| Oracle® Retail Assortment & Item Planning for Fashion/Softlines Cloud Service Implementation Guide Release 19.0 F24867-12 |
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| Oracle® Retail Assortment & Item Planning for Fashion/Softlines Cloud Service Implementation Guide Release 19.0 F24867-12 |
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The following information must be considered before configuring Assortment & Item Planning Cloud Service:
Assortment & Item Planning Cloud Service (A&IP CS) contains the solutions APFA (Assortment Planning for Fashion/Soft Lines) and IPCS (Item Planning). During implementation, the user has option to select the solution to deploy, only APFA, only IPCS, or both Assortment Planning and Item Planning. In addition, it also has the following provision options:
Provision Option 1 - Local Currency (LC)
Provision Option 2 - Location Clustering (SC)
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Note: Provisions are optional, but any one of the solutions should always be selected. |
Provision Option 1 - Local Currency
Retailers who want to plan in both primary currency as well as local currency can chose provisions containing this option. Selecting provisions with this option provides additional tasks, worksheets, and measures to support this process. The retailer must set up the Local Currency conversion details in the administration workbooks specific to this option. For more details, see the Oracle Retail Assortment & Item Planning for Fashion/Softlines Cloud Service User Guide.
Provision Option 2 - Location Clustering
Assortment & Item Planning Cloud Service supports using location clusters from external solutions, such as Oracle Retail Advanced Clustering Cloud Service. Enabling this option provides an out-of-the-box robust location clustering solution that provides embedded clustering science native to the RPAS platform and attribute-based clustering. Retailers who want to create Location Clusters using the RPAS-based clustering approach instead of Advanced Clustering can enable this provision option. Enabling this provision option includes additional tasks, worksheets, and measures to support this process. The administrator can create location clusters and use those clusters instead of clusters loaded from external systems, such as the Advanced Clustering solutions. Even if this option is enabled, users can still use both the RPAS-based clustering and Advanced Clustering option. For more details on Location Clustering, see the Oracle Retail Assortment & Item Planning for Fashion/Softlines Cloud Service User Guide.
A&IP CS needs the following sets of data from retailers, which are broadly classified as hierarchy files and data files. The data is described in the following sections. Based on solutions implemented in Assortment & Item Planning Cloud Service, only hierarchy files and data files specific for those solutions are needed and those are specified in the subsequent sections:
This is the foundation data to build any RPAS solution. Assortment & Item Planning for Fashion/Softlines Cloud Service requires the standard three hierarchy files, Calendar, Product, and Location. Also, additional sets of hierarchy files specific to different solutions are needed.
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Note: In all the hierarchy files, the hierarchy type User Defined Alternates (UDA) and data for those alternates do not need to be present in the hierarchy files. Administration users can directly set values for those alternates directly in the application. For more information, see the Oracle Retail Predictive Application Server Cloud Edition Administration Guide. If a retailer also provides these details in the hierarchy files, data for all user alternates for that hierarchy must be present in that file with header information. |
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Note: If hierarchy files contain header information, then columns can be in any order but the file name must be in the format <hier>.hdr.csv.dat. If the hierarchy files does not contain hierarchy header, the hierarchy data must be in same order as specified in the tables in the following sections without UDA dimensions. The file must be named <hier>.csv.dat. |
For information on the hierarchy files, see the following sections:
File name: clnd.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Name | Label | Hierarchy Type | Parent |
|---|---|---|---|
| DAY | Day | Main | None |
| WEEK | Week | Main | DAY |
| MNTH | Month | Main | WEEK |
| QRTR | Quarter | Main | MNTH |
| HALF | Half | Main | QRTR |
| YEAR | Year | Main | HALF |
| HLDY | Holiday | UDA | WEEK |
| EVNT | Event | UDA | WEEK |
| WOYR | Week of Year | Alternate | WEEK |
| STDB | STD/BTA | UDA | WEEK |
| BYPD | Assortment Period | UDA | WEEK |
day,day_label,week,week_label,mnth,mnth_label,qrtr,qrtr_label,half,half_label,year,year_label,hldy,hldy_label,evnt,evnt_label,woyr,woyr_label,stdb,stdb_label,bypd,bypd_label 20170129,1/29/2017,w01_2017,2/4/2017,m01_2017,Feb FY2017,q01_2017,Quarter1 FY2017,h1_2017,Half1 FY2017,a2017,FY2017,0,None,0,None,1,Week 01,1,STD,1,AP1 20170130,1/30/2017,w01_2017,2/4/2017,m01_2017,Feb FY2017,q01_2017,Quarter1 FY2017,h1_2017,Half1 FY2017,a2017,FY2017,0,None,0,None,1,Week 01,1,STD,1,AP1 20170131,1/31/2017,w01_2017,2/4/2017,m01_2017,Feb FY2017,q01_2017,Quarter1 FY2017,h1_2017,Half1 FY2017,a2017,FY2017,0,None,0,None,1,Week 01,1,STD,1,AP1 20170201,2/1/2017,w01_2017,2/4/2017,m01_2017,Feb FY2017,q01_2017,Quarter1 FY2017,h1_2017,Half1 FY2017,a2017,FY2017,0,None,0,None,1,Week 01,1,STD,1,AP1
Notes:
Though RPAS supports a string for position IDs, for calendar position week, it is preferred to use the date format YYYYMMDD. If the customer plans to use BDI or RMF CS integration, those expect the day and week position IDs at which data needs to be stored in the YYYYMMDD format.
