Noteworthy Enhancements

1 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.
- Medium: These UI or process-based features are typically comprised of field, validation, or program changes. Therefore the potential impact on users is moderate
- 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?
Analytics and Planning
Oracle Analytics Server Upgrade	Analytics and Planning	Medium	Enabled	No
Batch Schedule Updates	Analytics and Planning	Small	Enabled	No
Automatic Table Partitioning	Analytics and Planning	Medium	Enabled	Yes
Price Zone Extract Enhancements	Analytics and Planning	Small	Enabled	No
Daily Data Integrations for PDS	Analytics and Planning	Medium	Disabled	Yes
AI Foundation
Rules & Strategies Enhancements	AI Foundation	Medium	Enabled	No
Integration of Oracle Digital Assistant (ODA) and Generative AI	AI Foundation	Medium	Enabled	No
CDT Replatform to Jet UI	AI Foundation	Medium	Enabled	No
CDT Hierarchy as Alternate Hierarchy	AI Foundation	Small	Enabled	No
Transfer of Table Data between Environments	AI Foundation	Small	Enabled	No
Platform Technology Updates	AI Foundation	Small	Enabled	No
AIF Application Dashboard Update	AI Foundation	Medium	Enabled	No
Inventory Planning Optimization (IPO) Cloud Service-Inventory Optimization Enhancements
Cross-Docking Orders	Inventory Optimization (IPO-IO)	Large	Enabled	No
Initial Allocations	Inventory Optimization (IPO-IO)	Large	Enabled	No
Simplified Alert Thresholds	Inventory Optimization (IPO-IO)	Medium	Enabled	No
Alert Details	Inventory Optimization (IPO-IO)	Small	Enabled	No
Lifecycle Pricing Optimization (LPO) Cloud Service Enhancements
Lifecycle Pricing Optimization Replatform to Jet UI	Lifecycle Pricing Optimization	Medium	Enabled	No
Elasticity Report for Regular Price Optimization (RPO)	Lifecycle Pricing Optimization	Small	Enabled	No
Multiple Price Ladders as % Off	Lifecycle Pricing Optimization	Small	Enabled	No
What-If Runs Ability to Multi Select Sub-Departments (Run Level) and Price Zones	Lifecycle Pricing Optimization	Small	Enabled	No
User ID of the Approver	Lifecycle Pricing Optimization	Small	Enabled	No
Business Rule Updates	Lifecycle Pricing Optimization	Small	Enabled	No
Locking Mechanism	Lifecycle Pricing Optimization	Small	Enabled	No
Debug/Playback	Lifecycle Pricing Optimization	Small	Enabled	No
Retail Insights Cloud Service
Stock Count Dimension Extract	Retail Insights	Small	Disabled	Yes
Deal Income for Issues and Fixed Deals	Retail Insights	Small	Enabled	No
Inventory Receipt Expenses and Allowances	Retail Insights	Medium	Disabled	Yes
Clear Cache Agent Improvements	Retail Insights	Small	Enabled	No
Retail Home Content Updates	Retail Insights	Small	Enabled	No
Retail Predictive Application Server Cloud Edition Server Enhancements
Improved Dimension Labels in User Interface	Admin	Small	Yes	Yes
Improved Workspace Sharing and Notification	Admin	Small	Yes	No
Improved User Management	Admin	Small	Yes	Yes
Ability to Sort Single Hierarchy Select Picklists Using an Online Administration Tools (OAT) Task	Admin	Small	Yes	No
Retail Predictive Application Server Cloud Edition Client Enhancements
Ability to Contextually Launch into Planning from Data Visualization	Reporting	Medium	Yes	Yes
Last Refreshed Time Update on Manage Workspace	Usability	Small	Yes	No
Display Media Attribute Headers in Excel Export	Usability	Small	Yes	No
Ability to Sync Application Labels from Retail Home	Usability	Small	Yes	Yes
Update in Workspace Commit Action	Usability	Small	Yes	Yes
Retail Predictive Application Server Cloud Edition Configuration Tools Enhancement
Modularity in Configuration Tools	Configuration Tools	Medium	Yes	No
Assortment Planning Cloud Service Enhancement
Assortment Planning Packaged Reports	Reporting	Medium	Yes	No
Merchandise Financial Planning Cloud Service Enhancements
Modular Planning for Merchandise Financial Planning (MFP) Retail	MFP	Medium	Yes	No
Merchandise Financial Planning (MFP) Packaged Reports	Reporting	Medium	Yes	No

