2 Implementation Considerations

IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment is part of the Retail Analytics Platform (RAP) and imports the forecast generated by AI Foundation (AIF). The IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment application is tailored towards the workflow of a Forecast Analyst. Whereas the data scientist would interact with the AIF UI to set low level forecast tuning parameters. The following sections describe the overall implementation flow and whether it is configured on the IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment side or AIF side.

The following information must be considered before configuring Inventory Planning Optimization Cloud Service-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment:

• Configuration Considerations

• IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Hierarchies

• IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Input Data

• Integration

• User Roles and Securities

• Internationalization

Configuration Considerations

Before implementing IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment, an implementor should first answer the following questions listed in Table 2-1

Table 2-1 Configuration Considerations and Applications

Consideration	Applications
Is my forecasted item Long Lifecycle (LLC) or Short Lifecycle (SLC)?	AIF
What is the purpose of my forecast? To drive replenishment, allocation, or others?
Do I need to enable the Lifecyle module to generate the Allocation and Replenishment plans ? Does the retailer have inventory data ?
Are there any promotions that impact my forecast? If yes, how can I define the promotions?	AIF
Based on the purpose of my forecasting, which level should the forecast be generated on (sku/stor/week)? How many escalation levels are needed for the forecasting? Which level should the forecast be exported to?	IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment, AIF
What data is available to use for forecasting: rsal, psal, csal, Promotions, or Price?
What kind of preprocessing is needed: Outage, Outlier, Depromote, or Deseasonalize Smooth?	AIF
Do I need the Lifecyle Allocation and Replenishment solution?
How do I want to handle New Items? Is there any product attribute information?	IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment
Do I want to integrate IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment with other Applications?	IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment, AIF
If I want to use grouping in my escalation levels, how do I group my item/stores?	AIF
Do I need to generate daily forecast, and/or both weekly and daily forecasts?	IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment, AIF
Do I have a foundation system to provide foundation (hierarchy) data?

Depending on the answers to the previous questions, the implementor can use the IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment plug-in to generate IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment configurations. For details about how to generate IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment configuration, refer to IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Configuration. The generated IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment configuration can be customized to satisfy client specific requirement. For details about how to customize IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment configuration, refer to IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Extensibility.

Note:

In order to implement planning applications on RAP, you should ensure their foundation data such as Product and Organization hierarchies, align with RMFCS (Merchandising Systems) so that the foundation and transactional data can be used by all applications in RAP. They can have additional alternate dimensions than available in RMFCS (Merchandising Systems), if it is needed for their planning solution.

Customers can use the flex fields available in RAP Foundation files to interface this additional data. Also, if multiple planning applications like MFPCS, APCS, or IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment reside in the same PDS, then the common hierarchies should have the same dimension names to share the data interfaced from RAP. However additional non-shared dimensions can be present in each application.

IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Hierarchies

There are four type of hierarchies in IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment:

• Standard RPASCE Hierarchies Files

• User Managed IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Hierarchies

• Plug-in Generated IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Hierarchies

• RHS Hierarchies

Standard RPASCE Hierarchies Files

This is the foundation data to build any RPASCE solution. Inventory Planning Optimization Cloud Service-Demand Forecasting Inventory Planning Optimization Cloud Service-Lifecycle Allocation and Replenishment requires the standard three hierarchy files, Calendar, Product, and Location. Additional sets of hierarchy files specific to different solutions may also be needed. The standard hierarchy files for Calendar, Product, Location and Product Attributes need to be loaded into the RI interface. Refer to the Data Requirements section in the Oracle Retail Analytics Platform Implementation Guide.

Note:

The following format only shows the hierarchy structure used by IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment. The file to be loaded needs to conform to the RI interface. The user provides standard RPASCE hierarchy files.

For information on the hierarchy files, see the following sections:

• Calendar Hierarchy File (CLND)

• Product Hierarchy File (PROD)

• Location Hierarchy File (LOC)

• Products Attributes Hierarchy File (PATR)

Calendar Hierarchy File (CLND)

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
DOW	DAY OF WEEK	Alternate	DAY
WOYR	Week of Year	Alternate	WEEK

Product Hierarchy File (PROD)

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
VNDR	Vendor	ALT	SKU

Location Hierarchy File (LOC)

Name	Label	Hierarchy Type	Parent
STOR	Location	Main	None
DSTR	District	Main	STOR
REGN	Region	Main	DSTR
CHNL	Area	Main	REGN
CHAN	Chain	Main	CHNL
COMP	Company	Main	CHAN
SFMT	Store Format	Alternate	STOR
STCL	Store Class	Alternate	STOR
PHWH	Physical Warehouse	Alternate	STOR
STRC	Location Cluster	Alternate	STOR
CHNC	Channel	Alternate	STRC
CCTY	Channel Country	Alternate	CHNC
LOCT	Location Type	Alternate	STOR

Note:

The Store Cluster dimension (STRC) is not used in IPOCS, but is included so as to align with other planning apps (MFPCS, APCS). Currently it is mapped same as the store dimension. It can be customized to bring in clusters from another source field.

