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.

Important:

Due to the highly extensible nature of the Retail Analytics and Planning suite of cloud services, scheduled updates to its application features can affect your custom scripts, reports, datasets, and other objects added in the Innovation Workbench and Oracle Analytics Server. The customer is solely responsible for regularly backing up all custom objects created across the suite of Retail Analytics and Planning (RAP) cloud services and ensuring that these custom objects continue to function as intended after each major update. Oracle does not maintain backups of custom objects in a way that enables their individual restoration if they are lost or corrupted. For example, if a custom script is deleted by a user or modified in a way that makes it non-functional, Oracle cannot restore it without rolling back the environment to an earlier point in time (before the changes occurred).

Column Definitions

Analytics and Planning Enhancements

Oracle Analytics Cloud Update

This release of Analytics and Planning solutions includes Oracle Analytics Cloud (OAC) for both new and existing customers. Moving existing customer environments from Oracle Analytics Server (OAS) to OAC involves a one-time migration activity with several customer activities required. The migration will not be mandatory or automatic in this release however, you should explicitly state in your upgrade requests if you want to migrate to OAC or remain on OAS. When requesting the July release of RAP applications, make sure to account for any additional time needed to perform these activities. A summary of the actions required is provided below, and a Reference Paper is in development.

Change Area What Changes Customer Impact
Permissions OAS groups used an environment-specific system tenant ID. OAC groups must be created by the customer for each OAC environment using a customer/environment tenant name. You must create the OAC IAM groups, assign users matching their existing permission levels, and validate access in non-prod envs before production migration.
URL Existing OAS links redirect automatically to the new OAC service URL. The OAC path uses /ui/dv/ or /ui/analytics/ as the end-points. You should update bookmarks, portals, embedded links, and external references to use the direct OAC URL in order to avoid the automatic redirects from the OAS URL.
Content Validation Oracle migrates customer-created analytics content as part of the upgrade, but customers should validate content behavior and user access post-migration. Test a subset of workbooks, dashboards, analyses, Publisher reports, deliveries, data connections, and security in non-production first and raise any issues with Oracle before migrating the Production environment.
Update Frequency Oracle Analytics Cloud (OAC) is its own OCI service included as part of your Oracle Retail subscription and therefore operates on a separate patching and maintenance schedule. OAC is automatically updated on a regular basis (every 1-2 months) to apply security updates, bug fixes, and new features. Updates to OAC will not require an outage (also known as zero-downtime patching), however they may cause the application to go into a read-only state where reports can be executed but not edited. Most patches will not require this read-only mode and it will last 1-2 hours. All OAC updates are required and cannot be delayed or cancelled. Users should be made aware of the new read-only behavior of zero-downtime patching in OAC, so that they understand what is happening when the environment becomes read-only for a period of time. OAC will provide release notes and announcements for major feature updates based on their own release schedules independently of Oracle Retail. OAC does not send notifications for maintenance updates that contain stability improvements to existing product features, these updates are applied automatically without downtime.

Integration and Interface Updates

This release of Retail Analytics and Planning (RAP) applications includes a mandatory change to certain platform configurations in the AIF data warehouse, which will be applied to all customers automatically at the time of upgrade. These changes will ensure all customers are managing item and product hierarchy data in a consistent way following Oracle’s recommended configuration.

  • RI_ITEM_REUSE_IND will be set to Y, as this is the preferred method for managing item deletion and re-use
  • RI_PROD_COUNT_VALIDATION_IND will be set to Y, as this validation is critical for ensuring product data is cleanly loaded in batch and stopping the batch when issues arise
  • RI_ITEM_REUSE_AFTER_DAYS will be set to 7 if RI_ITEM_REUSE_IND is currently N or RI_ITEM_REUSE_AFTER_DAYS is currently 0

This release includes several updates to data integrations and commonly used batch programs in the AIF DATA batch schedule. All customers of RAP applications may be impacted by these changes, so review this content carefully and take action if required.

