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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

ConsiderationApplications
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?

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

Table 2-1 (Cont.) Configuration Considerations and Applications

ConsiderationApplications
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 IPOCSDemand 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 IPOCSDemand 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

If LAR is disabled in the plug-in, then an implementer needs to load a dummy position for the Databag Hierarchy (DTB) and Source Location Hierarchy.

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)

NameLabelHierarchy TypeParent
DAYDayMainNone
WEEKWeekMainDAY
MNTHMonthMainWEEK
QRTRQuarterMainMNTH
HALFHalfMainQRTR
YEARYearMainHALF
DOWDAY OF WEEKAlternateDAY
NameLabelHierarchy TypeParent
WOYRWeek of YearAlternateWEEK

Product Hierarchy File (PROD)

NameLabelHierarchy TypeParent
SKUItemMainNone
SKUPStyle/ColorMainSKU
SKUGStyleMainSKUP
SCLSSub-CategoryMainSKUG
CLSSCategoryMainSCLS
DEPTDepartmentMainCLSS
PGRPGroupMainDEPT
DVSNDivisionMainPGRP
CMPPCompanyMainDVSN
VNDRVendorALTSKU

Location Hierarchy File (LOC)

NameLabelHierarchy TypeParent
STORLocationMainNone
DSTRDistrictMainSTOR
REGNRegionMainDSTR
CHNLAreaMainREGN
CHANChainMainCHNL
COMPCompanyMainCHAN
SFMTStore FormatAlternateSTOR
STCLStore ClassAlternateSTOR
PHWHPhysical WarehouseAlternateSTOR
STRCLocation ClusterAlternateSTOR
CHNCChannelAlternateSTRC
CCTYChannel CountryAlternateCHNC
LOCTLocation TypeAlternateSTOR
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.

NameLabelHierarchy TypeAggs
PATVProd Attribute ValueMainNone
PATTProd AttributeMainPATV

The following table describes the fields in this file.

FieldDescription
Prod Attribute ValueThe various values that an attribute might have. For example, the package
type attribute might take the values bag, box, or convenience.
Prod AttributeThe 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 / IPOCSLifecycle 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)

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

  - 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.

NameLabelHierarchy TypeParent
offdOfferMainNone
prmdPromoMainoffd
camdCampaignMainprmd
offaOffer AliasALToffd
camaCampaign AliasALTcamd

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.

NameLabelHierarchy TypeParent
rdtpReward TypeMainNone

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.

NameLabelHierarchy TypeParent
suppSupplierMainNone
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.

NameLabelHierarchy TypeParent
altrAlertMainNone
alttAlert TypeAlternatealtr
altpAlert PriorityAlternatealtr
altcAlert ClassAlternatealtr
althAlert HierarcyAlternatealtr
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.

NameLabelHierarchy TypeParent
ATTDAttributeMainNone
ATDTAttribute Data TypeAlternateATTD
ATSCAttribute SourceMainATTD
ATSTAttribute Source TypeMainATSC
ATTPAttribute TypeAlternateATTD
Example:
attd,attd_label,atdt,atdt_label,atsc,atsc_label,atst,atst_label,attp,attp_labelbrand,Bran
d,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.

NameLabelHierarchy TypeParent
RULDBusiness RuleMainNone
NameLabelHierarchy TypeParent
RULGBusiness Rule GroupMainRULD
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.

NameLabelHierarchy TypeParent
CONDRule ConditionMainNone
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.

NameLabelHierarchy TypeParent
cstgConstraint GroupMainNone

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.

NameLabelHierarchy TypeParent
cstoConstraint ObjectMainNone
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.

NameLabelHierarchy TypeParent
dtbgDatabagMainNone
dtbpDatabag PartitionMaindtbg
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.

NameLabelHierarchy TypeParent
lprgLifecycle ProgMainNone
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.

NameLabelHierarchy TypeParent
listListMainNone
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.

NameLabelHierarchy TypeParent
rullRuleMainNone
rulgRule GroupMainrull
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.

NameLabelHierarchy TypeParent
SL0LSource Location MainMainNone
SL01Source DistrictMainSL0L
SL0GSource RegionMainSL01
SL03Source ChannelMainSL0G
SL0PSource ChainMainSL03
SL05Source CompanyMainSL0P
SL11Source StoreAlternateSL0L
SL21Source ClassAlternateSL0L
SLTYSource Location TypeAlternateSL0L
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.

NameLabelHierarchy TypeParent
ponpon_labelMainNone
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.

NameLabelHierarchy TypeParent
tfntfn_labelMainNone
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.