File name: prod.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Name | Label | Hierarchy Type | Parent |
|---|---|---|---|
| SKU | Item | Main | None |
| SKUP | Style/Color | Main | SKU |
| SKUG | Style | Main | SKUP |
| SCLS | Sub-Category | Main | SKUG |
| CLSS | Category | Main | SCLS |
| DEPT | Department | Main | CLSS |
| PGRP | Group | Main | DEPT |
| DVSN | Division | Main | PGRP |
| CMPP | Company | Main | DVSN |
| STA1 | Style UDA 1 | UDA | SKUG |
| BRND | Brand | Alternate | SKU |
| VNDR | Vendor | Alternate | SKU |
Example:
sku,sku_label,skup,skup_label,skug,skug_label,scls,scls_label,clss,clss_label,dept,dept_label,pgrp,pgrp_label,dvsn,dvsn_label,cmpp,cmpp_label,brnd,brnd_label,vndr,vndr_label 1000001,Lasagna,1000001,Lasagna,1000001,Lasagna,1000001,Lasagna,70000,Pasta,4000,Dry Goods,100,Shelf Stable Grocery,10,Center Store,1,Spaces Grocery,Brand,Placeholder Brand,Vendor,Placeholder Vendor 1000002,Spagetti,1000002,Spagetti,1000002,Spagetti,1000002,Spagetti,70000,Pasta,4000,Dry Goods,100,Shelf Stable Grocery,10,Center Store,1,Spaces Grocery,Brand,Placeholder Brand,Vendor,Placeholder Vendor 1000003,Rigatoni,1000003,Rigatoni,1000003,Rigatoni,1000003,Rigatoni,70000,Pasta,4000,Dry Goods,100,Shelf Stable Grocery,10,Center Store,1,Spaces Grocery,Brand,Placeholder Brand,Vendor,Placeholder Vendor 1234582,1234582 - Folgers Breakfast Roast Non-Flavored De-Caffeinated 12 oz Can,22222222,Ground De-Caffeinated Can,121212,Ground De-Caffeinated,100000,Ground,10000,Coffee,1000,Shelf Stable Beverages,100,Shelf Stable Grocery,10,Center Store,1,Spaces Grocery,Brand,Placeholder Brand,Vendor,Placeholder Vendor 1234600,1234600 - Maxwell House 100% Columbian Non-Flavored De-Caffeinated 12 oz Can,22222222,Ground De-Caffeinated Can,121212,Ground De-Caffeinated,100000,Ground,10000,Coffee,1000,Shelf Stable Beverages,100,Shelf Stable Grocery,10,Center Store,1,Spaces Grocery,Brand,Placeholder Brand,Vendor,Placeholder Vendor
Note:
In A&IP CS, the Group (pgrp) dimension is used as a partition dimension by default. During implementation, it can be changed to Department (dept) or Division (dvsn).
File name: loc.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Name | Label | Hierarchy Type | Parent |
|---|---|---|---|
| STOR | Location | Main | None |
| DSTR | District | Main | STOR |
| REGN | Region | Main | DSTR |
| CHNL | Channel | Main | REGN |
| CHAN | Chain | Main | CHNL |
| COMP | Company | Main | CHAN |
| STRC | Store Cluster | Alternate | STOR |
| CHNC | Channel | Alternate | STRC |
| SAT1 | Store Attribute 1 | UDA | STOR |
| SAT2 | Store Attribute 2 | UDA | STOR |
| SAT3 | Store Attribute 3 | UDA | STOR |
| LOCT | Location Type | Alternate | STOR |
| PHWH | Physical Warehouse | Alternate | STOR |
| FFLT | Fulfillment Type | Alternate | STOR |
| TDAR | Trade Area | Alternate | STOR |
Example:
STOR,STOR_LABEL,DSTR,DSTR_LABEL,REGN,REGN_LABEL,CHNL,CHNL_LABEL,CHAN,CHAN_LABEL,COMP,COMP_LABEL,LOCT,LOCT_LABEL,PHWH,PHWH_LABEL,FFLT,FFLT_LABEL,STRC,STRC_LABEL,CHNC,CHNC_LABEL,TDAR,TDAR_LABEL 1000,1000 Charlotte,1070,North Carolina,170,Mid-Atlantic,1,Brick & Mortar,1,US,1,Retailer Ltd,1,Store,WH-1,Warehouse - US,1,Store Pick Up / Take With,1000,1000 Charlotte,1,Brick & Mortar,170,Mid-Atlantic1001,1001 Atlanta,1023,Georgia,400,South Atlantic,1,Brick & Mortar,1,US,1,Retailer Ltd,2,Kiosk,WH-1,Warehouse - US,2,Deliver/Install at Customer ,1001,1001 Atlanta,1,Brick & Mortar,400,South Atlantic 1002,1002 Dallas,1104,Texas,230,Gulf States,1,Brick & Mortar,1,US,1,Retailer Ltd,1,Store,WH-1,Warehouse - US,3,Home Delivery,1002,1002 Dallas,1,Brick & Mortar,230,Gulf States 1003,1003 Boston,1051,Massachusetts,200,New England,1,Brick & Mortar,1,US,1,Retailer Ltd,1,Store,WH-1,Warehouse - US,4,Fulfill DC Mail to Customer,1003,1003 Boston,1,Brick & Mortar,200,New England 1004,1004 New York,1066,New York,200,New England,1,Brick & Mortar,1,US,1,Retailer Ltd,1,Store,WH-1,Warehouse - US,5,Store Mail to Customer,1004,1004 New York,1,Brick & Mortar,200,New England
Note:
The Store Cluster dimension (STRC) is dynamically set within the workbook. However, while loading the hierarchy file, the strc position should be loaded with the same position ID as stor and with the label as '.'. The Location clustering solution needs unique identifiers for creating store clusters and will use the unique store identifier loaded at these positions as internal identifiers for creating new clusters within the solution. Trade Area (TDAR) is a placeholder dimension to be used by Grocery/Hardline retailers. If the retailer does not have trade area, they can load it with same data as Region (REGN).
The following additional hierarchy files are needed:
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Note: All the hierarchy files are needed for the Assortment & Item Planning for Fashion/Softlines Cloud Service even if a particular solution is not enabled. The hierarchy files specific to a particular solution which is not enabled should be present during domain installation with at least one dummy data for that hierarchy. This is to maintain the hierarchy order during patching, in case the solution was enabled in later stages. |
The assortment hierarchy represents the grouping of assortments for a time period. It can be a group of weeks, months, or quarters for which an assortment is planned. This hierarchy is DPM enabled, so users can create new assortments as needed in the Assortment Maintenance workbook and assign the product/calendar association for that assortment period in that workbook.
This hierarchy is intended to be customized for the individual retailer's needs.
| Name | Label | Hierarchy Type | Aggs |
|---|---|---|---|
| FLOW | Assortment | Main | None |
| BPER | Assortment Group | Main | FLOW |
| BPLB | Assortment Label | UDA | BPER |
| BCLS | Assortment Detail | UDA | BPER |
File name: asrt.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Assortment | This defines different flow in an assortment group such as flow1, flow2, and so on. |
| Assortment Group | This uniquely groups the assortments for a sub-category/time frame. |
| Assortment Label | Assortment Label as user defined attribute given to group similar assortments using Label. |
| Assortment Detail | Assortment Detail as user defined attribute given to group similar assortments. |
Example:
flow,flow_label,bper,bper_label ap01f1,Flow 1,ap01,Assort Period 01 ap02f1,Flow 1,ap02,Assort Period 02 ap03f1,Flow 1,ap03,Assort Period 03
The cluster hierarchy is an internal application-specific hierarchy to provide unique cluster IDs to be used during Location Clustering. It needs to be populated with unique cluster IDs (which need to be same as Store Identifiers) used in the Location hierarchy file. There is an OAT process available to synchronize this hierarchy whenever the location hierarchy file is loaded. It also can be scheduled to run on-demand, so retailers do not have to maintain this hierarchy.
