DETAILED ACTION
This office action is in response to communication filed on 23 February 2024.
Claim 79 – 98 are presented for examination.
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 .
Drawings
The drawings are objected to because Figs. 4 – 24 and 26 – 31 are in gray scale and therefore illegible. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance. Examiner recommends re-submitting in purely black and white for clarity.
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 79 – 98 are rejected under 35 U.S.C. 101 because the claimed invention is directed to the judicial exception of abstract ideas without significantly more. The claims recite receive information related to one or more business propositions, create one or more business propositions based on the information received, analyze the one or more business propositions and group the one or more business propositions for one or more categories, and create one or more initiatives for the one or more categories. This judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance section 2106 of the MPEP (hereinafter, MPEP 2106).
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is noted that the system, the method, and the computer-readable medium are directed to an eligible categories of subject matter. Step 1 is satisfied.
With respect to Step 2A prong 1 of MPEP 2106, it is next noted that the claims recite an abstract idea by reciting concepts of creating business propositions, grouping by category, and creating initiatives for categories, which falls into the “certain methods of organizing human activity” group within the enumerated groupings of abstract ideas set forth in the MPEP 2106. The claimed invention also recites an abstract idea that falls within the mental processes grouping, as independent claims describe receiving information and analyzing steps. The limitations reciting the abstract idea in independent claims are receive information related to one or more business propositions, create one or more business propositions based on the information received, analyze the one or more business propositions and group the one or more business propositions for one or more categories, and create one or more initiatives for the one or more categories.
With respect to Step 2A Prong Two of the MPEP 2106, the judicial exception is not integrated into a practical application. The additional elements are directed to a memory, a processor, using an artificial intelligence engine, an application programming interface, and a non-transitory computer readable storage medium, to implement the abstract idea. However, these elements fail to integrate the abstract idea into a practical application because they are directed to the use of generic computing elements to perform the abstract idea, which is not sufficient to amount to a practical application (as noted in the MPEP 2106) and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional limitations are directed to: a memory, a processor, using an artificial intelligence engine, an application programming interface, and a non-transitory computer readable storage medium. These elements have been considered, but merely serve to tie the invention to a particular operating environment, though at a very high level of generality and without imposing meaningful limitation on the scope of the claim. This does not amount to significantly more than the abstract idea, and it is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo.
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself.
The dependent claims have been fully considered as well, however, similar to the finding for claims above, these claims are similarly directed to the abstract idea of concepts of user collaboration, managing business events, or generating reports, by way of example, without integrating it into a practical application and with, at most, a general purpose computer that serves to tie the idea to a particular technological environment, which does not add significantly more to the claims. The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to significantly more than the abstract idea.
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.
Claims 70 – 98 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. P.G. Pub. 2023/0011954 (hereinafter, Elserafy).
Regarding claim 79, Elserafy teaches a system comprising: a memory; and a processor that is communicatively coupled to the memory storing a sequence of instructions that when executed causes the processor to (¶ 41, “The memory 104 may store all or a portion of the various programs, modules and data structures for processing data transfers as discussed herein. For instance, the memory 104 can store a business plan generation application 150. In embodiments, the business plan generation application 150 may include instructions or statements that execute on the processor 102 or instructions or statements that are interpreted by instructions or statements that execute on the processor 102 to carry out the functions as further described below.”):
receive information related to one or more business propositions (¶ 166, “the business plan definition unit is configured to receive input data including a business strategy, a budget and constraints. These inputs may be received from a user via a graphical user interface.”);
create one or more business propositions based on the information received (¶ 166, “Additionally, the business plan definition unit may use these inputs to define a business plan. This user-defined business plan may be used together with other input data to generate a revised business plan that achieves the target business outcomes of the user. Further, the business plan definition unit may output a set of hyper parameters used to configure the machine learning model used by the business plan generation unit. These hyperparameters may be derived based on the business plan.”);
analyze, using an artificial intelligence engine, the one or more business propositions and group the one or more business propositions for one or more categories (¶ 136, “The organization function 1042 provides functionality for organizing the set of competitor business information acquired via the information acquisition functions 1010. For example, the organization function 1042 may include an aggregation function for grouping together competitor business information for multiple competing businesses in a single data table. As an additional example, the organization function 1042 may include natural language processing tools to parse and analyze unstructured textual data included in the set of competitor business information to derive insights about competing businesses, and database construction algorithms to represent the derived insights as database tables. Other types of organization functions are also possible”); and
create, using the artificial intelligence engine, one or more initiatives for the one or more categories (¶ 78, “Next, at Step S360, the forecasting unit (for example, the forecasting unit 276 of the business plan generation device 250 illustrated in FIG. 2) may identify a first event that is anticipated to impact a first business field to which the first business and its competitors belong, and generate, using a statistical analysis technique, a set of forecasting data that includes an impact factor that quantifies an impact of the first event on at least one of the first business or its competitors (e.g., the second business”) (¶ 155, “impact factors may be calculated to indicate the impact of the first event on a variety of targets. For instance, as illustrated in FIG. 13, the event identification function 1310 may determine a business growth impact factor 1312 to indicate the impact of the first event on the growth of the first business, a competitor growth impact factor to indicate the impact of the first event on the growth of one or more competing businesses, and a business strategy impact factor to indicate the impact of the first event on a variety of business strategies.”) (¶ 176, “each of the set of revised business plans specify a business strategy (e.g., a second business strategy) that characterizes a set of actions to be implemented as part of the revised business plan, a budget (e.g., a second budget) that defines an allotment of resources necessary for implementing the revised business plan”) (¶ 177, “he trained machine learning unit 1610 may repeat the business plan generation process for a number of iterations designated by the number of iterations 417 defined by the user. Performing a greater number of iterations may allow the machine learning unit 1610 to generate a greater number of revised business plans.”).
