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 .
Claims 1-21 are pending.
No claims are amended. Claim 21 is added. No claims are cancelled.
Response to Arguments
Applicant’s arguments, filed November 26, , with respect to Section 101 have been fully considered but they are not persuasive. Applicant argues, that Claims 1, 11, and 17 are not directed to an abstract idea of methods of organizing human activity and a mental process. While Applicant cites McRO Inc. dba Planet Blue v. Bandai Namco Games America Inc., the instant claims are in no way analogous to the automation of specific animation tasks. Applicant argues that “determining a set of constraints for the project” is a structured and integrated way that results in an improvement to computer-related technology. However, determining a set of constraints for a project is a process step that can be performed mentally, without any computer-related technology. The retrieval of data stored in a memory (e.g. knowledge repository) does not mean an abstract idea is not recited. The argument fails to otherwise address the rejection as written. While Applicant argues the method is performed in a computing environment, that argument relies on narrow interpretations not supported by the plain language of the claims. The recitation of a knowledge repository and a data feed from a plurality of data sources is addressed in the additional element analysis, and may include human actions such as reading a book (i.e. knowledge repository) and listening to the TV and radio (i.e. data feed from a plurality of data sources). Such considerations may be used to plan construction of a garden based on constraints such as the weather. As such, Applicant argument that “It is not possible for a human mind to analyze the one or more of parameters related to the project and the data feed from the plurality of data sources to derive/determine the set of constraints” is incorrect. It is also noted that the precision and accuracy of a processor are irrelevant as no processor is recited in claim 1. The remainder of Applicant’s argument fail for substantially similar reasons. For example, generating optimized models for projects may include the human planned garden that locates plants in areas with corresponding lighting such as partial sun and time constraints such as planting time and harvesting times based on a growing zone. As such, claim 1 clearly recites an abstract idea and the arguments are based on technical language not found in the claims.
With regards to Applicant’s arguments in view of Step 2A: Prong Two, Applicant again draws analogies to Example 42, without citing any technical elements from the claims. The claims simply fail to recited substantive technical features. Applicant argues that Claim 1 reflects "an improvement in the functioning of a computer, or an improvement to other technology or technical field", but fails to identify any technology in the claims other than that addressed in the rejections. As noted above, the broad recitation of a “knowledge repository” and “a data feed from a plurality of data sources” amounts to mere information retrieval that may amount to reading and listening to the radio. That is, the claims merely recite using generic storage technology elements, performing only the collection of data. It is well-settled that mere recitation of concrete, tangible components is insufficient to confer patent eligibility to an otherwise abstract idea." In re TLI Commc'ns Patent Litig., 823 F.3d 607, 613 (Fed. Cir. 2016). The Federal Circuit has generally found claims abstract where they are directed to some combination of acquiring information, analyzing information, and/or displaying the results of that analysis. See FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1094-95 (Fed. Cir. 2016) (claims "directed to collecting and analyzing information to detect misuse and notifying a user when misuse is detected" were drawn to a patent-ineligible abstract idea); Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1354 (Fed. Cir. 2016) (claims directed to an abstract idea because "[t]he advance they purport to make is a process of gathering and analyzing information of a specified content, then displaying the results, and not any particular assertedly inventive technology for performing those functions"); In re TLI Commc'ns LLC, 823 F.3d at 611 (claims were "directed to the abstract idea of classifying and storing digital images in an organized manner"); see also Elec. Power Grp., 830 F.3d at 1353-54 (collecting cases). As such, those arguments are not persuasive.
Applicant also argues that re directed to an abstract idea/judicial exception as the Office contends, the independent Claims 1, 11, and 17 amount to "significantly more" than an abstract idea. The argument fails to address any additional elements as amounting to significantly more. That is, "correlating the determined set of constraints with the one or more project objectives; evaluating the correlated set of constraints and the one or more project objectives to generate an optimized model; and creating a project manifest based on the optimized model for executing the project" are not additional elements. Those limitations define the abstract idea, as made clear in the write up of the rejection. The discussion of BASCOM is not related to any recited additional element. As such, those arguments are not persuasive.