  • New job RDX_EXT_LOAD_JOB is added for loading external files into inter-application (RDX) database tables. This program is disabled by default and should only be enabled for custom loads into specific RDX interfaces. The job is available in the nightly batch and as a standalone process.
  • New standalone process HIST_COST_LOAD_ADHOC is added for loading historical cost data for Base Cost (BCOST) and Net Cost (NCOST) facts in Retail Insights. New batch programs are added to this process to enable support for base/net cost history in the data warehouse.
  • New jobs prefixed with W_RTL_INVADJC* and W_RTL_TSF_CHRG* are added for new interfaces with Merchandising Foundation CS (MFCS) that load data for Retail Insights reporting. New RDE jobs RDE_EXTRACT_FACT_P4_TSFCHRGILDSDE_JOB and RDE_EXTRACT_FACT_P7_INVADJCILDSDE_JOB are also added for extracting the MFCS data to these interfaces. These jobs will be disabled by default and must be enabled before the related functionality can be used.
  • New job RDE_BATCHFINAL_SEND_BATCH_STATUS_JOB will post the extract status for a given business date to MFCS rdeBatchDependency web service. If this job is not called, MFCS will assume the AIF DATA batch did not run and will start falling behind by one or more days, requiring the use of HIST tables to catch up the data for past dates. This job must be enabled for all customers using MFCS as the source for foundation data.
  • New job EID_TO_E_REJECT_COPY_JOB is added for copying data streaming API rejections into the standard rejected record (E$) tables so that they can be reprocessed by the nightly batch when required. The job will be enabled by default but is not required when data streaming APIs are not in use.

This release includes the following changes to AIF APPS schedule jobs and processes:

  • IO_RULES_TO_RSE_LOAD_JOB is added to the nightly batch schedule. The job loads IO strategy rules data to the rules engine. The job accepts no parameters.
  • DT_PROD_LOC_EXCL_LOAD_PROCESS (and all 4 jobs in it) has been removed from the nightly batch schedule as it is no longer used.
  • PMO_RETURN_LOAD_PROCESS_ADHOC has been removed from the schedule as the same functionality is provided by PMO_RETURN_LOAD_ADHOC_PROCESS.
  • RSE_FCST_ADJ_LOAD_PROCESS (with 4 jobs prefixed with RSE_FCST_EXT_EFF_ADJ in the name) has been added to load external forecast adjustment factors into AIF, and a similarly named process PRO_FCST_ADJ_LOAD_PROCESS has been deprecated. The data can also be loaded via RSE_MASTER_ADHOC_JOB or RSE_MASTER_ADHOC_AIF_JOB by providing the following parameter to those jobs: --fcst_ext_adj
  • Batch jobs IO_REPL_ATTR_PROD_LOC_EXCP_SETUP_JOB and IO_LEAD_TIME_PROD_LOC_LOAD_JOB now have a default parameter (--skip-load-asn-po). The parameter is not editable for both jobs.
  • The following batch jobs have been added to the existing ORASE_END_PROCESS: RSE_STREAM_JOB_WEEKLY_MAINT_JOB, RSE_STREAM_JOB_DAILY_MAINT_JOB, and RSE_STREAM_JOB_RELEASE_JOB.

This release also includes the following changes to core AIF data warehouse structures:

  • The data warehouse has standardized the field length for item and product hierarchy IDs to allow for a minimum 80-character length. Some PROD_NUM or ITEM fields previously used a length of 30 either on the interfaces or internally on the data warehouse tables, and these lengths have been increased to 80. Related fields such as INTEGRATION_ID and PROD_CAT5 have also been increased to account for the maximum possible lengths in the source data.
  • The PRODUCT_IMAGE_ADDR field in the PRODUCT.csv interface and all related product tables has been increased to a length of 2048 bytes (2KB) to support encrypted string values and long URLs which exceeded the previous length. No change was made to how the URL field is used in the applications, this is only a data model update.

PDS Dimension View-Based Integration

This release adds additional view-based interfaces for PDS dimension integration so you can reduce reliance on RDX schema tables for moving data into planning applications. The release covers all dimension exports such as exchange rates, brand, differentiators, product attributes, supplier, UDA, customer segment, organization attributes, product pack, and replenishment attributes. These views are designed to preserve the data of the current RDX tables while supporting the newer direct integration patterns and run ID generation using PDS_DIMENSION_VIEW_JOB. All views added for integration purposes will have a naming scheme where “V” is appended to the end of the original table name, for example W_PDS_PRODUCT_D has a view named W_PDS_PRODUCT_DV that will contain the exact same data.

Existing customers are not required to move to the new views at this time and the table-based integrations remain fully functional and unchanged. Customers may start to see usage of these views in the GA templates in Planning where view-based integration is supported.

