OneStream, a leader in corporate performance management (CPM) solutions for the world’s leading enterprises, announced expanded capabilities for its Sensible ML solution which increases machine learning (ML) forecasting transparency and explainability of key business drivers. The solution is now available to both existing OneStream SaaS customers as well as prospective OneStream customers. Sensible ML is a time series ML solution that integrates with existing planning processes to drive improved forecasting accuracy and efficiency. These expanded capabilities provide additional transparency and trust for users while increasing agility, time to value and enterprise value associated with operational planning processes.
“The ability to quickly generate driver-based forecasts is essential to adapting to our changing business conditions”
This expanded release addresses OneStream customers’ rapidly expanding need to align financial planning with operational planning processes such as Sales Planning, Demand Planning and Sales & Operations Planning (S&OP). OneStream customers with existing planning solutions can leverage Sensible ML to drive improved forecasting accuracy and efficiency while seamlessly integrating it into their planning, reporting and dashboard processes.
“OneStream views the opportunity for AI no differently from core CPM processes – AI must be unified to core processes if it’s going succeed,” said Tom Shea, CEO at OneStream. “Traditional CPM tools offer the same challenges they always do. They are fragmented, require data movement and maintenance behind the scenes and do not contain actual ML modeling capabilities. Our expanded Sensible ML release allows users to align financial and operational planning across the enterprise, with enhanced capabilities for leveraging external data to further drive transparency and understanding of key business drivers while seamlessly integrating it into their existing CPM processes.”
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Sensible ML helps organizations evolve enterprise planning processes by making ML forecasting easy and intuitive for FP&A teams and operational analysts. Key capabilities of the expanded Sensible ML release include:
- Feature Library: Automatically graft external data sources into your Sensible ML project, including maritime container indices, Covid case rates, interest rates, CPI, stock prices, weather and more.
- Prediction Intervals: Set predictions intervals at 95%, 90%, 85%, to quantify the level of certainty around the Sensible ML point forecast for a given target and model.
- Feature Impact: Quantify how influential every feature during training and production for every target and model.
- Prediction Explanations: For any target, model, forecast date, quantify how much each feature negatively or positively influences the forecast from the model’s average forecast.
- Feature Generalization: Quantify how useful a feature is across the entire project’s target portfolio.
- New Consumption Exports: Export feature impact, prediction explanations, and predictions intervals to easily visualize these capabilities in downstream business planning solutions.
- New Data Visualizations and Advanced Data Views: Provide deeper insights and transparency into forecast drivers to help improve model confidence, accuracy and explainability.
Early adopting customers highlight the speed to value and increased accuracy of sales and demand forecasting with Sensible ML, making it a standout solution among competitors.
“The ability to quickly generate driver-based forecasts is essential to adapting to our changing business conditions,” said Melanie Hermann, Director, Finance Process & Systems at Polaris Industries. “Incorporating AI into our planning and forecasting through the OneStream Sensible ML solution accelerates the forecasting process and further elevates it with powerful ML data-driven forecasts. Sensible ML forecasts have shown to be significantly more accurate, and the value-add dashboard provides the business users insights into the key features driving the forecast to easily manage, improve and enhance the model.”
SOURCE: Businesswire