Products Attributes Hierarchy File (PATR)

The product attributes hierarchy represents attributes associated with products. These attributes are used to group products within categories.

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 to calculate similarity scores between items.

The retailer needs to load the Product Attributes into the RI interface. Refer to the Attribute Files section of the Oracle Retail Analytics Platform Implementation Guide.

In IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment, the Product Attribute hierarchy structure is described in this section.

Name	Label	Hierarchy Type	Aggs
PATV	Prod Attribute Value	Main	None
PATT	Prod Attribute	Main	PATV

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.

Note:

In RAP, the product attributes would flow from RI to RDX to PDS. When imported this way into PDS, the product attribute name is concatenated with the product attribute values using ‘_’ to make the product attribute values unique. The Product Attribute name for Supplier (W_PDS_SUPPLIER_D) is used as ‘supp’ and Brand (W_PDS_BRAND_D) is used as ‘brnd’.

User Managed IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Hierarchies

The implementor or retailer can update these IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment hierarchy files. The GA IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment package contains these hierarchy files.

For information on the hierarchy files, see the following sections:

These hierarchies can be classified into two categories:

• Hierarchies that are configured in AIF and IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment:

  • Offer Hierarchy (OFFH)

  • Reward Type Hierarchy (RDTH)

  • Supplier Hierarchy (SUP)

• Hierarchies that are configured only in IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment:

  • Alert Hierarchy (ALT)

  • Business Rule Attribute Hierarchy File (ATTH)

  • Business Rule Hierarchy File (RULH)

  • Condition Hierarchy File (CONH)

  • Constraint Group Hierarchy (CSG)

  • Constraint Object Hierarchy (CSO)

  • Databag Hierarchy (DTB)

  • Lifecycle Program Hierarchy (LPR)

  • List Hierarchy (LST)

  • Rule Hierarchy (RUL)

Offer Hierarchy (OFFH)

This hierarchy represents the offer/promo fields. If promo has been enabled in AIF this hierarchy will be imported during the batch. Refer to the RAP Integration for detailed information. If promo is not enabled in AIF, then the retailer can upload the GA offer hierarchy file. Note that the offer hierarchy needs to be populated for the Forecast Review workbook to build.

File name: offh.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
offd	Offer	Main	None
prmd	Promo	Main	offd
camd	Campaign	Main	prmd
offa	Offer Alias	ALT	offd
cama	Campaign Alias	ALT	camd

Reward Type Hierarchy (RDTH)

This hierarchy represents the reward type that can be associated per offer. If promo has been enabled in AIF this hierarchy will be imported during the batch. Refer to the RAP Integration for detailed information. This hierarchy is needed to build the Offer Analysis workbook. This workbook is useful only if promo is enabled.

File name: rdth.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
rdtp	Reward Type	Main	None

Supplier Hierarchy (SUP)

This hierarchy represents the list of suppliers. This hierarchy is imported during the batch. Refer to the RAP Integration chapter for detailed information.

File name: sup.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
supp	Supplier	Main	None

Example:

supp,supp_label

v1001,Supplier 1

v1002,Supplier 2

v1003,Supplier 3

Alert Hierarchy (ALT)

Alert hierarchy contains alerts for Inventory Planning Optimization Cloud Service-Lifecycle (IPOCS-Lifecycle). Alerts can be defined during implementation time.

File name:alt.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
altr	Alert	Main	None
altt	Alert Type	Alternate	altr
altp	Alert Priority	Alternate	altr
altc	Alert Class	Alternate	altr
alth	Alert Hierarcy	Alternate	altr

Example:

altr,altr_label,altt,altt_label,altp,altp_label,altc,altc_label,alth,alth_label

alert.c01,C01 Permanent,com,Common,3_l,3 Low,filter,Filter,prod-loc,PROD-LOC

alert.c02,C02 Seasonal,com,Common,3_l,3 Low,filter,Filter,prod-loc,PROD-LOC

Business Rule Attribute Hierarchy File (ATTH)

This is attribute hierarchy used in the Business Rule Engine functionality. Note that this is different from the PATR (Product Attribute) hierarchy. This hierarchy file is a hybrid between user-loaded attributes and IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment GA calculated attributes generated by the plug-in. Refer to the Appendix: IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Business Rule Engine for detailed information on Business Rule Engine.

