AIM-Ready: Production & Inventory Operations Optimization
About This Course
This intermediate-level course equips manufacturing planners to assess and plan the adoption of AI-enabled production and inventory operations optimisation.
Participants will learn to identify high-value AI application opportunities, map current planning workflows, diagnose performance gaps, define measurable KPIs, and determine the data, system and implementation requirements needed to improve planning decisions.
Through case studies and a structured readiness framework, participants will develop a practical roadmap that translates the current state into phased AI-enabled projects with measurable operational impact.
The course is suitable for supply chain, production and inventory planners. No prior coding, AI or optimisation experience is required, though participants should understand basic planning processes and work with production or inventory data.
What You'll Learn
- Identify high-value AI application opportunities across production and inventory planning.
- Translate planning challenges into AI-ready use cases with clear problem statements, baselines, target outcomes and KPIs.
- Map current planning workflows, including data flows, systems, assumptions and decision logic.
- Assess data readiness for AI-enabled optimisation, including data sources, quality, availability and planning parameters.
- Evaluate integration requirements across planning, production and inventory systems.
- Assess business value, implementation feasibility and adoption risks.
- Develop a phased implementation roadmap with prioritised projects, pilot scope, timelines, roles, success measures and next steps.
Entry Requirements
Applicants should possess a degree in any discipline or a Diploma with a minimum of 3 years of related working experience.
Applicants who do not have the required academic qualifications are still welcome to apply, but shortlisted candidates may be required to attend an interview for special approval.
Proficiency in written and spoken English.