integration into a practical application.
Dependent claim 4 recites details of the first and second selected nodes which is part of the abstract idea identified in claim 1. There is no integration into a practical application.
Dependent claims 5-13, 16, 17 each recites details of the input and output parameters and other features of the forecast generation which is part of the abstract idea identified in claim 1. None of claims 5-13, 16, 17 includes an additional element that integrates the abstract idea into a practical application.
Dependent claims 14-15 recites steps of processing proposed promotion parameter based on a permission level; and upon determining permission of approval, changing existing promotion plan; upon determining permission of proposing, sending proposed promotion parameters; or upon determining permission of promotion window change, updating only the time window of the existing promotion plan which are additional steps of the abstract idea identified in claim 1.
Claim 18 recites sending data to a client-side computer for presentation via a graphical user interface which amounts to using a computer as a tool to perform the abstract idea of claim 1 and does not integrate the abstract idea into a practical application.
Dependent claim 20 recites the server computers include: one or more web servers and one or more working servers configured to receive parameters and generate the forecast for presentation via an app on a client-side computer. This amounts to using a computer as a tool to perform the abstract idea and only generally links the abstract idea to a technical environment. There is no integration into a practical application.
The claims do not include limitations beyond generally linking the use of the abstract idea to a particular technological environment. When considered individually and in combination, the system and software claim elements only contribute generic recitations of technical elements to the claims. It is readily apparent, for example, that the claim is not directed to any specific improvements of these elements. The invention is not directed to a technical improvement. When the claims are considered individually and as a whole, the additional elements noted above appear to merely apply the abstract concept to a technical environment in a very general sense.
Lastly and in accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, and when considered individually and in combination, the additional elements amount to no more than mere instruction to apply the exception using generic computer component. Mere instruction to apply an exception using generic computer components cannot provide an inventive concept.
Claim Rejections - 35 USC § 102
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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-8 and 18 is/are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Ray et al, US 2016/0110733.
As per claim 1, Ray et al discloses a computer-implemented method for web-based management of consumer packaged goods (CPG) at a plurality of nodes of supplying a product, the product being a type of the CPG, the method comprising:
receiving, by a computing system: at least one input parameter associated with a first selected node of the nodes ([0024, 0033] – receiving data about SKUs to be sold at a retailer); and
a request to generate a forecast for at least one output parameter based upon the input parameter ([0024, 0032] – forecasting SKUs to be supplied from manufacturer to a retailer) ; and
generating, by the computing system, the forecast based upon a database storing data of the nodes and based upon implementing a model with the data and the input parameter ([0024] – implementing the forecasting model based on stored data and inputs).
As per claim 2, Ray et al discloses the method of claim 1, wherein the nodes include at least one retailer banner for selling the product, at least one retail store for selling the product, at least one manufacturer distribution center (DC), at least one customer DC, at least one plant manufacturing the product, or a combination thereof (at least [0023] – manufacturer to retailer analysis).
As per claim 3, Ray et al discloses the method of claim 1, wherein the output parameter being associated with a second selected node of the nodes, the second selected node being upstream relative to the first selected node ([0017] – manufacturer is upstream from retailer).
As per claim 4, Ray et al discloses the method of claim 3, wherein the first selected node includes a retail store and the second selected node see In re Gulack, 703 F.2d 1381, 1385, 217 USPQ 401, 404 (Fed. Cir. 1983); In re Lowry, 32 F.3d 1579, 32 USPQ2d 1031 (Fed. Cir. 1994); MPEP [WP TypographicSymbols font/0x27] 2106.
As per claim 5, Ray et al discloses the method of claim 3, wherein the input parameter includes a supply of the product to the second selected node, and the output parameter includes a predicted supply of the product assigned to the first selected node from the second selected node ([0017] – optimization of the inventory (supply at the 2nd node) to generate forecast supply (of what is needed at retailer)).
As per claim 6, Ray et al discloses the method of claim 3, wherein: said receiving further includes receiving an offset including an operational lead time between the first and second selected nodes; the input parameter includes a predicted demand at the first selected node; the output parameter includes a predicted demand at the second selected node; and said generating is further based upon the offset ([0022] - the replenishment time are determined, the count and a plurality of constraints may be processed by using the MILP model in order to obtain an optimal solution indicating the SKUs to be supplied by the CPG manufacturer to the retailer).
