All Dataleo news, jobs, analyses and tutorials around Forecasting in Supply Chain and Operations.
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 forecast ownership, data quality and the governance of recurring demand-planning decisions.
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 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 translating planning processes into governed models, workflows and user practices.
The role is relevant because it combines model design with direct responsibility for operational recommendations and measurable decision outcomes.
The role is relevant to governing forecast logic, solution architecture and integration across planning environments.
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.
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.
MediumAGR 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.
Tool selection should begin with decision scope, authoritative data, parameter ownership and integration architecture—not a feature checklist.
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.
Prebuilt agents can accelerate adoption, but companies still need ownership of forecast logic, exception thresholds and override rules before recommendations affect inventory or service decisions.
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.
Cloud-scale AI should remain bounded by data residency, role-based access and validation rules when models support inventory, forecasting or maintenance decisions.
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.