With regards to Section 102 and 103, Applicant’s arguments have been fully considered but they are not persuasive. Applicant argues that "correlating the determined set of constraints with the one or more project objectives; evaluating the correlated set of constraints and the one or more project objectives to generate an optimized model; and creating a project manifest based on the optimized model for executing the project," is not anticipated by Cullen. Applicant argues that two individual bid items are not correlated with each other in Cullen. However, the claims do not recite correlating one thing with itself. Rather, the claims recite “correlating the determined set of constraints with the one or more project objectives” which is clearly taught by the grading and scoring of Cullen. That is, as noted by Applicant, vendor response corresponding to each bid item is graded, according to set criteria that may include project objectives and time and regulation constraints, so that one vendor can be selected through comparison of scores of the vendor bid responses. As such, the argument is not persuasive.
Applicant also argues that Cullen fails teach "evaluating the correlated set of constraints and the one or more project objectives to generate an optimized model; and creating a project manifest based on the optimized model for executing the project," as recited in Claim 1. However, Cullen merely describes providing visibility to analytical data, such as project status, total project costs to date, requisition amount (i.e., the amount authorized for the project), the percentage spent on this project in comparison to all projects currently being handled by the buyer, the project margins and other relevant project costing analytical data. Cullen nowhere describes, for example, "evaluating the correlated set of constraints and the one or more project objectives to generate an optimized model," as recited in the independent Claim 1. Examiner respectfully disagrees, and notes that Cullen describes optimizing data processing and business administration endeavors through Statement Of Work (SOW) dependency modeling and collaborative work flow processing including planning through the bidding process that correlates correlated set of constraints and project objectives. See paragraph [0163]-[0165] of Cullen et al. As such, the argument is not persuasive.
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 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Representative claim 1 recites “receiving a request related to a project, the project is at least one of a construction project and a manufacturing project; determining one or more project objectives related to the request; determining a set of constraints for the project, the set of constraints are derived at least through a knowledge repository that includes one or more of parameters related to the project and a data feed from a plurality of data sources associated with the project; correlating the determined set of constraints with the one or more project objectives; evaluating the correlated set of constraints and the one or more project objectives to generate an optimized model; and creating a project manifest based on the optimized model for executing the project.” Therefore, the claim as a whole is directed to “Project Planning and Management”, which is an abstract idea because it is a method of organizing human activity, including commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) and managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). “Project Planning and Management” is considered to be is a method of organizing human activity because the claimed processes are ordinarily performed by architects, project managers, construction managers, and engineers in the process of organizing construction projects. Reviewing project objectives, determining constraints, and generating an optimized plan and project manifest are ordinary human activities for most construction projects, such as building a house. The Board has found similar applications to be directed to an abstract idea. See, for example, Appeal 2018-001298, Application 13/598,330. The claims may also be considered to be directed toward mental processes, as each of the steps may be performed as human analysis of building project considerations. As such, the claim is directed to an abstract idea.
This judicial exception is not integrated into a practical application. In particular, claim 1 recites the following additional element(s): a knowledge repository that includes one or more of parameters related to the project and a data feed from a plurality of data sources associated with the project. The additional elements amount to data about projects of unknown size stored and available to the computer system (paragraph [0097]). Claim 21 further recites an optimized model applying one or more of deep-learning, Artificial Intelligence (AI), and Machine Learning (ML) processes. These additional elements individually or in combination do not integrate the exception into a practical application. That is, the recitations of additional elements amount merely reciting the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). That is, storing data for access by a computer to perform organized processes does not integrate the abstract idea into a practical application. Rather, the additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)). For example, claim 21 further recites “applying one or more of deep-learning, Artificial Intelligence (AI), and Machine Learning (ML) processes”, which includes three different but overlapping forms of technology cited at a high level of generality presumably to perform known functions in a known manner a provided by off the shelf commercial versions of such technology. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claim 1 is directed to an abstract idea.
Claim 1 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, the additional elements individually and in combination recite are merely being used to apply the abstract idea to a technological environment. That is, rather than addressing a particular technological problem or presenting a particular technological solution, the claims are directed to an abstract idea with minimal limitations using generic computer elements. Such limitations stating a technological environment do not render the claims less abstract. See Intellectual Ventures I LLC v. Capital One Bank (USA), N.A., 792 F.3d 1363, 1366, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015) (“An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer”). Accordingly, claim 1 is ineligible.