Note:

Every time you add a new custom attribute, you must provide a complete file that includes all of the custom attributes.

File name: atth.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
ATTD	Attribute	Main	None
ATDT	Attribute Data Type	Alternate	ATTD
ATSC	Attribute Source	Main	ATTD
ATST	Attribute Source Type	Main	ATSC
ATTP	Attribute Type	Alternate	ATTD

Example:

attd,attd_label,atdt,atdt_label,atsc,atsc_label,atst,atst_label,attp,attp_labelbrand,Brand,3,String,ldprdattstr01,loaded Product Attribute 01,load,Loaded Attribute,prod,Product Attributeregn,Region,3,String,regn,region of location Hierarchy,hier,Hierarchy Attribute,loc,Location Attribute

Business Rule Hierarchy File (RULH)

This hierarchy structure is used to associate Business Rules within a Business Rule Group in the Business Rule Engine functionality. The GA hierarchy file loads five placeholder Business Rules per Rule Group. The implementor can customize this file, based on the maximum number of rules the retailer would like to define per Business Rule Group. Refer to the Appendix: IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Business Rule Engine for detailed information on Business Rule Engine.

File name: rulh.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
RULD	Business Rule	Main	None
RULG	Business Rule Group	Main	RULD

Example:

ruld,ruld_label,rulg,rulg_labelr001,Rule 1,g001,Rule Group 1r002,Rule 2,g001,Rule Group 1 r003,Rule 3,g001,Rule Group 1 r004,Rule 4,g001,Rule Group 1 r005,Rule 5,g001,Rule Group 1

Condition Hierarchy File (CONH)

This is the Condition hierarchy used to organize the strategies (conditions) in defining a business rule. Refer to the Appendix: IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Business Rule Engine for detailed information on Business Rule Engine.

File name: conh.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
COND	Rule Condition	Main	None

Example:

cond,cond_labelcond01, condition 01cond02, condition 02cond03, condition 03cond04, condition 04

Constraint Group Hierarchy (CSG)

Constraint Group Hierarchy is used for the constraint functionality framework.

File name: csg.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
cstg	Constraint Group	Main	None

Example:

cstg,cstg_label

csg.01,Constraint Group 01

csg.02,Constraint Group 02

Constraint Object Hierarchy (CSO)

Constraint Object Hierarchy is used for the constraint functionality framework.

File name: cso.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
csto	Constraint Object	Main	None

Example:

csto,csto_label

csto.0001,C.0001

csto.0002,C.0002

csto.0003,C.0003

csto.0004,C.0004

Databag Hierarchy (DTB)

Databag Hierarchy allows the grouping of data for planning in IPOCS-Lifecycle Allocation and Replenishment.

File name:dtb.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
dtbg	Databag	Main	None
dtbp	Databag Partition	Main	dtbg

Example:

dtbg,dtbg_label,dtbp,dtbp_label

dtb.01.01,Fashion.Replenishment.All,dp.01,Databag Partition Fashion 01

dtb.01.02,Fashion.Replenishment,dp.01,Databag Partition Fashion 01

Lifecycle Program Hierarchy (LPR)

Lifecycle Program Hierarchy contains phases of the lifecycle.

File name: lpr.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
lprg	Lifecycle Prog	Main	None

Example:

lprg,lprg_label

lprg_id_1,Phase 1

lprg_id_2,Phase 2

lprg_id_3,Phase 3

List Hierarchy (LST)

List Hierarchy contains lists for rule conditions.

File name: lst.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
list	List	Main	None

Example:

list,list_label

l.01,L.01

l.02,L.02

Rule Hierarchy (RUL)

Rule Hierarchy is for the definition of rules of Lifecycle and Replenishment.