| Name | Label | Hierarchy Type | Aggs |
|---|---|---|---|
| CLUS | Cluster | Main | None |
| CHN1 | Channel | Main | CLUS |
File name: clrh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Cluster | This is the unique Cluster identifiers from the Location hierarchy but with the label as '.'. The label is created dynamically and mapped to the unique ID present in this file through the Store Clustering process. The number of positions here represents the maximum pool of cluster positions available. |
| Channel | This is the same channel from the Location hierarchy. |
Example:
clus,clus_label,chn1,chn1_label 1000,.,1,Brick & Mortar 1001,.,1,Brick & Mortar 1002,.,1,Brick & Mortar 1003,.,1,Brick & Mortar 1004,.,1,Brick & Mortar 1005,.,1,Brick & Mortar 1006,.,1,Brick & Mortar 1007,.,1,Brick & Mortar 1008,.,1,Brick & Mortar
The cluster source hierarchy is an internal application-specific hierarchy. It should be the same as in the GA configuration and should not be changed. This hierarchy is used during wizard selection for Location Clustering to specify the source for clustering.
File name: csls.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Cluster Source | This is the unique Cluster Source identifier which can be Forecast, Plan or, Actual. |
Example:
csor,csor_label fcst,Forecast plan,Plan ty,Actual
The cluster version hierarchy is an internal application-specific hierarchy. It should be the same as in the GA configuration which contains five versions for customer-created cluster versions and one version for Loaded External Clusters. It is also DPM enabled so the user can add more cluster versions. This hierarchy is used in Location Clustering to approve different versions of location clusters.
Cluster Version 00 will be always used by batch to load the externally-imported clusters.
File name: cver.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Cluster Version | This is the unique Cluster Version identifier used during approval of a cluster. |
Example:
vers,vers_label 00,Loaded Cluster 01,Cluster Version 1 02,Cluster Version 2 03,Cluster Version 3 04,Cluster Version 4 05,Cluster Version 5
The clustering strategy hierarchy is an internal application-specific hierarchy. The retailer can customize this hierarchy during implementation and can use the GA dataset hierarchy as a reference. This hierarchy is used to define different clustering strategies to provide different weights for metrics used during location clustering such as, Sales R and Sales U. This hierarchy is DPM enabled, so users can add more strategies dynamically while assigning strategy weights in the Planning Administration workbook.
File name: pos2.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Clustering Strategy | This is the unique Clustering Strategy to use with different combinations of metric weights to create clusters. |
Example:
spl2,spl2_label 01,Sales R 02,Sales U 03,Sales AUR 04,GM R 05,GM R %
The currency hierarchy file is used to define unique currencies to be used in the application. The retailer can customize this hierarchy during implementation and can use the GA dataset hierarchy as a reference. If the Local Currency provision option is enabled during implementation, this hierarchy is loaded, and conversion rates are set in the Local Currency Setup workbook, users can review the plan data in more than one currency. For more information, see the Oracle Retail Assortment & Item Planning for Fashion/Softlines Cloud Service User Guide. This hierarchy is DPM enabled, so users can add more currencies dynamically in Local Currency Setup.
File name: curh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Currency | This is the unique currency. The plan data can be converted when the Local Currency provision option is enabled. |
Example:
curr,curr_label USD,USD EUR,EUR GBP,GBP BRL,BRL JPY,JPY DKK,DKK KRW,KRW
The curve points hierarchy file is used to define unique curve libraries that can be used to define different sales curve patterns to be used during seeding in Item Planning. The retailer can customize this hierarchy during implementation and can use the GA dataset hierarchy as a reference. This hierarchy is DPM enabled, so users can add more Curve Points dynamically in Curve Setup.
File name: curv.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Curve Library | This represents different curves that can be used to define different sales patterns. |
Example:
cnum,cnum_label C01,Curve 01 C02,Curve 02 C03,Curve 03 C04,Curve 04 C05,Curve 05 C06,Curve 06 C07,Curve 07 C08,Curve 08 C09,Curve 09 C10,Curve 10 C11,Curve 11 C12,Curve 12 C13,Curve 13 C14,Curve 14 C15,Curve 15 C16,Curve 16 C17,Curve 17 C18,Curve 18 C19,Curve 19 C20,Curve 20
Item Planning also has an additional internal hierarchy for custom messages used in the application called Custom Messages Hierarchy (CMSH). Custom messages used in the application are pre-configured in that hierarchy file and, unless a retailer needs different custom messages, that file does not need to be changed.
All custom messages used in Shared Services are loaded as hierarchy positions to enable the translation of custom messages to different languages. It is a single dimensional hierarchy with only one dimension, CMSD. By default, all positions are loaded in English during the hierarchy load. Custom message position names are hard coded in the application, so users should not change the position names. However, during implementation, custom messages can be changed if more descriptive messages are needed.
If a user wants to change the language of custom messages, the user needs to load the provided r_cmsdlabel.csv.ovr using the standard loadmeasure utility after removing languages not needed from that file.
File name: cmsh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Label | Hierarchy Type | Parent |
|---|---|---|---|
| CMSD | Custom Messages | Main | None |
Example:
cmsd,cmsd_label "ACSA01","Seed Assortment completed successfully." "ACSA02","Warning: Select Seed Source for Assortment from WP Seed Assortment." "ACSS01","Seed Sales completed successfully." "ACSS02","Warning: Select WP Seed Sales to execute the Seeding!" "ACCM01","Seed IPI Weights completed successfully."
The fixture hierarchy file is used to load the fixtures information available in Brick & Mortar locations.
This hierarchy is intended to be customized for the individual retailer's needs. This hierarchy is DPM enabled, so users can dynamically create fixture and formalize the same within the solution.
It requires two dimensions within the file, FIX (Fixture) and FIXG (Fixture Group) .
File name: fixt.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Fixture | Fixture type. |
| Fixture Group | Group of Fixtures based on Product association. |
Example:
fix,fix_label,fixg,fixg_label fx1,2-Tier Table A,mt1,Men's Tops fx2,2-way A,mt1,Men's Tops fx3,Rounder A,mt1,Men's Tops fx4,Table A,mt1,Men's Tops fx5,4-way A,mt1,Men's Tops
The location attributes hierarchy represents attributes associated with locations. These attributes are used to group locations during Location Clustering.
This hierarchy is intended to capture all location attributes for all locations. The attributes are then assigned to individual locations. This assignment is used when processing the dynamic rollups in location clustering.