Claims 11, 17 and 21 recite substantially similar features to those recited in representative claim 1 and are rejected based on substantially the same reasons. The additional recitation in claim 21 of “applying one or more of deep-learning, Artificial Intelligence (AI), and Machine Learning (ML) processes” is addressed in particular above. Claim 11 recites additional elements including one or more computer systems comprising one or more hardware processors and storage media; and instructions, stored in the storage media, implementing a factory interface module for performing a process substantially similar to claim 1. The broadly recited additional element does not substantially change the analysis provided above.
Dependent claims 2-10, 12-16, and 18-20 merely further limit the abstract idea and are thereby considered to be ineligible.
Dependent claim 2 further limits the abstract idea of “Project Planning and Management” by introducing the element of determining the one or more project objectives from at least one of: a time objective, a cost objective, a quality objective, a sustainability objective, an efficiency objective, and a health objective associated with the project, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 2 is also non-statutory subject matter.
Dependent claim 3 further limits the abstract idea of “Project Planning and Management” by introducing the element of determining the parameters related to the project based on at least one of: a historical data related to the project, an industry data associated with the project, an execution data for the project, and a forecast data associated with the project, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 3 is also non-statutory subject matter.
Dependent claim 4 further limits the abstract idea of “Project Planning and Management” by introducing the element of applying one or more of deep-learning, Artificial Intelligence (AI), and Machine Learning (ML) processes to generate the optimized model, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 4 is also non-statutory subject matter.
Dependent claim 5 further limits the abstract idea of “Project Planning and Management” by introducing the element of determining the set of constraints includes determining at least one of: pre-existing manufacturing data sets, supplier data sets, material data sets, geolocation data sets, and environmental data sets, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 5 is also non-statutory subject matter.
Dependent claims 6, 12, and 18 further limit the abstract idea of “Project Planning and Management” by introducing the element of analyzing real-time data and user modification associated with the set of constraints for achieving custom project objectives; determining an impact of the analyzed data on the one or more project objectives; and generating an updated project manifest based on the determined impact, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claims 6, 12, and 18 are also non-statutory subject matter.
Dependent claims 7 and 14 further limit the abstract idea of “Project Planning and Management” by introducing the element of creating the project manifest that includes the optimized model covering time, cost, and schedule aspects from at least one of project, manpower, equipment, source, material, logistics, and processes, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claims 7 and 14 are also non-statutory subject matter.
Dependent claims 8, 13, and 19 further limit the abstract idea of “Project Planning and Management” by introducing the element of monitoring a production efficiency associated with the project; and providing one or more of a causality data and a remedial data associated with the production efficiency, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claims 8, 13, and 19 are also non-statutory subject matter.
Dependent claims 9, 15, and 20 further limit the abstract idea of “Project Planning and Management” by introducing the element of receiving a bidding request for the request related to the project from one or more bidders who intend to work on the project; and providing a set of recommendations to the one or more bidders based on the generated optimized model associated with the project, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claims 9, 15, and 20 also non-statutory subject matter.
Dependent claim 10 further limits the abstract idea of “Project Planning and Management” by introducing the element of providing the set of recommendations including at least one of: a cost forecast, a project manifest associated with the project, a time forecast, and materials supplier information, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 10 is also non-statutory subject matter.
Dependent claim 16 further limits the abstract idea of “Project Planning and Management” by introducing the element of to receive bids related to the project from the one or more bidders based on the set of recommendations….; arrange the received bids based on the one or more project objectives; and provide the arranged bids related to the project …, which does not include an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of the abstract idea to a particular technological environment. Therefore, dependent claim 16 is also non-statutory subject matter.