File name:rul.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
rull	Rule	Main	None
rulg	Rule Group	Main	rull

Example:

rull,rull_label,rulg,rulg_label  R.01.01,R.01.01,RG.01,Rule Group Fashion 01

R.01.02,R.01.02,RG.01,Rule Group Fashion 01

Batch Generated Hierarchies

The IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment batch generates this hierarchy file using the Location and Supplier hierarchies:

• Source Location Hierarchy File

The IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment batch generates the following hierarchy files using purchase order and transfer order numbers retrieved from RMS:

• Purchase Order Number Hierarchy File

• Transfer Order Number Hierarchy File

Source Location Hierarchy File

This hierarchy file defines the locations that can be a source of a product.

File name: slc.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
SL0L	Source Location Main	Main	None
SL01	Source District	Main	SL0L
SL0G	Source Region	Main	SL01
SL03	Source Channel	Main	SL0G
SL0P	Source Chain	Main	SL03
SL05	Source Company	Main	SL0P
SL11	Source Store	Alternate	SL0L
SL21	Source Class	Alternate	SL0L
SLTY	Source Location Type	Alternate	SL0L

Example:

sl0l,sl0l_label,sl01,sl01_label,sl0g,sl0g_label,sl03,sl03_label,sl0p,sl0p_label,sl05,sl05_label,sl11,sl11_label,sl21,sl21_label,slty,slty_label
1000,New York City,1000,US,1000,North America,1000,The Americas,1000,Bricks & Mortar,100,JCB Trading Company,4,4,A,A,s,Store
w1001,w1001 Regional Warehouse 1,none,None,none,None,none,None,none,None,1,Retailer Ltd,none,None,none,None,w,Warehouse
v1001,Supplier 1,supplier,Supplier,supplier,Supplier,supplier,Supplier,supplier,Supplier,100,JCB Trading Company,supplier,Supplier,supplier,Supplier,v,Supplier

Purchase Order Number Hierarchy File

This hierarchy file defines purchase order number positions.

File name: ponh.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
pon	pon_label	Main	None

Example:

pon,pon_label
12345678,12345678

Transfer Order Number Hierarchy File

This hierarchy file defines transfer order number positions.

File name: tfnh.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
tfn	tfn_label	Main	None

Example:

tfn,tfn_label
123456789123,123456789123

Plug-in Generated IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Hierarchies

The IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment plug-in generates this hierarchy files based on the IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment configuration:

• Final Level Hierarchy File

Final Level Hierarchy File

This hierarchy file defines the Business Rule Group Types associated with a Final Level. Refer to the Appendix: IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Business Rule Engine for detailed information on Business Rule Engine.

File name: flvh.hdr.csv.dat

File format: comma-separated values file

The following table describes the fields in this file.

Name	Label	Hierarchy Type	Parent
RGTP	Business Rule Group Type	Main	None
FLVL	Final Level	Main	RGTP

Example:

rgtp,rgtp_label,flvl,flvl_labelaprv01,approve 01,01,01 Weekly Units Forecastnavi01,navigation 01,01,01 Weekly Units Forecast

RHS Hierarchies

The PROR and LOCR internal hierarchies are mirrored hierarchies of the PROD and LOC hierarchies. They are also referred as PROD RHS and LOC RHS. In the RPAS Cloud Edition versions 19.0 and later, PROR and LOCR are considered as virtual hierarchies. Refer to the Oracle Retail Predictive Application Server Cloud Edition Configuration Tools User Guide for information on Virtual Hierarchies.

Since these hierarchies are virtual, you do not have to load the hierarchy files. All of the other operations remain the same. You can register measures on PROR and LOCR and include them in workbooks.

Notes about these virtual hierarchies:

• PROR and LOCR hierarchies have been marked as virtual in the GA configuration.

• We cannot define security dimension on a virtual hierarchy or make them translatable.

• Virtual hierarchies cannot have user defined dimensions.

• If a retailer is upgrading from a pre-19.0 IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment version, then IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment will automatically mark them as virtual and conform to the virtual hierarchy requirements.

IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment Input Data

A detailed data set is required to use the capabilities of IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment to its fullest. Some of the data required is relatively easy to obtain, for example, information about sales. To simplify the data integration, all 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. Some of the Lifecycle measure data that can be logically grouped together are loaded into the same file.

Measure Name and Intersections

Because many RPASCE measure names and intersections are dynamically generated by IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment plug-in. Tokens are used to represent the IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment level names. The labeled intersection were also listed for measure intersection

Table 2-2 lists the Token names.