Purchase Order Expense and Duty Costs

This release adds purchase order expense and duty cost handling when MFCS is the source of data, so planning and analytics applications can account for estimated landed cost components beyond base item cost.

MFCS has added a new view in this release called V_ORDLOC_EST_LANDED_COST which the RDE integration job for purchase order extracts will read to calculate total on order cost inclusive of these components. A new C_ODI_PARAM parameter PO_COST_ELC_IND controls whether the PO_ONORD_COST_AMT_LCL calculation includes base unit cost plus unit expense and unit duty. The default value is N (disabled), so you must set PO_COST_ELC_IND to Y when you want total on-order cost to include estimated landed cost components. As this is a modification to an existing calculation, all downstream AIF and Planning applications will start to get the updated ELC-inclusive value after the parameter is enabled.

Enhanced Oracle Home Experience

The Oracle Home Experience introduces an updated home and navigation model across RAP solutions. This experience provides users with a more modern entry point for accessing applications, settings, notifications, and frequently used work areas.

Key capabilities include:

  • A Product Map that organizes application links, workflows, and actions in a structured navigation view.
  • A Suggestions List that can surface commonly or recently used links, helping users return to frequent tasks more quickly.
  • Access to notifications from the Oracle Home Experience, while preserving expected notification behaviors such as open, read, and dismiss where applicable.

This enhancement provides a more consistent experience across Oracle Retail applications. It also establishes the foundation for future intelligent search, navigation, and AI-assisted experiences as those capabilities continue to evolve.

Ability to Load Custom Documents to RAG

RAP now supports the ability to include customer-specific implementation documentation in the retrieval-augmented generation, or RAG, knowledge base used by AI-enabled experiences. This allows AI responses to consider both standard Oracle product documentation and customer-specific configuration or business process documentation.

This capability is especially valuable for customers whose RAP solutions have been configured or extended from the generally available product documentation. By adding customer-specific guides, implementation notes, or functional documentation to the RAG corpus, AI-assisted experiences can provide answers that better reflect the customer’s deployed solution.

Key capabilities include:

  • Customer documents can be uploaded for use by the RAG process and associated with the relevant application, module, version, and tenant context.
  • Uploaded documents are processed into vector embeddings so relevant content can be retrieved when AI responses are generated.
  • Customer-specific documents are kept tenant-specific, helping ensure that responses are grounded in the correct customer context.
  • Standard Oracle documentation and customer-specific documentation can be used together, improving answer relevance where customer configuration differs from the base product.

Customers should review their documentation strategy before using this feature, because uploaded documents become part of the AI knowledge experience. The quality, accuracy, and currency of customer-provided documentation directly affects the quality of AI-generated answers.

AI Services Enhancements

Future Period Planning in Portfolio Optimization

Portfolio Optimization scenarios now support future-period scenario planning by allowing users to select calendar periods up to two years ahead when creating scenarios. This helps planners generate optimization recommendations for the actual planning horizon they work in, such as planning the 2028 financial year while operating in 2026 or selecting future quarters for upcoming seasonal and financial planning cycles.

  • Users can work with a forward-looking calendar range that better matches the planning cycle.
  • The selected horizon supports scenario comparison before results are committed to the planning process.
  • The capability is useful when teams need to evaluate future periods beyond the immediate working plan.

Data Health Check Agent

The Data Health Science Agent helps users identify the underlying cause of any run failure and provides recommended next steps to resolve the issue.

AI Foundation Cloud Service Enhancements

Forecast What-If Scenarios

Forecasting now supports what-if review scenarios for baseline forecasts, new items, and promotions. Users can evaluate alternate forecast strategies from the forecast review and approval flow before deciding which forecast should be approved. This gives forecasting teams a more interactive way to understand the effect of assumptions or strategy choices, rather than relying only on a single generated forecast result.

Promotion Price Responsiveness

Promotion forecasting has been enhanced to make demand more responsive to price. The release introduces support for promotion behavior where discount depth can influence demand, addressing scenarios where a promotion price change should have a measurable effect on the forecast. This gives retailers a more realistic foundation for evaluating promotional demand and supports better downstream planning decisions.

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

Purchase Order Definition Enhancements

IPO purchase order generation has been enhanced to better align generated replenishment orders with Merchandising integration requirements and business practices. The prior purchase order definition was less flexible and could group destinations in ways that did not match downstream country and import rules.