As per claim 7, Ray et al discloses the method of claim 3, wherein the input parameter includes one or more pipe-fill configuration parameters of the first selected node, wherein the output parameter includes a predicted demand of the product at the second selected node ([0021-0022] - replenishment time indicates a specific time for ordering new inventories pertaining to the SKUs and is processed to generate an optimal solution indicating the SKUs to be supplied by the CPG manufacturer to the retailer).
As per claim 8, Ray et al discloses the method of claim 7, wherein the pipe-fill configuration parameters include an offset time including an operational lead time between the first and second selected nodes, and an amount of the product required for a new launch of the product at the first selected node ([0021-0022] - replenishment time indicates a specific time for ordering new inventories pertaining to the SKUs and is processed to generate an optimal solution indicating the SKUs to be supplied by the CPG manufacturer to the retailer).
As per claim 18, Ray et al discloses the method of claim 1, further comprising sending the forecast, data associated with at least the first selected node, and data associated with at least another node of the nodes that is either upstream or downstream relative to the first selected node, to a client-side computer for presentation via a graphical user interface ([0028-0032] – system includes processor and interface for the forecasting and analysis operations).
Claim(s) 1, 9-13 and 18-20 is/are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Keng et al, US 2021/0110429.
As per claim 1, Keng et al discloses a computer-implemented method for web-based management of consumer packaged goods (CPG) at a plurality of nodes of supplying a product, the product being a type of the CPG, the method comprising:
receiving, by a computing system: at least one input parameter associated with a first selected node of the nodes ([0046-0053] – receiving data about SKUs to be sold at a retailer); and
a request to generate a forecast for at least one output parameter based upon the input parameter ([0046-0053] – given a product (identified or referred to by its stock keeping unit (SKU)), its history of promotions and transactions, and any additional relevant causal factors, trying to predict the future demand of the SKU for a given promotion mechanic); and
generating, by the computing system, the forecast based upon a database storing data of the nodes and based upon implementing a model with the data and the input parameter ([0046-0053] – machine learning model uses regression based approaches using a variety of factors to predict future outcomes; given a product (identified or referred to by its stock keeping unit (SKU)), its history of promotions and transactions, and any additional relevant causal factors, trying to predict the future demand of the SKU for a given promotion mechanic).
As per claim 9, Keng et al discloses the method of claim 3, wherein the input parameter includes one or more promotion lift parameters of the first selected node, wherein the output parameter includes a predicted demand of the product at the second selected node ([0051-0053] – demand forecast based on promotion mechanics or arrangement in which product is promoted).
As per claim 10, Keng et al discloses the method of claim 9, wherein the promotion lift parameters include an increase of sale of the product at the first selected node and associated with a trade promotion ([0053] – increase in number of units projected to sell while on promotion).
As per claim 11, Keng et al discloses the method of claim 1, wherein the input parameter includes at least one proposed promotion parameters for the first selected node, and said generating includes generating the forecast of a promotion lift for the first selected node based upon the proposed promotion parameter ([0056-0058] - use of a regression model to determine forecasted lift as a result of a promotion).
As per claim 12, Keng et al discloses the method of claim 11, further comprising: obtaining an actual promotion lift during a promotion implemented at the first selected node according to the proposed promotion parameter; comparing the forecast of the promotion lift and the actual promotion lift; and receiving an update of the proposed promotion parameters based upon said comparing ([0065-0069] – computation of actual sales minus sales with no promotion).
As per claim 13, Keng et al discloses the method of claim 11, wherein the proposed promotion parameter includes at least one parameter of a new proposed promotion plan, or at least one parameter for changing an existing promotion plan ([0047-0051] – input parameters of the promotion reflect the objective of the promotion). .
As per claim 18, Keng et al discloses the method of claim 1, further comprising sending the forecast, data associated with at least the first selected node, and data associated with at least another node of the nodes that is either upstream or downstream relative to the first selected node, to a client-side computer for presentation via a graphical user interface ([fig2] – system includes computer and interface for the forecasting and analysis operations).
