Assortment Planning and Space Optimization Presentation
View the deck, Business Scenario Demonstration for Oracle Retail Assortment Planning & Space Optimization, presented to The Container Store team on July 15, 2022.
Business Scenario Demonstration Assortment & Space Planning
Kevin Walsh
Jim Hostler
Rachel Lewis
Oracle Retail
July 15, 2022
Agenda
[Date]Copyright © 2022, Oracle and/or its affiliates | Confidential: Internal/Restricted/Highly Restricted2
3 Store Clustering Demo
Demonstration of
the Store Clustering
Scenarios
2 Assortment Planning Demo
Demonstration of
the Demo Scenarios
related to
Assortment
Planning
5 Recap & Next Steps
Follow-up with a
recap of Why Oracle
Retail is the best
choice for The
Container Store
4 Space Optimization
Demonstration of
the Space Planning
Scenarios
1 Introductions and Business Process
Overview of the
Assortment
Planning Business
Process
Copyright © 2020, Oracle and/or its affiliates | Confidential: Internal/Restricted/Highly Restricted3
The Platform for Modern Retail
Retail Home BUSINESS KPI’S ADMINISTRATIVE MONITORING NOTIFICATIONSSERVICE PORTAL
Oracle Cloud Infrastructure / Next-Gen Architecture STORAGENETWORKING COMPUTE CONTAINER ORCHESTRATIONCONTAINERS
Retail AI Foundation
Forecasting
Engine
Affinity
Analysis
Profile
Science
Customer
Decision Trees
Demand
Transference
Innovation
Workbench
Attribute
Extraction
Advanced
Clustering
Customer
Segmentation
Retail Cloud Services
Merchandising
Inventory
Operations Brand
Compliance Planning
Store
Operations
Order
Broker
Analytics
Order
Management
Supply Chain Customer
Engagement Retail
Extensibility
Low-code App
Development
REST Data
Services
Cloud
Extensions
Retail Data Store AUTONOMOUS DATA WAREHOUSE DATA MANAGEMENT RETAIL SCHEMA EXTENSIONSPACKAGED RETAIL SCHEMAS
Retail Reference
Model
Business
Process Flows
Glossary
Technical
Models
Space & Assortment Planning
Copyright © 2022, Oracle and/or its affiliates
SERIES Collaborative & Data-Driven Planning
Beth Inventory Analyst
Jill Category Manager
Mei Planner
Merchandise Financial Plans are Created
Assortment & Space Plans
Created
Item Plans Created/Maintained
Allocation & Replenishment
Execution
Ivan Replenishment
Analyst
Ori AI Foundation
Refine Options By Attribute
Review Assortment Framework
Plan Buy Quantities
Optimize Skus by Planogram Constraints
Merchandise Financial Plans are Created
Determine # of Options by
Subclass
Hindsighting & Performance
Review
SERIES Collaborative & Data-Driven Assortment Planning
Placeholder Planning / Product Lifecycle
Management
Apply Demand Transference &
Optimization
Create Assortment Framework
Refine & Plan Assortment Buy
Refine to Space Constraints
Alex Buyer
Ivan Planner
Beth Inventory Analyst
Refine Replenishment Eligibility
Ori AI Foundation
Assortment Planning
Scenario Number Scenario Description
SA 8 Reconciliation with Demand Planning
SA 9 Reconciling top-down financial plans to detailed store cluster/store plans
SA 16 Building differentiated assortments for store clusters
SA 17 Suggesting new SKUs to optimize the assortment mix
SA 18 Managing assortment changes. Plug and Play: Replacing a current SKU with new skus. Evaluating the impact to that change.
SA 19 Introduction of Capsule collections or limited buys: Plan for newness, evaluate the potential sales impact.
SA 23 Understanding product affinities to build better assortments
Copyright © 2022, Oracle and/or its affiliates
Assortment Planning
Scenario Number Scenario Description
SA 20 Seasonal Assortments: Quantify buys based on short lifecycle
SA 21 “What if” scenario planning with real and TBD SKU’s
SA 22 Testing merchandising strategies – category extensions, new categories, pricing, product placement, etc.
SA 23 Understanding product affinities to build better assortments
SA 24 Building space-aware assortments
SA 25 Measuring our success with configurable metrics and dashboards
SA 15 Creating and managing category roles: Balancing assortments by different attributes/category roles.