Regarding claim 80, Elserafy teaches the system of claim 79, wherein the processor is operable to:
implement the one or more initiatives on one or more target environments (¶ 176, “each of the set of revised business plans specify a business strategy (e.g., a second business strategy) that characterizes a set of actions to be implemented as part of the revised business plan, a budget (e.g., a second budget) that defines an allotment of resources necessary for implementing the revised business plan”);
monitor at least one of tasks, activities, and events executed by the one or more initiatives into the one or more target environments (¶ 69, “Next, at Step S320, the business plan definition unit defines a set of target business outcomes. Here, the set of target business outcomes are a collection of data that defines the desired results that the user hopes to achieve by means of the business plan defined in Step S310. As an example, the set of target business outcomes may include a set of target key performance indicators (KPIs) that quantitatively define the desired performance of the business plan with respect to a plurality of business metrics.”); and
determine an actual performance score based on monitoring at least one of the tasks, the activities, and the events executed by the one or more initiatives into the one or more target environments (¶ 183, “The ranked set of revised business plans 1710 refer to a collection of business plans that alter, change, edit, or otherwise modify the business plan defined by the user via the business plan definition unit 272 and ranked according to the degree to which they accomplish the set of target business outcomes. Each of these revised business plans may be associated with a strategy 1714 that characterizes a set of actions to be implemented as part of the business plan, and a budget 1712 that defines an allotment of resources for use in implementing the business strategy 1714.”).
Regarding claim 81, Elserafy teaches the system of claim 80, wherein the processor is operable to determine an expected performance score based on analyzing the one or more initiatives (¶ 184, “The expected KPI time evolution pattern 1716 illustrates how the KPIs of each of the revised business plans are expected to evolve over time. In embodiments, the expected time evolution pattern 1716 may be represented in the form of a graph that indicates the predicted evolution of one or more KPI metrics over a defined time period.”).
Regarding claim 82, Elserafy teaches the system of claim 81, wherein the processor is operable to determine a deficit score based on comparison of the actual performance score and the expected performance score (claim 3, “a first target time frame that indicates a desired time period for achieving the first set of target key performance indicators; and a first tolerance threshold that defines a permissible range of variation of the first set of target key performance indicators or the first target time frame.”).
Regarding claim 83, Elserafy teaches the system of claim 82, wherein the processor is operable to determine, using the artificial intelligence engine, one or more issues based on the comparison of the actual performance score and the expected performance score (¶ 175, “a test set 1616 generated by the internal business information management unit 414 may be input to the trained machine learning unit 1610. The test set 1616 is a collection of data generated based on the internal business data of the first business. It should be noted that, in situations in which internal business data for the first business is not available, the test set 1616 may be a placeholder data set. The trained machine learning unit 1610 may utilize this test set 1616 to generate a revised set of business plans 1618.”).
