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2 Implementation Considerations
The following information must be considered before configuring Assortment Planning Cloud Service:
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Configuration Considerations
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Data
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Integration
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User Roles and Security
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Internationalization
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Batch Process and Scheduling
Configuration Considerations
Assortment Planning Cloud Service (APCS) contains the solutions APFA (Assortment Planning) and IPCS (Item Planning). During implementation, the user has option to extend the application configuration using Extensibility guidelines. For more details about the extensibility of the configuration, see the Oracle Retail Analytics and Planning Implementation Guide .
Data
APCS 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 Planning Cloud Service, only hierarchy files and data files specific for those solutions are needed and those are specified in the subsequent sections:
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Hierarchy Files
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Data Files
Hierarchy Files
This is the foundation data to build any RPASCE solution. Assortment Planning Cloud Service requires the base foundation hierarchy files, such as Calendar, Product, and Location; also, additional sets of hierarchy files specific to different solutions used in APCS. By default, APCS can get the base foundation hierarchy details as part of RAP integration. The customer only needs to upload hierarchy files which are not part of RAP integration. To load the hierarchy files during the batch process, the customer can upload their hierarchy files as individual files into Object Storage under the input directory or zip them up as hiers.zip and upload the file to the same input directory in Object Storage. All hierarchy files should have at least one valid entry, otherwise the customer will face issues in the application if the hierarchy is used in the workbook templates and if it is empty.
Note
In order to implement Planning cloud services on Retail Analytics and Planning (RAP), the customer should ensure their foundation data, that is, Product and Organization hierarchies align with Oracle Retail Merchandising Foundation Cloud Service (RMFCS) so that the foundation and transactional data can be used by all services in RAP. They can have more alternate dimensions than available in RMFCS if needed for their Planning Cloud Services.
Customers can use the flex fields available in RAP Foundation files to interface this data. Also, if multiple Planning cloud services such as MFPCS, APCS, and IPOCSDemand Forecasting are residing in the same PDS, then hierarchies which are common across them should have the same dimension names so they can share the same data interfaced from RAP. However, additional non-shared dimensions can be present in each service, but shared dimensions should have the same name.
Note
Hierarchy files should always contain header information and columns in any order but the file name must be in the format
For information on the base hierarchy files that can be readily interfaced in RAP integration, see the following sections:
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Calendar Hierarchy File
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Product Hierarchy File
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Location Hierarchy File
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Cluster Hierarchy File
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Product Attributes Hierarchy File
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Location Attributes Hierarchy File
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Size Hierarchy File
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Customer Segment Hierarchy File
Calendar Hierarchy File
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 |
| Name | Label | Hierarchy Type | Parent |
|---|---|---|---|
| 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 |
Example:
day,day_label,week,week_label,mnth,mnth_label,qrtr,qrtr_label,half,half_label,year,year_l
abel,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
Note:
Though RPASCE supports a string for position IDs, for calendar position week, it is preferred to use the date format YYYYMMDD. If the customer uses RAP integration to get the data, the day and week position IDs at which the data needs to be stored are in the YYYYMMDD format.
Note:
For non-template customers, it is also recommended to align with the GA Calendar Hierarchy structure for the dimension names for day, week, mnth, qrtr, half, and year so that they can upgrade/implement other GA solutions in a multi-app environment. They can use different labels. The lowest dimension should be day and it is mandatory. The rest of the dimensions are optional and their equivalents should be named accordingly.
Product Hierarchy File
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 |
| Name | Label | Hierarchy Type | Parent |
|---|---|---|---|
| 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_l
abel,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:
For non-template customers, it is also recommended to align with the GA Product Hierarchy structure for the dimension names for sku, skup, skug, scls, clss, dept, pgrp, dvsn, and cmpp so that they can upgrade/implement other GA solutions in a multi-app environment. They can use different labels. The lowest dimension should be sku and it is mandatory. The rest of the dimensions are optional and their equivalents should be named accordingly.