NameLabelHierarchy TypeParent
RGTPBusiness Rule Group TypeMainNone
FLVLFinal LevelMainRGTP
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 / IPOCSLifecycle 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 / IPOCSLifecycle 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 NameDescription
CFForecast Final Level Name, such as01
#LLC_frcst_L_#Forecast final level intersection generated by plug-in based on user
specified plug-in input parameters

Table 2-2 (Cont.) Token Names

Token NameDescription
#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

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

  • 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 NameMeasure
Description
Base
Intersection
Measure
Type
Module
Used
Require
d or
Optional
Load
Freque
ncy
Data
Source
Load
Intersection
rsalRegular
Sales
#SLS_INTX#RealallRequiredWeeklyRMS/RI#DAYSLS_INTX
#
psalPromotion
Sales
#SLS_INTX#RealallRequiredWeeklyRMS/RI#DAYSLS_INTX
#
csalClearance
Sales
#SLS_INTX#RealallRequiredWeeklyRMS/RI#DAYSLS_INTX
#
ldactivefcstitemActive
Forecast
Item
Indicator
#SLSNC_INTX
#
BooleanallOptionalWeekly
prdattTProduct
Attribute
#NIT_SKU_AT
T#
StringNew ItemOptionalWeeklyRMS/RI
nitdattwgtAttribute
Weight
#NIT_ATT_WG
T#
RealNew ItemOptionalWeekly
nitfcststovrNew Item
Forecast
Start Date
#NIT_SKUSTR
_ INTX#
DateNew ItemOptionalWeekly
nisrosNew Item
Base Rate
of Sales
#NIT_SKUSTR
_ INTX#
RealNew ItemOptionalWeekly
likeitemexmaskLike Item
Exclusion
Mask
#NIT_SKUSTR
_ INTX#
BooleanNew ItemOptionalWeekly

Table 2-3 (Cont.) RPASCE Measure Names and Intersections

Measure NameMeasure
Description
Base
Intersection
Measure
Type
Module
Used
Require
d or
Optional
Load
Freque
ncy
Data
Source
Load
Intersection
LPInBookedUInput
Booked
Units
sku_storRealLAROptionalDailyRI
LPInOnHandUInput On
Hand Units
sku_storRealLARRequiredDailyRI
LPInCustOrdUInput Cust.
Order Units
sku_stor_dayRealLAROptionalDailyRI
LPInInitFcstPLW
kU
ext_initfrcst.csv
Initial Buy
Plan Week
Units (Pre-
Season
Forecast)
sku_stor_weekRealLAROptionalDailyIPO/MF
P
LPInInTrnsUInput In
Transit Units
sku_stor_dayRealLARRequiredDailyRI
LPInOnOrdInUInput On
Order (in)
Units
sku_stor_dayRealLARRequiredDailyRI
LPInOnOrdOutUInput On
Order (out)
Units
sku_stor_dayRealLAROptionalDailyRI
LPInOTBV
otb.csv
OTB valueclss_storRealLAROptionalDailyExternal/
AP
LPInOTBPriceV
otb_price.csv
OTB pricesku_storRealLAROptionalDailyExternal/
AP
LPInExtAstPLE
assortment.csv
Ext. Asst.
Prod-Loc
sku_storIntegerLAROptionalDaily
LPInExtAstPLEn
dDt
assortment.csv
Ext. Asst.
Prod-Loc
End Date
sku_storDateLAROptionalDailyExternal/
AP
LPInExtAstPLStr
Dt
assortment.csv
Ext. Asst.
Prod-Loc
Start Date
sku_storDateLAROptionalDailyExternal/
AP
LPInDspQUDisplay Qty
Units
sku_storRealLAROptionalDailyRI
LPInFixTS1U
init_alloc.csv
Fixed TS 1
Units
sku_storRealLAROptionalDailyExternal
LPInActLocRcpUInput Actual
Loc. Recpt
Units
sku_stor_weekRealLAROptionalDaily
LPInFrcstWkU
ext_frcst.csv
Input Week
Forecast
Units
sku_stor_weekRealLAROptionalDaily
lppmlfcphsorderiLfc. Phase
Order
lprgIntegerLARRequired

Table 2-3 (Cont.) RPASCE Measure Names and Intersections

Measure NameMeasure
Description
Base
Intersection
Measure
Type
Module
Used
Require
d or
Optional
Load
Freque
ncy
Data
Source
Load
Intersection
*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 preconfigured 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

MeasureHierarchyDimension
skuimagePRODsku
skupimagePRODskup
skugimagePRODskug
skurimagePRORskur
skprimagePRORskpr
skgrimagePRORskgr
patvimagePATRpatv
pattimagePATRpatt

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 Guide .


In this guide