This hierarchy is intended to be customized for the individual retailer's needs.
| Name | Label | Hierarchy Type | Aggs |
|---|---|---|---|
| SATV | Loc Attribute Value | Main | None |
| SATT | Loc Attribute | Main | SATV |
File name: satr.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Loc Attribute Value | The various values that an attribute might have. For example, the climate attribute might take the values cold, hot, or humid. |
| Loc Attribute | The name of a location attribute, such as climate, store volume, and so on. |
Note:
This file must include two attributes, grade and space, to be hard coded as in the GA dataset. Those two attributes are default attributes used in Location Clustering so they should be present in the location attribute file. The remaining attributes can be customized for the retailer needs.
Example:
satv,satv_label,satt,satt_label grade,Sales Perf Grp,grade,Sales Perf Grp space,Space,space,Space sfmt1,Downtown,sfmt,Store Format sfmt2,Strip Mall,sfmt,Store Format sfmt3,Standalone,sfmt,Store Format clmt1,Marine,clmt,Climate clmt2,Cold,clmt,Climate clmt3,Very Cold,clmt,Climate clmt4,Hot Dry,clmt,Climate clmt5,Mixed Dry,clmt,Climate clmt6,Mixed Humid,clmt,Climate clmt7,Hot Humid,clmt,Climate clmt8,Mediterranean,clmt,Climate clmt9,N/A,clmt,Climate
The location space hierarchy is an internal application-specific hierarchy to define different location space metrics available based on which location can be clustered. The retailer can customize this hierarchy during implementation and use the GA dataset hierarchy as a reference.
File name: sspc.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Space by Location | This is the unique location metrics that can be used to define a location such as Square Meter, Avg # of Fixtures, Fixture Capacity, and so on. |
Example:
sloc,sloc_label sqmetr,Square Meter sqfeet,Square Feet avgfix,Avg # of Fixtures avgfacings,Fixture Capacity
The markdown hierarchy is used to load the different permanent markdown events like Fall Clearance etc which can affect pricing of items which in turn affects the Clearance Sales of the Items used in Item Planning.
This hierarchy is intended to be customized for the individual customer's needs. This hierarchy is DPM enabled, so user can dynamically create promotions and can formalize the same within the solution.
It is a single dimension hierarchy. The only dimension is Markdown (MKDN).
File name: mkdh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Markdown | Markdown event. |
Example:
mkdn,mkdn_label 01,Valentine's 03,Friends and Family 05,Annual event 07,Ready for Summer
The performance group hierarchy is an internal application-specific hierarchy to define different performance grouping (grading) to use during Location Clustering. The retailer can customize this hierarchy during implementation and use the GA dataset hierarchy as a reference. This hierarchy is DPM enabled, so users can add more performance groups if needed during location clustering.
File name: pos1.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Performance Group | This is the unique performance grouping to use during clustering such as grades A, B, C, and so on. |
Example:
clst,clst_label 01,A 02,B 03,C 04,D 05,E
The product attributes hierarchy represents attributes associated with products. These attributes are used to group products within categories. This grouping is what consumer decision trees are built on and are used when showing dynamic rollups at item level.
This hierarchy is intended to capture all product attributes for all product types. The attributes are then assigned to individual products. This assignment is used when processing the dynamic rollups.
This hierarchy is intended to be customized for the individual retailer's needs.
| Name | Label | Hierarchy Type | Aggs |
|---|---|---|---|
| PATV | Prod Attribute Value | Main | None |
| PATT | Prod Attribute | Main | PATV |
File name: patr.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Prod Attribute Value | The various values that an attribute might have. For example, the package type attribute might take the values bag, box, or convenience. |
| Prod Attribute | The name of a product attribute, such as brand, family type, flavor, grain, package type, size, or temperature. |
Example:
patv,patv_label,patt,patt_label prodtype~basic,Basic,prodtype,Product Type prodtype~seasonal,Seasonal,prodtype,Product Type brand~dylanrose,Dylan Rose,brand,Brand brand~forevercali,Forever Cali,brand,Brand brand~legaci,Legaci,brand,Brand
|
Note: PATR is used as the Attribute Hierarchy to support the 2-dimensional Product attribute measure. For detailed information how this configuration is set up, refer to the Oracle Retail Predictive Application Server Cloud Edition Configuration Tools User Guide. |
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Note: A&IP FSL CS has separate workbook flows defined for Items classified as Basic or Seasonal based on the product attribute Product Type. It is recommended to use the Product Type attribute with Basic and Seasonal attribute values as provided in the Example for all the Items. The Basic type defines items whose selling pattern is the same across all assortment periods where the Seasonal items selling pattern varies by Season. |
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Note: A&IP uses the Nested Dynamic Rollup of Hierarchies option to review products based on the combination of various product attributes. If Enterprise Edition customers want to use the same features, customization of their configuration is needed.For more details about customizing the configuration to use Nested Dynamic Rollup, see the Oracle Retail Predictive Application Server Cloud Edition Configuration of Nested Dynamic Hierarchies Reference Paper. It is available on My Oracle Support in the Oracle Retail Predictive Application Server (RPAS) Cloud for Planning and Optimization / Supply Chain Cloud Services Documentation Library |
The promotion hierarchy is used to load the different promotion events such as Valentine's, Back to School, and so on, which can affect promotional pricing of items which in turn affects the Promotional Sales used in Item Planning.
This hierarchy is intended to be customized for the individual retailer's needs. This hierarchy is DPM enabled, so users can dynamically create promotions and formalize the same within the solution.
It is a single dimension hierarchy. The only dimension is Promotion (PROM).
File name: prmh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Promotion | Promotion event. |
Example:
prom,prom_label prm01,Valentine's prm02,Friends and Family prm03,Annual event prm04,Ready for Summer prm05,Summer celebration prm06,Luxury event prm07,Fall Promotion prm08,Pre-holiday prm09,Christmas Event prm10,Post-Christmas
The Size Hierarchy is the size hierarchy required in SPO (Size & Pack Optimization Solution). The Size Hierarchy file contains additional dimensions not currently required in Item Planning.
Item Planning only requires Size (SIZD) and Size Range (SRNG) information. The solution can handle loading both the SPO size hierarchy file and a custom size hierarchy file containing only the Size and Size Range dimensions.
File name: sizh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Size | Size. |
| Size Range | Size range. |
Example:
sizd,sizd_label,srng,srng_label 04_0t15,4 Master,0t15master,Master 0t15 06_0t15,6 Master,0t15master,Master 0t15 08_0t15,8 Master,0t15master,Master 0t15 10_0t15,10 Master,0t15master,Master 0t15
The VAT hierarchy file is used to define unique Value-Added Tax to be used in the application. The retailer can customize this hierarchy during implementation and can use the GA dataset hierarchy as a reference. Users can set more than one VAT group and VAT rates for them in the administration workbooks. Then, user have the options to choose any one VAT group to use within the solution. For more information, see the Oracle Retail Assortment & Item Planning for Fashion/Softlines Cloud Service User Guide. This hierarchy is DPM enabled, so users can add more currencies dynamically in VAT Setup workbook.