Analytics and Planning Enhancements

Oracle Analytics Server Upgrade

This release of Retail Analytics and Planning applications includes an upgrade of Oracle Analytics Server (OAS) to the 2024 release version. Review the full list of changes here:

https://docs.oracle.com/en/middleware/bi/analytics-server/whats-new-oas/

There are no required actions that you need to perform prior to upgrade, but it is always a good practice to regularly back up your reports catalog using the available options (Archive action from Analytics Classic catalog or Export to DVA action from DV catalog). After any upgrade of the Analytics server, you should also review your Business Intelligence (BI) agents to ensure all reports continue to go out as scheduled with the appropriate content delivered.

Some OAS features may not be available for Retail application usage, or they have been pre-configured with certain limitations. This includes:

Creating your own data connections, such as to non-Oracle data sources, remains disabled (no change from prior releases) and you will not have access to any new Connections listed.
The Auto Insights feature is not supported on subject areas, meaning it will not be available for use on Retail Insights data unless you write a custom dataset using SQL, and then apply Auto Insights on that dataset.
The Export to Excel option in Data Visualization supports export of a single visual per file and up to 25,000 rows of data. The export option is available for Table and Pivot Table views.
The new features relating to fine-grain permission controls are not accessible to Retail cloud customers and you will still be limited to the predefined application roles listed in Oracle Retail documentation.

This release includes changes to the user interface that will affect how you use the system, and you may wish to inform your end-user community about them prior to upgrade.

Workbook Interface Change	Usage Details
Workbooks may open in a new View-only mode without the data or properties panels visible.	If a workbook opens in View-only mode, then an Edit icon (displayed as a yellow pencil inside a box) will appear on the top of the workbook to open the full editor. Click the icon to access the normal workbook editor screen. Users may disable this behavior by going into their Profile from the upper-right application menu, selecting the Advanced tab, and disabling the Open Workbooks as a Viewer option.
Your filter selections in workbooks do not show the actual values you have selected, only the names of the filter attributes.	Filters now hide the selection values by default to minimize the amount of space they take up on screen. You may change this by clicking the new Filter Bar Menu option on the right side of the filter bar, and selecting the option Filter Values > Show All.
You need to modify the formatting or properties of a measure in your report but cannot locate the Properties panel.	All options relating to formatting and column settings have been moved into a new Properties panel, which can be selected using an icon above the existing Grammar panel.
Users may notice several other new icons and actions on the task bar in their workbooks and will need to know how to use them.	The following new icons or menus may appear in your workbooks after upgrade: Preview - This icon is shown as a triangle or "play" icon, and it returns the workbook to View-only mode if it is currently in Edit mode. Auto Insights - This icon is shown as a lightbulb and allows users to run analytics on their dataset (SQL- or Excel-based data only) to automatically suggest relevant charts or views. Navigation Menu - This icon shows as a bookmark symbol and provides direct access to Analytics Classic dashboards that the user has permissions to view. Parameters - This icon appears as "(X)" on the upper left side of the screen, above the data panel, and it opens a new panel. Users may now create parameters and use them as variables in many workbook objects. Add to Watchlist - This icon appears as a plus sign (+) in a box when hovering over a visualization. Watchlists are a new feature allowing you to add important visuals and metrics to your home page, where they will be displayed at the top of the screen when you log in to Oracle Analytics.

Batch Schedule Updates

This release of the AIF DATA schedule in POM includes the following changes to jobs and processes, which may impact your nightly or standalone flows after upgrade.