Dependent claims 2-10, 12-16, and 18-20 also do not integrated into a practical application. The dependent claims recite an optimizer module, a monitor production efficiencies module, a marketplace debut module, and a digital marketplace interface. These recitations amount to indicating that the human organized activities are to be performed in software without addressing any technical problems or presenting any technical solutions. As such, the recitations of additional elements individually or in combination do not integrate the exception into a practical application, but rather, the recitation of any recitations of additional elements amounts to merely reciting the words ‘‘apply it’’ (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). The dependent claims also do 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, the additional element of a computing system is merely being used to apply the abstract idea to a technological environment. That is, the claims provide no practical limits or improvements to any technology. Accordingly, dependent claims 2-10, 12-16, and 18-20 are also ineligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of pre-AIA 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 1-3 and 5-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Application Publication No. 20060190391 to Cullen et al.
With regards to claim 1, 11, and 17, Cullen et al. teaches:
one or more computer systems comprising one or more hardware processors and storage media; and instructions, stored in the storage media, implementing a factory interface module (paragraph [0173], “For example, the administrative module 135 can populate web pages pushed to the administrative browser 20 d using the data stored in the administrator database 155 d. It should be noted that the vendor module 115, buyer module 110, contractor module 130 and administrative module 135 can each include any hardware, software and/or firmware required to perform the functions of the vendor module 115, buyer module 110, contractor module 130 and administrative module 135, and can be implemented as part of the bid web server 120, or within an additional server (not shown).”), which when executed by the computing system, causes the computing system to:
receiving a request related to a project, the project is at least one of a construction project and a manufacturing project (paragraph [0162], “Buyers can solicit bids from vendors for a particular good and/or service (hereinafter referred to as a project) in a form specified by the buyer using a bid request generated from a pre-established list of bid items related to the project type. Therefore, the bid responses submitted from vendors all have the same form, enabling efficient and effective evaluation of the bid responses. Embodiments of the present invention further combine the bid process with project management to enable the buyer, vendor, contractor and administrator to track the performance of the project after the bid is awarded.”);
determining one or more project objectives related to the request (paragraph [0162], “Buyers can solicit bids from vendors for a particular good and/or service (hereinafter referred to as a project) in a form specified by the buyer using a bid request generated from a pre-established list of bid items related to the project type.”, paragraph [0250], et seq. including Table 26, where bid items may include project objectives time and constraints including time and regulation requirements);
determining a set of constraints for the project, the set of constraints are derived at least through a knowledge repository that includes one or more of parameters related to the project and a data feed from a plurality of data sources associated with the project (paragraph [0250], et seq. including Table 26, where bid items may include project objectives and constraints including time and regulation requirements; paragraph [0345], “Exemplary database structures for storing contractor information and ensuring that relevant documents are obtained from the contractor or agreed to by the contractor are shown in Tables 60-63 below. Table 60 lists various sample documents that either need to be obtained from the contractor or that the contractor needs to execute at some point during the project. Table 60 also lists the time constraints for obtaining or executing such documents. Table 61 lists the contractor information, such as the identity of the contractor, the number of billable hours authorized, the amount of expenses authorized, the execution date of various documents and the contractor type.”);
correlating the determined set of constraints with the one or more project objectives (paragraph [0250], et seq. including Table 26, where bid items may include project objectives and constraints including time and regulation requirements; paragraph [0314], “Upon receipt of vendor bid responses (step 3200), the bid item selections to be used for grading purposes are identified (step 3210). The bid item selections are associated with the bid request soliciting the vendor bid responses, and vendor bid response data is included within the bid item selections chosen for grading purposes. Using the vendor bid response data within the graded bid items, the vendor bid responses are graded (step 3220).”);
evaluating the correlated set of constraints and the one or more project objectives to generate an optimized model (paragraph [0163], “Project change in plan/scope (PCIP/S) administrative management functionality is provided that permits the enterprise to limit risks applicable to changes in plan/scope and optimize data processing and business administration endeavors through Statement Of Work (SOW) dependency modeling and collaborative work flow processing.”; paragraph [0479], “FIG. 79 is a screen shot of an exemplary web page 61 containing analytical data 270 related to project performance data for a particular project that is presented in a project performance summary reporting view 360. The analytical data 270 can include the project status, the project phase completion count, the past due phase count, the deliverable completion count, the past due deliverable completion count, the percentage of on-time deliverable completions, and other project performance analytical data. At the bottom of the web page 61 are links to different project performance reporting views 360 summarized by different types of transactional data, such as business impact type, geography, vendors, etc.”); and
creating a project manifest based on the optimized model for executing the project (paragraph [0477], “As an example, if a user clicked on the link to summarize the estimated future project spending by project sector and family, a reporting view 360 similar to the one shown in FIG. 78 may be presented on an exemplary web page 61 to the user. The reporting view 360 shown in FIG. 78 is an estimated future spending model aggregated by project sector/family reporting view 360 containing analytical data 270 related to the estimated future spending on projects in different project sector/families.”).
