1 Feature Summary
Retail Analytics and Planning 23.2.401.0 is a Critical Update.
This chapter describes the feature enhancements in this release.
Noteworthy Enhancements
This guide outlines the information you need to know about new or improved functionality in the Oracle Retail Analytics and Planning applications update and describes any tasks you might need to perform for the update. Each section includes a brief description of the feature, the steps you need to take to enable or begin using the feature, any tips or considerations that you should keep in mind, and the resources available to help you.
Column Definitions
-
Feature: Provides a description of the feature being delivered.
-
Module Impacted: Identifies the module impacted associated with the feature, if any.
-
Scale: Identifies the size of the feature. Options are:
-
Small: These UI or process-based features are typically comprised of minor field, validation, or program changes. Therefore, the potential impact to users is minimal.
-
Large: These UI or process-based features have more complex designs. Therefore, the potential impact to users is higher.
-
-
Delivered: Is the new feature available for use immediately after upgrade or must the feature be enabled or configured? If no, the feature is non-disruptive to end users and action is required (detailed steps below) to make the feature ready to use.
- Customer Action Required: You must take action before these features can be used. These features are delivered disabled and you choose if and when to enable them.
Table 1-1 Noteworthy Enhancements
| Feature | Module Impacted | Scale | Delivered | Customer Action Required? |
|---|---|---|---|---|
|
Inventory Planning Optimization (IPO) Cloud Service Announcement |
||||
| Inventory Planning Optimization (IPO) Cloud Service Announcement |
All |
Large |
No |
Yes |
|
Lifecycle Pricing Optimization (LPO) Cloud Service Announcement |
||||
| Lifecycle Pricing Optimization (LPO) Cloud Service Announcement |
All |
Large |
No |
Yes |
|
Retail Analytics and Planning |
||||
| Load Aggregate Facts to Planning |
Integration |
Small |
Yes |
No |
|
AI Foundation Cloud Service |
||||
| Automatically Determine Forecast Source |
Forecasting |
Small |
Yes |
No |
| Ability to Override Prices on the Daily Interface |
Integration |
Small |
Yes |
No |
| Ignore Partial Calendar Years |
Integration |
Small |
Yes |
No |
| Alternate Hierarchy Setup Changes |
Integration |
Small |
Yes |
No |
|
Inventory Optimization Cloud Service |
||||
| Upcoming Name Changes |
User Interface |
Small |
Yes |
No |
|
Promotion and Markdown Cloud Service |
||||
| Upcoming Name Changes |
User Interface |
Small |
Yes |
No |
|
Retail Demand Forecasting Cloud Service |
||||
| Upcoming Name Changes |
User Interface |
Small |
Yes |
No |
|
Retail Insights Cloud Service |
||||
| New Reporting Metrics |
Reports |
Small |
Yes |
No |
|
Retail Predictive Application Server Cloud Edition |
||||
| Ability to Build and Edit Workspace from Recent Plans |
Usability |
Small |
Yes |
No |
| Ability to Search a Metric in the Edit Measure View for a Selected Metric |
Usability |
Small |
Yes |
No |
| Ability to Override Date Format |
Usability |
Small |
Yes |
No |
| Dimension Attributes Manager |
Usability |
Small |
Yes |
No |
New Feature Description
This section describes the new features.
Inventory Planning Optimization (IPO) Cloud Service Announcement
With this update, Oracle is announcing the new IPO Cloud Service. A retailer’s most significant investment is its inventory. IPO Cloud Service offers retailers the ability to best predict how much demand there will be and enables them to deploy their inventory to optimize the demand throughout the course of an item’s lifecycle. Throughout this lifecycle, the solution is able to react to changes in consumer behavior to ‘right size’ inventory deployment and demand methodologies. The end result allows retailers to manage their current and future inventory at scale, to ensure the right products and quantities are in the right place for the right customers at the right time.
IPO Cloud Service is composed of the modules below.
Inventory Planning Optimization (IPO) Cloud Service-Demand Forecasting
Inventory Planning Optimization (IPO) Cloud Service-Demand Forecasting provides accurate forecasts that enable retailers to coordinate demand-driven outcomes that deliver connected customer interactions. With a single view of demand, IPO Cloud Service-Demand Forecasting provides pervasive value across retail processes. Exception-driven and prioritized alerts allow users to maximize the value of their time. Enhanced AI capabilities and models within the forecast allow the application to make more sense of large and disperse data sets, driving increased accuracy over time. The ability to simulate various casual factors allows users to understand the components that impact their demand. Forecasting allows retailers to maximize the value of their inventory by accurately predicting how much inventory is needed and where to place it.
Inventory Planning Optimization (IPO) Cloud Service-Inventory Optimization
Inventory Planning Optimization (IPO) Cloud Service-Inventory Optimization allows users to optimize the settings that drive their replenishment process. Understanding the inventory necessary to achieve a target service level is critical to achieving business goals, and doing so with the least investment reduces need for markdowns and/or missed sales due to out of stocks. The curve in IPO Cloud Service-Inventory Optimization helps you to understand the trade-off between service levels and the cost of associated inventory. IPO Cloud Service-Inventory Optimization recommends an initial service level. With your target service level defined, IPO Cloud Service-Inventory Optimization optimizes target stock levels, which translates into item-location replenishment policies. The replenishment policies are used to complete a full replenishment simulation, giving you visibility into the resulting purchase and into the placement of inventory in a time-phased plan. Finally, IPO Cloud Service-Inventory Optimization drives successful outcomes in end-of-life by recommending rebalancing transfers between stores to increase sell-through in order to avoid markdowns. Rebalancing can be disabled for lower-margin categories where transferring goods is most often cost-prohibitive.