Location Hierarchy File
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 | Store | Main | None |
| DSTR | District | Main | STOR |
| REGN | Region | Main | DSTR |
| CHNL | Area | Main | REGN |
| CHAN | Chain | Main | CHNL |
| COMP | Company | Main | CHAN |
| Name | Label | Hierarchy Type | Parent |
|---|---|---|---|
| SSTR | Space Cluster | Alternate | STOR |
| STRC | Store Cluster | Alternate | SSTR |
| STC1 | Cluster | Alternate | STRC |
| CHNC | Channel | Alternate | STC1 |
| CCTY | Country | Alternate | CHNC |
| LOCT | Location Type | Alternate | STOR |
| PHWH | Physical Warehouse | Alternate | STOR |
| FFLT | Fulfillment Type | 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,SSTR,SSTR_LABEL,STRC,STRC_LABEL,ST
C1,STC1_LABEL,CHNC,CHNC_LABEL,CCTY,CCTY_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,Brick & Mortar,1000,1000
Charlotte,1000,1000 Charlotte,1000,1000 Charlotte,1,Brick & Mortar,1,USA
1001,1001 Atlanta,1023,Georgia,400,South Atlantic,1,Brick & Mortar,1,US,1,Retailer
Ltd,2,Kiosk,WH-1,Warehouse - US,1,Brick & Mortar,1001,1001 Atlanta,1001,1001
Atlanta,1001,1001 Atlanta,1,Brick & Mortar,1,USA
1002,1002 Dallas,1104,Texas,230,Gulf States,1,Brick & Mortar,1,US,1,Retailer
Ltd,1,Store,WH-1,Warehouse - US,1,Brick & Mortar,1002,1002 Dallas,1002,1002
Dallas,1002,1002 Dallas,1,Brick & Mortar,1,USA
1003,1003 Boston,1051,Massachusetts,200,New England,1,Brick & Mortar,1,US,1,Retailer
Ltd,1,Store,WH-1,Warehouse - US,1,Brick & Mortar,1003,1003 Boston,1003,1003
Boston,1003,1003 Boston,1,Brick & Mortar,1,USA
1004,1004 New York,1066,New York,200,New England,1,Brick & Mortar,1,US,1,Retailer
Ltd,1,Store,WH-1,Warehouse - US,1,Brick & Mortar,1004,1004 New York,1004,1004 New
York,1004,1004 New York,1,Brick & Mortar,1,USA
Note:
The Space Cluster (SSTR), Store Cluster (STRC), and Cluster (STC1) dimensions are dynamically set within the workbooks. However, while loading the hierarchy file, those positions should be loaded with the same position ID as stor. 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.
Note:
The Planning Location Hierarchy is aligned with the Merchandising Organization Hierarchy for RAP integration, so Region aggregates to Area as in the Merchandising Hierarchy. Channel is an attribute in RMFCS and is not part of the Organization Hierarchy. RMFCS integration to RAP will send the Planning Channel and Planning Country and that will be mapped to the Channel (CHNC) and Country (CCTY) dimension. Store Clusters defined within APCS or interfaced should be below this Channel level.
Note:
If the customer has warehouses holding inventory and receipts data, the Virtual Warehouse locations for each Channel can be loaded as locations with the Location type as ‘W’. The batch process allows splitting of Warehouse Inventory to locations to include in the Location Inventory for Location Planning.
Note:
For the non-template customer, it is also recommended to align with the GA Location Hierarchy structure for the dimension names for stor, dstr, regn, chnl, chan, comp, strc, chnc, and ccty so that they can upgrade/implement other GA solutions in a multi-app environment. They can use different labels. The lowest dimension should be stor and it is mandatory. The rest of the dimensions are optional and their equivalents should be named accordingly.
Cluster Hierarchy File
The cluster hierarchy is an internal application-specific hierarchy used 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 can also 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 | Cluster 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. |
| Cluster Channel | Channel below which the Clusters will be created. This Channel should have the same CHNC (Channel) values in 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
Product Attributes Hierarchy File
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 the 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_llc,LLC,prodtype,Product Type
prodtype_slc,SLC,prodtype,Product Type
prodtype_z9999,Z_Other,prodtype,Product Type
brand_dylanrose,Dylan Rose,brand,Brand
brand_forevercali,Forever Cali,brand,Brand
brand_legaci,Legaci,brand,Brand
brand_z9999,Z_Other,brand,Brand
Note
PATR is used as the Attribute Hierarchy to support the 2-dimensional Product attribute measure. For detailed information on how this configuration is set up, see the Oracle Retail Predictive Application Server Cloud Edition Configuration Tools User Guide .
Note
APCS has separate workbook flows defined for Items classified as LLC or SLC based on the product attribute Product Type. It is recommended to use the Product Type attribute with LLC and SLC attribute values for all the Items. The LLC type defines items whose selling pattern is the same across all assortment periods where the SLC items selling pattern varies by Season. The customer can assign any UDA to identify the SLC/LLC items in RMFCS and later can assign that attribute and attribute value in the Planning Admin → Batch Setup view for the Item Attribute for Basic Items and Product Attribute Value for SLC/LLC Item measures.
Note
APCS uses the Nested Dynamic Rollup of Hierarchies option to review products based on the combination of various product attributes. If non-template 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 Doc ID: 2492295.1.
Note
APCS GA uses the Z_Other attribute values for all the attributes with the hard-coded value as z9999. This specific Attribute is used to dynamically group the Attributes with sales below a preset threshold to focus more on critical attribute values for assortments, so the customer needs to include that attribute value if they are loading attributes using a flat file. If they are importing attributes from RAP, then they need to enable the Integration variable PATR_OTHER to Y in order to include the hard-coded attribute value as part of Product Attribute Hierarchy Import.