With regards to claim 2, Cullen et al. teaches determining the one or more project objectives from at least one of: a time objective, a cost objective, a quality objective, a sustainability objective, an efficiency objective, and a health objective associated with the project (paragraph [0163], “Project change in plan/scope (PCIP/S) administrative management functionality is provided that permits the enterprise to limit risks applicable to changes in plan/scope and optimize data processing and business administration endeavors through Statement Of Work (SOW) dependency modeling and collaborative work flow processing.”; paragraph [0275], “The vendor response data can include costing information including costing elements (e.g., resource requirements, expense types, etc.) and associated pricing information (e.g., resource rates, expense amounts, etc.) and deliverables information including deliverables types (e.g., number of units to be completed, phasing information, etc.) and completion information (e.g., project end date, phase end dates, etc.). Each of the costing elements and deliverables types is associated with a different bid item selection to enable effective comparison and grading of vendor bid responses.”).
With regards to claim 3, Cullen et al. teaches determining the parameters related to the project based on at least one of: a historical data related to the project, an industry data associated with the project, an execution data for the project, and a forecast data associated with the project (paragraph [0482], “For example, a user can select a particular project sector/family and choose from various impact variables (e.g., filters 280), such as geography, vendor tier, etc., and various project performance reporting views 360 to present a reporting view 360 containing aggregate summary analytical data 270 associated with every combination of the listed impact variables associated with the specific historical project performance data. This type of reporting view 360 may be useful to a user to provide significant insight into which business configurations (variable aggregates) have been successful and which ones have not.”).
With regards to claim 5, Cullen et al. teaches determining the set of constraints includes determining at least one of: pre-existing manufacturing data sets, supplier data sets, material data sets, geolocation data sets, and environmental data sets (paragraph [0507], “7) A supplier management system 9015, which is a supplier application module by which a buyer entity can manage various facets of supplier management relative to their commerce environment. Various business aspects of supplier management, from specific liability protection through strategic supplier spend management, can be achieved within configuration elements of the supplier management system 9015 if the necessary business information to do so is available. Typical configuration elements may include, but are not necessarily limited to: designation and attribute definition of supplier types, designation and attribute definition of supplier business qualifiers, designation and attribute definition of supplier insurance qualifiers, designation and attribute definition of supplier tiers, designation and attribute definition of supplier agreements, designation and attribute definition of supplier business audits, designation and attribute definition of supplier business qualification waivers and of course specification of supplier provision capacity in relation to buyer-utilized commodities.”).
With regards to claims 6, 12, and 18, Cullen et al. teaches
analyzing real-time data and user modification associated with the set of constraints for achieving custom project objectives (paragraph [0168], “3) select specific SOW record(s) and modify the condition or attribute data of the record(s), such as, for example, a status or expected completion date, to generate a system diagnostic risk report indicating, based upon prior user configuration, the impact to related business records, the diagnostic risk report output typically providing views into impacted deliverables, service units, goods/shipments, project phasing, human resource assignments, purchase orders/cash flow planning, budgeting/accruals, related business events, contracts, asset management, suppliers, and users;”);
determining an impact of the analyzed data on the one or more project objectives(paragraph [0168], “4) create a communications session whereby impacted project work parties can be provided information applicable to at risk SOW elements and projects, wherein the communications can be broadcast in, for example, macro or micro modes dependent upon user configuration and specific broadcasted records configured in such a manner as to enable bi-directional data processing capabilities applicable to an at risk SOW element”); and
generating an updated project manifest based on the determined impact (paragraph [0168], “5) process mutually agreed upon communications session records in a manner that systematically updates application SOW element, purchase order and other related records while maintaining a history of the communications records as well as superseded SOW element, purchase order and other related records; 6) systematically initiate global/macro condition/status code changes of a record set premised upon a presumed SOW record condition/status type change; 7) systematically initiate global/macro record attribute changes of a record set premised upon a presumed condition/status type change; 8) send notifications to impacted parties upon systematic record updating modification; 9) systematically generate a report consisting of pertinent RFx bid response records applicable to an at risk SOW element;”).