Inventory Planning Optimization (IPO) Cloud Service-Lifecycle Allocation and Replenishment
Inventory Planning Optimization (IPO) Cloud Service-Lifecycle Allocation and Replenishment is an automated allocation and replenishment planning system that constantly monitors inventory conditions and lifecycle phases. IPO Cloud Service-Lifecycle Allocation and Replenishment enables users to create strategies that control how an item is allocated and replenished from introduction to end of life. IPO Cloud Service-Allocation and Replenishment uses strategies, inventory positions, and the demand forecast, along with operational constraints of the retailer’s supply chain network, to create orders and transfers. The strategies automatically adjust deployment methodologies as products go through their different lifecycle phases to ensure the best deployment method. When new products or locations are introduced, the system can automatically determine which strategy applies and raise an alert for its review. Dynamic business rules can be set up in order to alert users and drive an exception-driven workflow and maximize the value of users’ time. IPO Cloud Service-Lifecycle Allocation and Replenishment dynamically deploys inventory throughout an item’s lifecycle and allows users to spend their time managing exceptions. Ultimately, this increases the inventory efficiency and margin across a product’s lifecycle.
Lifecycle Pricing Optimization (LPO) Cloud Service Announcement
With this update, Oracle is announcing the new LPO Cloud Service.
LPO Cloud Service manages various aspects of lifecycle pricing, optimizing promotions and markdowns to drive higher in-season sell-through, as well as increasing revenue and/or gross margin throughout the end of life. Additionally, LPO Cloud Service drives engagement and revenue from key customers and segments through the optimization of Customer Targeted Offers. LPO delivers this functionality by enabling retailers to forecast demand of their customer segments as well as to understand which customer segment has the highest probability of redemption for marketing offers. LPO Cloud Service leverages a variety of AI models in order to determine who, what, when, where and for how much, the price of various items should be throughout their lifecycle in order to maximize return on investment.
Analytics and Planning
Load Aggregate Facts to Planning
The aggregate fact interfaces previously added to the AIF data warehouse are now also integrated with PDS. These tables are intended for use only when you cannot provide SKU/store level data for core foundational areas like sales and inventory, and you instead wish to load pre-aggregated fact measures at your target intersections for Planning applications. These pre-aggregated measures will be loaded into AIF and PDS at the same intersection you provide them at. The integration is not pre-defined; as part of your implementation you would be expected to configure each interface and provide the mappings to AIF and PDS so the applications know which measures will be used and at what levels. Many advanced AIF features will not be available if pre-aggregated data is used, such as Offer Optimization and CDTs, because they require transaction data at SKU/store level.
AI Foundation Cloud Service
Automatically Determine Forecast Source
Previously, the choice of approved forecast source was a global
choice for an environment made by setting the RSE_APPROVED_FCST_SOURCE parameter in the RSE_CONFIG table in the Manage
System Configurations screen. The choices were RDF or AIF. The choices
remain the same, but it will now be automatically determined for each
run type. As a result, RSE_APPROVED_FCST_SOURCE configuration
has been removed. Whenever a forecast run type is mapped to RDF (regardless
of which other apps the same run type is also mapped to), then the
approved forecast source automatically becomes RDF. Otherwise, the
approved forecast source automatically becomes AIF.
Ability to Override Prices on the Daily Interface
The PRICE.csv interface has been updated with
2 additional columns on the end of the file:
-
ORIG_SELLING_UNIT_RTL_AMT_LCL– original price override -
LST_REG_RTL_AMT_LCL– last regular price override
These columns will be used to directly update the same-named fields in the Price fact table when they are provided. They can be provided in scenarios where you need to override the value already in the database, or you can use them to set the full price for an item/location at the same time that item/location is marked down.
Ignore Partial Calendar Years
Previously, the calendar load from RI to AIF would fail if the first year is a partial year, which forced users to load the first year as a full year. This change will allow the data load to complete by just ignoring the first year if it is a partial year. The load would only process from the 2nd year onwards into the AIF calendar tables.
Alternate Hierarchy Setup Changes
The RI tables W_INT_ORG_DTS and W_INT_ORG_DS can
be declared as data sources for alternate hierarchies in AI Foundation.
When you are looking to use a “standard” hierarchy level as one of
your alternates, you will specify W_INT_ORG_DTS as the table source
for that level, even if you are not populating this table directly.
The ETL programs will know how to obtain the standard hierarchy level
data any time W_INT_ORG_DTS is specified for a standard hierarchy
level like region or area.
Retail Predictive Application Server Cloud Edition
Ability to Build and Edit Workspace from Recent Plans
Users can now build and edit the workspace directly from the Recent Plans action menu. The Build action initiates the building process for the selected workspace. The Edit action opens the wizard for the selected workspace for users to make edits for the position selection. This saves users the time of navigating to the wizard window every time to edit or build the workspace.
Ability to Search a Metric in the Edit Measure View for a Selected Metric
With this release, users can now search for a measure in the selected measure list (right hand side) of the Edit Measure view.
Ability to Override Date Format
This feature allows the Administrator to override the default date format for all locales and all users. The configured date format will appear in the pivot table, Administration dashboard, Recent Plans, and Last Committed Status.
Dimension Attributes Manager
The ability to register, unregister, or get a report of Dimension Attributes is now provided through an Online Administration Tools (OAT) task. On certain occasions, customers/implementers will need visibility into all the registered dimension attributes. Previously, this was done by raising an SR to the Cloud support group. The ability to register, unregister, and generate a report on the existing dimension attributes will allow the customer/implementer to access this information quickly and make an informed decision.