File name: vath.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| VAT Group | This is the unique VAT group used to define different VAT rates that can be used within the application. |
Example:
vatb,vatb_label "VAT00","Zero Rate" "VAT05","Reduced Rate" "VAT20","Standard Rate"
The Customer Segment hierarchy represents the different customer segments used by ORASE to load the input Assortment Elasticities and Attributes Weights for calculating Demand Transference data that will be interfaced at the Customer Segment level. Currently, A&IP FSL only expects data at the All Customer Segment level. So it needs only one valid position for All Customer Segments that is used by ORASE.
This hierarchy is intended to be customized for the individual retailer's needs.
| Name | Label | Hierarchy Type | Aggs |
|---|---|---|---|
| CSVD | Customer Segment Version | Main | None |
| CSGD | Customer Segment | Main | CSVD |
File name: csgh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Customer Seg Version | Version of Customer Segment. |
| Customer Segment | Customer Segment Identifier. |
Note:
The customer can use the GA customer segment hierarchy file unless the customer segment id in ORASE for All Customer Segment Position varies.
Example:
csvd,csvd_label,csgd,csgd_label 1v1,All Customer Segment - Version 1,1,All Customer Segment
The Level hierarchy is an internal application-specific hierarchy to define different levels of the Dynamic Hierarchy Rollup for Product and Location using its attributes in various workbook templates. It is hard-coded to have three levels in the A&IP CS solution.
File name: lvlh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Level | Attribute Roll-Up Level. |
Example:
lvld,lvld_label lvl1,Level 1 lvl2,Level 2 lvl3,Level 3
The RHS Product Hierarchy is a duplicate copy of the Product Hierarchy. It is defined as a Virtual Hierarchy using Platform features. Each dimension in the RHS Product Hierarchy is mapped to a corresponding dimension from the Product Hierarchy. It is used within A&IP to review Similarity Data and Demand Transference data across products in the Build Wedge process. The customer does not have to load any data for this hierarchy. Internally, the platform will create virtual positions for each position loaded into the Product Hierarchy.
A broad and detailed data set is required to use the capabilities of A&IP CS to its fullest. Some of the data required is relatively easy to obtain, for example, information about sales, cost, space, and the like.
To simplify the data integration, most of the measure files are configured to be loaded as one measure per file. Each measure's data must be present in a separate file and the file name must be the same as the measure name with the .csv.ovr extension. All files must be in csv format.
During the initial domain build, all data files marked as required are needed with historical data to build the domain.
Measures: drtyslsregu, drtyslsregr
Base Intersection: week/sku/stor
Data Type: real
File Name: drtyslsreg.csv.ovr
Example:
w04_2018,1234582,1003,72,490.25 w05_2018,1234582,1003,74,506.75 w06_2018,1234582,1003,96,656.55 w07_2018,1234582,1003,83,570.63 w13_2018,1234582,1003,94,641.20 w18_2018,1234582,1003,67,461.00
The following tables list the data files (measures) with different details such as Measure Label, Base Intersection, File Name, Data Type, Required or Optional, Load Frequency, Data Source, Solution Used, Load Data Set, and so on.
The following columns are available in the tables:
File Name
The input file name that the measure should be present in. If more than one measure has the same file name, it means the measures are to be present in the same input file and in the same order. Input files should be CSV files with extension .csv.ovr unless specified in Table 2-1. If File Name is not present, then file name is the same as the measure name.
Required or Optional
Required means the data is needed. Optional means that during data load and, if not loaded, certain functionality which uses those measures cannot be used. All administration measures are marked as Optional for data load, since those can be directly set in the Admin workbooks as well.
Load Frequency
This specifies the suggested frequency for the data load. It uses the following values:
W - Weekly.
A - Anytime as needed or when the values change in source system; it can be weekly, monthly, quarterly, or yearly.
Data Source
This specifies the typical data source to get that measure data:
RI - Oracle Retail Insights or equivalent Data Warehouse solutions
Admin - Data can be set by Administrator based on customer data referencing sample data in GA domain.
MFP - Oracle Retail Merchandise Financial Planning Cloud Service or equivalent.
ORASE - Oracle Retail Science. Those are the derived measure files extracted from ORASE integration files.
RMS - Oracle Retail Merchandising System or equivalent. Can be readily loaded from RMS or derived from data loaded from RMS.
3P - Third-party data aggregator such as Nielsen or Symphony IRI.
Load Data Set
All data loads in batch after initial domain build are done by scheduling batch tasks in Online Administration Tools. This information specifies which Load Set user needs to use to load that particular data file while scheduling the Online Administration Tool Tasks. For more details, see the Oracle Retail Assortment & Item Planning for Fashion/Softlines Cloud Service Administration Guide.