With regards to claims 7 and 14, Cullen et al. teaches creating the project manifest that includes the optimized model covering time, cost, and schedule aspects from at least one of project, manpower, equipment, source, material, logistics, and processes (paragraph [0163], “Project change in plan/scope (PCIP/S) administrative management functionality is provided that permits the enterprise to limit risks applicable to changes in plan/scope and optimize data processing and business administration endeavors through Statement Of Work (SOW) dependency modeling and collaborative work flow processing.”).
With regards to claims 8, 13, and 19, Cullen et al. teaches
monitoring a production efficiency associated with the project (paragraph [0319], “For each of the selected graded bid items 236, the grader can also enter a weighting percentage 850 for that graded bid item 236. The grader can adjust the weighting percentages 850 based on pre-established criteria or personal preferences until the weighted percentage 850 total equals one-hundred percent. As discussed above, in other embodiments, all graded bid items 236 can be assigned equal weights, so that the weighting percentages 850 would not need to be displayed to or selected by the grader.”, where production efficiency may be a determined ability of the meet the preferences for the bidding process); and
providing one or more of a causality data and a remedial data associated with the production efficiency (paragraph [0327], “After a vendor bid response is received and graded, the buyer user may provide the opportunity for a vendor to submit a re-quote on one or more graded bid items to improve the vendor's score. For example, a vendor that the buyer user typically chooses or that has high grades on other graded bid items may have a lower score than another vendor, and the buyer user may want to provide the vendor the opportunity to revise the vendor bid response data for the one or more graded bid items that have low grades.”).
With regards to claims 9, 15, and 20, Cullen et al. teaches
receiving a bidding request for the request related to the project from one or more bidders who intend to work on the project (paragraph [0194], “In addition, the buyer information can be stored in the vendor's buyer list for reference when receiving bid requests and preparing bid responses (step 760).”); and
providing a set of recommendations to the one or more bidders based on the generated optimized model associated with the project (paragraph [0191], “The buyer-defined vendor criteria data 164 can identify the specific goods and/or services that the buyer 50 desires, the specific geographical areas that the buyer 50 wants the goods and/or services and other buyer constraints, such as the preferred size of the vendor, requisite vendor insurance needs, requisite vendor certifications, etc.”, where buyer preferences are passed through as part of optimized model for bidding request).
With regards to claim 10, Cullen et al. teaches providing the set of recommendations including at least one of: a cost forecast, a project manifest associated with the project, a time forecast, and materials supplier information (paragraph [0191], “The buyer-defined vendor criteria data 164 can identify the specific goods and/or services that the buyer 50 desires, the specific geographical areas that the buyer 50 wants the goods and/or services and other buyer constraints, such as the preferred size of the vendor, requisite vendor insurance needs, requisite vendor certifications, etc.”).
With regards to claim 16, Cullen et al. teaches instructions, stored in the storage media, implementing a bid manager, which when executed by the computing system, causes the computing system to:
receive bids related to the project from the one or more bidders based on the set of recommendations provided by the marketplace debut module (paragraph [0162], “Buyers can solicit bids from vendors for a particular good and/or service (hereinafter referred to as a project) in a form specified by the buyer using a bid request generated from a pre-established list of bid items related to the project type. Therefore, the bid responses submitted from vendors all have the same form, enabling efficient and effective evaluation of the bid responses. Embodiments of the present invention further combine the bid process with project management to enable the buyer, vendor, contractor and administrator to track the performance of the project after the bid is awarded.”);
arrange the received bids based on the one or more project objectives (paragraph [0290], “For example, in table tblRFX 801, general information concerning the bid request can be stored, such as the bid tracking number assigned to the bid request by the system, the bid request name assigned by the originator, the identity of the bid request originator, the bid template type, the project type, project work location, budgeted expenditure amount for the project, the status of the bid request (e.g., new, submitted, evaluated, awarded, etc.), whether or not top-level database vendors received the bid request and whether any approval was required.”); and
provide the arranged bids related to the project on a digital marketplace interface (paragraph [0232], “To facilitate the bid process in the context of a complete bid/project process, bid templates can be used for specific project types to solicit the requisite information from vendors for the specific project type in a uniform and comprehensive manner to enable efficient and effective evaluation of bid responses.”).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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 4 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 20060190391 to Cullen et al. as applied to claims 1-3 and 5-20 above, and further in view of U.S. Patent Application Publication No. 20220027826 to Makhija et al.
