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Alain Matar and SupChains collaborate on a planner-facing forecasting application

Lokad continues to challenge forecast-centric planning with probabilistic and financially prioritized decisions

Atlas Copco moves to probability-based supply-chain planning with ToolsGroup

Five demand-forecasting mistakes supply-chain leaders are rethinking

GenAI lowers the automation threshold, but error economics determine what should be automated

Forecast accuracy is an input to the decision—not the business outcome

Why cumulative and lag-one forecasts matter for inventory decisions

Retail demand forecasting across promotions, shortages and new products

Machine-learning forecasting with promotions, prices, sell-outs and inventory

Forecast vs. actual: why protocol design breaks clinical supply plans

Forecast variability: when human enrichment destabilizes planning

Is MAPE Still the Right Forecast Accuracy Metric for Demand Planning?

Outgrowing the classical safety-stock formula

Demand Forecasting in an Era of Disruption: What Actually Works

Forecasting becomes more accessible with AI, but data still makes the difference

Nucleus: CCH Tagetik customer cases report 98%+ forecast accuracy

Combining Forecasts and Pull Flow for Predictable Demand Events

Why Forecast Accuracy Matters More Than AI Labels

Predictive inventory risk needs an operational fallback and a financial loss owner

o9, Kinaxis, OMP and Anaplan: Four Different Visions for AI-Driven Supply Chain Planning

Five questions that expose weak IBP maturity

How to Validate an AI Demand Forecast Before Planners Use It

How to Compare Forecast Models Before Selecting One in AWS Supply Chain

Supply Chain Outlier Detection 101: Build a simple demand-sensing review team with AI agents

Adde Jans