Location Attributes Hierarchy File
The Location Attributes hierarchy represents attributes associated with locations. These attributes are used to group locations to plan in the 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 the location planning templates.
| 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.
| Name | 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 hierarchy data needs hard-coded values of two attributes z_grade for Sales Perf Group and z_space for Space Group with hard-coded Loc Attribute values as shown in the Example below that is used by AP Location Clustering, rest of the attributes can be customer data.
Note: This hierarchy data can be imported as part of RAP integration from RMFCS or the customer can also directly provide the location attribute hierarchy with at least one valid data. If the customer is importing Location Attributes data for AP GA, then they need to set to the Integration Environment variable ‘SATR_GROUP’ to ‘Y’ in order to include hard-coded Location Attributes used by AP GA during import.
Example:
satv,satv_label,satt,satt_label
G_01,A,z_grade,Sales Perf Group
G_02,B,z_grade,Sales Perf Group
G_03,C,z_grade,Sales Perf Group
G_04,D,z_grade,Sales Perf Group
G_05,E,z_grade,Sales Perf Group
S_01,A,z_space,Space Group
S_02,B,z_space,Space Group
S_03,C,z_space,Space Group
S_04,D,z_space,Space Group
S_05,E,z_space,Space Group
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
Size Hierarchy File
The Size hierarchy represents different sizes associated with products. Also, different sizes are grouped by size range. Different product types by Class/Sub-class can be allowed to use different size ranges within the solution.
AP uses this size hierarchy to further plan buy quantity and receipts by different sizes for newly planned Style/Colors based on the Size Profiles either pre-defined by an Administrator or loaded from the Size Profile Optimization module. AP GA currently does not use the Size Hierarchy but this hierarchy is kept for use of non-template customers to customize and use the RAP Interfaces available if they are using the same.
This hierarchy is intended to be customized for the individual retailer’s needs.
| Name | Label | Hierarchy Type | Aggs |
|---|---|---|---|
| SIZD | Size | Main | None |
| SRNG | Size Range | Main | SIZD |
File name: sizh.hdr.csv.dat
File format: comma-separated values file
The following table describes the fields in this file.
| Field | Description |
|---|---|
| Size | Different unique sizes such ase S, XS, M, L, XL |
| Size Range | Different grouping of Size Ranges such as Men’s Shoes, Men’s Shirt |
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
10_5_mensshoes,10.5 Master,mensshoesmaster,Master Men's Shoes
10_5_womensshoes,10.5 Master,womensshoesmaster,Master Women's Shoes
10_mensshoes,10 Master,mensshoesmaster,Master Men's Shoes
Notes:
In RAP Integration with AIF, AP can get the Size hierarchy and Size Profiles from AIF or if the customer is not planning to use the SPO, they can also load the Size Hierarchy and load and use the Admin level Size Profiles.
Customer Segment Hierarchy File
AP currently uses Customer Segments only to interface DT data available from AIF which is available at the Customer Segment level. Currently, this file needs to be loaded manually by customers using the same customer segments available in AIF once or whenever any changes to Customer Segments happened in AIF.
AP GA currently does not use the Customer Segment Hierarchy but this hierarchy is kept for use of non-template customers to customize and use the RAP Interfaces available if they are using the same.
| Name | Label | Hierarchy Type | Aggs |
|---|---|---|---|
| CSVD | 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 |
|---|---|
| Version | This is the version of Customer Segment. If there are no versions of customer |
| segment, this can be mapped to the same value as Customer Segment. | |
| Customer Segment | Customer Segment unique id used in AIF. |
Example:
csvd,csvd_label,csgd,csgd_label
5100,All Customers,5100,All Customers
5101,Value Seekers,5101,Value Seekers
5102,Top Spenders,5102,Top Spenders
5103,Seasonal Shopper,5103,Seasonal Shopper
5104,Loyal Customers,5104,Loyal Customers
Note:
In RAP Integration with AIF, AP can get the Customer Segment Hierarchy from AIF.