All jobs relating to deprecated Data Mining functionality have been removed. The following 4 processes and all jobs in them are dropped from the schedule: MINING_START_PROCESS, MINING_PROCESS, MINING_POST_SLSPR_BL_PC_IT_LC_WK_A_PROCESS, SIL_WEEK_INITIAL_PROCESS.
A new maintenance job PURGE_OLD_RDX_EXPORTS_JOB is added to the weekly AIF DATA maintenance cycle (RI_MAINTENANCE_CYCLE), which is responsible for erasing old run data in all RDX integration tables from RI to PDS. Runs will be erased based on their maximum retention days in the RAP_INTF_CFG table. This is enabled by default.
A new RDE job is added for Stock Count integration (refer to Retail Insights enhancements). This is disabled by default.
New RDE and RI jobs are added for Non-Merchandise Expenses and Allowances data (refer to Retail Insights enhancements). This is disabled by default.
Standalone processes such as DAT_REPROCESS_ADHOC and RI_DIM_INITIAL_ADHOC have additional jobs to support the above enhancements. They are enabled by default.

In addition to added or removed jobs, all jobs in the AIF DATA schedule have now been assigned Phases. Phases in POM are logical groupings of jobs that will be summarized in the nightly batch completion emails to show total runtimes by phase. The phase summary report provides a simpler way to monitor batch performance without keeping track of individual jobs by name.

Automatic Table Partitioning

The process to initialize the AIF data warehouse with foundation data no longer requires manual partitioning of all tables at the start of a new data load. Data warehouse tables are now dynamically partitioned at runtime by their individual fact load programs. The partition-related programs have been removed from the CALENDAR_LOAD_ADHOC process and do not need to be executed when loading calendar data. If you need to perform manual partitioning at any point, you may still use the CREATE_PARTITION_ADHOC process, which contains the same set of jobs previously in CALENDAR_LOAD_ADHOC. These jobs will still function the same way as in prior releases, but they are no longer mandatory.

If you have not been running the RUN_PARTITION_MAIN_VALIDATOR_JOB as part of routine batch executions or RI_MAINTENANCE_CYCLE weekly processes, then you must enable this job and run it before upgrading to this version of the application. This job will make sure there are no tables that are missing partition setup, which will in turn prevent excessive run times in the first nightly batch after the upgrade.

For existing customer environments, there is also a parameter in the C_ODI_PARAM table that controls partitioning behavior. If any table in your environment still has data in a MAX partition on upgrade, then the parameter REAL_TIME_PARTITION_PREP will be set as disabled and all automated partition functions will be skipped or ignored. After your MAX partitions are cleaned of all data using the maintenance cycles, you must update this parameter to enable automated runtime partitioning.

Price Zone Extract Enhancements

The interface with Pricing Cloud Service to extract price zone information has been enhanced to use an additional source table RPM_MARKDOWN_ZONE_GROUP_DEF to populate the target table W_RTL_CLSTR_GRP_PRD_DS. The source table is used to define optional mappings of price zones to merchandise hierarchy nodes that are in addition to the initial pricing setup. These mappings can be for markdown zone groups that need to be associated with merchandise nodes for use in Lifecycle Pricing Optimization. Both the initial price zones and all other zone groups will be combined and extracted to the existing data warehouse tables for price zones. As part of this change, there is also a new column on the interface named DEFAULT_MKDN_FLG. This flag is an optional way to indicate which markdown zone group is the primary one to be used when multiple groups are assigned to the same merchandise node. The flag is currently for reference only and is not used by any application logic in this release.

You must upgrade MFCS to version 25 or later to leverage this integration change, as the Pricing CS table is new in version 25. If RI and AIF are upgraded without MFCS, then the interface will not extract the new data.

Daily Data Integrations for PDS

This release adds support for daily fact data integrations from the data warehouse to Planning applications (PDS). These enhancements are applied to the existing integration tables such as W_PDS_SLS_IT_LC_WK_A. New configuration options are added to C_ODI_PARAM, which will set the export level to weekly or daily data, with the existing week-level integration being enabled by default. When changed to use daily data for a specific interface, that interface will begin sourcing data from day-level data warehouse tables and writing the results into the existing PDS target table. By using the same PDS tables, the impact to the RPAS configurations is minimized as all the same tables and measures are used, only the base intersection (from week to day) would change. In this initial release of the functionality, only the standard fact measures can be integrated at day level for the Sales fact interface. Flex columns are not supported, because the day-level data warehouse tables do not currently support the flex column integrations.

For more details on the configuration options added with this feature, refer to the Retail Analytics and Planning Implementation Guide.

