BOSTON — February 28, 2023 — ToolsGroup, a global leader in retail and supply chain planning and optimization software, has announced the latest version of its Service Optimizer 99+ (SO99+) software, making major advancements in its forecasting and demand sensing capabilities. This is just the latest of the company’s significant strides towards making supply chains a force for good by helping organizations guarantee service, reduce excess stock, and increase profits.
“ToolsGroup SO99+ improved the accuracy of our forecasts for slower moving items by 5-10%,” said Sarah Voorhees, Vice President of Demand and Inventory Planning at American Tire Distributors. “Better probabilistic forecasts translate into better fulfillment, helping us reduce inventory, carry less safety stock, and increase revenue through fewer stockouts.”
With the release of v8.60, ToolsGroup aims to further improve customer experience and supply chain performance with expanded capabilities that now deliver:
- A New Product Introduction (NPI) Dashboard that provides an interactive display for SO99+ NPI forecasting. The dashboard enables immediate what-if scenario planning for all the attributes that may impact the performance of a new product introduction, a deeper understanding of the variables that affect the success of a new product launch, and the rationale supporting the projections for the launch forecast.
- Automatic Forecast Model Backtesting that eliminates the typically time-consuming, manual calibration process of configuring, defining, and simulating forecast models, delivering significant forecasting accuracy improvements nearly automatically.
- Re-Forecasting Based on Pre-orders that empowers users to incorporate actual orders into probabilistic forecasts to better determine future demand, improving short- and medium-term forecast accuracy while enabling customers to respond quickly and proactively to market changes.
- Machine Learning Speed and Accuracy Enhancements, thanks to the implementation of new light gradient-boosting machine functionality (LightGBM) into the SO99+ machine learning engines. By incorporating this advanced modeling technique, SO99+ delivers unmatched machine learning scalability and results, ensuring faster processing and major forecast accuracy improvements.
- Flexible Forecast Aggregation that simplifies demand planning by allowing demand teams to plan at the aggregate level, while retaining the variables and details necessary for accurate supply planning processes. This ensures higher-quality, more flexible forecasts because SKUs are no longer restricted to a single hierarchical view.
- Probabilistic Forecasting that combines historical, real-time, and other demand-relevant data into an probabilistic model that determines the possibility (and likelihood) of a range of outcomes, accounting for risk and enabling greater planning dexterity. It seamlessly self-adjusts to a wide variety of demand behaviors, generating optimal forecasts in uncertain demand scenarios.
- Demand Sensing that helps users better leverage granular data to capture changes in the market before they happen, ensuring proactive adjustments in demand planning and lower downstream latency while still delivering optimal service levels, ensuring fewer lost sales and increased revenues.
- Self-Adaptive, Frequency-Based Forecasting that effectively forecasts both fast-moving items and products with intermittent demand by capturing network-wide changes and events and accounting for both order size and order frequency, delivering the most accurate forecast available.
- Machine Learning Engines that are mapped to every unique attribute that can affect a forecast, from seasonality and promotions to causals and external factors, ensuring the most accurate and robust forecasts on the market.