Additional Specific Hierarchy Files
The following additional hierarchy files are also needed. They are not part of RAP integration, so the customer needs to explicitly provide the input files:
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Assortment Hierarchy File
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Cluster Source Hierarchy File
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Cluster Version Hierarchy File
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Clustering Strategy Hierarchy File
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Curve Points Hierarchy File
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Custom Messages Hierarchy File
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Location Space Hierarchy File
-
Performance Group Hierarchy File
-
Level Hierarchy File
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RHS Product Hierarchy File
Assortment Hierarchy File
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
Cluster Source Hierarchy File
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
Cluster Version Hierarchy File
The cluster version hierarchy is an internal application-specific hierarchy. It should be the same as in the GA configuration which contains 20 versions with 00 to 09 reserved for customercreated cluster versions within the applications and versions 10 to 20 for Loaded Clusters of different date ranges from external systems or from Advanced Clusters from AI Foundation. This hierarchy is used in Location Clustering to approve different versions of location 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,vlbl,vlbl_label
01,Version 01,01,Version 01
02,Version 02,02,Version 02
03,Version 03,03,Version 03
04,Version 04,04,Version 04
05,Version 05,05,Version 05
06,Version 06,06,Version 06
07,Version 07,07,Version 07
08,Version 08,08,Version 08
09,Version 09,09,Version 09
10,Version 10,10,Version 10
11,Version 11,11,Version 11
12,Version 12,12,Version 12
13,Version 13,13,Version 13
14,Version 14,14,Version 14
15,Version 15,15,Version 15
16,Version 16,16,Version 16
17,Version 17,17,Version 17
18,Version 18,18,Version 18
19,Version 19,19,Version 19
20,Version 20,20,Version 20
Clustering Strategy Hierarchy File
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 %
Curve Points Hierarchy File
The Curve Points hierarchy is an internal application-specific hierarchy. It should be the same as in the GA configuration, that can be used to define different sales curve patterns to be used during seeding in Item Planning.
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
bc01,1. Bell Curve
tc01,2. Trending Curve
sc01,3. Slow Intro Curve
mp01,4. MFP Curve
ly01,5. Last Year Curve
c01,User Curve 01
c02,User Curve 02
c03,User Curve 03
c04,User Curve 04
c05,User Curve 05
c06,User Curve 06
c07,User Curve 07
c08,User Curve 08
c09,User Curve 09
c10,User Curve 10
Custom Messages Hierarchy File
AP Cloud Service 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 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.
| Name | Label | Hierarchy Type | Parent |
|---|---|---|---|
| CMSD | 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."
Location Space Hierarchy File
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
Performance Group Hierarchy File
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
Level Hierarchy File
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 APCS solution.
File name: lvlh.hdr.csv.dat
File format: comma-separated values file
The following table describes the field in this file.
| Name | Description |
|---|---|
| Level | Attribute Rollup Level. |
Example:
lvld,lvld_label
lvl1,Level 1
lvl2,Level 2
lvl3,Level 3
RHS Product Hierarchy File
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 AP 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.
Data Files
A broad and detailed data set is required to use the capabilities of APCS to its fullest.
The following tables describe the data files (measures) needed, load intersection, data type, file name, required/optional, and expected data source details. In the Data Source column, RI means any Data Warehouse or equivalent/RMS and those data are readily available from RAP integration, RSP means data from AI Foundation which is also available as part of RAP integration, Internal means any retailer internal system or the data using data files, and Admin means either data can be directly set up by an administration user or can be loaded as files.
Load Data Set
All data loads in batch after the initial domain build are done by scheduling batch tasks in Online Administration Tools. This information specifies which Load Set the 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 Planning Cloud Service Administration Guide .
Table 2-1 Assortment Planning Cloud Service Measure List - Details 1
| Measure Name | Measure Label | Data Type | **Load Intersection ** | File Name | Agg Type | Required or Optional? | Data Source |
|---|---|---|---|---|---|---|---|
| drtyeop1c | Ty EOP Reg+Promo C | real | week_sku_stor | eopx.csv.ovr | pet | Required | RI |
