All Dataleo news, jobs, analyses and tutorials around Forecasting in Supply Chain and Operations.
The role is relevant to roadmap ownership, integration, data governance and translating planner needs into controlled enterprise capabilities.
The role is relevant to governing forecast logic, solution architecture and integration across planning environments.
The role is relevant because it combines model design with direct responsibility for operational recommendations and measurable decision outcomes.
The role is relevant where revenue signals connect to demand planning, inventory and supply decisions; governance is needed around assumptions, model versions and downstream use.
The role is relevant to governed planning because project forecasts, dependencies and change control directly influence delivery decisions and operational risk.
The role is relevant to forecast ownership, data quality and the governance of recurring demand-planning decisions.
This position shows how supply chain AI in e-commerce is built into decisions on assortment, fulfillment, allocation and logistics optimization. Governance depends on objective design, cost-service trade-offs and control of automated decisions at scale.
The role is relevant to inventory-policy ownership, forecast alignment, cross-functional planning and controlled management of category assumptions.
The role is relevant to forecast governance, analytical model ownership, scenario planning and the translation of uncertain demand into accountable business decisions.
HighMediumMediumHighHighMediumMediumAGR published a comparison of inventory-planning platforms including RELEX, Slimstock, EazyStock and Netstock. The article reflects growing demand for dedicated forecasting, replenishment and inventory-optimization capabilities beyond spreadsheets and standard ERP functionality.
MediumA June 19 comparison reviews AGR, RELEX, Slimstock, EazyStock and Netstock across forecasting, inventory optimization, replenishment and planning automation.
Platform selection should begin with the decisions and data model, not the feature list. Buyers should test parameter ownership, version control, override governance and ERP integration.
MediumINFORM argues that AI recommendations affecting supplier priorities, forecasts and inventory adjustments can create material consequences when outputs are erroneous or misunderstood.
Explainability should be designed around the decision: which inputs changed, which constraints were active, and whether the planner can safely override the recommendation.
MediumMees van den Brink selected Slimstock to improve forecasting and inventory processes internationally. The signal reflects continued mid-market demand for dedicated planning platforms beyond spreadsheets and basic ERP functionality.
The value depends on whether service levels, supplier constraints, safety stock and replenishment parameters receive explicit owners during implementation.
HighLogility has launched DemandAI+ through Aptean AppCentral, combining AI-first forecasting with prebuilt planning agents designed for rapid activation. The offer targets demand-planning teams seeking faster deployment of automated analysis and recommendations.
MediumSKU Science introduced a product-lifecycle module designed to transfer historical data across product transitions and preserve forecast continuity during phase-in and phase-out.
Lifecycle forecasting requires governed predecessor-successor links, ownership of history-transfer rules and validation before the new product forecast is published.
MediumSKU Science outlined 2026 platform updates including forecasts in multiple business units, faster trend detection, stronger product-lifecycle management, dynamic ABC/XYZ classification and multilingual tutorials.
The updates strengthen usability, but governance still depends on controlled classifications, validated lifecycle links and traceable forecast adjustments.
HighThe Body Shop selected RELEX to replace manual forecasting and replenishment processes across stores, franchises and distribution centers.
The transition should retire parallel spreadsheets and define ownership of forecasts, replenishment parameters and overrides.
HighInfor expanded its strategic collaboration with AWS to accelerate generative AI adoption across industry cloud applications and operational workflows.
HighPetco Mexico selected RELEX to improve forecasting, replenishment, seasonal planning and inventory efficiency across 145 stores and two distribution centers.
Retail AI needs store-level data quality, transparent replenishment rules and controlled local overrides.
Better forecasts do not automatically produce better purchasing, inventory, allocation or production decisions.
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Forecast enrichment is valuable only when humans or agents contribute material information unavailable to the baseline model.
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US manufacturing activity rose as companies front-loaded orders against shortage and inflation risks, while factory employment weakened. The divergence complicates interpretation of <a href="/search?q=Demand%20Planning">demand</a> and capacity signals.
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A more accurate forecast creates value only when it changes inventory, capacity, service or financial decisions in a measurable way.
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The recurring issue is not the lack of AI vocabulary, but the lack of public evidence connecting architecture to operating results.
Read more →A fixed lead time hides uncertainty, calendar effects and process-stage variability that directly affect inventory and service decisions.
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