AI Foundation Cloud Service

Rules & Strategies Enhancements

The following notable changes have been made to the Rules & Strategies functionality in AI Foundation:

A new feature named Rule Builder was added so that users can create rule criteria and rule values independently and map them together to create business rules. This feature is an alternative way of creating business rules and is an addition to the existing create rule functionally.
A new feature for copying rules was added. This will allow users to select one or multiple business rules and create a copy of them. During the copy process, users will be given an option to edit the criteria and/or rules values.
A new feature was added to support using primary supplier as criteria in Inventory Planning Optimization rules. These criteria are enabled by default in cross-docking and initial allocation rules.
A new rule sub-category for cross-docking was added for Inventory Planning Optimization. This will allow users to enable cross docking for warehouse locations, using different criteria such as merchandise hierarchy, product attribute, and primary supplier.
A new feature was added such that the alert rules in Inventory Planning Optimization can be created in “Simple” mode. This will allow users to set up alert rules with fewer and more intuitive parameters. The simple mode of alert setup is accessible through the same alert rule screens.
A new rule category named Regular was added for Lifecycle Planning Optimization. This will allow users to set up business rules such inter-item and inter-location rules for regular price optimization.

Integration of Oracle Digital Assistant (ODA) and Generative AI

A new AI function was introduced to Oracle Digital Assistant (ODA) so that users can ask questions using ODA and get answers to generic (non-data-related) questions about application features, tables, configurations, and so on. Users will also be able to get answers to data-related questions such as performance metrics and a summary of optimization results. In this release, the latter feature is supported for IPO and LPO only.

CDT Replatform to Jet UI

CDT has been replatformed from ADF to Jet UI. The new user interfaces will be the primary interfaces accessible to users starting with the 25.1.101.0 release. The links to the older ADF screens are being decommissioned in this release.

CDT Hierarchy as Alternate Hierarchy

The CDT output (hierarchy) should be extracted out and fed into the AIF alternate hierarchy building flow. The existing process is a combination of both manual and automated processes. The new alternate hierarchy will be based on the data of the existing job that populates CDT_CM_BRANCH_ITEM_ATTR. When the existing ad hoc job is executed, the alternate hierarchy staging tables will now be populated, which is used by the nightly process in generating the new hierarchy types and hierarchy levels. The nightly batch for alternate hierarchies will execute and the new hierarchies will be generated on the RSE_PROD_HIER tables.

Transfer of Table Data between Environments

With this release, we have expanded on the feature that enabled a user to export data from the RSE_CONFIG table from one environment to another. The feature update now allows for exporting of table data from one environment for direct import into the same table in another environment. User will be able to download data from tables that are available in the System Configuration screen and import into another environment using the import icon in the same screen. This aims to make it easier for users to move data between environments. The utility will export the data into a .csv file. The generated file should then be imported directly into the target environment using the same utility. It does not allow for edits to the .csv file, thereby ensuring data consistency and security.

Platform Technology Updates

For this release of AI Foundation and Innovation Workbench, the following technology updates are included:

Python upgrade to latest supported version
Data Studio upgrade to latest supported version

AIF Application Dashboard Update

The AIF Application Dashboard on the main page after login has been reworked in this release. It is moving from ADF to Jet UI. The new Jet UI dashboard will largely be a menu that contains links that will launch the different AIF applications. Jet UI applications (such as SPO, LPO, and so on) will be launched in a new tab within the same browser window. ADF applications (such as Customer Segmentation, Advanced Clustering, and so on) will be launched in a new browser window.

Inventory Planning Optimization (IPO) Cloud Service-Inventory Optimization Enhancements

Cross-Docking Orders

Inventory Planning Optimization–Inventory Optimization now supports cross-docking purchase orders through a warehouse to another warehouse or store. A warehouse is set up to cross-dock products in Rules & Strategies. You will define the target timeframe ‘locking-in’ the allocation either prior to shipment, or in a window prior to receipt. This allows time for refining the assortment plan, reviewing forecasts, or reacting to the latest sales (replenishment cross-docking) before generating an allocation for the purchase order or warehouse.

Initial Allocations

When you define repeatable, lifecycle-based Initial Allocation rules for stores, the optimization engine will now recommend the allocation quantity to give out for new item/locations. The store launch date or assortment period will define when a product or store is new.

