Allocation systems are well suited to distribute inventory to stores based on historical demand (Weeks on Hand) and meet rules such as presentation minimums and size/pack requirements. When demand shifts and inventory levels become unbalanced, these Allocation systems can exasperate the problem resulting in over- and under-stocked stores with margin bleeding markdowns or missed sales. Forecast Horizon looks at Weeks of Supply by Location, Class, and Week to set the model stock to bring inventory levels in balance and align inventory with demand. Forecast Horizon Model Stock Optimization injects intelligent forecasts and inventory targets into existing Allocation systems (e.g., JDA Arthur Allocation) with significant improvements such as:

• Improve Inventory Management through reducing under-stocks and over-stocks
• Increase revenue by shifting inventory to under-stocked stores
• Improve margin by reducing inventory at over-stocked stores
• Reducing unnecessary markdowns by as much as 50%
• Reduces the spread of WOS across the chain and volatility across classes and time

Better Inventory Balance

Each week Planners and Merchants manage against Plan. With Forecast Horizon, these users have science-based answers in context of how they already make pricing decisions. Recommendations in context of the Plan objective and Pricing Rules with the necessary supporting information improve performance and improve efficient collaboration across planners and merchants. Forecast Horizon reports are configurable to display the metrics that matter and employs innovative data visualization to easily identify performance against target. Users easily drill down to understand recommendations and can perform on demand What If pricing scenarios with Revenue and Margin impact.