Assortment Performance Analysis
AI-driven analysis of SKU performance by category, attribute, and price tier to optimize product mix and identify underperforming items
Why This Matters
What It Is
AI-driven analysis of SKU performance by category, attribute, and price tier to optimize product mix and identify underperforming items
Current State vs Future State Comparison
Current State
(Traditional)Merchandisers manually export sales data by SKU into Excel spreadsheets, create pivot tables to analyze performance by category and attribute, and manually identify slow-moving items. They compare sell-through rates across price tiers using basic formulas and create PowerPoint presentations with findings. The analysis typically covers 10-20% of the assortment due to time constraints and relies heavily on historical averages rather than predictive insights.
Characteristics
- • ERP Systems
- • Excel and Spreadsheets
- • Assortment Planning Software (e.g., Centric Planning, RELEX Solutions)
- • Business Intelligence Tools (e.g., Tableau, Power BI)
- • AI and Machine Learning Platforms
- • Communication Tools (e.g., Email, Collaboration Platforms)
Pain Points
- ⚠ Data Silos and Disconnected Systems
- ⚠ Manual Processes leading to inefficiencies
- ⚠ Overstock and Stockouts due to poor inventory management
- ⚠ Limited Localization affecting assortment effectiveness
- ⚠ Complexity in SKU Rationalization
- ⚠ Lack of Real-Time Insights for timely decision-making
- ⚠ Legacy tools and spreadsheets create fragmented data
- ⚠ Time-consuming manual SKU evaluation limits agility
Future State
(Agentic)An Assortment Intelligence Orchestrator coordinates analysis across the entire product catalog in real-time. A Performance Analysis Agent applies ML models to identify performance patterns across all SKUs, considering seasonality, trends, and external factors. An Attribute Intelligence Agent analyzes performance by product attributes (color, size, material, brand) to identify winning combinations. A Price Tier Agent segments products into micro-tiers and evaluates elasticity and margin contribution. A Recommendation Engine Agent generates specific actionable recommendations for assortment optimization, including items to add, remove, or reposition.
Characteristics
- • POS systems
- • ERP systems
- • External market data
- • Customer behavior analytics
Benefits
- ✓ 50% time reduction in SKU evaluation due to automation of data collection and analysis.
- ✓ Error reduction of up to 70% in performance classification through AI-driven analysis.
Is This Right for You?
This score is based on general applicability (industry fit, implementation complexity, and ROI potential). Use the Preferences button above to set your industry, role, and company profile for personalized matching.
Why this score:
- • Applicable across multiple industries
- • Moderate expected business value
- • Time to value: 3-6 months
- • (Score based on general applicability - set preferences for personalized matching)
You might benefit from Assortment Performance Analysis if:
- You're experiencing: Data Silos and Disconnected Systems
- You're experiencing: Manual Processes leading to inefficiencies
- You're experiencing: Overstock and Stockouts due to poor inventory management
This may not be right for you if:
- Requires human oversight for critical decision points - not fully autonomous
Parent Capability
Performance Management
Continuous performance feedback and development with real-time goal tracking, 360 insights, and predictive attrition alerts.
What to Do Next
Related Functions
Metadata
- Function ID
- assortment-performance-analysis