  • Purchase Orders are segregated by destination type.
  • Retailer configurations define product level grouping and single, or multi-location PO grouping.
  • Destinations in different countries will be assigned to separate purchase orders.
  • The benefit is fewer downstream integration failures and executable purchase orders that do not require additional review.

Bulk Edit for Policy Overrides

Inventory planners can now override replenishment policy settings for multiple items more efficiently. This helps when a planner needs to adjust policy for a meaningful group of items rather than editing each item one at a time.

  • Advanced Options supports creating and maintaining items and locations that match the launch context from the plan.
  • Overrides can be managed by setting filters and sub-filters. Filters can be defined independently from the main plan view page.
  • Preview and what-if behavior remain available so users can review the impact before committing the override.
  • The business value is faster exception management when policy changes need to be applied consistently across a broader part of the assortment.

Substitute Item Inventory Planning

IPO now supports substitute item relationships across replenishment, initial allocation, and user allocation workflows. Substitute Items are used to phase in inventory while selling through the existing inventory. Substitute items are used when inventory can be sold or fulfilled interchangeably, such as replacement items, temporary items, or grey-market items. The combining of inventory reduces overstock while achieving desired service levels.

  • The Oracle Retail Merchandising Foundation Cloud Service (MFCS) Substitute Item setup is leveraged to link substitute skus to the main sku and define locations included in substitutions.
  • The included stores will have their sales history combined in order to generate a single demand forecast.
  • While planning to a single stock level you will take precise action on the actual item stock available.
  • The benefit is that retailers can use interchangeable stock to satisfy demand while still preserving operational visibility and planner control over the specific items being moved.

Select Allocation Doc Type

Initial allocation rules can now specify the document type to allocate. This addresses cases where allocation should wait for confirmed shipment visibility instead of being triggered as soon as a purchase order exists.

  • Rules can support ASN-only behavior for scenarios where allocation must wait for shipment confirmation.
  • This is especially important for cross-dock and initial allocation flows where triggering too early can create operational issues.
  • The business value is a more realistic allocation timeline that better matches inbound supply visibility.

One-Step Approve and Export

IPO approval flows have been streamlined so approval and export will be executed in a single action. This reduces user steps without removing the business approval point.

  • The benefit is a simpler planner workflow when the intent is to approve and send the recommendation downstream in one motion.

Holdback Override and What-If

IPO holdback planning now allows users to override calculated holdback quantities and preview the effect through what-if behavior. This supports exception handling when the holdback calculated from rules and strategies does not match the immediate business need.

  • Users can adjust the calculated holdback quantity.
  • Preview behavior lets users evaluate the effect before committing the override.
  • The benefit is more flexible inventory protection when planners need to reserve stock for specific operational or business reasons.

N-Tier Cross-Docking

IPO cross-docking has been enhanced to support automated allocation through multiple warehouse tiers. The auto-allocation can create linked allocation documents through the cross-dock route.

  • IPO can identify intermediate warehouse nodes between the source and final destination.
  • The solution will create the linked allocations needed to move inventory through the cross-dock route.
  • Inventory planners can review the parent allocation from the first cross-docked warehouse to the final destination.
  • The capability supports more automated distribution for complex supply chains where inventory must pass through one or more warehouses before reaching stores or other destinations.

Automated Allocations Using Assortment Plan

IPO automated allocation rules can now use an assortment plan as an allocation input instead of relying only on forecast information. This helps align allocations to the approved assortment intent.

  • The business value is that allocation can leverage the assortment where sales history is insufficient to generate a forecast, improving consistency between planning and execution.

Allocation Detail Usability and Validation Enhancements

IPO allocation detail screens have been enhanced to improve review, rounding visibility, and validation before approval. These updates help planners understand what is being allocated and prevent approval of quantities that cannot be supported by available supply.

  • Planners can review style-color totals that include pack component quantities and drill into SKU and pack detail.
  • The screen can compare system, user, and final allocated quantities and show header metrics summarizing allocation totals.
  • Final quantities reflect order multiple rounding.
  • Approval validates that final allocation quantities do not exceed available source quantity intra-day supply changes.

IPO Rule Agent

IPO introduces a Rules Agent that Business Rules and Strategies that enables Business Rules and Strategies users to describe an inventory rule in plain business language and create a structured rule from that description.

