Friday Jan 10, 2014

Documentation in Oracle Retail Advanced Science Engine 14.0

Oracle Retail Advanced Science Engine (ORASE) is the centralized science engine that powers analytics for both the Oracle Retail Modeling Engine (ORME) and Oracle Retail Assortment and Space Optimization (ORASO) in support of retail business processes.

ORME performs data mining and calculates model parameters to support business processes in Oracle Retail Category Management, Oracle Retail Demand Forecasting (RDF), and Oracle Retail Analytics.The ORME 14.0 release contains the following modules: Customer Decision Tree, Demand Transference, Advanced Clustering, and Market Basket Analysis (a back-end process only). ORME solutions share a common workflow and user interface (UI). The common workflow lets users implement and interact with the new science modules using similar techniques. 

ORASO is a separate application that is used to optimize the use of space in a location or store cluster for a retailer’s product assortments.

 This new suite of products provides the functionality described below.

Customer Decision Tree

Customers make purchasing decisions by the characteristics, or attributes, of the competing products they are considering.  Because customers purchase products by attributes, retailers can understand customer purchasing behavior by understanding how customers perceive the attributes by using the Customer Decision Tree module. A customer decision tree presents, in tree form, a hierarchy of attributes. The level of each attribute within the tree indicates the relative importance a customer places on each attribute when deciding what to purchase.

The CDT application uses historical transaction data from the retailer to derive a customer decision tree, which segments the products by attributes. The application provides a measure called the CDT score that indicates how good a generated customer decision tree is. Retailers can analyze their product assortments using the information provided by the application in conjunction with the standard merchandise hierarchies.

Demand Transference

Demand Transference allows retailers to understand customer purchasing behavior in terms of item substitutability and to improve assortments by knowing how items in the assortment may substitute for each other. With the information provided by the application, retailers can optimize assortments to available space. In addition, retailers can understand how total category sales may be affected by assortment changes. Demand Transference can also demonstrate how total category sales are affected by assortment changes. It can show whether adding items to the assortment may result in large or small increases in total category sales.

Advanced Clustering

Advanced Clustering allows retailers to group locations based on product and store selling characteristics and other key attributes. The resulting clusters can be used to drive assortment, pricing, promotion, forecasting, allocation, and supply chain processes. Retailers can target specific customers by understanding customer characteristics, including the profile mix of who is shopping in the store or trading area and customer demographics such as ethnicity, income levels, education, household size, and family status.

Market Basket Analysis

Market Basket Analysis employs data mining to provide insight into the correlation among products in a customer's basket.

ORASO

ORASO is used by Category Management to make optimized assortment decisions. It is used to optimize the space for a category manager’s preliminary assortment. The category manager creates a preliminary assortment and wants to determine how well that list of products can fit in stores, given the available space, product sizes, and merchandising goals and rules. ORASO creates virtual planograms that organize products onto shelves according to these requirements in a way that optimizes total performance. 

Highlighted End User Documentation Updates

The documentation set for this new suite of products is described below.

Oracle Retail Advanced Science Engine Implementation Guide

The Implementation Guide provides detailed instructions regarding the configuration and implementation of ORME and ORASO. These details include WebLogic, database, user, and module-specific configurations, as well as information about data interfaces, ETL batch scripts, and database schemas.

Oracle Retail Advanced Science Engine Security Guide

The Security Guide describes the implementation of the required security features for ORME and ORASO. These include securing access to the applications and managing any security vulnerabilities.

Oracle Retail Modeling Engine Installation Guide

The Installation Guide describes the pre-installation setup procedures for the database, application server, and password stores, and provides detailed procedures for installing the application.

Oracle Retail Modeling Engine User Guide

The User Guide provides an orientation to the ORME user interface. In addition, it describes in detail how to configure the application based on specific retailer constraints and how to interpret the analytical results of the calculations performed by Customer Decision Tree, Demand Transference, and Advanced Clustering.

Oracle Retail Assortment and Space Optimization Installation Guide

The Installation Guide describes the pre-installation setup procedures for the database, application server, and password stores, and provides detailed procedures for installing the application.

Oracle Retail Assortment and Space Optimization User Guide

The User Guide provides an orientation to the ORASO user interface. In addition, it describes in detail how to configuration the application based on specific retailer constraints and how to interpret the analytical results of the space and assortment optimization performed by the application.

Wednesday May 29, 2013

Documentation in Oracle Retail Category Management, Release 13.4.1

The 13.4.1 release of Oracle Retail Category Management is a completely new solution and is only available for use with the Oracle Retail Predictive Application Server (RPAS) Fusion User Interface. This solution supports the development of category business plans and broadly follows the traditional Category Management business process. Oracle Retail Category Management brings in the contemporary best-practices from the retail industry as part of its functionality. The key differentiating factors of Category Management, which facilitate decision making in the category management business practice, include the following:

  • Consumer Segment perspective based on demographics and psychographics 
  • Market, competition, and household customer perspectives based on external data sourced from third-party data aggregation companies
  • Item Performance Index (IPI) to rank item's/product category's performance
  • Consumer Decision Trees to understand the consumer's buying process based on consumer segments so as to align the retailer's offerings accordingly

Oracle Retail Category Management consists of the following modules:
  • Category Planning enables the retailer to perform higher-level category planning activities.
  • Assortment Planning and Rationalization enables a retailer to analyze their current assortment, determine appropriate market coverage, and rationalize and quantify assortment decisions for both store clusters and at the individual store level.

Highlighted End User Documentation Enhancements

  • Oracle Retail Category Management User Guide for the RPAS Fusion Client
    This guide includes a chapter for each task in the taskflow. For each task, the chapter is further organized by the steps, tabs, and views available for that task. The tabs within a step group views together based on related purpose. For each view, a screenshot and list of the measure labels available in that view are provided. Taskflow diagrams for the Category Planning, Assortment Rationalization by Cluster, and Assortment Rationalization by Store tasks are included. A Glossary and an Appendix contain descriptions for measure labels.
  • Oracle Retail Category Management Implementation Guide
    This guide describes post-installation tasks that need to be performed in order to bring Category Management online and ready for production use. The document is addressed to an implementer who understands the interface requirements of the integrated applications and data sources for the master data, demand, and inventory history. The Implementation Guide addresses the following topics:
    • Implementation Considerations
      An overview of the factors that need to be considered when planning the implementation, including data requirements, hardware issues, and security.
    • Build Scripts
      A discussion of the setup that is required before building the Category Management domain. This includes environment variables, required hierarchy and data files, and the build script for the domain.
    • Data Flow
      An overview of the flow of data between Category Management and other applications (external source, data aggregator, and merchandising system).
    • Script Integration
      A discussion of the export script used for exporting data from Category Management and the import script used for importing data into Category Management.
    • Configuration Considerations
      Details about changing the configuration of the Category Management hierarchies.
    • Batch Processing
      A summary of the scripts and rule groups used to maintain Category Management through batch processing.
    • Internationalization
      An overview of how Category Management addresses Localization (translations, for example) and Internationalization.
    • Data
      A list of Category Management measures to assist when planning the data that must be loaded into each measure.

List of End User Documents in Category Management, Release 13.4.1

The following documents are included in release 13.4.1:

  • Oracle Retail Category Management Release Notes
  • Oracle Retail Category Management Installation Guide
  • Oracle Retail Category Management Implementation Guide
  • Oracle Retail Category Management User Guide for the RPAS Fusion Client

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