Production Planning

AI helps teams plan production by combining supplier, demand, and order data to adjust forecasts and scheduling.

Business impact

• Forecast accuracy — Danone reports forecast accuracy rising to 92% after a 20% reduction in forecast error.
• Forecast error — Danone reports a 20% reduction in forecast error.
• Order fulfillment rate — Lenovo reports a 23% improvement in order fulfillment rate.
• Production-order backlog — Lenovo reports a 20% reduction in the backlog of production orders.
• Service levels — Danone reports service levels increasing to 98.6% after a 30% reduction in lost sales.
• Lost sales — Danone reports a 30% reduction in lost sales.
• Product obsolescence — Danone reports a 30% reduction in product obsolescence.
• Net uplift from promotions — Danone reports a 55% improvement in net uplift from promotional events.
• Orders assessed — General Mills reports that more than 3,000 orders were assessed overnight.
• Recommendations produced — General Mills reports 500 recommendations produced.

Data requirements

• Supplier information (tabular) — Used in Airbus planning forecasts.
• Point-of-sale feeds (tabular) — Used in Danone demand sensing.
• Orders (tabular) — Used in General Mills and Lenovo planning decisions.
• Demand variability data (tabular) — Used by ToolsGroup to improve demand planning.
• Production orders (tabular) — Used in Lenovo’s scheduling platform.

AI methods and techniques

• Demand sensing — Used to incorporate point-of-sale feeds into demand planning.
• Machine learning — Used to analyze demand variability and improve forecasting.
• Digital twin simulation — Used by General Mills to assess orders and recommend planning adjustments.
• Deep reinforcement learning — Used by Lenovo to balance production volume, changeover cost, and order fulfillment in scheduling.
• Forecast simulation — Used in the Airbus proof of concept to simulate forecasts for production-needs planning.

Industries

Real-world evidence

5 documented case studies on record.

Companies using this: Airbus, General Mills, Lenovo, Nestlé, Danone.