  • The agent reduces the translation effort between business policy intent and rules-framework configuration.
  • Business users get a more approachable starting point for creating inventory rules.
  • The generated rule can be reviewed in the standard rules review screen before use.

Assortment Start and End Date Loading

IPO now provides a way to load assortment start and end dates needed for product lifecycle use cases. This is important for retailers that do not use Oracle Retail Assortment Planning (APCS) but still need lifecycle dates to drive IPO behavior.

  • The dates support product lifecycle processing and initial allocation rules.
  • The benefit is that retailers can use lifecycle and initial allocation capabilities without depending on APCS‑specific assortment output.

Lifecycle Pricing Optimization (LPO) Cloud Service Enhancements

Price Modeling Workflow for Regular Pricing

Price Modeling provides a guided workflow for evaluating and preparing price changes before they are submitted for approval. The workflow helps pricing users move from an item or recommendation context into a modeling experience where they can review the relevant product, location, price, margin, lifecycle, competitor, and rule information together.

  • Users can launch Price Modeling from "Manage Recommendations - Regular" for selected or all items and directly from Price Modeling from the Task menu in all-items mode.
  • The workflow supports product and location navigation, item and price-zone selection, and modeling of price, cost, and margin outcomes.
  • Users can review lifecycle context and competitor price information while evaluating the proposed price change.
  • Existing rules, inter-item rules, and inter-location rules can be applied as part of the modeling process.
  • The experience ends with summary review and submission for approval, giving pricing teams a clearer path from recommendation to governed decision.

Typical use cases include reviewing regular prices before approval, evaluating how a price change affects margin, and checking whether competitor pricing or rule constraints should change the final recommendation.

Product Groups for Promotion and Markdown Rules

LPO rule setup now allows product groups to be used more broadly as rule criteria. Product groups were already available in selected contexts, but this release extends their use across additional categories - Sell-Through Target, Markdown and Promotion.

  • Business users can target rules to the product segments they already use to manage pricing and promotions.
  • Rules using product groups can participate in the related optimization run.
  • The benefit is more precise rule targeting without forcing users to maintain equivalent rules across less natural product hierarchy selections.

Natural Language Rules Agent

LPO introduces a Rules Agent that enables users to create pricing rules using natural language. Users can describe the intended rule in business terms and have it converted into a structured rule definition for review.

  • The capability makes rule creation more approachable for users who understand the business policy but do not want to build the rule from scratch.
  • Generated rules remain available for review in the standard rules experience before use.

Examples:

  1. For department: Men's Activewear in price zone: Sweden, season: 2023 Summer, product group: Color - Rosewood, set No. of Weeks Added to Exit Date (Reference Date Month 1):52, No. of Weeks Added to Exit Date (Reference Date Month 2-12): 26, Reference Date Type: M.
  2. For Class 3-Coffee & Tea in United States, Volume for group of items needs to be greater or equal than this value: 500. Soft priority 4.

LPO Digital Assistant - Dashboard

Added a new Pricing Optimization Key Insights dashboard that can be generated directly through the Ask Oracle conversational interface by asking a question such as, “Generate a default LPO dashboard and filter it to 24-United States price zone.” The dashboard provides an executive summary of key LPO metrics, including current versus optimal revenue, gross margin, and inventory, with department-level visualizations and the ability to drill down into departments and classes for more detailed analysis.

The enhancement also introduces optional Price Zone filtering, SQL transparency through Show SQL, quick navigation to Manage Recommendation and Run Overview, and Export to Excel support, enabling a seamless and explainable workflow from insight generation to action.

Retail Insights Cloud Service Enhancements

Transfer Up Charges

This release of Retail Insights adds transfer upcharge reporting so you can analyze the additional cost of inventory transfers and allocations, including transportation, handling, storage, freight, insurance, or other upcharges recorded in MFCS.

Retail Insights introduces W_RTL_TSF_CHRG_IT_LC_DY_FS, W_RTL_TSF_CHRG_IT_LC_DY_F, and W_RTL_TSF_CHRG_IT_LC_WK_A tables for storing transaction codes 28 and 29. The fact includes transfer or allocation identifiers, quantity, cost, and retail values, and supports reporting by item, organization, calendar, transaction code, transfer status, allocation, product organization attributes, clusters, and supplier.

