Partner webinar
Transforming Retail and Supply Chain Planning with Pigment AI
Nigel Gale
Partner
Sean Culligan
Director
James Aldrich
Enterprise Account Executive
Pigment is a leading alternative for strategic planning
Anaplan
Pigment natively integrates with over 30 business applications (ERP, CRM, HRIS, BI solutions and more).
Native integrations are limited to fewer than 10 business applications using the Anaplan Data Orchestrator.
Pigment is a natively sparse engine and workspaces are not limited in capacity.
Standard Workspace size is limited, and additional products may be purchased to manage larger volumes of data up to a limit of 720GB.
Data is shared across business functions without needing to manage imports between models.
Data imports must be set up and maintained to copy data across multiple models.
Data updates happen automatically, without end users needing to trigger a data refresh for real-time planning and visibility of changes.
End users must refresh their pages to see the effect of data updates by other users while working in the same model.
Data inputs can be made by end users while imports and data recalculations are in progress.
End users are prevented from making changes to the model while data imports, exports and susbtantial recalculations are in progress.
Join us for an insightful lunchtime session exploring how AI-powered planning is transforming the retail industry.
This webinar will focus on financial and supply chain planning using Pigment, a modern AI business planning platform designed for agility and collaboration.
Whether you're a retail planner, supply chain strategist, or finance leader, this session will provide actionable insights into:
- Improving profits by reducing stockouts, inefficiencies, and making faster decisions
- Implement predictive inventory management: Use machine learning models to forecast demand at SKU and store level, reducing stockouts and excess inventory.
- Real-time dashboards: Deploy AI-powered dashboards for instant visibility into inventory, sales, and supply chain KPIs.
- Automated replenishment triggers: Set dynamic reorder points based on demand patterns and lead time
- Running scenarios at scale to see the impact of demand changes on financial statements
- Scenario modeling with AI: Build models that simulate demand shifts and their effect on revenue, COGS, and margins.
- Integrated planning tools: Connect demand planning with financial planning systems to visualize P&L impacts in real time.
- Stress testing: Run “what-if” analyses for promotions, seasonality, and economic changes
- Measuring the impact of promotions and price changes across the supply chain
- Promotion ROI modeling: Use historical data and elasticity models to predict uplift and cannibalization.
- Dynamic pricing engines: Adjust prices based on demand signals, competitor pricing, and inventory level
- Cross-channel optimization: Ensure promotions don't create imbalances between online and offline channels
