PCT/U32018I054888 08.01.2019
`
`From the INTERNATIONAL SEARCHING AUTHORITY
`
`PATENT COOPERATION TREATY
`
`NOTIFICATION OF TRANSMITTAL OF
`THE INTERNATIONAL SEARCH REPORT AND
`TH E WRITTEN OPINION OF THE INTERNATIONAL
`SEARCHING AUTHORITY, OR THE DECLARATION
`
`(PCT Rule 44.1)
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`223:5,‘233225 o 8' l A N 2019
`
` PCT
`To': MICHAEL J. SWOPE
`
`BAKER & HOSTETLER LLP
`
`
`CIRA CENTRE, 12TH FLOOR, 2929 ARCH
`STREET
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`PHILADELPHIA, PA 19104-2891
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`Applicant’s or agent‘s file reference
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`lntemational application No.
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`lntemational filing date
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`Applicant SEARS BRANDS, L.L.C.
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`I. [Z] The applicant is hereby notified that the international search report and the written opinion of the international Searching
`Authority have been established and are transmitted herewith.
`Filing ofamendmcnts and statement under Article 19:
`The applicant is entitled, if he so wishes, to amend the claims of the international application (see Rule 46):
`When? The time limit for filing such amendments is nomially two months from the date oftransmittal ofthe intemational
`search report.
`Directly to the lntemational Bureau of WIPO preferably through ePCT or on paper to, 34 chemin des Colombettes
`l21 l Geneva 20, Switzerland, Facsimile No.: +41 22 338 82 70
`For more detailed instructions, see PCT Applicant '5 Guide. International Phase, paragraphs 9.004 - 9.011.
`
`2.
`The applicant is hereby notified that no international search report will be established and that the declaration under
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`Article l7(2)(a) to that effect and the written opinion of the International Searching Authority are transmitted herewith.
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`How?
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`3. El With regard to any protest against payment of (an) additional fee(s) under Rule 40.2, the applicant is notified that:
`the protest together with the decision thereon has been transmitted to the lntemational Bureau together with any
`request to forward the texts of both the protest and the decision thereon to the designated Offices.
`[3 no decision has been made yet on the protest;
`the applicant will be notified as soon as a decision is made.
`4. Reminders
`
`The applicant may submit comments on an informal basis on the written opinion of the International Searching Authority
`to the lntemational Bureau. These comments will be made available to the public after international publication. The
`lntemationai Bureau will send a copy of such comments to all designated Offices unless an intemationai preliminary
`examination report has been or is to be established.
`Shortly alter the expiration of 18 months from the priority date. the international application will be published by the
`lntemational Bureau.
`if the applicant wishes to avoid or postpone publication, 3 notice of withdrawal of the intemationai
`application, or of the priority claim, must reach the international Bureau before the completion of the technical preparations for
`international publication (Rules 90bis.l and 90171253).
`Within 19 months from the priority date. but only in respect ofsome designated Offices, a demand for international preliminary
`examination must be filed if the applicant wishes to postpone the entry into the national phase u ntil 30 months from the priority
`date (in some Offices even later); otherwise, the applicant must, within 20 months from the priority date, perform the
`prescribed acts for entry into the national phase before those designated Offices.
`in respect of other designated Offices, the
`time limit of 30 months (or later) will apply even if no demand is filed within 19 months. For details about the applicable time
`limits, Office by Office, see www.wipo.int/pct/en/texts/time_limits.html and the PCT Applicant '5 Guide, National Chapters.
`Within 22 months from the priority date, the applicant may request that a supplementary international search be carried
`out by a different International Searching Authority that offers this service (Rule 45b/‘s.l). The procedure for requesting
`supplementary international search is described in the PCT Applicant 's Guide, lntemational Phase, paragraphs 8.006-8.032.
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`Telephone NO. p31 OSP: 571.272.7774
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`Name and mailing address of the [SA/US
`Commissioner for Patents
`Mail Stop PCT, Attn: ISA/US
`
`PD. Box 1450, Alexandria. Virginia 22313-1450
`Facsimile N0. 571.273'8300
`Form PCT/ISA/220 (July 2014)
`
`Authorized officer
`
`Lee W. Young
`
`POT Halpnesk: 571.272.4300
`
`

`

`PCT/U3201 8/054888 08.01 .201 9
`
`From the
`INTERNATIONAL SEARCHING AUTHORITY
`
`PATENT COOPERATION TREATY
`
`WRITTEN OPINION OF THE.