Table 2-1 Assortment & Item Planning for Fashion/Softlines Cloud Service Measure List - Details 1
| Measure Name | Measure Label | Base Intersection | File Name |
|---|---|---|---|
|
drtyslsregu |
Ty Sales Reg U |
week/sku/stor |
drtyslsreg |
|
drtyslsregr |
Ty Sales Reg R |
week/sku/stor |
drtyslsreg |
|
drtyslsprou |
Ty Sales Promo U |
week/sku/stor |
drtyslspro |
|
drtyslspror |
Ty Sales Promo R |
week/sku/stor |
drtyslspro |
|
drtyslsclru |
Ty Sales Clear U |
week/sku/stor |
drtyslsclr |
|
drtyslsclrr |
Ty Sales Clear R |
week/sku/stor |
drtyslsclr |
|
drtyslsc |
TY Sales C |
week/sku/stor |
|
|
drtyeopu |
TY EOP U |
week/sku/stor |
drtyeop |
|
drtyeopc |
TY EOP C |
week/sku/stor |
drtyeop |
|
drtyeopr |
TY EOP R |
week/sku/stor |
drtyeop |
|
drtyrcptu |
TY Receipts U |
week/sku/stor |
drtyrcpt |
|
drtyrcptc |
TY Receipts C |
week/sku/stor |
drtyrcpt |
|
drtyoou |
TY On Order U |
week/sku/stor |
drtyoo |
|
drtyooc |
TY On Order C |
week/sku/stor |
drtyoo |
|
drtytrafficu |
TY Traffic Count U |
week/sku/stor |
|
|
drtytransactu |
TY Transaction Count U |
week/sku/stor |
|
|
drtyrtnu |
TY Customer Returns U |
week/sku/stor |
drtyrtn |
|
drtyrtnr |
TY Customer Returns R |
week/sku/stor |
drtyrtn |
|
drtyrtnc |
TY Customer Returns C |
week/sku/stor |
drtyrtn |
|
addvvatvp |
VAT Rate |
week_vatb |
|
|
addvlocattt |
Location Attribute |
stor_satt |
|
|
addvlikeloct |
Like Location |
stor |
|
|
addvlocdesct |
Location Description |
stor |
|
|
addvlocstatb |
Location Active |
stor |
|
|
addvslscrvv |
Sales Curve % |
woyr_scls_chnc_cnum |
|
|
addvslsprcc |
Base Unit Cost |
sku_stor |
|
|
addvslsprcr |
Base Unit Price |
sku_stor |
|
|
addvslswgtu |
Sales Weight U |
spl2 |
addvstrcwgt |
|
addvslswgtr |
Sales Weight R |
spl2 |
addvstrcwgt |
|
addvslswgtar |
Sales Weight AUR |
spl2 |
addvstrcwgt |
|
addvgmwgtr |
Gross Margin Weight R |
spl2 |
addvstrcwgt |
|
addvgmwgtrp |
Gross Margin Weight R % |
spl2 |
addvstrcwgt |
|
addvspacev |
Location Space |
dept_stor_sloc |
|
|
addvprcelasvp |
Markdown Discount % |
scls_mkdn |
|
|
addvprcelaszp |
Markdown Sales Lift % (Override) |
scls_mkdn |
|
|
addvprcelasv |
Price Elasticity |
scls |
|
|
addvprmplnvp |
Promo Discount % |
scls_prom |
|
|
addvprmplnzp |
Promo Sales Lift % (Override) |
scls_prom |
|
|
mlcpsls1u |
MFP Loaded CP Sales Reg+Promo U |
week_scls_chnl |
mfp_mpcp |
|
mlcpsls1r |
MFP Loaded CP Sales Reg+Promo R |
week_scls_chnl |
mfp_mpcp |
|
mlcpsls2u |
MFP Loaded CP Sales Clr U |
week_scls_chnl |
mfp_mpcp |
|
mlcpsls2r |
MFP Loaded CP Sales Clr R |
week_scls_chnl |
mfp_mpcp |
|
mlcpslsc |
MFP Loaded CP Sales C |
week_scls_chnl |
mfp_mpcp |
|
mlcprcptu |
MFP Loaded CP Receipts U |
week_scls_chnl |
mfp_mpcp |
|
mlcprcptc |
MFP Loaded CP Receipts C |
week_scls_chnl |
mfp_mpcp |
|
mlcprcptr |
MFP Loaded CP Receipts R |
week_scls_chnl |
mfp_mpcp |
|
mlcpeopu |
MFP Loaded CP EOP U |
week_scls_chnl |
mfp_mpcp |
|
mlcpeopc |
MFP Loaded CP EOP C |
week_scls_chnl |
mfp_mpcp |
|
mlcpeopr |
MFP Loaded CP EOP R |
week_scls_chnl |
mfp_mpcp |
|
mlcprtn1u |
MFP Loaded CP Returns Reg+Promo U |
week_scls_chnl |
mfp_mpcp |
|
mlcprtn1r |
MFP Loaded CP Returns Reg+Promo R |
week_scls_chnl |
mfp_mpcp |
|
mlcprtn2u |
MFP Loaded CP Returns Reg+Promo U |
week_scls_chnl |
mfp_mpcp |
|
mlcprtn2r |
MFP Loaded CP Returns Reg+Promo R |
week_scls_chnl |
mfp_mpcp |
|
mlwpooadju |
MFP WP OO Adj U |
week_scls_chnl |
mfp_otb.rpl |
|
mlwpooadjc |
MFP WP OO Adj C |
week_scls_chnl |
mfp_otb.rpl |
|
mlwpotbu |
MFP WP OTB U |
week_scls_chnl |
mfp_otb.rpl |
|
mlwpotbc |
MFP WP OTB C |
week_scls_chnl |
mfp_otb.rpl |
|
drdvsrtd |
Loaded Cluster Start Date |
Scalar |
|
|
drdvendd |
Loaded Cluster End Date |
Scalar |
|
|
drdvstrclust |
Last Loaded Location Cluster |
clss_stor |
|
|
drdvstrclusl |
Last Loaded Location Cluster Label |
clss_stor |
|
|
adlylagwt |
LY Week Map |
week |
|
|
adwpsizeprfp |
Size Profiles |
scls_stor_sizd |
|
|
ietyslsszu |
Sales U by Size |
week_scls_stor_sizd |
|
|
addvfixmn |
Min Options per Fixture |
scls_fix |
|
|
addvfixmx |
Max Options per Fixture |
scls_fix |
|
|
addvfixct |
Fixture Count per Location |
scls_stor_fix |
|
|
addvecomb |
Direct location flag |
stor |
|
|
fctyslsu |
Fcst Sales U |
week_sku_stor |
|
|
addvskupimgt |
Style-Color Image |
skup |
|
|
addvpatvimgt |
Attribute Value Image |
patv |
|
|
addvcntryt |
Country/Region ID |
stor |
addvcntry |
|
addvcntryl |
Country/Region |
stor |
addvcntry |
|
drtyassrtelasv |
TY Assortment Elasticity |
scls_chnl_csgd |
drtyassrtelasv |
|
drtyattrwgtv |
TY Attribute Weight % |
scls_chnl_patt_csgd |
drtyattrwgtv |
|
drtyfuncfitb |
TY Functional Fit |
scls_chnl_patt_csgd |
drtyattrwgtv |
Table 2-2 Assortment & Item Planning for Fashion/Softlines Cloud Service Measure List - Details 2
| Measure Name | Data Type | Required or Optional? | Load Frequency | Data Source | Load Data Set |
|---|---|---|---|---|---|
|
drtyslsregu |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyslsregr |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyslsprou |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyslspror |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyslsclru |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyslsclrr |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyslsc |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyeopu |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyeopr |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyeopc |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyrcptu |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyrcptc |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyoou |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyooc |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtytrafficu |
real |
Required |
W |
RI |
Actuals |
|
drtytransactu |
real |
Required |
W |
RI |
Actuals |
|
drtyrtnu |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyrtnr |
real |
Required |
W |
RMS/RI |
Actuals |
|
drtyrtnc |
real |
Required |
W |
RMS/RI |
Actuals |
|
addvlcratet |
string |
Optional |
W |
RMS/Admin |
Admin Data |
|
addvlcratex |
real |
Optional |
W |
Admin |
Admin Data |
|
addvvatvp |
real |
Optional |
W |
Admin |
Admin Data |
|
addvlocattt |