New batch jobs include RDE_EXTRACT_FACT_P4_TSFCHRGILDSDE_JOB and RDE_TSFCHRGILDSDE_INITIAL_JOB (for MFCS extraction), W_RTL_TSF_CHRG_IT_LC_DY_FS_COPY_JOB and W_RTL_TSF_CHRG_IT_LC_DY_FS_STG_JOB (for flat file loads), and W_RTL_TSF_CHRG_IT_LC_DY_F_JOB and W_RTL_TSF_CHRG_IT_LC_WK_A_JOB (for data warehouse import and aggregation). You must enable and schedule the relevant POM jobs and provide transfer upcharge data in the source system before the fact will be populated. Historical extract and load programs are available in POM to migrate past transactions from MFCS or flat file to RI if required.

Inventory Cost Adjustments

This release of Retail Insights adds an inventory cost adjustments fact so you can report on cost variance activity that affects margin without changing inventory units.

Retail Insights introduces W_RTL_INVADJC_IT_LC_DY_FS, W_RTL_INVADJC_IT_LC_DY_F, and W_RTL_INVADJC_IT_LC_WK_A tables for storing transaction codes 19, 69, 70, 71, 72, and 73. The fact captures item, organization, business date, transaction code, quantity, cost, and retail values, and supports reporting by item, organization, calendar, and transaction code.

New batch jobs include RDE_EXTRACT_FACT_P7_INVADJCILDSDE_JOB and RDE_INVADJCILDSDE_INITIAL_JOB (for MFCS extraction), W_RTL_INVADJC_IT_LC_DY_FS_COPY_JOB and W_RTL_INVADJC_IT_LC_DY_FS_STG_JOB (for flat file loads), and W_RTL_INVADJC_IT_LC_DY_F_JOB and W_RTL_INVADJC_IT_LC_WK_A_JOB (for data warehouse import and aggregation). You must enable and schedule the relevant POM jobs and provide cost adjustment data in the source system before the fact will be populated. Historical extract and load programs are available in POM to migrate past transactions from MFCS or flat file to RI if required.

Source Parent Allocation ID Reporting

This release of Retail Insights adds the MFCS source parent allocation ID to allocation data so you can connect allocations created by another system, such as from IPO, back to their original source records.

Retail Insights loads SOURCE_PARENT_ALLOC_ID into W_RTL_ALC_DETAILS_DS and W_RTL_ALC_DETAILS_D and exposes the value as Source Parent Alloc Number in the Allocation dimension. File-based and intraday allocation loads also support the new field.

The enhancement is ready to use when the source application sends the field. Non-MFCS integrations can populate SOURCE_PARENT_ALLOC_ID in W_RTL_ALC_DETAILS_DS.dat when they need the same traceability.

Allocation Intercompany Unit Cost

This release of Retail Insights adds allocation transfer price support so you can report on allocations where the intercompany cost differs from the current weighted average cost.

Retail Insights maps the MFCS TSF_PRICE value to IC_UNIT_COST_AMT_LCL on W_RTL_ALC_IT_LC_DY_FS and W_RTL_ALC_IT_LC_DY_F. The value is available through batch, file-based, and intraday allocation loads.

A new measure Allocation Intercompany Unit Cost is exposed in as-is and as-was reporting. The metric is ready to use when MFCS or the file interface provides the new field

Simple Pack Attributes

This release of Retail Insights adds simple pack item attributes to product nightly and intraday loading so non-MFCS integrations can include the same pack information as the existing MFCS-to-RI batch design.

This change adds SIMPLE_PACK_ITEM and SIMPLE_PACK_QTY to the W_PRODUCT_DTS table and related product intraday streaming tables. These values map to W_PRODUCT_ATTR_DS.PRODUCT_ATTR18_NAME and W_PRODUCT_ATTR_DS.PRODUCT_ATTR4_NUM_VALUE for product reporting and downstream use. MFCS integration already populates these fields in the nightly batch, this update only adds the columns for other sources of data to begin populating them if required.

Location Latitude and Longitude

This release of Retail Insights adds latitude and longitude attributes for organization reporting so you can build map-based views and support location-based analytics.

This change adds columns LATITUDE and LONGITUDE into W_INT_ORG_DTS, W_INT_ORG_ATTR_DS, and W_INT_ORG_ATTR_D. The attributes are exposed as Loc Latitude and Loc Longitude in Organization As-Is and As-Was.

The attributes are ready to use when MFCS or your file/API integration provides the coordinates for each location.