`INTERNATIONAL SEARCHING AUTHORITY
`
`(PCT Rule 43bis. I)
`
` PCT
`
`To: MICHAEL J. SWOPE
`BAKER & HOSTETLER LLP
`
`
`CIRA CENTREl 12TH FLOOR, 2929 ARCH
`STREET
`
`PHILADELPHIA, PA 19104-2891
`
`
`
`Date ofmailing
`(day/monrh/year)
`
`08 JAN 2019
`
`
`
`FOR FURTHER ACTION
`Applicant’s or agent‘s file reference
`
`
`105562.002022
`International filing date (day/monlh/war)
`lntemational application No.
`
`
`08 October 2018 (08.10.2018)
`PCT/US 18154888
`International Patent Classification (IPC) or both national classification and IPC
`
`”30(3) _ 6060 30/00 (2018.01)
`
`
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`Cpc _
`GOSQ 30/0202, G060 30/02, 6060 30/0201. (3060 10/087. G060 10/06, 6060 10/06375. GOSQ
`10/0639. GOGN 99/005. GOBN 3/08, G06N 3/04, G06F 17/30707. (306K 9/6269
`
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`Applicant SEARS BRANDS. L.L.C.
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`See paragraph 2 below
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`Priority date (day/manrh/year)
`24 May 2018 (24.05.2018)
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`I. This opinion contains indications relating to the following items:
`
`Box No.
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`1
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`Basis of the opinion
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`2. FURTHER ACTION
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`If a demand for international preliminary examination is made, this opinion will be considered to be a written opinion of the
`International Preliminary Examining Authority (“IPEA”) except that this does not apply where the applicant chooses an Authority
`other than this one to be the [PEA and the chosen [PEA has notified the lntemational Bureau under Rule 66.Ibis(b) that written
`opinions of this International Searching Authority will not be so considered.
`If this opinion is, as provided above, considered to be a written opinion of the IPEA, the applicant is invited to submit to the [PEA
`a written reply together, where appropriate, with amendments, before the expiration of3 months from the date ofmailing of Form
`PCT/ISA/ZZO or before the expiration of 22 months from the priority date, whichever expires later.
`For further options, see Form PCT/ISA/ZZO.
`
`Name and mailing address of the ISA/US Date of completion of this opinion
`Mall Stop PCT. Attn: ISA/US
`Commlssloner tor Patents
`P.O. Box 1450, Alexandria, Virglnla 22313-1450
`Facsimile No. 571~273-8300
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`07 December 2018
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`PCT 05?; 571-272-7774
`
`Authorized officer
`Lee W. Young
`PCT "mm: 57147243”
`
`Form PCT/ISA/237 (cover sheet) (January 2015)
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`Box No. II
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`Priority
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`Box No. III
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`Nonoestablishmcnt of opinion with regard to novelty, inventive step and industrial applicability
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`Box No. IV Lack of unity ofinvention
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`DEE]EDDDE Box No. VIII Certain observations on the international application
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`Box No. V
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`Reasoned statement under Rule 43bis. l (a)(i) with regard to novelty, inventive step and industrial applicability;
`citations and explanations supporting such statement
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`Box No. VI
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`Certain documents cited
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`Box No. Vll Certain defects in the intemational application
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`

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`PCT/USZO18IO54888 08.01.201 9
`
`WRITTEN OPINION OF THE
`INTERNATIONAL SEARCHING AUTHORITY
`
`’
`
`lntemational application No.
`PCT/US 18154888
`
`Box No. l
`
`Basis of this opinion
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`1. With regard to the language, this opinion has been established on the basis of:
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`E] the international application in the language in which it was filed.
`D a translation of the international application into
`furnished for the purposes of international search (Rules 12.3(a) and 23.1(b)).
`
`which is the language of a translation
`‘
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`This opinion has been established taking into account the rectification of an obvious mistake authorized by or notified to
`this Authority under Rule 9| (Rule 43bis. l(a)).