Regarding claim 84, Elserafy teaches the system of claim 83, wherein the processor is operable to communicate feedback information back to the processor based on the issues, wherein the feedback information comprises at least one of a resource strategy, a scope strategy, a priority strategy, and a budget strategy (¶ 176, “Here, the set of revised set of business plans 1618 include a collection of business plans that alter, change, edit, or otherwise modify the business plan defined by the user via the business plan definition unit 272 to accomplish the set of target business outcomes in a more efficient manner (e.g., faster, using less resources, achieving greater performance). More particularly, each of the set of revised business plans specify a business strategy (e.g., a second business strategy) that characterizes a set of actions to be implemented as part of the revised business plan, a budget (e.g., a second budget) that defines an allotment of resources necessary for implementing the revised business plan, a set of target KPIs (second set of target KPIs) that indicate a predicted degree of performance of the first business with respect to one or more performance metrics, and a confidence level that indicates an accuracy of the revised business plan”).
Regarding claim 85, Elserafy teaches the system of claim 84, wherein the processor is operable to update at least one of the one or more business propositions and the one or more initiatives based on the feedback information (¶¶ 98-101, “the business plan 410 primarily includes a business strategy table 261, a budget 530, and constraints 540. The business strategy table 261 is a data table for storing business strategies. Here, a business strategy refers to a sequence of one or more actions to be performed to achieve a business goal. As examples, the business strategy may include securing an investment budget for incentivizing a particular business sector to generate a particular business outcome. As illustrated in FIG. 5, a business strategy may be defined using one or more pre-defined strategy templates 522 or as a custom strategy 524. The pre-defined strategy templates 522 provide stock, pre-set strategy templates that may be adapted and modified by users for a specific purpose. As an example, in order to accomplish a business goal of generating ideas for new product lines, a strategy template may define a sequence of actions for organizing a competition in which individuals submit ideas for new products, and winners are rewarded with prizes. Other types of pre-defined strategy templates are also possible. The business strategy templates 522 may be suitable for users who are unfamiliar with business strategy creation. Custom strategies 524 may allow for users to create business strategies from the beginning, and customize every aspect of the strategy. The custom strategies 524 may be suitable for high-level users who wish to have a large degree of control over each aspect of the business strategy. The budget 530 defines an allotment of resources (e.g., financial resources, personnel resources) for use in implementing the business strategy defined in the business strategy table 261. Here, users may specify a range of the amount of resources ($10,000 to $20,000 dollars) or an upper limit of the amount of resources (up to $20,000 dollars) that can be used for implementing the business strategy.”).
Regarding claim 86, Elserafy teaches the system of claim 85, wherein the processor is operable to update at least one of scope, budget, resource, and priority in at least one of the one or more business propositions and the one or more initiatives based on the feedback information (¶ 83, “advising the user to revise the strategy, budget, or constraints of the business plan”).
Regarding claim 87, Elserafy teaches the system of claim 86, wherein the processor is operable to generate a real-time report using at least one of analysis, historical trends, historical patterns, historical records, the issues, the feedback information, and the update performed (¶ 169, “the forecasting unit is configured to receive, as inputs, either a user input defining a first event or past event data that may be used to predict the occurrence and impact of a first event on the first business. The forecasting unit may use the user input or the past event data to predict one or more events (e.g., a first event),the area of business anticipated to be impacted by the event (e.g., communications, service development, marketing, overall growth), and one or more impact factors (e.g., the business growth impact factor, competitor growth impactor factor, and/or the business strategy impact factor) that quantitatively indicate the impact of the identified events on the first business.”).
Regarding claim 88, Elserafy teaches the system of claim 79, where the processor is operable to communicate with one or more external applications through an application programming interface (API) and exchange the information (¶ 130, “The web scraping tool 1022 may include an API configured to search an external network (e.g., the Internet) to recognize unique HTML site structures, extract and transform content, temporarily store scraped data, extract data from databases and APIs, and perform other necessary functions to acquire competitor business information from the external network. More specifically, the web scraping tool 1022 may use a search engine together with a natural language processing technique to search for and identify businesses that may be potential competitors to the first business (e.g., businesses that belong to the same business field, businesses that offer similar products or services to the first business), and subsequently collect information about the current state of these identified businesses (e.g., number of services, number of customers, amount of revenue) as the set of competitor business information. The collected set of competitor business information may be presented to the user in a graphical user interface (see FIG. 19) via the output function 1024.”).