Store Conditions

This release of Retail Insights adds store condition reporting so you can analyze store operations and sales patterns in the context of weather events, natural disasters, geopolitical instability, or other conditions that affect normal store operations.

Retail Insights introduces W_RTL_LOC_COND_DS and W_RTL_LOC_COND_D tables, which are standalone interfaces for this release. This interface is only populated via custom inserts from Innovation Workbench, it does not have a nightly batch RDE extract. The LOAD_LOC_COND_D_ADHOC process is added in POM to enable on-demand loads of the dimension table, and W_RTL_LOC_COND_D_JOB will populate it in nightly batch based on data inserted to the W_RTL_LOC_COND_DS staging table.

The Organization dimension in RI exposes new attributes Store Condition, Store Condition Desc, Store Condition Start Date, and Store Condition End Date.

Pricing Last Week and Last Year Metrics

This release of Retail Insights adds last week and last year pricing metrics so you can compare current pricing against prior-week and prior-year values in the Pricing fact.

The release adds Original Price LW, Original Price LY, Last Regular Price LW, Last Regular Price LY, Last Markdown Price LW, Last Markdown Price LY, Price LW, and Base Cost (Price) LW. The metrics are available in as-is and as-was reporting after upgrade.

Retail Predictive Application Server Cloud Edition Server Enhancements

This section includes RPAS CE workspace, administration, explainability, and Planning Platform configuration enhancements. Planning Platform configuration capabilities are presented here because Solution Designer and Workflow Manager are part of the RPAS CE configuration and administration experience.

Enhanced Position Level Security

RPAS CE position-level security has been enhanced to support read-only access for selected positions while preserving full read/write access for other positions. This allows administrators to support business roles where users need visibility across broader areas of the hierarchy but update responsibility only for selected positions. The result is a more flexible security model for planning teams that need shared visibility without granting unnecessary update access.

Measure-Level GenAI Explainability for RPAS Planning Data

When enabled and configured, RPAS CE supports GenAI explanations for planning data and selected AI-driven measures in AP and MFP workspaces. Planners can select a view, dataset, or measure cell and invoke an explanation that summarizes key trends, variances, anomalies, or drivers in plain language.

  • The feature is disabled by default and must be enabled/configured before use.
  • Users can understand likely drivers behind a value without leaving the planning workspace.

  • This reduces manual data mining and supports faster review of plan health

Workbook Deletion by Last Opened Timestamp

RPAS CE now supports workbook cleanup based on the last opened timestamp. Administrators can remove workbooks older than a selected age criterion instead of coordinating manual cleanup user by user or relying on slower UI/back-end processes.

  • The cleanup process helps maintain a cleaner set of active workbooks in the application.
  • Reducing inactive workbook data can improve workbook build, recalculation, and batch processing efficiency.
  • Administrators can manage cleanup more consistently using timestamp-based criteria.

Revised RPAS Workspace UI

The RPAS workspace user experience has been refreshed to improve navigation, workspace usability, and available screen space. The update brings several workspace and view-management changes together so users can move through configured workflow steps and work with planning information more efficiently.

  • Revised workflow navigation and top-level action buttons make common actions easier to access.
  • Workspace tabs, a view management drawer, and drag-and-drop view assignment improve how users organize views.
  • Configurable one-to-four pane layouts, pane resizing, pane swapping, and auto-collapse behavior help users make better use of screen space.

  • Manage View ordering and drag-and-drop a view to show an Add Panel target and open it in a new pane.

Solution Designer

Planning Platform introduces a new configuration toolset organized around Solution Designer and Workflow Manager. Solution Designer is the standalone configuration tool used to manage base solution and custom module configuration, giving system integrators and administrators a more visible way to maintain delivered and customized planning content. Instead of manually repeating the same setup across releases or customer implementations, implementers can save configuration decisions as reusable base setting & custom module files and apply them again when needed. This tool is available as part of the Starter Kit.

  • Base solution configuration includes dimensions, roles, base intersections, modules, and styles.
  • Custom module configuration includes components, measures, rules, tasks, alerts, and custom menus.
  • The tool reduces reliance on manual configuration file updates and makes configuration changes easier to understand and govern.
  • It also helps implementation teams keep delivered base configuration separate from customer-specific customization, reducing rework and improving control over configuration changes.