`
`3. E] With regard to any nucleotide and/or amino acid sequence disclosed in the international application. this opinion has
`been established on the basis of a sequence listing:
`
`a. E] forming part of the international application as filed:
`[:3 in the form ofan Annex CIST.25 text file.
`E] on paper or in the form of an image file.
`b. E] fitmished together with the international application under PCT Rule 13rer.l(a) for the purposes of international
`search only in the form of an Annex C/S'l‘.25 text file.
`
`0. E] fumished subsequent to the intemational filing date for the purposes of international search only:
`C] in the form of an Annex CIST.25 text tile (Rule l3!er.l(a)).
`D on paper or in the form of an image file (Rule lBter.l(b) and Administrative instructions, Section 713).
`
`4‘ E] In addition, in the case that more than one version or copy ofa sequence listing has been filed or furnished, the required
`statements that the information in the subsequent or additional copies is identical to that forming part of the application as
`filed or does not go beyond the application as filed, as appropriate, were firmished.
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`5. Additional comments:
`
`Form PCT/lSA/237 (Box No. 1) (January 2015)
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`

`

`PCT/U52018I054888 08.01.2019
`
`WRITTEN OPINION OFTHE
`INTERNATIONAL SEARCHING AUTHORITY
`
`lntemationai application No.
`PCT/US iii/54888
`
`Box No. V
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`Reasoned statement under Rule 43bis.t(a)(i) with regard to novelty. inventive step or industrial applicability;
`citations and explanations supporting such statement
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`Statement
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`Novelty (N)
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`inventive step (18)
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`Industrial applicability ([A)
`
`Claims
`Claims
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`Claims
`Claims
`
`Claims
`Claims
`
`--(continued in the Supplemental Boxes)»-
`
`Citations and explanations:
`2.
`Claims 1-20 lack novelty under PCT Article 33(2) as being anticipated by US 2006/0015416 A1 to Hoffman et al. (hereinafter "Hoffman").
`
`Regarding claim 1, Hoffman discloses a demand forecasting system (100). comprising: a forecast engine (130) configured to generate
`forecast data (Based on this analysis. a forecast is made of one or more aspects of the supply chain at the selected point in the supply
`chain in operation 938, para [0297]. Fig. 9); a history database (120) operatively coupled to the forecast engine (This historical data relates
`to at least the sale of goods by the stores and can be further categorized based on seasonality. past marketing and/or advertising support.
`etc. para [0310]); a plurality of data collectors (110) operatively coupled to the history database (Forecasting of at least one aspect of a
`supply chain is performed in operation 1132 based on a first set of data collected from a plurality of stores of the supply chain utilizing a
`network. para [0306]. Fig. 11); a SIM-TO engine (150) operatively coupled to the forecast engine (Coupled to the network 4404 is a
`plurality of computers which may take the form of desktop computers 4406, lap-top computers 4408. hand-held computers 4410 (including
`wireless devices 4412 such as wireless PDA's or mobile phones). or any other type of computing hardware/software. para [0400]. Fig.
`44); a forecast database (160) operatively coupled to the forecast engine (FIG. 15 is a flowohart of a process 1530 for collecting data to
`forecast sales in a supply chain. para [0314], Fig. 15); and an application unit (170) operatively coupled to the forecast engine (T0 date,
`Web development tools have been limited in their ability to create dynamic Web applications which span from client to server and
`Intemperate with existing computing resources. para [0443]); wherein the forecast engine and the forecast database are configured to
`provide inputs to the application unit to plan promotion activities. achieve optimal inventory and resource allocation. and minimize
`operating costs (The electronic ordering capability enables the restaurants to reduce the costs and times associated with preparing.