string |
Optional |
W |
Admin |
Admin Data |
|
addvprdattt |
string |
Optional |
W |
RMS/Admin |
Admin Data |
|
addvprdattb |
Boolean |
Optional |
W |
Admin |
Admin Data |
|
addvlikeloct |
string |
Optional |
W |
Admin |
Admin Data |
|
addvlocdesct |
string |
Optional |
W |
Admin |
Admin Data |
|
addvlocstatb |
Boolean |
Optional |
W |
Admin |
Admin Data |
|
addvslscrvv |
real |
Optional |
W |
Admin |
Admin Data |
|
addvslsprcc |
real |
Optional |
W |
RMS/Admin |
Admin Data |
|
addvslsprcr |
real |
Optional |
W |
RMS/Admin |
Admin Data |
|
addvslswgtu |
real |
Optional |
W |
Admin |
Admin Data |
|
addvslswgtr |
real |
Optional |
W |
Admin |
Admin Data |
|
addvslswgtar |
real |
Optional |
W |
Admin |
Admin Data |
|
addvgmwgtr |
real |
Optional |
W |
Admin |
Admin Data |
|
addvgmwgtrp |
real |
Optional |
W |
Admin |
Admin Data |
|
addvspacev |
real |
Optional |
W |
Admin |
Admin Data |
|
addvprcelasvp |
real |
Optional |
W |
Admin |
Admin Data |
|
addvprcelaszp |
real |
Optional |
W |
Admin |
Admin Data |
|
addvprcelasv |
real |
Optional |
W |
Admin |
Admin Data |
|
addvprmplnvp |
real |
Optional |
W |
Admin |
Admin Data |
|
addvprmplnzp |
real |
Optional |
W |
Admin |
Admin Data |
|
mlcpsls1u |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcpsls1r |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcpsls2u |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcpsls2r |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcpslsc |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcprcptu |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcprcptc |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcprcptr |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcpeopu |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcpeopc |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcpeopr |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcprtn1u |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcprtn1r |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcprtn2u |
real |
Required |
W |
MFP |
MFP Plan |
|
mlcprtn2r |
real |
Required |
W |
MFP |
MFP Plan |
|
mlwpooadju |
real |
Required |
W |
MFP |
MFP Plan |
|
mlwpooadjc |
real |
Required |
W |
MFP |
MFP Plan |
|
mlwpotbu |
real |
Required |
W |
MFP |
MFP Plan |
|
mlwpotbc |
real |
Required |
W |
MFP |
MFP Plan |
|
addvprdattt |
string |
Required |
W/A |
ORASE/RMS |
Product Attributes |
|
addvprdattb |
Boolean |
Required |
W/A |
ORASE/RMS |
Product Attributes |
|
drdvsrtd |
date |
Optional |
W/A |
ORASE |
Location Clusters |
|
drdvendd |
date |
Optional |
W/A |
ORASE |
Location Clusters |
|
drdvstrclust |
string |
Optional |
W/A |
ORASE |
Location Clusters |
|
drdvstrclusl |
string |
Optional |
W/A |
ORASE |
Location Clusters |
|
addvlcratet |
string |
Optional |
W |
Admin |
Local Currency |
|
addvlcratex |
real |
Optional |
W |
RMS/Admin |
Local Currency |
|
adlylagwt |
string |
Required |
A |
Admin |
LY Mapping |
|
adwpsizeprfp |
real |
Optional |
A |
Admin |
Admin/SPO |
|
ietyslsszu |
real |
Optional |
A |
Admin |
Admin |
|
addvfixmn |
real |
Optional |
A |
Admin |
Admin |
|
addvfixmx |
real |
Optional |
A |
Admin |
Admin |
|
addvfixct |
real |
Optional |
A |
Admin |
Admin |
|
addvecomb |
real |
Optional |
A |
Admin |
Admin |
|
fctyslsu |
real |
Optional |
W/A |
RDF |
RDF Forecast |
|
addvskupimgt |
string |
Required |
A |
Admin |
Admin |
|
addvpatvimgt |
string |
Required |
A |
Admin |
Admin |
|
addvcntryt |
string |
Required |
A |
Admin |
Admin |
|
addvcntryl |
string |
Required |
A |
Admin |
Admin |
|
drtyassrtelasv |
real |
Optional |
A |
ORASE |
ORASE DT Data |
|
drtyattrwgtv |
real |
Optional |
A |
ORASE |
ORASE DT Data |
|
drtyfuncfitb |
Boolean |
Optional |
A |
ORASE |
ORASE DT Data |
It is recommended that you have at least one full year of historical data to create in Assortment & Item Planning for Fashion/Softlines Cloud Service. Less data can be used, but the more data that is available, the more statistical significance can be given to the plan data.
More than one year of data is good to produce an optimal forecast, if customer wants to use embedded forecast in Assortment & Item Planning for Fashion/Softlines Cloud Service. Adding more than one year of history will increase domain size requirements.
Data is loaded into Assortment & Item Planning for Fashion/Softlines Cloud Service using the Online Administration Tools, which in turn use standard RPAS utilities. For more information on loading and extracting data using Online Administration Tools, see the Oracle Retail Assortment & Item Planning for Fashion/Softlines Cloud Service Administration Guide.
Assortment & Item Planning Cloud Service is pre-configured to provide the item level image view in the templates. The measure set up as the item level image attribute is addvskupimgt with the base intersection of Style/Color and product attributes images to addvpatvimgt.
The Content Server exposes the client's image files placed into a particular directory as HTTP URLs. The images available in http://{content server url}/imgfetch/{sub directory if defined}/<image-file-name> must be defined in the load file in xml format.
Sample file for addvskupimgt.csv.ovr:
1234582,"<image id=""main"" label=""Front View""><url size=""thumb"">http://<server>:<port>/<image_path>/sku_10000019_main_thumb.jpg</url></image>" 1234600,"<image id=""main"" label=""Front View""><url size=""thumb"">http://<server>:<port>/<image_path>/sku_10000053_main_thumb.jpg</url></image>"
The first field represents the Style Color ID followed by the required image location. At a minimum, a "thumb" size image file must be loaded to show in the pivot table. However, both the "thumb" and "full" size images can be loaded. For example:
10000010,"<image id=""main"" label=""Front View""><url size=""thumb"">http:// <server>:<port>/<image_path>/sku_10000010_main_thumb.jpg</url><url size=""full"">http://<server>:<port>/<image_path>/sku_10000010_main_full.jpg</url></image>
Assortment & Item Planning Cloud Service supports the flat file integration of hierarchy and data files from source systems. Assortment & Item Planning Cloud Service supports in-build integration with ORASE, MFP Cloud Service, RDF Cloud Service, and RMF CS.
