Assortment planning has long been a cornerstone of retail strategy, yet many organizations still rely on offline Excel sheets to manage this complex process. While Excel offers flexibility, it quickly becomes a bottleneck when planners need to balance SKU depth, category breadth, regional preferences, and margin targets across hundreds or thousands of products. The manual effort required to maintain consistency, version control, and real-time collaboration often leads to missed opportunities and reactive decision-making. IBM Planning Analytics transforms this landscape by offering a dynamic, scalable platform that integrates historical and external data, and empowers planners to enable data-backed decisions to make faster and more confident decisions.

How IBM Planning Analytics Powers Assortment Planning

1. Historical Data Modeling & SKU Depth Analysis

IBM Planning Analytics allows planners to use historical sales data and company targets to define the right mix of SKUs for each category. This includes:

• Determining the allocation of funding by category.
• Determining SKU count per category.
• Balancing breadth vs. depth (e.g., more styles vs. more units per style).
• Modelling new SKUs based on similar historical performance.

This is especially critical for seasonal planning cycles like spring-to-fall, where assortment decisions influence S&OP, store labor, and warehouse operations.

2. Guided Workflow & Version Control

Planning Analytics supports guided workflows that walk users through the assortment planning process. This structure ensures consistency across teams and reduces the risk of manual errors common in Excel.

• Lock plans or forecasts.
• Create multiple versions for scenario comparison.
• Display plans in dollars or units, or different currencies, depending on the audience.

3. Spreading & Driver-Based Planning

One of the most requested features from companies is spreading and driver-based planning—the ability to distribute values across time or categories based on drivers like seasonality or promotional cadence. Planning Analytics supports:

• Driver-based planning.
• Ability to model a category or SKU after another category or SKU.
• Real-time updates and refreshes.

4. Integration with Data Warehouses & BI Tools

Planning Analytics is data source agnostic, so assortment plans can be integrated with an ERPs, data warehouses, or other planning and/or reporting tools an organization may have. Planning Analytics supports:

• Bi-directional data flows.
• On-demand updates.
• Scheduled updates.

This ensures that plans are not siloed but part of a broader analytics ecosystem.

5. Security & Collaboration

Retail teams often need to limit editing rights while allowing visibility. Planning Analytics enables:

• Role-based access.
• Submission tracking.
• Audit trails for changes.

This is crucial for managing large teams and ensuring accountability.

In today’s fast-paced retail environment, assortment planning is no longer a static spreadsheet exercise—it’s a dynamic, data-driven strategy that directly impacts customer satisfaction and profitability. IBM Planning Analytics empowers organizations to move beyond offline Excel by offering scalable automation, guided workflows, and real-time collaboration. With the ability to model historical performance, optimize SKU depth, and integrate seamlessly with BI tools and data warehouses, retailers can make smarter decisions faster. Ultimately, it’s about delivering on the timeless promise: the right product, in the right place, at the right time. Planning Analytics makes that promise achievable—consistently, intelligently, and at scale.