Merchandising is hit or miss...

Customers love or hate the product.

If they love it, you are constantly sold out!

If they hate it, you bleed margin clearing it out!

Optimize where to place your bets and how much to buy for maximum profit and predictable performance.

Improving the Buy Improves the Business

Forecast Horizon calculates the optimal breadth and depth for optimal inventory, revenue, turns, and margin.

• Better Forecast: Optimal Weeks of Supply and corresponding Demand.
• Better Buy Plan: Inventory to meet Demand at required Service Level (ex. 99%).
• Optimal Breadth: Satisfy customer need and reduce margin risk. Fine tune with Size Profiles.
• Better Allocation: Forecast input to Allocation system optimally adjusts distribution post receipt.
• Decision Support: Intuitive, what if capabilities, impact of decisions (Revenue/Margin projections)

Pre-Season Planning

Forecast Horizon enables Financial Planners to get a better handle on the forecast and underlying assumptions driving the Plan.

Scenario planning levers include:

• Budget
• Goals (grow comp. sales by 2%; maintain at least 40% margin, 3 Turns)
• Season Start/ End
• Minimum number of styles (by class)
• Pricing Strategy (Clearance after 6 weeks)

Optimized History for Better Forecasting

Forecast Horizon optimizes historical data to understand true demand patterns at the Store and Class levels.

Forecast Horizon calculates:

• Seasonality, Elasticity, Stock-outs
• True Average per Store (APS)
• Bottom up Demand Forecast

Fine Tune with Localized Assortment

Retailers with hundreds of locations know there is no average store.
The core customer profile and demand varies by class and store. Variables such as demographics, climate, and preferences all drive how the product sells and how the business performs.

Forecast Horizon enables a Localized Assortment strategy for the way that you look at your business and brand.

Leveraging historical data, Forecast Horizon uses advanced retail analytics and interactive scenario planning to define size and demand profiles by class and store. The result is a more reliable forecast used for the pre-season Buy, setting and adjusting optimal Model Stocks, and more effective in-season promotions.