Table 2-2 Token Names

Token Name	Description
_CF_	Forecast Final Level Name, such as 01
#LLC_frcst_L_#	Forecast final level intersection generated by plug-in based on user specified plug-in input parameters
#LLC_frcstTS_L_#	Forecast final level timeseries intersection = LLC final level intersection – clnd dim generated by plug-in based on user specified plug-in input parameters
#SLS_INTX#	Sales History intersection. This labeled intersection is user defined
#SLSNC_INTX#	Sales History intersection -clnd dim This labeled intersection is user defined
#NIT_ATT_WGT#	Attribute weight intersection, generated by plug-in based on user specified plug-in input parameters
#NIT_SKU_ATT#	Product attribute intersection, generated by plug-in based on user specified plug-in input parameters
#NIT_SKUSTR_INTX#	New Item assignment intersection, generated by plug-in based on user specified plug-in input parameters
#PRESLS_INTX#	Forecast Preprocessing data source input intersection
#LP_P0S#	Lowest level in Product hierarchy foe example, SKU
#LP_L0L#	Lowest level in Location hierarchy foe example, stor
#LP_P0G#	Product group scope defined in the Lifecycle plugin foe example, clss
#LP_L0G#	Location group scope defined in the Lifecycle plugin foe example, regn

Measure Names and Descriptions

Table 2-3 lists the measure names and descriptions. The measure field descriptions include:

Module Used

This field explains which solution is using the file. The possible values can be:

• All

• New Item

• Forecast

• Preprocess

• Inventory Planning Optimization Cloud Service-Lifecycle Allocation and Replenishment (IPOCS-Lifecycle Allocation and Replenishment)

Required or Optional Required

This field means the data is necessary. 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:

• Daily

• Weekly

• 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.

• IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment or equivalent. Can be readily loaded from RMS or derived from data loaded from RMS.

• ORASE - Oracle Retail Advanced 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 Intersection

Most of the time, the load intersection of the measure is the same as the base intersection of the measure. When the field is empty, the load intersection is the same as base intersection.

Table 2-3 RPASCE Measure Names and Intersections

Measure Name	Measure Description	Base Intersection	Measure Type	Module Used	Required or Optional	Load Frequency	Data Source	Load Intersection
rsal	Regular Sales	#SLS_INTX#	Real	all	Required	Weekly	RMS/RI	#DAYSLS_INTX#
psal	Promotion Sales	#SLS_INTX#	Real	all	Required	Weekly	RMS/RI	#DAYSLS_INTX#
csal	Clearance Sales	#SLS_INTX#	Real	all	Required	Weekly	RMS/RI	#DAYSLS_INTX#
ldactivefcstitem	Active Forecast Item Indicator	#SLSNC_INTX#	Boolean	all	Optional	Weekly
prdattT	Product Attribute	#NIT_SKU_ATT#	String	New Item	Optional	Weekly	RMS/RI
nitdattwgt	Attribute Weight	#NIT_ATT_WGT#	Real	New Item	Optional	Weekly
nitfcststovr	New Item Forecast Start Date	#NIT_SKUSTR_ INTX#	Date	New Item	Optional	Weekly
nisros	New Item Base Rate of Sales	#NIT_SKUSTR_ INTX#	Real	New Item	Optional	Weekly
likeitemexmask	Like Item Exclusion Mask	#NIT_SKUSTR_ INTX#	Boolean	New Item	Optional	Weekly
LPInBookedU	Input Booked Units	sku_stor	Real	LAR	Optional	Daily	RI
LPInOnHandU	Input On Hand Units	sku_stor	Real	LAR	Required	Daily	RI
LPInCustOrdU	Input Cust. Order Units	sku_stor_day	Real	LAR	Optional	Daily	RI
LPInInitFcstPLWkU ext_initfrcst.csv	Initial Buy Plan Week Units (Pre-Season Forecast)	sku_stor_week	Real	LAR	Optional	Daily	IPO/MFP
LPInInTrnsU	Input In Transit Units	sku_stor_day	Real	LAR	Required	Daily	RI
LPInOnOrdInU	Input On Order (in) Units	sku_stor_day	Real	LAR	Required	Daily	RI
LPInOnOrdOutU	Input On Order (out) Units	sku_stor_day	Real	LAR	Optional	Daily	RI
LPInOTBV otb.csv	OTB value	clss_stor	Real	LAR	Optional	Daily	External/AP
LPInOTBPriceV otb_price.csv	OTB price	sku_stor	Real	LAR	Optional	Daily	External/AP
LPInExtAstPLE assortment.csv	Ext. Asst. Prod-Loc	sku_stor	Integer	LAR	Optional	Daily
LPInExtAstPLEndDt assortment.csv	Ext. Asst. Prod-Loc End Date	sku_stor	Date	LAR	Optional	Daily	External/AP
LPInExtAstPLStrDt assortment.csv	Ext. Asst. Prod-Loc Start Date	sku_stor	Date	LAR	Optional	Daily	External/AP
LPInDspQU	Display Qty Units	sku_stor	Real	LAR	Optional	Daily	RI
LPInFixTS1U init_alloc.csv	Fixed TS 1 Units	sku_stor	Real	LAR	Optional	Daily	External
LPInActLocRcpU	Input Actual Loc. Recpt Units	sku_stor_week	Real	LAR	Optional	Daily
LPInFrcstWkU ext_frcst.csv	Input Week Forecast Units	sku_stor_week	Real	LAR	Optional	Daily
lppmlfcphsorderi	Lfc. Phase Order	lprg	Integer	LAR	Required
*LAR is an abbreviation for Lifecycle Allocation and Replenishment