Assortment & Item Planning Cloud Service also supports in-build integration using Bulk Data Integration (BDI) and Planning Data Storage (PDS) to integrate with RMF CS. For more details, see Appendix F, "Appendix: Using BDI and PDS".
Assortment & Item Planning Cloud Service integrates with MFP Cloud Service for Merchandising Plan Data to use them as Financial Target while creating assortments, RDF Cloud Service to get Forecast Data, and ORASE for Advanced Location Cluster information. For more details on integration with MFP CS, RDF CS, and ORASE, see Appendix A, "Appendix: Integration with MFP Cloud Service, RDF Cloud Service, and ORASE".
Assortment & Item Planning for Fashion/Softlines Cloud Service can be integrated with RMF CS to get the foundation data and actuals data. For more details, see Appendix C, "Appendix: RMF CS Integration".
Assortment & Item Planning for Fashion/Softlines Cloud Service provides some standard exports that can be used by external systems that need Item Plan Level Data. For details about the standard exports from Assortment & Item Planning for Fashion/Softlines Cloud Service, Appendix B, "Appendix: Standard Exports".
Retailers must extract and provide the hierarchy files and data files from their respective source systems as flat files in the required format and upload them to the Oracle Cloud SFTP server. The automated process send those files over to the RPAS DB Server and from there the files can be accessed by batch process triggered using the Online Administration Tools. In the same way, exported files in CSV format from the solution are pushed back to the Oracle Cloud SFTP server and from there retailers can download the extracted files. The retailer must integrate it with any other system that requires extracted plan data from Assortment & Item Planning for Fashion/Softlines Cloud Service.
To define workbook template security, the system administrator grants individual users, or user groups, access to specific workbook templates. Granting access to workbook templates provides users with the ability to create, modify, save, and commit workbooks for the assigned workbook templates. Users are typically assigned to groups based on their user application (or solution) role. Users in the same group can be given access to workbook templates that belong to that group alone. Users can be assigned to more than one group and granted workbook template access without belonging to the user group that typically uses a specific workbook template. Workbook access is either denied, read-only, or full access. Read-only access allows a user to create a workbook for the template, but the user is not able to edit any values or commit the workbook. The read-only workbook can be refreshed.
The following table provides guidance regarding which Assortment & Item Planning for Fashion/Softlines Cloud Service users must have access to each of the workbooks.
Table 2-3 User's Access Permission for A&IP CS Workbooks
| Workbook | Solution | User Roles |
|---|---|---|
|
Planning Administration |
Planning Administrator |
|
|
Currency Administration |
Planning Administrator |
|
|
Validate Loaded Data |
Planning Administrator |
|
|
Placeholder Maintenance |
Planner, Planning Administrator |
|
|
Location Clustering |
Planner, Planning Administrator |
|
|
Assortment Period Maintenance |
Planner, Planning Administrator |
|
|
Curve Maintenance |
Planner, Planning Administrator |
|
|
Create Assortment |
APFA |
Planner |
|
Build Wedge |
APFA |
Planner |
|
Item Planning Administration |
IPCS |
Planning Administrator |
|
In-Season Planning |
IPCS |
Planner |
|
Item Planning |
IPCS |
Planner |
|
Item Planning @ Store |
IPCS |
Planner |
|
Assortment Strategy |
IPCS |
Planner |
For more information on security, see the Oracle Retail Predictive Application Server Cloud Edition Administration Guide. For more information on data security in a cloud environment, see the Hosting Policy documents for the cloud solution.
Internationalization is the process of creating software that can be translated more easily. Changes to the code are not specific to any particular market.
Oracle Retail applications have been internationalized to support multiple languages.
The RPAS platform supports associated solution extensions and solution templates.
A solution extension includes a collection of code and generally available configurations. Typically, solution extensions are implemented by a retailer with minimal configuration.
A solution template does not include code. A solution template is most typically implemented as a retailer configuration.
Oracle Retail releases the translations of the RPAS server and client, as well as strings from the solution extensions.
Translations of the solution templates are released. All templates have the ability to support multi-byte characters.
For more information on internationalization, see the Oracle Retail Predictive Application Server Cloud Edition Administration Guide.
Translations are available for Assortment & Item Planning for Fashion/Softlines Cloud Service for the following languages:
Chinese (Simplified)
Chinese (Traditional)
Croatian
Dutch
French
German
Greek
Hungarian
Italian
Japanese
Korean
Polish
Portuguese (Brazilian)
Russian
Spanish
Swedish
Turkish
|
Note: For information about adding languages for the first time or for translation information in general, see the Oracle Retail Predictive Application Server Cloud Edition Administration Guide. |
Batch scripts are lists of commands or jobs executed without human intervention. A batch window is the time frame in which the batch process must run. It is the upper limit on how long the batch can take. Batch scripts are used for loading foundation data received from a merchandising system, importing and exporting data, and generating targets. The retailer must decide the best time for running batch scripts within the available batch window.
How often to upload updated sales and inventory data and how often to recreate targets must be determined.
You must consider at what interval to load the latest sales and inventory data. A weekly load of transactional type data is supported, since the base intersection is at week. It is recommended that the information transactional system, such as RMS, be loaded daily.
Product availability and seasonal changes can be reasons for recalculating the targets. This can also be triggered by the addition of new products and availability of substantial new sales and inventory history.
The recommended batch schedule for Assortment & Item Planning for Fashion/Softlines Cloud Service is to load historical and actual data on a weekly basis. All hierarchy changes can be loaded on a weekly or monthly basis.
In Assortment & Item Planning Cloud Service, batch tasks can be controlled by a system administrator by using the Online Administration Tools. Those tasks, in turn, call the batch scripts with preset parameters to perform the batch tasks. For more information on the Online Administration Tool tasks, see the Oracle Retail Assortment & Item Planning for Fashion/Softlines Cloud Service Administration Guide.
For more details about the list of batch control files, the batch process using them, and details about updating them, see the Enterprise Edition Batch framework in the Oracle Retail Predictive Application Server Cloud Edition Implementation Guide.
The customer can also use JOS/POM if implemented to schedule pre-configured daily and weekly batch tasks in A&IP CS together with other integrated applications. Those tasks scheduled using JOS/POM in turn call the same Configured batch tasks under the Online Administration Tool tasks. For more details about scheduling of tasks using JOS/POM, see the Oracle Retail Predictive Application Server Cloud Service Administration Guide. For details about application-specific tasks, see Appendix G, "Appendix: Batch Schedule in JOS/POM".
