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The challenge
Estimating aggregated demand months out is established practice. Predicting customer orders over the next several weeks is harder. Channels keep multiplying, promotions and order patterns shift week to week, and point-of-sale activity varies by retailer and route to market. Traditional demand planning was built for a simpler environment, and a monthly forecast spread evenly across the days of the month rarely matches what is actually happening in the near term.
The solution
E2open Demand Sensing applies AI and machine learning to current supply chain data. It weighs the influence of multiple demand signals and produces a daily forecast for every item at every location across the near-term planning window. The result is more precise replenishment and execution decisions, grounded in what demand is doing right now rather than what a plan assumed a month ago.
What's inside the data sheet?
Key capabilities that deliver daily, item-location forecast accuracy
Proven results, including 30% to 40% better near-term accuracy and 10% to 15% lower inventory
How e2open Demand Sensing works, from signal analysis to daily forecast publication
What is demand sensing?
Demand sensing is a forecasting discipline that reads current, near-term demand signals, such as orders, promotions, and point-of-sale data, to predict demand over the next several weeks. It differs from traditional demand planning, which projects monthly demand for longer-range business decisions. Demand sensing instead produces daily, item-location forecasts built to guide replenishment and execution in supply chains.
Key capabilities
Daily, item-location forecasting – Produces accurate daily forecasts for every item, at every location and channel, across a typical six- to eight-week near-term horizon.
Multi-signal demand analysis – Draws on orders, promotions, point-of-sale information, historical sales, and other downstream indicators to sense demand shifts as they happen.
AI-led technique selection – Evaluates statistical and machine learning techniques and selects the best fit for each item, location, and time period.
Configurable planning parameters – Supports shipping calendars, intermittent-demand treatment, and other business-specific settings.
Automated daily publishing – Pushes daily forecasts to connected planning and execution systems without requiring manual review each cycle.
Continuous self-tuning – Refines its blend of algorithms and demand signals as drivers change over time.
Enterprise-proven scale – Scales across large numbers of items, locations, and channels, with a proven track record in some of the world's largest supply chains.
Proven results
Companies using e2open Demand Sensing have achieved:
30-40%
improvement in short-term forecast accuracy over traditional methods
10-15%
reduction in inventory, freeing up cash and improving return on capital
180
countries reached through more than a decade of production use
$250
billion in annual sales volume supported
How demand sensing works
Analyze – current demand signals such as orders, promotions, point-of-sale data, historical sales, and other downstream indicators.
Select – the forecasting technique with the best statistical and machine learning fit for each item, location, channel, and time period.
Publish – a daily forecast to connected planning and execution systems, no manual review required.
Refine –the blend of algorithms and signals continuously as demand drivers change.
Why demand sensing is the way forward
Key benefits include:
Sharper short-term accuracy – Improves near-term forecast accuracy by aligning daily forecasts to the latest market signals.
Leaner inventory – Reduces the buffer stock many teams carry to compensate for short-term forecast error.
Stronger service levels – Improves product availability by keeping forecasts current with real demand.
Less manual tuning – Automates signal analysis, technique selection, and daily forecast generation.
Faster response –Helps planners and execution teams react to demand shifts inside the near-term window.
Who benefits from demand sensing?
Demand planners – seeking a more accurate near-term baseline without manual model selection.
Replenishment and execution teams – seeking daily, item-location visibility to guide near-term decisions.
Supply chain leaders – seeking to reduce inventory buffers while protecting service levels.
Ready to improve forecast accuracy across planning horizons?
Download this data sheet to see how e2open Demand Sensing can help your company build a stronger baseline across every planning horizon and focus planner expertise where it adds measurable value.
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