Regarding claim 89, Elserafy teaches the system of claim 79, wherein the processor is operable to enable one or more users to collaborate in real-time and analyze at least one of the one or more business propositions and the one or more initiatives, determine issues, and update at least one of the one or more business propositions and the one or more initiatives (¶ 80, “Next, at Step S370, the business plan generation unit (for example, the business plan generation unit 278 of the business plan generation device 250 illustrated in FIG. 2) may generate a set of revised business plans for the first business. Here, the business plan generation unit may use a machine learning model to generate, based on the business plan defined in Step S310, the set of target business outcomes defined in Step S320, and the set of business state information (the set of internal business information acquired in Step S330 and/or the set of competitor business information acquired in Step S340 and modified in Step S350), a set of output data that includes at least a set of revised business plans for achieving the set of target business outcomes.”) (¶ 205, “Embodiments according to this disclosure may be provided to end-users through a cloud-computing infrastructure. Cloud computing generally refers to the provision of scalable computing resources as a service over a network. More formally, cloud computing may be defined as a computing capability that provides an abstraction between the computing resource and its underlying technical architecture (e.g., servers, storage, networks), enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. Thus, cloud computing allows a user to access virtual computing resources (e.g., storage, data, applications, and even complete virtualized computing systems) in “the cloud,” without regard for the underlying physical systems (or locations of those systems) used to provide the computing resources.”).
Regarding claim 90, Elserafy teaches the system of claim 79, wherein the processor is operable to determine at least one of resources, budgets, priorities, and scopes, using one or more estimation models, for at least one of the one or more business propositions and the one or more initiatives (¶¶ 97-98, “The business plan generation unit uses this user-defined business plan 410 together with other input data (e.g., internal business information and/or competitor business information, set of forecasting data, number of iterations), and uses it to generate a revised business plan that achieves the target business outcomes of the user. As illustrated in FIG. 5, the business plan 410 primarily includes a business strategy table 261, a budget 530, and constraints 540.”).
Regarding claim 91, Elserafy teaches the system of claim 80, wherein the processor is operable to at least one of manage execution of agendas, manage the activities, manage the events, manage tasks, trigger, and host online meetings, manage actions, take meeting notes, and record activities in a repository (¶ 86, “Next, at Step S395, the set of revised business plans are applied to the business. Here, the user may allocate resources, establish business policies, and contact any number of individuals or businesses to facilitate the implementation of the set of revised business plans with respect to the first business.”) (¶ 187, “As illustrated with reference to the above-described FIG. 17 and FIG. 18, a set of output data that defines the features of the revised business plans generated by the business plan generation unit can be created and output to a graphical user interface (see FIG. 19) of the client terminal for confirmation, review, and implementation by a user.”) (¶ 67, “a business plan generally refers to a collection of data including a business strategy that characterizes a set of actions to be implemented, a budget that defines an allotment of resources for use in implementing the business strategy, and a set of constraints that define restrictions on implementation of the business strategy. In embodiments, the business plan may be defined by a user (e.g., business manager) who sets a business strategy, a budget, and constraints via a graphical user interface displayed on a client terminal for receiving inputs to the business plan definition unit.”).
Regarding claim 92, Elserafy teaches the system of claim 80, wherein one or more agents execute the activities, the tasks, and the events at scheduled dates and times based on one or more commands (¶ 111, “The target time frame 705 specifies a desired time period for achieving the set of target KPIs. As an example, a user may specify a target time frame of “1 year” in which to achieve the set of target KPIs of the target KPIs table 262.”) (¶ 112, “The tolerance threshold 706 defines a permissible range of variation of the set of target key performance indicators or the target time frame 705. The tolerance threshold 706 may be defined in terms of a percentage, or in terms of the specific units of the quantity to which it applies. For instance, the tolerance threshold 706 may be set as “ ± 10%,” “± 2 months” or the like. Setting a tolerance threshold 706 provides greater flexibility for generating business plans that achieve the set of target KPIs.”).
Regarding claims 93 and 96, the claims recite substantially similar limitations to claim 79. Therefore, claims 93 and 96 are similarly rejected for the reasons set forth above with respect to claim 79.
Regarding claim 94, the claim recites substantially similar limitations to claim 80. Therefore, claim 94 is similarly rejected for the reasons set forth above with respect to claim 80.
Regarding claim 95, the claim recites substantially similar limitations to claim 92. Therefore, claim 95 is similarly rejected for the reasons set forth above with respect to claim 92.
Regarding claim 97, the claim recites substantially similar limitations to claim 89. Therefore, claim 97 is similarly rejected for the reasons set forth above with respect to claim 89.
Regarding claim 98, the claim recites substantially similar limitations to claim 85. Therefore, claim 98 is similarly rejected for the reasons set forth above with respect to claim 85.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMANDA GURSKI whose telephone number is (571)270-5961. The examiner can normally be reached Monday to Thursday 7am to 5pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Brian Epstein can be reached at 571-270-5389. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AMANDA GURSKI/Primary Examiner, Art Unit 3625
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