The initial allocation rules are defined at stores and aggregated to PO destination warehouses when calculating recommendations. You will define how demand is calculated with the option to define minimum and maximum quantities. The IPO Demand Forecast is used to calculate store need for non-fixed-quantity allocations.

You will define a target allocate-by time window. The beginning of this window or the window required to cross-dock the item will determine when the allocation is calculated.

Simplified Alert Thresholds

Alerts will support ‘simple’ and ‘advanced’ alert definitions for each of the rule types. The simple alert thresholds are defined relative to the target stock levels: Order Point and Order Up to Level. This allows you to set more broadly applicable rules achieving meaningful alerts while requiring fewer overrides. The advanced rules allow you to define more-specific targets. The ‘simple’ alert rules are defined along with the advanced alert rules in the existing Rules & Strategies screen.

Alert Details

Alert details are now provided in the Inventory Planning interface. Clicking an alerted cell will open the Advanced Options panel that contains the existing Policies tab, and a new Alerts tab. You can review detailed information about the item/location alert such as the ‘size’ of the alert in terms of units and retail value.

Lifecycle Pricing Optimization (LPO) Cloud Service Enhancements

Lifecycle Pricing Optimization Replatform to Jet UI

Existing ADF screens in LPO have been replatformed from ADF to Jet UI. The new user interfaces will be the primary interfaces accessible to users starting with the 25.1.101.0 release. The links to the older ADF screens will be available along with the links to the new screens, when the configuration PRO_OO_SWITCH_TO_JET is set to N. ADF links will be decommissioned in the July release. As part of this streamlined workflow:

Metrics in the Run Overview and Overview context panel have been enhanced.
New tab named Planned Events has been added.
Results tab has been enhanced to have the same look and feel as Manage Recom UI.
Sales, Returns, and Exceptions screens have been absorbed into the what-if run workflow.

Elasticity Report for Regular Price Optimization (RPO)

Elasticity reports for both Promotion/Markdown or Regular Price Optimization can now be generated and attached to the Reports Dashboard of the Manage Recom UI.

Multiple Price Ladders as % Off

LPO can now process the multiple price ladders, specified as percentage off a reference price, for post-processing. Previously, post-processing ladders (for ladder count >0) had to be of type ‘A’; but with this enhancement, it can accept PR/PT/PO as well.

What-If Runs Ability to Multi Select Sub-Departments (Run Level) and Price Zones

LPO now allows users to submit multiple what-if runs for creation and optimization to evaluate a new strategy or to work with different business rules. To accomplish this, LPO allows a multi-creation option in the Scope screen of the what-if run UI. These requests will be queued up to be executed in the daily batch. Users can review and delete the requests in the Multi-run Request task menu.

User ID of the Approver

LPO Manage Recom UI will now display the User ID of the approver of a recommendation.

Business Rule Updates

Regular business rules have been re-organized into multiple subcategories and two new categories named Inter-Item and Inter-Location have been added. Users will now be able to specify Inter-Item or Inter-Location business rules through the Business Rules UI. Please refer to the complete list of enhancements listed in Rules & Strategies Enhancements.

Locking Mechanism

The locking mechanism in all screens has been enhanced to address an issue when the user is locked up by accidentally closing or refreshing the browser session. Furthermore, there is a configuration (PRO_UI_LOCK_LIMIT) that puts an expiration time on the lock (default is 1 hour).

Debug/Playback

Users can now use the Debug/Playback button to download the relevant data (with internal IDs) for a single what-if run. This information is useful for debugging a particular run between two systems (for example, Stage vs Prod) and should be included when submitting a Service Request for assistance on what-if run issues.

Retail Insights Cloud Service Enhancements

Stock Count Dimension Extract

A new integration program is added to the AIF DATA schedule in POM for extracting stock count header information from Merchandising to RI. The program name is RDE_EXTRACT_DIM_P21_STKCNTSDE_JOB and will be disabled by default in your nightly schedule. The sources for this program are the STAKE_HEAD and STAKE_LOCATION tables in MFCS. This program populates the existing table W_RTL_LOC_STOCK_CNT_DS in the data warehouse, and all downstream functionality is unchanged.

