1 DATASHEET | Oracle Retail Inventory Optimization Cloud Service

Version 1 Copyright © 2022, Oracle and/or its affiliates

Oracle Retail Inventory

Optimization Cloud Service

Inventory is a retailer's most significant financial investment. It is also the

most complex to manage efficiently. Consumers have instant access to

product availability, and the retailer that fulfills wins the sale and their

loyalty. The right strategy is a balancing act between the cost of inventory

and service to customers.

However, in the real world, the execution of the best inventory strategy is

susceptible to surprises and excess inventory and reduction of service levels

are inevitable. Often retailers have outdated replenishment solutions with

strategies that do not take forecasting into consideration. Setting an

inventory strategy without insight into forecasting is a risky proposition.

Oracle Retail Inventory Optimization Cloud Service adds intelligence to a

retailer's existing solutions to drive scalable execution of inventory

strategies. Define the strategies, and the system will do the work.

Retailers continue to face the fundamental need to position inventory at the

right place, at the right time, and in the right quantities. As the focus on the

customer and the flexibility in supply chains increases, so must the

emphasis on inventory strategies that can scale.

MAXIMIZING INVENTORY PRODUCTIVITY AND

OPTIMIZING WORKING CAPITAL

Oracle Retail Inventory Optimization Cloud Service pairs with the Oracle Retail AI

Foundation, which provides analytical insights to drive planning, buying, moving and

selling decisions. These capabilities enable retailers to drive profit and remain flexible

to the changing retail environment. Oracle Retail Inventory Optimization Cloud

Service maximizes the productivity of inventory across the entire supply chain, with a

self-learning and self-tuning approach to optimizing working capital.

The solution helps retailers to optimize the daily replenishment decision, aligning the

actual service level to the targets with the minimum amount of inventory. It also

drives a reduction in working capital (mainly inventory), freeing up cash that could be

re-invested more strategically.

Key Benefits:

 Reduces inventory - one-time

inventory reduction up to 20%

 Reduces working capital and

inventory handling cost

 Increases service level up to

5% and revenue up to 3%

 Provides results in 3-6 months

 Increases in-stock availability

 Increases end-user

productivity and emphasis on

strategies

1 DATASHEET | Oracle Retail Inventory Optimization Cloud Service

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VALUE DRIVERS

An average grocery retailer, with 30,000 SKUs and at least 1,000 stores, will have

millions of SKU store combinations. Determining the optimal replenishment plan

without the help of industry-leading science is near impossible. Retailers will need to

leverage AI to do the heavy lifting at scale, since people can’t scale like AI. Oracle

Retail Inventory Optimization Cloud Service enables retailers to reap the rewards of

AI, at scale, without changing the existing replenishment system.

ORACLE CLOUD INFRASTRUCTURE

All Oracle Retail Analytics and Planning cloud services are deployed as cloud-native

Software-as-a-Service solutions within Oracle Cloud Infrastructure (OCI) upon

Oracle’s Autonomous Data Warehouse, and are based upon an architecture and

technology stack that is optimally engineered for rapid, low-cost deployments and

exceptional performance and scalability, and the highest levels of system availability

and security - from storage to scorecard.

ORACLE RETAIL AI FOUNDATION

Core retail AI and machine learning (ML) powers all Oracle Retail Analytics and

Planning cloud services. For example:

 Forecasting Engine - Provide an intelligent starting point for your

planners, increasing automation and accuracy. Move to a more touchless

and exception management planning process.

 Customer Segmentation - Group customers based on attributes,

behaviors, and transactions to tailor offers, pricing, and assortments

accordingly, incorporating previously hidden patterns in your data.

 Advanced Clustering - Cluster your stores based upon traditional

approaches of volume, square footage, region, etc., or leverage machine

learning techniques to cluster stores based upon similar selling patterns,

truly creating a customer-centric assortment.

 Profile Science - Determine the best size ratio for your buys by

understanding the true demand of your sizes while considering stock-outs.

 Attribute Extraction and Binning - Extract item attributes from free-form

descriptions, correcting short forms, misspellings, and other

inconsistencies, and apply them to Demand Transference, Customer

Decision Trees, Advanced Clustering, and more.

 Customer Decision Trees - Understand how your customers are shopping

your assortments to drive attribute-based alternate hierarchies and

effectively plan your assortment the way your customer shops.

 Demand Transference - Understand how unique your items are and the

incremental revenue that item brings to determine the most optimal

assortment for your customer.