`submitting and receiving orders. para [0562]); wherein at least some of the forecast data generated by the forecast engine is stored in the
`forecast database (The first is to distribute consumption and forecast data to the supply chain participants (franchisees 5802. distributors
`5804. suppliers 5806, and raw material suppliers 5808) that can use it to effective plan purchases and inventory. The second is to
`automate restaurant ordering (food and packing. equipment and promotions. etc.). para [0559]. Fig. 58); and wherein the SIM-TO engine
`comprises a processor and a computer readable medium containing instructions that. upon execution by the processor. cause the SIM-TO
`engine to perform a process to identify items that are similar to a new Item identified by the data collector, enabling the forecast engine to
`provide forecast data indicative of a demand forecast for the new item. said process comprising: determining a classification of the new
`item (302) (For each attribute category the supply chain coordinator decides to include in the directory store. administration screens may
`be required to add. modify. or delete the attribute data. para [1255]); identifying a set of attributes of the new item (306); calculating
`matching scores for existing items within the determined classification. wherein the matching scores are calculated using the set of
`attributes (310) (In one aspect, the maximum acceptable amount of loss includes a predetermined amount of money. In another aspect,
`the acceptable ordering standards allow the calculation of a maximum amount of products that can be ordered as a function of the data.
`para [1488]); and identifying an existing item as similar to the new item in response to determining that a matching score for the existing
`item is equal to or greater than a predetermined threshold value (312) (in such an aspect. the data may be parsed to match each
`corresponding supply chain participant. para (0283]).
`
`Regarding claim 2, Hoffman discloses wherein the determined classification comprises a hierarchy of classifications, including as a
`division. a category, and a subcategory. and wherein the process to identify items that are similar further comprises performing an
`expanded search of existing items by conducting a search within a higher level of classification (Class hierarchies and containment
`hierarchies provide a flexible mechanism for modeling reai«worid objects and the relationships among them. para [0423]).
`
`Regarding claim 3. Hoffman discloses wherein the process to identify items that are similar further comprises adjusting the set of attributes
`and the predetermined threshold value so as to identify a desirable number of similar-to items (FIG. 158 illustrates the page 15800 under
`the items tab. As shown. the left side of the page under each tab is the search and selection area. it functions in the same manner as the
`rest of the Supply System, in that the user enters a search string and clicks search. and similar names to the search string will be
`retrieved, para [1593]. Fig. 158).
`
`Form PCT/iSA/237 (Box No. V) (January 2015)
`
`

`

`‘
`
`PdT/USZO18I054888 08.01.2019
`
`WRITTEN OPINION OF THE
`INTER A l
`THORITY
`N T ONALSEARCHINGAU
`
`Supplemental Box
`
`
`
`intematronal application No.
`PCT/US18I54BBB
`
`
`
`
`in case the space in any of the preceding boxes is not sufficient.
`Continuation of:
`Box V, item 2. Citations and explanations:
`
`Regarding claim 4. Hoffman discloses wherein the forecast engine is configured to: divide gathered data from the data collectors into a set
`
`
`of training data and a set of test data (Forecasting of at least one aspect of a supply chain is performed in operation 1132 based on a first
`
`set of data collected from a plurality of stores of the supply chain utilizing a network, para [0306], Fig. 11); train a plurality of machine
`
`
`learning models using the set of training data (This framework is more complex and consists of significant collections of collaborating
`classes that capture both the small scale patterns and major mechanisms that Implement the common requirements and design in a
`
`
`specific application domain, para [0428]); generate fitness functions for the plurality of machine learning models; select a model with the
`
`
`highest degree of fitness across the set of training data (invoice level sales data is transmitted from the supplier to the supply chain
`
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`manager utilizing a network in operation 4632, para [0477]. Fig. 46): evaluate forecast accuracy of the selected model using the set of test
`
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`data (After receiving confirmation concerning successful processing of the Test data, a notification is sent to begin Production reporting
`
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`according to the reporting period specified in the Franchisee information Layout section, para [0484]): and determine whether the forecast
`
`
`accuracy of the selected model is acceptable (The new technological infrastructure and its associated electronic reporting and feedback
`
`
`systems equips retailer management with accurate. timely. and previously unavailable information from the Supply Chain on sales.
`
`
`marketing and other performance indicators allow Supply Chain management to fully engage in managing supply and distribution
`
`
`processes and channels toward identified and agreed strategic objectives provide franchisees and retailers with the Supply Chain
`
`
`information they need to operate efficiently and make effective management decisions minimally impacts the resources of Supply Chain
`management, para [1429]).