Deal Income for Issues and Fixed Deals

The Deal Income fact interface has been enhanced to accept additional types of deal income from Merchandising. The interface now accepts transactions for fixed-deal income and issues-based income. The extract from Merchandising is enhanced to pull transaction codes 8 (fixed income) and 9 (issues income) and write the data into new columns on the interface W_RTL_DEALINC_IT_LC_DY_FS. These columns have been included in the export to Planning Data Store (PDS) for use in Planning applications (non-GA implementations only). The new columns are also available in the file-based interface for DEAL_INCOME.csv. The data is exposed in Retail Insights for reporting using new measures in the Deal Income folder.

Inventory Receipt Expenses and Allowances

A new reporting area has been added to RI for tracking the non-merchandise expenses and allowances associated with the receipt of purchase orders from a supplier into an owned location. In Merchandising Foundation Cloud Service, this is represented as additional transactions in IF_TRAN_DATA that use transaction code 20 but are associated with one or more non-merchandise codes that identify the type of expense or allowance that should be added to the cost of the received inventory units. New RDE programs are added to the AIF DATA schedule to extract the non-merchandise codes into a new dimension and the additional transaction code 20 records into a new fact. Both the dimension and fact loads are added into the nightly AIF DATA batch schedule and relevant standalone processes. The interfaces support file-based loads, in addition to the direct MFCS extracts.

More details can be found in the following documents:

RAP Data Interfaces Guide is updated with the new extract programs and interface definitions.
AIF Operations Guide is updated with the new historical data load process.

Clear Cache Agent Improvements

The Cache Clear Agent used for erasing Retail Insights report caches can be used as a mechanism for triggering other agents at the end of the nightly batch, which is useful for delivering reports by email automatically while ensuring the latest data is always used. You may take the following steps to enable this functionality:

Create a folder named Oracle under the shared Custom folder (with full path like /shared/Custom/Oracle/).
Copy the Clear Cache Agent from /shared/Oracle/ to /shared/Custom/Oracle/.
Edit the newly created agent: Go to the Actions tab and add “Invoke Agent” actions for each of your BI agents that you want automatically triggered any time the Cache Clear Agent is executed. If you will have many linked agents, then it’s best to create a sequential chain of actions, where each agent has one action to trigger the next one in order. Running too many agents in parallel can result in consuming all available resources on the database, which will slow down all of the executions. When finished, be sure to save the agent before navigating away from it.
In POM, go to Batch Administration and select the AIF DATA Nightly Schedule. Locate the OBIEE_CACHE_CLEAR_JOB and select the Edit Parameters option in the Actions menu. Add the path to your custom agent as the only parameter value (for example, /shared/Custom/Oracle). Do not include a trailing slash character, just the folder name and root path as shown. The folder path should not contain any spaces or special characters besides the “/” characters.

Restart the AIF DATA schedule from Batch Monitoring by clicking the Restart Schedule button. The next time the job executes, it will use your custom version of the BI agent instead of the base version. Any custom BI agents attached to the Clear Cache Agent will be triggered automatically when the agent completes.

Retail Home Content Updates

The Retail Insights seed data for Retail Home has been updated with additional tiles representing our Retail application pillars such as Plan, Market, and Allocate. New report templates for linking these tiles to measures in Retail Insights are also available if you want to leverage them as a starting point for new dashboards. In RI's catalog, there is a new folder at the path /shared/Retail Home/CxO Dashboard/ that contains the report templates referenced by the Retail Home seed data.

Retail Predictive Application Server Cloud Edition Server Enhancements

Improved Dimension Labels in User Interface

Customers can now opt to have position IDs prefixed to dimension labels by setting the preferred option through PDS Properties. This allows the customers to choose the hierarchies where they want to see the position ID and label concatenated. This concatenation of ID and label allows the user to distinguish items with the same label from each other.

Multiple enhancements are provided on the workspace sharing and notification framework. With this enhancement, if a workspace is shared with another user and if any commit operations are performed on the shared workspace, both the owner and shared user receive notifications. This allows all the related users using the same workspace to be notified that the data has been modified and committed. Also, whenever workspaces are shared, an Online Administration Tools (OAT) task has been introduced to allow the administrator to know all the users the workspace is shared with. This allows the Administrator to know all the shared users of the workspace. For example, this enables the Administrator to take appropriate action in case one of the users has gone on a long absence and the Administrator is trying to purge user details. The OAT task will allow the Administrator to clear all the workspace and ownership issues before purging user details. An additional column has also been added to the manage workspace dashboard that lists the users a workspace is shared with.