 Affinity Analysis - Determine how items interact with each other to drive a

more effective promotional strategy within your financial planning process.

 Innovation Workbench - Leverage open source along with your data

science team to create your own AI and ML models. Utilize the language of

your choice with Jupyter/Zeppelin notebooks.

Key Features

 Continuously optimizes the

replenishment parameters at

the item-location level

allowing retailers to achieve

target service level with

minimum inventory

 Leverages advanced self-

learning science and

automatically adapts to

market changes and patterns

 Embeds an automatic

forecasting algorithm

 Enables end-users to interact

with strategies and

recommendations

 Provides transparency to

recommendations and

underlying predictions

 Implements quickly with a

high ROI and short payback

 Enhances the legacy

replenishment solution

without replacing it

 Minimizes IT and

organizational disruption

 Embedded Retail AI Foundation,

powering Oracle Retail Demand

Forecasting Cloud Service with:

o Forecasting Engine

o Customer Segmentation

o Advanced Clustering

o Profile Science

o Attribute Extraction &

Binning

o Customer Decision Trees

o Demand Transference

o Affinity Analysis

o Innovation Workbench

 Further extensibility with:

o Oracle Retail Home

o Oracle Analytics

o Oracle Application Express

o Oracle REST Data Services

o Oracle Machine Learning

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ORACLE RETAIL HOME

Oracle Retail Home is a single access point, to simplify a user’s interactions with the

data and applications that are most relevant to their roles, and to better empower them

to anticipate informed actions, and to inspire engagement.

Based on a robust and flexible portal framework, Retail Home is intended first to

provide timely and role-specific high-level insights, and second to enable selectively

drilling into relevant applications for more details.

ORACLE ANALYTICS

Oracle Analytics can be used to generate and consume analytics from Oracle Retail AI

Foundation data, and in turn can also surface dashboards to Oracle Retail Home.

Oracle Analytics is a comprehensive platform that parlays data into information to

provide business insights, federating a broad array of features to suit business users,

power-users and data scientists:

Governed Self-Service Augmented

 Corporate Dashboards  Data Preparation  Natural Language Processing

 Pixel Perfect Report  Data Visualization  Voice and Chatbot

 Semantic Models  Storytelling  Data Enrichment

 Role-based Access Control  Sharing and Collaboration  One-Click “Explain”

 Query Federation  Mobile Apps  Adaptive Personalization

The Oracle Retail Analytics and

Planning family of cloud services

includes:

 Oracle Retail AI Foundation

 Oracle Retail Insights

 Oracle Retail Assortment and Space

Optimization

 Oracle Retail Promotion and

Markdown Optimization

 Oracle Retail Offer Optimization

 Oracle Retail Merchandise Financial

Planning

 Oracle Retail Assortment Planning

 Oracle Retail Demand Forecasting

 Oracle Retail Inventory Optimization

https://video.oracle.com/detail/video/5828487828001

Beyond the extensibility afforded by the Oracle Retail AI Foundation’s Innovation

Workbench, Oracle Analytics, and Oracle Retail Home, these areas are also included:

ORACLE DATA STORE AND APPLICATION EXPRESS

Oracle Retail Data Store can supply data for Oracle Application Express (APEX) apps

and Oracle REST Data Services, which both are included. APEX is a low-code

development platform that enables you to build scalable, secure enterprise apps with

world-class features that can be deployed anywhere.

Developers can quickly develop and deploy compelling apps that solve real problems

and provide immediate value using APEX. You won't need to be an expert in a vast

array of technologies to deliver sophisticated solutions. Focus on solving the problem

and let APEX take care of the rest.

ORACLE REST DATA SERVICES

Oracle REST Data Services bridges HTTPS and your Oracle Database, providing,

among other things, a REST API, SQL Developer Web, a PL/SQL Gateway, SODA for

REST, and the ability to publish RESTful Web Services for interacting with the data and

stored procedures in your Oracle Database.

ORACLE MACHINE LEARNING

Oracle Machine Learning supports data exploration, preparation, and machine

learning modeling at scale using SQL, R, Python, REST, Auto ML, and no-code

interfaces. It includes more than 30 high-performance in-database algorithms

producing models for immediate use in applications.

By keeping data inside the database, organizations can simplify their overall

architecture and maintain data synchronization and security. It enables data scientists

and other data professionals to build models quickly by simplifying and automating

key elements of the machine learning lifecycle.

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