With regards to claim 4, while Cullen et al. teaches the use computerize processes including bid response grading to automatically generate an optimized model (see paragraph [0320]), Cullen et al. fails to explicitly teach the specified processes. However, Makhija et al. teaches applying one or more of deep-learning, Artificial Intelligence (AI), and Machine Learning (ML) processes to generate the optimized model (paragraph [0017], “In another embodiment the category management method includes encapsulating one or more awarding scenario on the category workbench application user interface by the bot wherein an AI engine incorporates rules and target constraints including preferable number of suppliers, preferential awards to incumbent suppliers, minimum lead times, and savings goals to automatically arrive at a most efficient cost for executing recommended strategy.”).
This part of Makhija et al. is applicable to the system of Cullen et al. as they both share characteristics and capabilities, namely, they are directed to project planning and management. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Cullen et al. to include the AI engine for project management data analysis as taught by Makhija et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Cullen et al. in order to provide efficient analysis of organizational strategic goals and sourcing (see paragraphs [0006]-[0009] of Makhija et al.).
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 20060190391 to Cullen et al. in view of U.S. Patent Application Publication No. 20210142286 to Hajian.
With regards to claim 21, Cullen et al. teaches
receiving a request related to a project, the project is at least one of a construction project and a manufacturing project (paragraph [0162], “Buyers can solicit bids from vendors for a particular good and/or service (hereinafter referred to as a project) in a form specified by the buyer using a bid request generated from a pre-established list of bid items related to the project type. Therefore, the bid responses submitted from vendors all have the same form, enabling efficient and effective evaluation of the bid responses. Embodiments of the present invention further combine the bid process with project management to enable the buyer, vendor, contractor and administrator to track the performance of the project after the bid is awarded.”);
determining one or more project objectives related to the request from at least one of: a time objective, a cost objective, a quality objective, a sustainability objective, an efficiency objective, and a health objective associated with the project (paragraph [0250], et seq. including Table 26, where bid items may include project objectives and constraints including time and regulation requirements; paragraph [0345], “Exemplary database structures for storing contractor information and ensuring that relevant documents are obtained from the contractor or agreed to by the contractor are shown in Tables 60-63 below. Table 60 lists various sample documents that either need to be obtained from the contractor or that the contractor needs to execute at some point during the project. Table 60 also lists the time constraints for obtaining or executing such documents. Table 61 lists the contractor information, such as the identity of the contractor, the number of billable hours authorized, the amount of expenses authorized, the execution date of various documents and the contractor type.”);
determining a set of constraints for the project, the set of constraints are derived at least through a knowledge repository, wherein the knowledge repository includes one or more of parameters related to the project and a data feed from a plurality of data sources associated with the project (paragraph [0250], et seq. including Table 26, where bid items may include project objectives and constraints including time and regulation requirements; paragraph [0345], “Exemplary database structures for storing contractor information and ensuring that relevant documents are obtained from the contractor or agreed to by the contractor are shown in Tables 60-63 below. Table 60 lists various sample documents that either need to be obtained from the contractor or that the contractor needs to execute at some point during the project. Table 60 also lists the time constraints for obtaining or executing such documents. Table 61 lists the contractor information, such as the identity of the contractor, the number of billable hours authorized, the amount of expenses authorized, the execution date of various documents and the contractor type.”);
determining the parameters related to the project based on at least one of: a historical data related to the project, an industry data associated with the project, an execution data for the project, and a forecast data associated with the project (paragraph [0482], “For example, a user can select a particular project sector/family and choose from various impact variables (e.g., filters 280), such as geography, vendor tier, etc., and various project performance reporting views 360 to present a reporting view 360 containing aggregate summary analytical data 270 associated with every combination of the listed impact variables associated with the specific historical project performance data. This type of reporting view 360 may be useful to a user to provide significant insight into which business configurations (variable aggregates) have been successful and which ones have not.”);