Following is a sample header line for each of the files that are loaded together (if loading flat files):

• assortment.csv.* : sku,stor,LPinextastple,LPinextastplstrdt,LPinextastplenddt

* indicates that the file extension could be either .rpl or .ovr.

Direct Load Interfaces

The following files are optional and to use them, you must load the files into PDS.

• Input Week Forecast Units

  ext_frcst.csv.ovr

  This is an optional adjustment to the measure specified in the LIP plugin (RDF approved forecast).

• Initial Buy Plan Week Units (Pre-Season Forecast)

  ext_initfrcst.csv.ovr

  This is optional and can be loaded from external source.

• Fixed TS 1 Units

  init_alloc.csv.ovr

  This is optional and if loaded is the Fixed Target Stock 1 initial allocation for point in time replenishment.

Note:

In the Inventory Planning Optimization Cloud Service-Demand Forecasting / Inventory Planning Optimization Cloud Service-Lifecycle Allocation and Replenishment User Guide, refer to Fixed 1 (Initial Allocation). If IPO-LAR is integrated with AP, then the initial allocation can flow from AP to IPO. You must enable the Import Initial Allocation from AP in the IPO Batch flow management workspace.

Historical Data

It is recommended that you have at least two full years of historical data for long life cycle forecasting and one full year of historical data for short life cycle forecasting.

Loading and Extracting Data

Data is loaded into IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment using the Online Administration Tools, which in turn use standard RPASCE utilities. For more information on loading and extracting data using Online Administration Tools, see the Oracle Retail Inventory Planning Optimization Cloud Service-Demand Forecasting / Inventory Planning Optimization Cloud Service-Lifecycle Allocation and Replenishment Administration Guide

Loading Image Based Data

IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment is pre-configured to support the display of images for items and product attributes in the Forecast Review and New Item workbooks. Table 2-4 lists the dimension attribute measures used to load images.

Table 2-4 Labeled Intersections

Measure	Hierarchy	Dimension
skuimage	PROD	sku
skupimage	PROD	skup
skugimage	PROD	skug
skurimage	PROR	skur
skprimage	PROR	skpr
skgrimage	PROR	skgr
patvimage	PATR	patv
pattimage	PATR	patt

The Content Server exposes the client's image files placed into a particular directory as HTTP URLs. The images must be defined in the load file in an xml format. The images are available at:

http://{content server url}/imgfetch/{sub directory if defined}

Sample File for skuimage.csv.ovr

The first field represents the SKU 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.

10000010,"<image id=""main"" label=""Front View"">\<url size=""thumb"">http://msp00alq.us.oracle.com:9001/contentserver/imgfetch/sku_10000010_main_thumb.jpg</url></image>"

Example File for skuimage.csv.ovr

10000010,"<image id=""main"" label=""Front View"">\
<url size=""thumb"">http://msp00alq.us.oracle.com:9001/contentserver/imgfetch/sku_10000010_main_thumb.jpg</url>
<url size=""full"">http://msp00alq.us.oracle.com:9001/contentserver/imgfetch/ sku_10000010_main_full.jpg</url></image>"

Integration

IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment is part of the Retail Analytics Platform (RAP). The foundation data needs to be loaded into the RI data interface. Any hierarchy or data specific for IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment can be loaded via the File Transfer Service (FTS).

User Roles and Securities

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 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 cannot edit any values or commit the workbook. The read-only workbook can be refreshed.

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 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 IPOCS-Demand Forecasting / IPOCS-Lifecycle Allocation and Replenishment for the following languages:

• English (United States, Great Britain, Canada, Australia)

• 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.