`
`Regarding claim 5. Hoffman discloses wherein the system is further configured to update the forecast data generated by the selected
`model as data associated with existing or similar-to items become available (After data has been entered, the proposal can be generated
`and printed. in the reporting module of the proposal process, a user can update specific documents for a supplier, print any of the reports
`included in the proposal, and/or generate the entire proposal, para [1578]).
`
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`
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`Regarding claim 6. Hoffman discloses wherein the system is further configured to adjust the data gathered by the forecast engine to
`
`
`improve the forecast accuracy of one or more machine learning models (Also, key demand information is gathered directly from the store.
`greatly increasing accuracy and reducing response time. para [0301]).
`
`Regarding claim 7, Hoffman discloses wherein the plurality of data collectors are located in a number of stores of a retail entity and are
`
`
`
`configured to collect various data relating to items sold by the retail entity, including locations of stores, categories and descriptions of
`
`
`items, times, prices and sales (in such an aspect, the price of the goods may be calculated from the electronic order forms utilizing a table
`
`
`mapping a plurality of goods with a plurality of prices. para [0669]); and wherein the data collected by the data collectors is stored in the
`history database (For the very first time. retail outlet management will be able to evaluate Supply Chain and retail outlet sales Information
`
`
`to develop Brand menu and marketing program strategies. in addition, another first, retailer management is allowed to evaluate the
`
`
`success of past marketing programs by comparing actual sales to forecasts and reviewing Gross Profit Margin analyses of programs. para
`[0292]).
`
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`Regarding claim 8, Hoffman discloses wherein the forecast engine and the SIM-TO engine are accessible via an application programming
`interface (API) or user interface, and wherein the forecast engine and SlM-TO engine are configured to provide an analysis and summary
`of results to a requesting user (Java applets are small, specialized applications that comply with Sun's Java Application Programming
`interface (API) allowing developers to add "Interactive content" to Web documents (e.g., simple animations. page adomments, basic
`games. etc.), para [0454]).
`
`
`
`
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`Regarding claim 9, Hoffman discloses wherein calculating matching scores for existing items comprises assigning a value of "1" to an
`existing item if the existing item has an attribute matching one among the set of attributes of the new item, and otherwise assigning a value
`
`
`
`of ”0" to the existing item; and wherein a matching score of each existing item is determined by dividing a sum of values assigned to each
`existing item by the number of attributes among the set of attributes (The supply chain coordinator receives a load of updated retailer
`
`
`information from the retailer manager. This information is currently batch loaded into the SQL database and updates are made to tables
`matching retailers to suppliers, distributors. and supply chain members. para [1334]).
`
`Regarding claim 10, Hoffman discloses a system comprising a forecast engine configured to generate forecast data, a history database
`
`
`(This historical data relates to at least the sale of goods by the stores and can be further categorized based on seasonality, past marketing
`
`
`and/or advertising support. etc. para [0310]). a plurality of data collectors (Forecasting of at least one aspect of a supply chain is performed
`in operation 1132 based on a first set of data collected from a plurality of stores of the supply chain utilizing a network, para [0306], Fig.
`11). a SIM-TO engine, and a forecast database (Based on this analysis, a forecast is made of one or more aspects of the supply chain at
`the selected point in the supply chain in operation 938, para [0297]. Fig. 9), a method performed by the SIM—TO engine to identify items
`that are similar to a new item identified by a data collector (The first is to distribute consumption and forecast data to the supply chain
`participants (franchisees 5802, distributors 5804, suppliers 5805. and raw material suppliers 5808) that can use it to effective plan
`purchases and inventory. The second is to automate restaurant ordering (food and packing, equipment and promotions. etc), para [0559],
`Fig. 58), said method comprising the steps of: determining a classification of the new item (302) (For each attribute category the supply
`chain coordinator decides to include in the directory store, administration screens may be required to add, modify, or delete the attribute
`data. para [1255]); identifying a set of attributes of the new item (306); calculating matching scores for existing items within the determined
`classification. wherein the matching scores are calculated using the set of attributes (310) (in one aspect, the maximum acceptable
`amount of loss includes a predetermined amount of money. in another aspect, the acceptable ordering standards allow the calculation of a
`maximum amount of products that can be ordered as a function of the data, para [1488]); and identifying an existing item as similar to the
`new item in response to determining that a matching score for the existing item is equal to or greater than a predetermined threshold value
`(312) (in such an aspect, the data may be parsed to match each corresponding supply chain participant, para [0283]).
