Inventory Optimization Software
Today’s consumers demand more variety, and trends shift rapidly. As a result, companies are managing more slow-moving items with unpredictable, intermittent demand. Traditional ABC inventory planning methods from the 1950s no longer work in this environment. ToolsGroup’s inventory optimization software leverages self-adaptive demand and inventory models to define the ideal inventory mix across multi-echelon supply chains, helping you meet high service levels while minimizing inventory and reducing costs.
Analyze demand uncertainty to minimize inventory risk
Optimize inventory for uncertain demand
When dealing with slow-moving and intermittent demand items, ToolsGroup stands above other solutions. Our unique analytical relationships between inventory and service levels deliver reliable results, even for long-tail items. This allows for optimizing large assortments across different locations and various levels in the Bill of Materials (BOM), balancing inventory while maintaining high service levels.
Achieve high service levels while reducing inventory
Unlike traditional methods that apply a blanket approach to inventory within item groups, our inventory optimization software tailors service and inventory targets across product categories, BOM levels, and locations in your distribution network. This targeted approach ensures you meet customer service goals efficiently without excess inventory.
Unlock working capital
By using advanced modeling and artificial intelligence (AI) to optimize inventory for each SKU and location, ToolsGroup’s inventory optimization solution typically reduces overall inventory by 10-30%. This means less capital is tied up in inventory, giving you more liquidity for strategic initiatives.
"My only regret is not upgrading sooner! I’m proud to leave behind a highly efficient spare parts operation ready for the future." – Shalom Asayag, Service and Aftermarket Director
Shalom Asayag,
Service and Aftermarket Director
- Inventory levels reduced by 20-30% without affecting 96-97% service levels (well above the industry benchmark)
- Rush air shipments cut by a third
- €1.5 million saved in the first year due to inventory reductions alone
- Reduced inventory write-offs and provided complementary rental cars
- Increased planning productivity from two full-time to one part-time planner
ToolsGroup has proven to be an ideal partner in helping O2 plan a supply chain that can respond to changes in demand."
David Flaxten,
Demand Planning Manager
- Improved forecast accuracy by 10%
- Raised handset availability service levels to 97% in warehouses and 96% in retail stores
- Reduced days of stock by nearly 30%
Key Features of Inventory Optimization Software
Inventory Modeling
ToolsGroup’s inventory modeling eliminates the rough approximations used in traditional inventory management. Our solution creates reliable relationships between average inventory and service levels for each SKU and location, allowing you to define the optimal inventory mix across products and networks to meet service targets at the lowest cost.
Service-Driven Optimization
Unlike ABC inventory planning, which is focused on operations, service-driven inventory optimization centers around sales, marketing, and customer needs. It uses “service classes” that sales and marketing teams can easily understand, optimizing every SKU-location against target service levels within each class. This delivers an aggregated service goal with minimal stock investment.
Multi-Echelon Inventory Optimization (MEIO)
To fully serve the end customer, the entire supply chain—from raw materials and factories to distribution centers—needs the right inventory levels. Our MEIO solution balances inventory across multiple echelons, locations, and BOM levels, optimizing safety stock and aligning upstream and downstream inventory. This approach supports centralized demand planning, reduces supply chain costs, and streamlines operations.
Probabilistic Forecasting
Our probabilistic forecasting is the foundation of effective inventory planning. It helps you manage the risk of demand volatility by offering a range of possible outcomes with their probability of occurrence. Machine learning enhances traditional forecasts by analyzing internal demand signals and incorporating external data, delivering more accurate demand forecasts and better inventory planning.