| drtyeop1r | Ty EOP Reg+Promo R | real | week_sku_stor | eopx.csv.ovr | pet | Required | RI |
| drtyeop1u | Ty EOP Reg+Promo U | real | week_sku_stor | eopx.csv.ovr | pet | Required | RI |
| drtyeop2c | Ty EOP Clr C | real | week_sku_stor | eopx.csv.ovr | pet | Required | RI |
| drtyeop2r | Ty EOP Clr R | real | week_sku_stor | eopx.csv.ovr | pet | Required | RI |
| drtyeop2u | Ty EOP Clr U | real | week_sku_stor | eopx.csv.ovr | pet | Required | RI |
Table 2-1 (Cont.) Assortment Planning Cloud Service Measure List - Details 1
| Measure Name | Measure Label | Data Type | Load Intersectio | n File Name | Agg Type | Required or Optional? | Data Source |
|---|---|---|---|---|---|---|---|
| drtynslsclrc | Ty Net Sales Clear C | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtynslsclrr | Ty Net Sales Clear R | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtynslsclru | Ty Net Sales Clear U | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtynslsproc | Ty Net Sales Promo C | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtynslspror | Ty Net Sales Promo R | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtynslsprou | Ty Net Sales Promo U | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtynslsregc | Ty Net Sales Reg C | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtynslsregr | Ty Net Sales Reg R | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtynslsregu | Ty Net Sales Reg U | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtyrtnclrc | Ty Return Clear C | real | week_sku_stor | rtn.csv.ovr | total | Required | RI |
| drtyrtnclrr | Ty Return Clear R | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtyrtnclru | Ty Return Clear U | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtyrtnproc | Ty Return Promo C | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtyrtnpror | Ty Return Promo R | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtyrtnprou | Ty Return Promo U | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtyrtnregc | Ty Return Reg C | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtyrtnregr | Ty Return Reg R | real | week_sku_stor | nsls.csv.ovr | total | Required | RI |
| drtyrtnregu | Ty Return Reg U | real | week_sku_stor | rtn.csv.ovr | total | Required | RI |
| drtyooc | Ty On Order C | real | week_sku_stor | oo.csv.ovr | total | Required | RI |
| drtyoor | Ty On Order R | real | week_sku_stor | oo.csv.ovr | total | Required | RI |
| drtyoou | Ty On Order U | real | week_sku_stor | oo.csv.ovr | total | Required | RI |
| drtyporcptc | Ty PO Receipt C | real | week_sku_stor | rcpt.csv.ovr | total | Required | RI |
| drtyporcptr | Ty PO Receipt R | real | week_sku_stor | rcpt.csv.ovr | total | Required | RI |
| drtyporcptu | Ty PO Receipt U | real | week_sku_stor | rcpt.csv.ovr | total | Required | RI |
| drtytraninbc | Ty Transfers In Book C | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytraninbr | Ty Transfers In Book R | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytraninbu | Ty Transfers In Book U | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
Table 2-1 (Cont.) Assortment Planning Cloud Service Measure List - Details 1
| Measure Name | Measure Label | Data Type | **Load Intersection ** | File Name | Agg Type | Required or Optional? | Data Source |
|---|---|---|---|---|---|---|---|
| drtytraninic | Ty Transfers In ICT C | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytraninir | Ty Transfers In ICT R | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytraniniu | Ty Transfers In ICT U | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytraninr | Ty Transfers In R | real | week_sku_stor | tranx.csv.ovr | total | Required | RI |
| drtytraninc | Ty Transfers In C | real | week_sku_stor | tranx.csv.ovr | total | Required | RI |
| drtytraninu | Ty Transfers In U | real | week_sku_stor | tranx.csv.ovr | total | Required | RI |
| drtytranoutbc | Ty Transfers Out Book C | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytranoutbr | Ty Transfers Out Book R | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytranoutbu | Ty Transfers Out Book U | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytranoutic | Ty Transfers Out ICT C | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytranoutir | Ty Transfers Out ICT R | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytranoutiu | Ty Transfers Out ICT U | real | week_sku_stor | tranx.csv.ovr | total | Optional | RI |
| drtytranoutr | Ty Transfers Out R | real | week_sku_stor | tranx.csv.ovr | total | Required | RI |
| drtytranoutu | Ty Transfers Out U | real | week_sku_stor | tranx.csv.ovr | total | Required | RI |
| drtytranoutc | Ty Transfers Out C | real | week_sku_stor | tranx.csv.ovr | total | Required | RI |
| drtyicmkdr | TY Inter-Company Markdown R | real | week_sku_stor | ic_mkd.csv.ovr | total | Optional | RI |
| drtyicmkur | TY Inter-Company Markup R | real | week_sku_stor | ic_mkd.csv.ovr | total | Optional | RI |
| drtywfslsr | TY W/F Sales R | real | week_sku_stor | wfms.csv.ovr | total | Optional | RI |
