Optimise inventory. Improve service.
Horizon Inventory Optimization



Smarter features, built for planners







Why supply chain planning leaders recommend us
Real stories from supply chain planning leaders who've faced the same stockouts, inventory waste, and manual workarounds you have.
“Impressed by the knowledge and fast results of Horizon. Together we turned plans into action in no time.”

“After 40+ years of implementing different planning tools, Horizon is by far the easiest to set up and adapt. It combines strong models with a flexibility we haven't seen elsewhere.”

“What stood out was how quickly our team could use Horizon and how easily it was integrated with our current systems: the planning team saw the impact on their day-to-day immediately, and it improved collaboration and decision-making from a management perspective.”
Frequently Asked Questions
It ensures that the right products are available at the right time and place without overstocking or running out.
A well-optimized inventory plan:
Minimizes carrying costs and waste.
Reduces stockouts that lead to lost sales.
Accounts for factors like demand variability, lead times, and shelf life.
In short, inventory optimization aligns production and procurement decisions with what the market actually needs freeing up capital while improving service levels.
However, most companies follow one of these three strategic models:
Traditional control methods: Use safety stock, reorder points, or min-max levels to trigger replenishment.
Optimization-driven planning: Balance working capital and service level trade-offs using mathematical and statistical models.
Multi-echelon inventory optimization (MEIO): Manage inventory across multiple locations or warehouses, ensuring stock is placed where it's most needed. By combining these strategies, businesses can reduce total supply chain cost while maintaining a consistent customer experience.
Here's how:
Adaptive safety stock: Machine learning identifies demand shifts and adjusts safety stock dynamically.
Anomaly detection: AI flags irregular stock movements or forecasting errors before they cause disruption.
Data translation: AI transforms real-world business constraints (like supplier limits or working capital goals) into structured inputs for optimization models. While mathematical optimization (like linear and mixed-integer programming) remains the backbone of inventory planning, AI enhances it with real-time learning and faster decision support.
Here's what a good solution should deliver:
Real-time tracking: Always know your current stock position and what's on order.
Dynamic replenishment: Automatic reorder triggers based on optimized levels.
Scenario modeling: Simulate different stocking strategies and evaluate cost vs. service trade-offs.
Integration: Sync seamlessly with ERP and demand planning tools for a single source of truth. With software support, planners spend less time firefighting and more time optimizing.
Here's what sets Horizon apart:
Intelligent recommendations: Optimization models that consider your service targets, costs, and supply constraints.
Dynamic replenishment planning: Automatically generates replenishment proposals for raw materials and finished goods.
Real-time adaptability: When forecasts change, Horizon instantly updates stocking and replenishment plans.
Custom optimization goals: Whether your focus is service level, cost reduction, or cash flow.
Seamless integration: Works directly with demand planning and ERP systems for end-to-end visibility. In essence, Horizon ensures you always have the right stock at the right place and time without overinvesting in inventory.