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` ~-(continued on the next page)—--
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`Form PCT/lSA/237 (Supplemental Box) (January 2015)
`
`

`

`PCTIU32018I054888 08.01 .201 9
`
`WRITTEN OPINION OF THE
`INTERNATIONAL SEARCHING AUTHORITY
`
` intcmationai application No.
`
`PCT/US 18154888
`
`
`
`Supplemental Box
`
`Regarding claim 14, Hoffman discloses updating the forecast data generated by the selected model as data associated with existing or
`similar-to items become available (After data has been entered, the proposal can be generated and printed. In the reporting module of the
`proposal process, a user can update specific documents for a supplier, print any of the reports included in the proposal, and/or generate
`the entire proposal. para [1578]).
`
`Regarding claim 16, Hoffman discloses wherein the plurality of data collectors are located in a number of stores of a retail entity and collect
`various data relating to items sold by the retail entity, including locations of stores, categories and descriptions of items, times, prices and
`sales (In such an aspect, the price of the goods may be calculated from the electronic order forms utilizing a table mapping a plurality of
`goods with a plurality of prices, para [0669]); and store the data collected in the history database (For the very first time. retail outlet
`management will be able to evaluate Supply Chain and retail outlet sales information to develop Brand menu and marketing program
`strategies. in addition. another first, retailer management is allowed to evaluate the success of past marketing programs by comparing
`actual sales to forecasts and reviewing Gross Profit Margin analyses of programs, para [0292]).
`
`
`
`In case the space in any ofthe preceding boxes is not sult'icien t.
`Continuation of:
`Box V. item 2. Citations and explanations:
`
`
` Regarding claim 11, Hoffman discloses wherein the determined classification comprises a hierarchy of classifications. including as a
`
`
`division. a category, and a subcategory. and wherein the method to identify items that are similar further comprises performing an
`
`expanded search of existing items by conducting a search within a higher level of classification (Class hierarchies and containment
`hierarchies provide a flexible mechanism for modeling real-world objects and the relationships among them. para [0423]).
`
`
` Regarding claim 12. Hoffman discloses wherein the method to identify items that are similar further comprises adjusting the set of
`
`attributes and the predetermined threshold value so as to identify a desirable number of similar-to items (FIG. 158 illustrates the page
`
`
`158th under the Items tab. As shown. the left side of the page under each tab is the search and selection area. it functions in the same
`
`
`manner as the rest of the Supply System. in that the user enters a search string and clicks search. and similar names to the search string
`will be retrieved, para [1593], Fig. 158).
`
`
` Regarding claim 13, Hoffman discloses wherein the forecast engine performs the following steps: dividing gathered data from the data
`collectors into a set of training data and a set of test data (Forecasting of at least one aspect of a supply chain is performed in operation
`1132 based on a first set of data collected from a plurality of stores of the supply chain utilizing a network, para [0306]. Fig. 11): training a
`
`
`plurality of machine teaming models using the set oi training data: generating fitness functions for the plurality of machine learning models
`(This framework is more complex and consists of significant collections of collaborating classes that capture both the small scale patterns
`and major mechanisms that implement the common requirements and design in a specific application domain. para [0428]); selecting a
`model with the highest degree of fitness across the set of training data; evaluating forecast accuracy of the selected model using the set of
`
`
`test data (invoice level sales data is transmitted from the supplier to the supply chain manager utilizing a network in operation 4632, para
`[0477]. Fig. 46); and determining whether the forecast accuracy of the selected model ls acceptable (The new technological infrastructure
`
`and its associated electronic reporting and feedback systems equips retailer management with accurate. timely. and previously unavailable
`
`information from the Supply Chain on sales. marketing and other performance indicators allow Supply Chain management to fully engage
`in managing supply and distribuflon processes and channels toward identified and agreed strategic objectives provide franchisees and
`
`retailers with the Supply Chain information they need to operate efficiently and make effective management decisions minimally impacts
`the resources of Supply Chain management. para [1429]).