| drtywfslsu | TY W/F Sales U | real | week_sku_stor | wfms.csv.ovr | total | Optional | RI |
| drtywfslsc | TY W/F Sales C | real | week_sku_stor | wfms.csv.ovr | total | Optional | RI |
| drtywfrtnr | TY W/F Returns R | real | week_sku_stor | wfms.csv.ovr | total | Optional | RI |
| drtywfrtnu | TY W/F Returns U | real | week_sku_stor | wfms.csv.ovr | total | Optional | RI |
| drtywfrtnc | TY W/F Returns C | real | week_sku_stor | wfms.csv.ovr | total | Optional | RI |
| drdvprdattt | Product Attribute - Item Level | string | sku_patt | drdvprdattt.csv. ovr | mode_pop | Required | RI |
| drdvppatvt | RMS Product Attribute Value | string | patv | drdvppatvt.csv. ovr | mode_pop | Required | RI |
| drtyudab | TY RMS UDA | Boolea n | patt | drtyudab.csv.ov r | or | Required | RI |
| addvlocopnd | Location Open Date | date | stor | stor_a.csv.ovr | ambig_pop | Required | RI |
Table 2-1 (Cont.) Assortment Planning Cloud Service Measure List - Details 1
| Measure Name | Measure Label | Data Type | **Load Intersection ** | File Name | Agg Type | Required or Optional? | Data Source |
|---|---|---|---|---|---|---|---|
| addvlocendd | Location Close Date | date | stor | stor_a.csv.ovr | ambig_pop | Required | RI |
| addvlocrefd | Location Refurbish Date | date | stor | stor_a.csv.ovr | ambig_pop | Required | RI |
| addvloctypet | Location Type | string | stor | stor_a.csv.ovr | ambig_pop | Required | RI |
| drtypclsst | TY RMS Class Display Id | string | sku | prod_a.csv.ovr | ambig_pop | Required | RI |
| drtypsclst | TY RMS Sub- Class Id | string | sku | prod_a.csv.ovr | ambig_pop | Required | RI |
| addvlocattt | Location Attribute | string | stor_satt | addvlocattt.csv. ovr | mode_pop | Required | Admin |
| adlylagwt | LY Week Map | string | week | adlylagwt.csv.ov r | mode_pop | Optional | Admin |
| addvprdattb | Class - Product Attribute Eligibility | Boolea n | clss_patt | addvprdattb.csv .ovr | or | Optional | Admin |
| addvslscrvv | Sales Curve % | real | woyr_scls_chnc_c num | addvslscrvv.csv. ovr | total | Optional | Admin |
| addvslsprcc | Override Cost | real | skup_stor | addvslsprc.csv. ovr | max_pop | Optional | Admin |
| addvslsprcr | Override Retail Price | real | skup_stor | addvslsprc.csv. ovr | max_pop | Optional | Admin |
| addvslswgtu | Sales Weight U | real | chnc_spl2 | addvstrcwgt.csv .ovr | average_pop | Optional | Admin |
| addvslswgtr | Sales Weight R | real | chnc_spl2 | addvstrcwgt.csv .ovr | average_pop | Optional | Admin |
| addvslswgtar | Sales Weight AUR | real | chnc_spl2 | addvstrcwgt.csv .ovr | average_pop | Optional | Admin |
| addvgmwgtr | Gross Margin Weight R | real | chnc_spl2 | addvstrcwgt.csv .ovr | average_pop | Optional | Admin |
| addvgmwgtrp | Gross Margin Weight R % | real | chnc_spl2 | addvstrcwgt.csv .ovr | mode_pop | Optional | Admin |
| drdvstrclust | Loaded Location Cluster | string | week_dept_stor | drdvstrclus.csv. ovr | mode_pop | Optional | AI Foundatio n |
| drdvstrclusl | Loaded Location Cluster Label | string | week_dept_stor | drdvstrclus.csv. ovr | mode_pop | Optional | AI Foundatio n |
| drdvsrtd | Start Date | date | week_dept_stor | drdvstrclus.csv. ovr | ambig_pop | Optional | AI Foundatio n |
| drdvendd | End Date | date | week_dept_stor | drdvstrclus.csv. ovr | ambig_pop | Optional | AI Foundatio n |
Table 2-1 (Cont.) Assortment Planning Cloud Service Measure List - Details 1
| Measure Name | Measure Label | Data Type | Load Intersection | File Name | Agg Type | Required or Optional? | Data Source |
|---|---|---|---|---|---|---|---|
| fcdvsls1u | Fcst Sales Reg+Promo U | real | week_scls_stor | fcst_scls.csv.ovr | total | Optional | AI Foundatio n |
| fcdvsls1r | Fcst Sales Reg+Promo R | real | week_scls_stor | fcst_scls.csv.ovr | total | Optional | AI Foundatio n |
| fctyfcpmu | Fcst Pre-Season Sales U | real | week_sku_stor | fcst.csv.ovr | total | Required | AI Foundatio n |
| fctyfcimu | Fcst In-Season Sales U | real | week_sku_stor | fcst.csv.ovr | total | Required | AI Foundatio n |
| fctyfcpmr | Fcst Pre-Season Sales R | real | week_sku_stor | fcst.csv.ovr | total | Required | AI Foundatio n |
| fctyfcimr | Fcst In-Season Sales R | real | week_sku_stor | fcst.csv.ovr | total | Required | AI Foundatio n |
| mlcpeopc | MFP Loaded CP EOP C | real | week_scls_stor | mfp_mpcp.csv.o vr | pet | Required | MFP |
| mlcpeopr | MFP Loaded CP EOP R | real | week_scls_stor | mfp_mpcp.csv.o vr | pet | Required | MFP |
| mlcpeopu | MFP Loaded CP EOP U | real | week_scls_stor | mfp_mpcp.csv.o vr | pet | Required | MFP |
| mlcprcptc | MFP Loaded CP Receipts C | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcprcptr | MFP Loaded CP Receipts R | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcprcptu | MFP Loaded CP Receipts U | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcprtn1r | MFP Loaded CP Returns Reg+Promo R | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcprtn1u | MFP Loaded CP Returns Reg+Promo U | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcprtn2r | MFP Loaded CP Returns Clear R | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcprtn2u | MFP Loaded CP Returns Clear U | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcpsls1r | MFP Loaded CP Sales Reg+Promo R | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcpsls1u | MFP Loaded CP Sales Reg+Promo U | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
