AI and Big Data for Supply Chain Optimization

Name: AI and Big Data for Supply Chain Optimization Course
Availability: InStock

Use AI and operational data to improve demand, inventory, supplier, logistics, and disruption decisions with human oversight and monitoring.

At a glance

Duration: 5 days
Format: Classroom
Cities: Sharm El-Sheikh, Frankfurt, Bali, Paris, London, New York and more
Next session: 12 – 16 October 2026, Sharm El-Sheikh
Average fee: 5,800 €

Home
Our Categories
AI and Big Data for Supply Chain Optimization Course

Download Brochure (PDF) Print PDF

Course Overview

AI and Big Data for Supply Chain Optimization Course is a five-day advanced course for supply-chain planners, procurement analysts, logistics managers, inventory personnel, operations analysts, and transformation teams. Participants frame AI use cases, assess data readiness, interpret demand and disruption predictions, connect forecasts to inventory and logistics decisions, define human oversight, and monitor deployed models. They leave with a Supply Chain AI Optimization Playbook. Agile Leaders Training Center delivers AI and big data for supply chain optimization training.

Who Should Attend

Supply-chain planners responsible for demand and supply decisions
Inventory personnel responsible for replenishment and service levels
Procurement analysts monitoring suppliers and related risks
Logistics managers managing lead times, capacity, and exceptions
Transformation teams governing AI-enabled operational decisions

The course assumes practical supply-chain knowledge and basic data literacy. It excludes data-science coding, platform configuration, and vendor certification.

Departments and Industries

The course supports planning and operations in manufacturing, retail, distribution, healthcare supply, energy, logistics, and public-sector supply networks.

Supply-chain planning
Procurement and supplier management
Inventory and warehouse operations
Logistics and distribution
Operations analytics and transformation

Learning Objectives

By the end of this course, participants will be able to:

Prioritise AI use cases by value, feasibility, and risk
Assess supply-chain data quality and signal readiness
Interpret demand forecasts, uncertainty, and accuracy measures
Connect predictive outputs to inventory, supplier, and logistics decisions
Define human oversight, monitoring, and exception controls
Build a Supply Chain AI Optimization Playbook

Course Agenda

Day 1: AI Use Cases and Decision Context

Supply Chain Decision and Pain-Point Map
AI Use-Case Value and Feasibility Grid
Prediction-versus-Optimization Boundary
Human Decision Right Matrix
Use-Case Risk and Assumption Register

Day 2: Big Data and Forecast Readiness

Supply Chain Data Source Inventory
Demand, Inventory, Supplier, and Logistics Signal Map
Data Quality and Timeliness Scorecard
Outlier and Missing-Data Decision Log
Forecast Baseline and Accuracy Plan

Day 3: Demand and Inventory Optimization

Forecast Horizon and Granularity Decision
Probabilistic Forecast Interpretation
Demand Driver and Scenario Board
Inventory Policy and Service-Level Link
Replenishment Recommendation Review Gate

Day 4: Suppliers, Logistics, and Disruptions

Supplier Risk Signal Framework
Lead-Time Prediction and Variability Map
Logistics Capacity and Exception Triage
Disruption Scenario and Response Options
Constraint-Aware Decision Comparison

Day 5: Oversight and Operational Monitoring

Model Output Challenge Checklist
Human Override and Decision Evidence Log
Forecast Drift and Performance Dashboard
Incident, Escalation, and Decommissioning Route
Capstone Supply Chain AI Optimization Playbook

Practical Exercises

Participants work with realistic supply-chain scenarios and remain responsible for interpreting AI outputs in context.

Suggested activity: rank demand, inventory, supplier, and logistics use cases
Suggested activity: assess a fragmented operational data set for readiness
Suggested activity: compare forecast ranges and inventory responses
Suggested activity: challenge a disruption recommendation and record the human decision

FAQs

Who suits the AI and Big Data for Supply Chain Optimization Course?

The course suits experienced supply-chain and operations professionals who evaluate or use AI-enabled forecasts, recommendations, and risk signals without needing to build models in code.

How do prediction and optimization differ?

Prediction estimates likely demand, lead time, disruption, or other outcomes. Optimization compares feasible actions against objectives, constraints, costs, service requirements, and risk.

Why use probabilistic forecasts?

Probabilistic forecasts show a range of plausible outcomes rather than one point estimate, helping planners connect uncertainty with inventory, capacity, and service decisions.

What human oversight is needed?

Oversight defines who reviews outputs, challenges assumptions, authorises actions, records overrides, monitors performance, escalates incidents, and suspends or retires an unsuitable model.

What belongs in a Supply Chain AI Optimization Playbook?

The playbook contains use-case priorities, data and signal maps, readiness checks, forecast measures, decision rules, scenario tools, human rights, monitoring indicators, and escalation routes.

Conclusion

Participants take back a governed approach for turning supply-chain data and AI outputs into accountable decisions. The Supply Chain AI Optimization Playbook links forecasts and risk signals to operational constraints, human judgment, performance monitoring, and continuous review.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

Download Brochure (PDF) Print PDF

Showing 61-76 of 76 events

Location	Dates	Duration	Mode	Price
Rome	Week 32, 2027 9 – 13 August 2027	5 Days	Onsite	€5,700
Abu Dhabi	Week 32, 2027 9 – 13 August 2027	5 Days	Onsite	€4,700
Johannesburg	Week 32, 2027 15 – 19 August 2027	5 Days	Onsite	€4,500
Tbilisi	Week 33, 2027 16 – 20 August 2027	5 Days	Onsite	€5,000
Porto	Week 34, 2027 23 – 27 August 2027	5 Days	Onsite	€5,700
Cairo	Week 35, 2027 30 August – 3 September 2027	5 Days	Onsite	€4,100
Nice	Week 35, 2027 30 August – 3 September 2027	5 Days	Onsite	€5,700
Chicago	Week 35, 2027 5 – 9 September 2027	5 Days	Onsite	€12,000
Tokyo	Week 36, 2027 6 – 10 September 2027	5 Days	Onsite	€10,000
Barcelona	Week 38, 2027 20 – 24 September 2027	5 Days	Onsite	€5,700
Munich	Week 38, 2027 20 – 24 September 2027	5 Days	Onsite	€5,700
Baku	Week 39, 2027 27 September – 1 October 2027	5 Days	Onsite	€5,000
Berlin	Week 39, 2027 27 September – 1 October 2027	5 Days	Onsite	€5,700
Trabzon	Week 39, 2027 3 – 7 October 2027	5 Days	Onsite	€6,800
Casablanca	Week 40, 2027 4 – 8 October 2027	5 Days	Onsite	€4,100
Al Jubail	Week 40, 2027 10 – 14 October 2027	5 Days	Onsite	€5,700

Frequently asked questions

What does this course cover?

Course OverviewAI and Big Data for Supply Chain Optimization Course is a five-day advanced course for supply-chain planners, procurement analysts, logistics managers, inventory personnel, operations analysts, and transformation teams. Participants frame AI use cases, assess data readiness, interpret demand and disruption predictions, connect forecasts to…

Are training dates available?

Yes. Available dates and destinations are listed in the course dates section on this page.

How can I register?

Choose an available date on this page and complete the registration form, or send a programme enquiry.

Can I download the course brochure?

Yes. Use the brochure download link provided on this page.

AI and Big Data for Supply Chain Optimization