`
`
`
`
`Regarding claim 15, Hoffman discloses adjusting the data gathered by the forecast engine to improve the forecast accuracy of one or more
`machine teaming models (Also, key demand information is gathered directly from the store. greatly increasing accuracy and reducing
`response time. para (03011).
`
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` Regarding claim 18, Hoffman discloses wherein calculating matching scores for existing items comprises assigning a value of 11111 to an
`existing item if the existing item has an attribute matching one among the set of attributes of the new item, and otherwise assigning a value
`of 11011 to the existing item; and wherein a matching score of each existing item is determined by dividing a sum of values assigned to
`
`each existing item by the number of attributes among the set of attributes (The supply chain coordinator receives a load of updated retailer
`information from the retailer manager. This information is currently batch loaded into the SQL database and updates are made to tables
`matching retailers to suppliers. distributors, and supply chain members. para [1334]).
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`Regarding claim 17. Hoffman discloses wherein the forecast engine and the SIM-TO engine are accessible via an application
`programming interface (API) or user interface. and wherein forecast engine and SIM“) engine provide an analysis and summary of
`results to a requesting user (Java applets are small, specialized applications that comply with Sun's Java Application Programming
`interface (APl) allowing developers to add "interactive content" to Web documents (e.g.. simple animations, page adornments, basic
`games, etc.). para [0454]).
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`—-(contlnued on the next page)---
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`Form PCT/[SA/237 (Supplemental Box) (January 2015)
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`PCT/U32018I054888 08.01.201 9
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`WRITTEN OPINION OF THE
`INTERNATIONAL SEARCHING AUTHORITY
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`Supplemental Box
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`In case the space in any of the preceding boxes is not sufficient.
`Continuation of.
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`Box V, item 2. Citations and explanations:
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` international application No.
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`PCT/US 18/54888
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`Regarding claim 19. Hoffman discloses a computer readable medium containing instructions thatI upon execution by a processor, cause
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`the processor to perform a process to identify items that are similar to a new item identified by a data collector (Forecasting of at least one
`aspect of a supply chain is performed in operation 1132 based on a first set of data collected from a plurality of stores of the supply chain
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`utilizing a network. para [0306]. Fig. 11). said instructions comprising: instructions for determining a classification of the new item (For each
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`attribute category the supply chain coordinator decides to include in the directory store, administration screens may be required to add,
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`modify, or delete the attribute data, para (1255]); instructions for identifying a set of attributes of the new item; instructions for calculating
`matching scores for existing items within the determined classification. wherein the matching scores are calculated using the set of
`attributes (in one aspect, the maximum acceptable amount of loss includes a predetermined amount of money. in another aspect, the
`acceptable ordering standards allow the calculation of a maximum amount of products that can be ordered as a function of the data, para
`[1488]); and instructions for identifying an existing item as similar to the new item in response to determining that a matching score for the
`existing item is equal to or greater than a predetermined threshold value (in such an aspect. the data may be parsed to match each
`corresponding supply chain participant, para [0283]).
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`Regarding claim 20. Hoffman discloses wherein the instructions for calculating matching scores for existing items Include instructions for
`assigning a value of 11111 to an existing item if the existing item has an attribute matching one among the set of attributes of the new
`item. and otherwise assigning a value of 11011 to the existing item; and instructions for dividing a sum of values assigned to each existing
`item by the number at attributes among the set of attributes (The supply chain coordinator receives a load of updated retailer information
`from the retailer manager. This information is currently batch loaded into the SQL database and updates are made to tables matching
`retailers to suppliers. distributors. and supply chain members. para [1334]).
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` Claims 1‘20 have industrial applicability as defined by PCT Article 33(4), because the subject matter can be made or used in Industry,
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`Form PCT/lSA/237 (Supplemental Box) (January 2015)
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`

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`PCT/US$201 8/054888 08.01.2019
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`PATENT COOPERATION TREATY
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`PCT
`
`INTERNATIONAL SEARCH REPORT
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`(PCT Article 18 and Rules 43 and 44)
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`App'im” °" “3““ file ”fem”
`105562002022
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`FOR FURTHER
`ACTION
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`see Form PCT/lSA/220
`as well as, where applicable, item 5 below.
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`International application No.
`PCT/U5 18/54883
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`lntemational filing date (day/