Table 2-1 (Cont.) Assortment Planning Cloud Service Measure List - Details 1
| Measure Name | Measure Label | Data Type | **Load Intersection ** | File Name | Agg Type | Required or Optional? | Data Source |
|---|---|---|---|---|---|---|---|
| mlcpsls2r | MFP Loaded CP Sales Clr R | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcpsls2u | MFP Loaded CP Sales Clr U | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlcpslsc | MFP Loaded CP Sales Reg+Promo C | real | week_scls_stor | mfp_mpcp.csv.o vr | total | Required | MFP |
| mlwpooadjc | MFP Loaded WP On Order Adj C | real | week_scls_stor | mfp_otb.csv.rpl | total | Required | MFP |
| mlwpooadjr | MFP Loaded WP On Order Adj R | real | week_scls_stor | mfp_otb.csv.rpl | total | Required | MFP |
| mlwpooadju | MFP Loaded WP On Order Adj U | real | week_scls_stor | mfp_otb.csv.rpl | total | Required | MFP |
| mlwpotbc | MFP Loaded WP OTB C | real | week_scls_stor | mfp_otb.csv.rpl | total | Required | MFP |
| mlwpotbr | MFP Loaded WP OTB R | real | week_scls_stor | mfp_otb.csv.rpl | total | Required | MFP |
| mlwpotbu | MFP Loaded WP OTB U | real | week_scls_stor | mfp_otb.csv.rpl | total | Required | MFP |
| lplaeopc | LP AP EOP C | real | week_dept_stor | mfp_ lpap.csv.ovr | pet | Optional | MFP |
| lplaeopr | LP AP EOP R | real | week_dept_stor | mfp_ lpap.csv.ovr | pet | Optional | MFP |
| lplaeopu | LP AP EOP U | real | week_dept_stor | mfp_ lpap.csv.ovr | pet | Optional | MFP |
| lplarcptc | LP AP Receipts C | real | week_dept_stor | mfp_ lpap.csv.ovr | total | Optional | MFP |
| lplarcptr | LP AP Receipts R | real | week_dept_stor | mfp_ lpap.csv.ovr | total | Optional | MFP |
| lplarcptu | LP AP Receipts U | real | week_dept_stor | mfp_ lpap.csv.ovr | total | Optional | MFP |
| lplartnr | LP AP Returns R | real | week_dept_stor | mfp_ lpap.csv.ovr | total | Optional | MFP |
| lplartnu | LP AP Returns U | real | week_dept_stor | mfp_ lpap.csv.ovr | total | Optional | MFP |
| lplaslsu | LP AP Sales U | real | week_dept_stor | mfp_ lpap.csv.ovr | total | Optional | MFP |
| lplaslsr | LP AP Sales R | real | week_dept_stor | mfp_ lpap.csv.ovr | total | Optional | MFP |
| lplaslsc | LP AP Sales C | real | week_dept_stor | mfp_ lpap.csv.ovr | total | Optional | MFP |
| addvpskugt | Rename Style Id | string | skug | addvpskugt.csv. ovr | mode_pop | Optional | Admin |
| addvpskupt | Rename Style/ Color Id | string | skup | addvpskugt.csv. ovr | mode_pop | Optional | Admin |
Table 2-1 (Cont.) Assortment Planning Cloud Service Measure List - Details 1
| Measure Name | Measure Label | Data Type | **Load Intersection ** | File Name | Agg Type | Required or Optional? | Data Source |
|---|---|---|---|---|---|---|---|
| addvpskut | Rename Item Id | string | sku | addvpskugt.csv. ovr | mode_pop | Optional | Admin |
| addvskuimgt | Item Image | string | sku | addvskuimgt.cs v.ovr | mode_pop | Optional | Admin |
| addvskupimgt | Style-Color Image | string | skup | addvskupimgt.c sv.ovr | mode_pop | Optional | Admin |
| addvskugimgt | Style Image | string | skug | addvskugimgt.c sv.ovr | mode_pop | Optional | Admin |
| addvsclsimgt | Sub-Class Image | string | scls | addvsclsimgt.cs v.ovr | mode_pop | Optional | Admin |
| addvpatvimgt | Product Attribute Value Image | string | patv | addvpatvimgt.c sv.ovr | mode_pop | Optional | Admin |
| addvpattimgt | Product Attribute Image | string | patt | addvpattimgt.cs v.ovr | mode_pop | Optional | Admin |
| drdvslsprcr | Item Initial Retail Price | real | sku | drdvslsprc.csv.o vr | avg_pop | Optional | AI Foundatio n |
| drdvslsprcc | Item Initial Cost | real | sku | drdvslsprc.csv.o vr | avg_pop | Optional | AI Foundatio n |
| drdvskuimgt | Item Image Name | string | sku | drdvskuimg.csv. ovr | mode_pop | Optional | AI Foundatio n |
| drdvskuimgl | Item Image Address | string | sku | drdvskuimg.csv. ovr | mode_pop | Optional | AI Foundatio n |
| addvppattt | Rename Product Attribute | string | patt | addvppattt.csv. ovr | mode_pop | Optional | Admin |
| addvppavt | Rename Product Attribute Value | string | patv | addvppatvt.csv. ovr | mode_pop | Optional | Admin |
| drdvsizdt | SKU Size | string | sku | drdvsizdt.csv.ov r | mode_pop | Optional | Admin |
| drdvsrngt | SKU Size Range | string | sku | drdvsrngt.csv.o vr | mode_pop | Optional | Admin |
All measure files that need to be loaded as data files need to be grouped based on the File Name. The files should contain the header for the measures to be loaded and it should be in .csv format. Measures within a file can be grouped in any order as long as the header column is specified correctly. If a measure is optional in a file, the customer can ignore that measure and group the remaining measures which are available for the customer.