As per claim 19, Keng et al discloses a system for web-based management of consumer packaged goods (CPG) at a plurality of nodes of supplying a product, the product being a type of the CPG, the system comprising: one or more server computers; and one or more memory devices having one or more programs stored thereon for instructing said server computers [0038] to: receiving, by a computing system: at least one input parameter associated with a first selected node of the nodes ([0046-0053] – receiving data about SKUs to be sold at a retailer); and
a request to generate a forecast for at least one output parameter based upon the input parameter ([0046-0053] – given a product (identified or referred to by its stock keeping unit (SKU)), its history of promotions and transactions, and any additional relevant causal factors, trying to predict the future demand of the SKU for a given promotion mechanic); and
generating, by the computing system, the forecast based upon a database storing data of the nodes and based upon implementing a model with the data and the input parameter ([0046-0053] – machine learning model uses regression based approaches using a variety of factors to predict future outcomes; given a product (identified or referred to by its stock keeping unit (SKU)), its history of promotions and transactions, and any additional relevant causal factors, trying to predict the future demand of the SKU for a given promotion mechanic).
As per claim 20, Keng et al discloses the system of claim 19, wherein said server computers include: one or more web servers configured to receive the request and the input parameter; and one or more working servers configured to generate the forecast for presentation via an app on a client-side computer ([0038] - Any module, unit, component, server, computer, terminal, engine or device exemplified herein that executes instructions may include or otherwise have access to computer readable media such as storage media, computer storage media, or data storage devices (removable and/or non-removable) such as, for example, magnetic disks, optical disks, or tape. Computer storage media may include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. Examples of computer storage media include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by an application, module, or both).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 14, 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Keng et al, US , in view of Sultan, US 6804657.
As per claim 14, Keng et al discloses the method of claim 11, but fails to explicitly disclose further comprising, upon request, processing the proposed promotion parameter based on a permission level of a user submitting the proposed promotion parameter. Sultan discloses a system which generates real time global sales forecasts at any level of the sales force hierarchy and each member of the sales force is assigned a permission level that determines what information is available to each person within the sales force and in particular, what forecast information is visible, accessible and/or modifiable to and by each person. It would have been obvious to one of ordinary skill in the art at the time of the invention to include in the system of Keng et al the ability to consider permission levels as taught by Sultan since the claimed invention is merely a combination of old elements and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 15, Keng et al discloses changing a promotion window based on analysis ([0049-0052] – time period for promotion), but fails to explicitly disclose determining that the user has a permission of promotion window change and the proposed promotion parameter includes a change of a time window of the existing promotion plan, updating only the time window of the existing promotion plan based upon the proposed promotion parameter. Sultan discloses a system which generates real time global sales forecasts at any level of the sales force hierarchy and each member of the sales force is assigned a permission level that determines what information is available to each person within the sales force and in particular, what forecast information is visible, accessible and/or modifiable to and by each person. It would have been obvious to one of ordinary skill in the art at the time of the invention to include in the system of Keng et al the ability to consider permission levels as taught by Sultan since the claimed invention is merely a combination of old elements and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Keng et al, US , in view of Blust et al, US 2024/0046203.
As per claim 16, Keng et al fails to explicitly teach, while Blust et al discloses wherein the input parameter includes starting and ending inventories of the product at the first selected node of one or more days, and said generating includes generating the forecast of days-on-hand at the first selected node based upon the input parameter ([0071-0074] – days on hand forecast based on inventory levels). It would have been obvious to one of ordinary skill in the art at the time of the invention to include in the system of Keng et al the ability to consider days-on-hand as taught by Blust et al since the claimed invention is merely a combination of old elements and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
As per claim 17, Keng et al fails to explicitly disclose, while Blust et al discloses wherein said generating includes generating, based upon the forecast of the days-on-hand, a forecast of a production plan at a plant manufacturing the product, a forecast of a stock allocation from the plant to at least one manufacturer DC, or a combination thereof ([0072-0073] – based on the days-on-hand the system generates an order for a volume of product form a distributor). It would have been obvious to one of ordinary skill in the art at the time of the invention to include in the system of Keng et al the ability to consider days-on-hand as taught by Blust et al since the claimed invention is merely a combination of old elements and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Numerous prior art is made of record in the attached PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNA LOFTIS whose telephone number is (571)272-6736. The examiner can normally be reached M-F 7:00am-3:30pm.
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JOHNNA LOFTIS
Primary Examiner
Art Unit 3625
/JOHNNA R LOFTIS/Primary Examiner, Art Unit 3625