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Anaplan Study Frames Slow Planning Decisions as a Measurable Latency Tax

MANE selects Kinaxis Maestro to modernize global demand planning

Kinaxis Links Adaptive Planning to Tire-Industry Volatility and Reverse Logistics

Oracle embeds new AI agents across end-to-end supply chain operations

d-Matrix adopts Nvidia NVLink Fusion for inference-focused AI servers

Samsara introduces agentic shipment visibility and disposable tracking labels

Associate Director — Integrated Digital Supply Chain Planning, Solution Architect

EVENT: Optilogic examines how supply-chain design can close the decision-speed gap

RISK: Slow S&OP Decisions Can Create a Hidden Financial Latency Tax

WARNING: Legacy Data Gaps Continue to Limit AI-Based Supply Chain Response

EVENT: TDWI, SAP and Databricks examine real-time context for production Supply Chain AI

WARNING: Digital twins can create a second version of capacity if planning systems are not synchronized

EVENT: The supply chain you have vs. the one you need

EVENT: Production Scheduling AI — how it works and where it fits

EVENT: SAP IBP Business Forum Brings Integrated Planning to Oman

AI is making Supply Chain insight cheaper—but decision latency remains the bottleneck

Anaplan study links decision latency to supply-chain margin loss

Forecast Accuracy Is Not Enough: S&OP Must Measure Decision Latency

EDI Data Freshness Is a Decision Constraint for AI-Driven Replenishment

Demand planning AI should be measured by decision latency, not only forecast accuracy

AI and decision engineering can reduce planner heroics

Planning benchmarks should test decision speed, not feature breadth

AI adoption metrics are meaningless without a decision-quality metric

Sponsored insight: How AI is reshaping supply chain decision-making

Supply Chain Skills Are Becoming Decision Architecture Skills

Always-on planning changes the economics of supply-chain latency

Kinaxis and the “SaaS-pocalypse” test: why supply chain software may be different

Supply Chain Data Will Never Be Perfect—Decision Logic Must Account for It

Rajesh Gangadharan argues that agentic AI will hit an organizational operating-model wall

Manufacturing agent adoption is moving faster than data readiness

Planners + Agents: Why Supply Chain Planning Needs Human Judgment and Governed AI Agents

Inventory Reduction Is a Consequence, Not a Transformation Objective

AI priorities in manufacturing: talent, operating model and data foundation come before agentic AI

The moment of truth in supply chain planning happens after the plan

Energy-aware scheduling research makes production trade-offs measurable

Edge AI requires lifecycle control, not only real-time inference

Always-on demand forecasting changes the infrastructure assumptions behind planning AI

Erik Bush reframes the trillion-dollar inventory problem as an operating-model failure

Build a governed autonomous replenishment agent for SAP S/4HANA with Claude and MCP

Kinaxis

Meta Llama

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Aera Technology

ThroughPut AI

KBRW

Infor Supply Chain Planning

Fivetran

Denodo

Crisp

Mark Sawaya