Example:
In following example, the customer is using RAP integration and only grouping the data that is not coming in RAP (or RI) in a file for which customer has the data.
File Name: tranx.csv.ovr
Base Intersection: week/sku/stor
Data Type: real
week,sku,stor,drtyroyalr,drtymiscadju,drtymiscadjr,drtycogsr
w01_2021,100000,1000,30.96,31.52,0,0
w02_2021,100000,1000,169.13,112.61,1,37.85
w03_2021,100000,1000,233.54,50.26,1,35.09
Historical Data
It is recommended that you have at least one full year of historical data to create in Assortment Planning 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.
By default, RAP integration is set up to interface two years of history into Planning.
Loading and Extracting Data
Data is loaded into Assortment Planning 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 Planning Cloud Service Administration Guide .
Loading Image Based Data
Assortment Planning Cloud Service is pre-configured to provide the item level image view in the templates. The measure set up as the Style-Color 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/image-library/{sub directory if defined}/
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>
The customer can also use the same format to upload image URLs for the Item Image, Style Image, and Sub-Class Images. The same image URLs can also be directly managed in Planning Admin → Define Product Image. They can also set the Item Image Name and Item Image Address and enable the Aggregate Boolean to create the Image URLs for different levels from the same base Item Image.
In order to view the images, the Valid Image URL Hosts property should include the Image URL server name. That needs to be set in RPASCE UI Settings → System Configuration → Config Properties → Images.
Assortment Planning Cloud Service provides some standard exports that can be used by external systems that need Assortment and Item Plan Data. For details about the standard exports from Assortment Planning Cloud Service, see Appendix: Standard Exports.
Retailers using either the template or non-template version must extract and provide the foundation files needed from other source systems as flat files in the required format as needed by RAP integration and then upload to Object Storage. Any data or hierarchy files that are specific to their Planning Solution that cannot be integrated using RAP integration can be directly uploaded to Object Storage for Planning. In the same way, exported files from the solution if not part of RAP integration are sent back to the Object Storage and retailers can download the extracted files from there. The retailer must integrate it with any other system that requires extracted plan data from APCS, if not part of RAP integration
User Roles and Security
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 Planning Cloud Service users must have access to each of the workbooks.
Table 2-2 User’s Access Permission for APCS Workbooks
| Workbook | User Roles |
|---|---|
| Planning Administration | Planning Administrator |
| Validate Loaded Data | Planning Administrator |
| Location Clustering | Planner, Planning Administrator |
| Assortment Period Setup | Planner, Planning Administrator |
| Curve Maintenance | Planner, Planning Administrator |
| Create Assortment | Planner |
| Item Plan | 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
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 RPASCE 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 RPASCE server and client, as well as strings from the solution extensions.
Translations of the solution templates are not released. All templates have the ability to support multi-byte characters.
For more information on internationalization, see the Oracle Retail Predictive Application Server Cloud Service Administration Guide .
Translations are available for Assortment Planning 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 Process and Scheduling
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 Planning Cloud Service is to load historical and actual data on a weekly basis. All hierarchy changes can be loaded on a weekly basis.
In Assortment 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 Planning 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 use JOS/POM if RAP integration is used and implemented to schedule preconfigured daily and weekly batch tasks in APCS. 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 more details about the APCS schedule in JOS/POM, see Appendix: APCS Scheduling in JOS/POM.
In this guide
- Guide: Assortment Planning Cloud Service Implementation Guide
- Previous: 1 Introduction
- Next: 3 RAP Integration
Related chapters
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