Hybrid AI Demand Forecasting
Traditional forecasting methods struggle to keep pace with complex and ever-changing demand patterns. That's where Manhattan Active Supply Chain Planning's UFM.ai comes in.
Hybrid Optimization Intelligence
Traditional statistical forecasting methods on their own struggle to keep pace with complex and ever-changing demand patterns. Manhattan’s enhanced Unified Forecasting Method with ML (UFM.ai) is different.
By continuously combining the best of multiple leading statistical methods into a refactored model and combining it with machine learning, UFM.ai within Manhattan Active® Supply Chain Planning has forged a new foundation for forecasting accuracy and insight.
The most sophisticated and highest performing forecasting engines in the world are not statistical models or machine learning models – they are hybrids.
Manhattan is delivering cutting-edge demand forecasting performance that was engineered from the ground up to move the right inventory to the right place at the right time, all the time.
Key Features of UFM.ai
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Hybrid Power
UFM.ai doesn't abandon traditional statistical methods, it uses all of them! By refactoring the best of traditional statistical models and combining it with machine learning, it creates a modern forecasting engine that was engineered to handle the complexity of modern retail and supply chain demands.
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Advanced Learning
UFM.ai continuously adapts to evolving demand patterns autonomously by analyzing complex non-linear relationships. This allows for incredibly broad and deep demand modeling.
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Enhanced Sensing
UFM.ai seamlessly accommodates external data sources, such as weather trends and social media sentiment, to provide a comprehensive picture of market forces.
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Effortless Adoption
UFM.ai automatically evaluates and updates its model, continuously improving without specialized and expensive staffing or training.
Proven Success Across Industries
UFM.ai is backed by years of validation and has consistently delivered strong results in real-world applications. Whether benchmarked against traditional methods or specialized machine learning models, UFM.ai has demonstrated its superiority in handling diverse and complex demand signals.
By uniting the best of traditional and modern approaches, UFM.ai ensures your supply chain is always a step ahead, ready to meet the challenges of today and tomorrow.
“Outside-In” Data Integration
Traditional forecasting methods struggle to keep pace with complex and ever-changing demand patterns. Manhattan Active® Supply Chain Planning (SCP) features Unified Forecasting Method with artificial intelligence (UFM.ai) to provide a solution.
The Power of External Data Integration
UFM.ai leverages data from a wide variety of external sources—everything from market trends and social media sentiment to local events and climate data. By integrating these diverse data streams, the software provides a 360-degree view of the factors influencing demand.
This holistic approach means the system isn’t just reacting to historical sales data; it’s anticipating future demand by factoring in real-world variables. Whether it’s an unexpected weather event that impacts supply needs or a new social media trend that drives a sudden spike in sales, the platform ensures that your supply chain is prepared for every scenario.
Holistic View of Demand Drivers
Outside-In
Incorporates real-time external factors such as market trends, competitive activity, economic indicators, social media sentiment, weather patterns and local events.
Inside-Out
Utilizes internal data such as historical sales, inventory levels, production schedules, customer behavior and past forecasting performance.
Combined Impact
Merging these data streams, organizations gain a unique view of the factors driving demand. This comprehensive perspective allows businesses to anticipate shifts more accurately and respond proactively.
An AI Conversation - What Makes UFM.ai So Unique?
We discuss the evolution of demand forecasting and explains why traditional forecasting methods are limited when trying to predict the complex and dynamic demand patterns of today’s markets.
Leveraging External Insights for Enhanced Supply Chain Precision
Integration of External Data
By incorporating market, industry, consumer and macroeconomic data, the platform provides a holistic view that goes well beyond traditional forecasting methods.
Better Risk Analysis
External data sources help identify potential risks in the supply chain, enabling proactive measures to mitigate disruptions.
Reduced Latency
Real-time data integration minimizes the lag between demand signals and supply chain response, ensuring your operations are always aligned with current conditions.
Stronger Collaborative Planning
Sharing insights from external data fosters cooperation across the supply chain, aligning partners and stakeholders toward common goals.
Enhanced Responsiveness
With a broader range of data inputs, the solution can quickly adjust forecasts, allowing for agile decision-making.
Customer-Centric Focus
By responding to consumer behaviors and preferences in real time, Manhattan Active SCP ensures your supply chain delivers what customers want, when they want it.
Improved Forecast Accuracy
The combination of internal and external data improves the precision of demand forecasts, reducing the risk of stockouts or overstocks.
Unified Supply Chain Planning
This is not just an evolution in supply chain planning—it’s a revolution.
Demand Forecasting
A hybrid approach to forecasting that seamlessly blends the power of proven statistical models with cutting-edge AI.
Replenishment
Seamlessly integrates AI-driven insights with real-time data to autonomously optimize inventory levels across all channels, ensuring the right products are always in the right place at the right time, without the need for manual intervention.
Allocation
Maximize sales opportunities, minimize stockouts, and optimize inventory across all locations and channels with unparalleled precision. Powered by cutting-edge AI and machine learning, our solution ensures your products are always in the right place at the right time.