correlating the determined set of constraints with the one or more project objectives (paragraph [0250], et seq. including Table 26, where bid items may include project objectives and constraints including time and regulation requirements; paragraph [0314], “Upon receipt of vendor bid responses (step 3200), the bid item selections to be used for grading purposes are identified (step 3210). The bid item selections are associated with the bid request soliciting the vendor bid responses, and vendor bid response data is included within the bid item selections chosen for grading purposes. Using the vendor bid response data within the graded bid items, the vendor bid responses are graded (step 3220).”);
evaluating the correlated set of constraints and the one or more project objectives to generate an optimized model …. (paragraph [0163], “Project change in plan/scope (PCIP/S) administrative management functionality is provided that permits the enterprise to limit risks applicable to changes in plan/scope and optimize data processing and business administration endeavors through Statement Of Work (SOW) dependency modeling and collaborative work flow processing.”; paragraph [0479], “FIG. 79 is a screen shot of an exemplary web page 61 containing analytical data 270 related to project performance data for a particular project that is presented in a project performance summary reporting view 360. The analytical data 270 can include the project status, the project phase completion count, the past due phase count, the deliverable completion count, the past due deliverable completion count, the percentage of on-time deliverable completions, and other project performance analytical data. At the bottom of the web page 61 are links to different project performance reporting views 360 summarized by different types of transactional data, such as business impact type, geography, vendors, etc.”); and
creating a project manifest based on the optimized model for executing the project (paragraph [0477], “As an example, if a user clicked on the link to summarize the estimated future project spending by project sector and family, a reporting view 360 similar to the one shown in FIG. 78 may be presented on an exemplary web page 61 to the user. The reporting view 360 shown in FIG. 78 is an estimated future spending model aggregated by project sector/family reporting view 360 containing analytical data 270 related to the estimated future spending on projects in different project sector/families.”). while Cullen et al. teaches the use computerize processes including bid response grading to automatically generate an optimized model (see paragraph [0320]), Cullen et al. fails to explicitly teach but fails to teach applying one or more of deep-learning, Artificial Intelligence (AI), and Machine Learning (ML) processes.
However, Hajian teaches evaluating the correlated set of constraints and the one or more project objectives to generate an optimized model applying one or more of deep-learning, Artificial Intelligence (AI), and Machine Learning (ML) processes (paragraph [0050], “The machine learning models 312 apply intelligence to identify complex patterns in the input and to leverage those patterns to produce output and refine systemic understanding of how to process the input to produce the output. The machine learning models 312 may be used by the parameterized score estimation software tool 302 and/or by the parameterized score optimization software tool 304. The machine learning models 312 may be or include one or more of a neural network (e.g., a convolutional neural network, recurrent neural network, or other neural network), decision tree, vector machine, Bayesian network, genetic algorithm, deep learning system separate from a neural network, or other machine learning model.”; paragraph [0051], “he parameterized score estimation software tool 302 is a software tool which processes a limited set of inputs to determine and output a score estimation. The parameterized score estimation software tool 302 extrapolates upon the limited set of inputs according to one or more selected processing criteria to determine the score estimation. In the example in which the parameterized score estimation software tool 302 is used for estimating scores for construction projects, the limited set of inputs may be or otherwise refer to a set of design metrics representing first input parameter values, and the one or more selected processing criteria may be or otherwise refer to a set of historical project data representing second input parameter values.”).
This part of Hajian is applicable to the system of Cullen et al. as they both share characteristics and capabilities, namely, they are directed to project planning and management. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Cullen et al. to include the use of machine learning for project management data analysis as taught by Hajian. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Cullen et al. in order to provide intelligent automated functionality which analyzes parameterized information (see paragraphs [0002]-[0003] of Hajian).
Conclusion
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/J.D.S./Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626