Copyright © 2022, Oracle and/or its affiliates
What Can We Configure in the Planning Solutions? Providing retailer-specific solutions in the cloud without leaving the upgrade path
• Hierarchies
• Measures
• Rules / Business Logic
• Planning Process & Layout
• Dashboards
9 Copyright © 2022, Oracle and/or its affiliates | Confidential: Internal/Restricted/Highly Restricted [Date]
[Date]Copyright © 2022, Oracle and/or its affiliates | Confidential: Internal/Restricted/Highly Restricted10
[Date]Copyright © 2022, Oracle and/or its affiliates | Confidential: Internal/Restricted/Highly Restricted11
Category Planning - Industry Best Standards
Destination
RoutineConvenience
Seasonal / Occasional
C u
s to
m e
r P
e n
e tr
a ti
o n
Purchase Frequency
Maintain Cash Machine Flagship
Rehab Under Fire Core Traffic
G ro
s s M
a rg
in %
Sales Dollars ($)
Market Data Driven Role Assignments
Retailer Data Driven Role Assignments
High
HighLow
High
HighLow
A Single / Central Enterprise Clustering Solution
• Leverage customer insights to localize planning & execution processes; driving a notable increase in sales / customer satisfaction
• Dynamic and flexible allowing the ability to dynamically cluster at multiple hierarchy levels Leverage multiple clustering approaches
• Key insights enable workload prioritization
• Identify the optimal # of clusters
• Embedded scoring logic to assess the quality of store clusters
• Use What-If capabilities to identify the optimal clusters
Store BaseStore Base
Store Clustering
Confidential – © 2022 Oracle Internal/Restricted/Highly Restricted
Store Clustering Cluster Criteria
Customer Profiles • Segments • Demographics • Customer Behaviors • Trips & Spend • Etc.
Store Attributes • Population Density • Income • Climate • Store Format • Etc.
Product Attributes • Brand • Color • Size/Fit • Seasonality • Etc.
Product Performance •Sales Revenue •Sales Units •Gross Margin $ •Etc.
Consumer Profiles •Market Demographics •Market Customer Behaviors •Market Trips & Spend •Etc.
Product Forecast •Forecast Sales Unit •Forecast Sales $ •Forecast Gross Margin $ •Forecast Gross Margin % •Etc.
Mixed Attributes
•Discrete data •Continuous data •Mix together
Confidential – © 2022 Oracle Internal/Restricted/Highly Restricted
http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRxqFQoTCLfR34jShskCFUPjYwodvK4Adg&url=http://www.dynamic-concepts.nl/en/segmentation/&bvm=bv.106923889,d.cGc&psig=AFQjCNGX--x-WWDHKB7oe4PY2jdSEICLpQ&ust=1447271861459494
Store Clustering
Scenario Number Scenario Description
SA 1 Create Clusters: Constrain by space and utilize sales history by store/product category to group.
SA 2 Create Clusters: Modification/adjustment of clusters. Timing and flexibility
SA 3 Manage Clusters: Manage exceptions without full statistical re-run
SA 4 Manage Clusters: New Stores
SA 5 Creating traditional format-based store clusters
SA 6 Creating “intelligent” store clusters: Using store attributes and product performance statistically
SA 7 Connect clusters to assortments and replenishment
Copyright © 2022, Oracle and/or its affiliates
Demo
Copyright © 2022, Oracle and/or its affiliates
Assortment Space Optimization
Scenario Number Scenario Description
SA 10 Assortments and Planograms: Pull items from assortments into planograms
SA 11 Fixture management: Assign fixtures with facings and depth. Evaluate productivity by fixture.
SA 12 Store Presentation, product at the shelf
SA 13 Planograms: Visualized output for stores and merchants
SA 14 Planograms: Vendor communication
Copyright © 2022, Oracle and/or its affiliates
Demo
Copyright © 2022, Oracle and/or its affiliates
Assortment Planning
Scenario Number Scenario Description
SA 26 Endless Aisle
Copyright © 2022, Oracle and/or its affiliates
Why Retailers Choose Oracle for Assortment Planning
AI Foundation Agility Automation What-if scenario
modeling &
simulation-
Extensibility Scalability User Adoption Continuous
Delivery