Workflow Manager

Workflow Manager is the second part of the new Planning Platform configuration toolset accessible from the RPASCE UI. It allows administrative users and system integrators to manage the workflow experience that planners see in the application, without relying heavily on back-end configuration changes.

  • Enables to configure Task flows, Available measures, and Temporary measures without rebuilding the full application configuration.
  • Taskflow configuration can be managed across activity, task, step, tab, and view levels.
  • Available Measures lets users select realized measures and update task-level properties
  • Temporary measures allow to create additional calculated measures that appear in the application UI without adding requiring permanent configuration change. Supports creation of Contribution, Variance & Custom Calculation measures.
  • The benefit is a clearer, application-level way to maintain workflow configuration for planners.
  • It reduces dependency on full configuration rebuilds, supports customer-specific workflow tailoring, improves governance, and makes it easier to move workflow changes across environments.

Assortment Planning Cloud Service Enhancements

Smart Item Flow

Smart Item Flow introduces AI-supported recommendations into the Assortment Planning item flow process for short life cycle items. Item Flow is used to create the weekly sales plan for assorted items based on AI driven recommendation of the weekly sales flows.

  • AP can receive recommended weekly sales flow from AI Foundation by week, style-color, and store cluster.
  • Recommendations use inputs such as sales potential, product attributes, store clusters, assortment period, historical flow, and user-defined planning constraints.
  • Planners can use the recommendation as a starting point, continue to manually create update sales and generate receipts using the current process. Store exceptions can still be planned where a different weekly flow is needed.

Size Breaks for Receipts

Assortment Planning now supports breaking style-color receipt quantities into size level/ SKU receipt quantities before export. For short life cycle items, AP creates receipt units by week, style-color, and store. Some retailers need those receipts broken down to size before commitments or purchase orders are created in the execution systems.

  • A new Receipts by Size workspace uses size profile information from AI Foundation Size Profile Optimization to spread style-color receipts to SKU/store/week.
  • Users can review the size contribution percentages used in the spread and choose whether to calculate size breaks by week or across the full delivery window.
  • After reviewing rounding impact, users can approve SKU receipt quantities and make the approved SKU-level receipt plan available for export.

AP Planning Administration Workspace Simplification

The Assortment Planning administration workspace has been streamlined to simplify key setup workflows and remove administration views and processes that are no longer required.

The following workspace updates are included:

  • Product Attribute Type is now available in the wizard.
  • The Product wizard planning level changes from Department to Class.
  • A Location wizard is now available at the Channel level.
  • The Assign Product Attributes view and its supporting measures are removed. The Base Unit Price/Cost view and its supporting measures are removed. These values can instead be maintained for placeholders through the existing Assortment Planning/Item Flow workflow.
  • The Planning Administration automatic weekly build batch process is removed.

Customers should review any procedures or automation that rely on the removed views or weekly build process.

Merchandise Financial Planning (MFP) Cloud Service Enhancements

MFP Modular Configuration

MFP configuration is being rebuilt into modular configuration content managed through the updated Planning Platform configuration tools. Instead of treating the full delivered solution as one large configuration set, MFP content is organized into modules that represent major planning areas, workflows, roles, and metric families.

  • Retailers and system implementers can assemble and maintain configuration in smaller, more understandable units.
  • Modules support clearer ownership of delivered and customer-specific configuration.
  • The modular structure creates a better foundation for future solution assembly, upgrades, and implementation work.

Updated MFP Tasks and Workflow

MFP configuration is being rebuilt into modular configuration content managed through the updated Planning Platform configuration tools. Instead of treating the full delivered solution as one large configuration set, MFP content is organized into modules that represent major planning areas, workflows, roles, and metric families.

  • Retailers and system implementers can assemble and maintain configuration in smaller, more understandable units.
  • Modules support clearer ownership of delivered and customer-specific configuration.
  • The modular structure creates a better foundation for future solution assembly, upgrades, and implementation work.

MFP-LPO Integration Enhancement for Markdown Budget

The existing integration between MFP and LPO has been enhanced so MFP can send an aggregated in-season markdown budget for a defined period. This is an enhancement to the existing integration rather than a new integration flow.

  • LPO receives a budget signal that represents the defined remaining period rather than only isolated weekly values.
  • The enhancement helps keep financial planning and markdown optimization aligned as the season progresses.
  • Pricing teams can use the updated budget view when evaluating markdown recommendations that need to stay within the available plan.