Improved User Management

Every time users are added, edited, or deleted from IDCS, Sync users from IDCS OAT task was executed to synchronize the user details in IDCS and Planning. This has now been further streamlined by providing the ability to sync the user edits made in IDCS with Planning by running a batch task. With this improvement, users do not need to run the OAT task repeatedly; they can add the Sync users from IDCS task to their batch framework and execute as part of the batch.

Ability to Sort Single Hierarchy Select Picklists Using an Online Administration Tools (OAT) Task

Administration users can now set the sorting option for the SHS picklist measure and picklist measures using an OAT task. The sorted picklist will help users make a quick selection from the list. Based on the picklist type, the Administration user can choose from the following sort options that can be applied to the picklist: Alphanumeric, sort by Label sort, and sort by Internal name. The selected sort option for the picklist measure will reflect on the RPASCE UI.

Retail Predictive Application Server Client Enhancements

Ability to Contextually Launch into Planning from Data Visualization

With this release, users can now contextually launch into planning workspaces from a data visualization report. This will help users to make quick data updates on the planning workspaces. The reports are linked with workspace templates by the System Implementer / tech user using the configuration.

Last Refreshed Time Update on Manage Workspace

The manage workspace table has been enhanced to display the last refreshed time of the workspace along with the last refreshed date. With this functionality, users can keep track of the last refresh time while working with multiple workspaces throughout the day.

Display Media Attribute Headers in Excel Export

The media attribute headers are now displayed in the Excel export. The headers will be visible for multiple media attributes in the normal, block, and block & exclude sub-total modes of export output.

Ability to Sync Application Labels from Retail Home

Administration users can now update the Planning application name centrally in the Retail Home application navigator page. When the application name is updated in Retail Home, the same will be reflected in the respective Planning applications.

Update in Workspace Commit Action

By default, RPAS CE now prompts for commit only upon closing the workbook, and the commit button is removed from the UI.

Work within a workspace is continually saved and does not need to be committed until it is finalized. This change provides better overall performance for all users, by avoiding frequent commits of incomplete workspaces, which can lead to excessive commit task queuing and locking. Your users will receive guidance on this change through an on-screen guided learning note. However, if exceptionally required by the business process, the Commit button can be reinstated.

Retail Predictive Application Server Cloud Edition (RPASCE) Configuration Tools Enhancement

Modularity in Configuration Tools

Configuration Tools has been enhanced to include solution modularity functionality.

The System Implementer can select from predefined modules within a solution using the newly introduced Modularity Tools utilities option within Configuration Tools.

This allows selected parts of the GA configuration to be picked as a starting base configuration, that can then be built on to suit the customer’s business process.

Modular planning is available only for the MFP GA Retail accounting method.

Assortment Planning Enhancements

Assortment Planning Packaged Reports

Data Visualization reports are now available out-of-the-box for the Assortment Planning application. These reports allow the users to analyze KPIs by visually leveraging the best reporting capabilities Oracle offers. The reports also allow the users to slice and dice data across different dimensions or aggregate data from different sources to generate meaningful, actionable reports. The reports provided out-of-the-box are expected to serve as a starting point for the customers. They can then further build required reports tailored to their specific needs.

Merchandise Financial Planning Cloud Service Enhancements

Modular Planning for Merchandise Financial Planning (MFP) Retail

With this release, the MFP GA retail configuration has been modularized by breaking it down into various meaningful modules. This will help System Implementers to trim down the MFP GA configuration to a base configuration by simply removing the modules that are not required for the customer. The MFP GA configuration has been divided into modules based on roles, metric, UOM, and so on, so users can define their roles and associated planning levels.

Merchandise Financial Planning (MFP) Packaged Reports

Data Visualization reports are now available out-of-the-box for the MFP application. These reports allow the users to analyze KPIs visually leveraging the best reporting capabilities Oracle offers. The reports also allow the users to slice and dice data across different dimensions or aggregate data from different sources to generate meaningful, actionable reports. The reports provided out-of-the-box are expected to serve as a starting point for the customers. They can then further build required reports tailored to their specific needs.