Supply Chain Analytics & Demand Intelligence
Demand forecasting, inventory optimization, and end-to-end supply chain visibility in volatile markets.
The executive challenge
The problem this program solves
A vendor promised that your supply chain analytics programme would transform the institution in ninety days. Eighteen months later, the invoices keep arriving and the transformation is still a slide. Meanwhile, regulators are moving from encouragement to scrutiny — ungoverned supply chain analytics is becoming a supervisory finding, not a technicality. This programme converts scattered supply chain analytics pilots into a sequenced, governed portfolio — evidence before enthusiasm, value before volume.
Context
Why this matters now
Capability
What you will be able to do
- Evaluate where supply chain analytics creates economic value across the organisation — and where it reliably does not.
- Read supply chain analytics evidence — dashboards, model outputs, vendor claims — and know exactly what to trust.
- Construct a supply chain analytics roadmap sequenced by value, feasibility and risk.
- Defend a supply chain analytics investment case before a board that has been disappointed before.
The IPAT Course Standard
The ten-day journey
Each day is a deliberate progression in managerial capability — from strategic context, to analytical frameworks, to applied practice, to executive judgement under pressure, to a capstone that produces something your organisation keeps. This program assumes no prior coding experience: Week 1 builds Python and R fluency from zero; Week 2 applies those tools to the full programme.
IPAT Signature Case™
The Supply Chain Analytics Model Nobody Can Explain
A a pan-African retail bank deployed a supply chain analytics model into daily operations. It performs — until a customer dispute, a journalist and the regulator arrive in the same week, and no one can reconstruct why the model decided what it decided.
Your decision: Pause the model pending an explainability rebuild, defend it as deployed, or restrict it to advisory use — each response signals something different to the regulator, the market and your own staff.
IPAT Data Lab™
Three functions at a fast-scaling e-commerce platform report three different truths about the same supply chain analytics question.
Dataset: Synthetic multi-source supply chain analytics dataset — finance, operations and customer tables that disagree.
Your task: Reconcile the sources, build the single defensible view, and decide which dashboard the executive committee keeps.
A reconciled supply chain analytics decision view and the data architecture behind it.
Data → Analysis → Decision, not Data → Code → Certificate
Day 10 · The Capstone
What will you change when you return to work?
Build a twelve-month analytical and AI roadmap for your organisation: the value case, the data foundations, the governance, and the first 90 days.
Methodology
Frameworks you will master
- • IPAT Data-to-Decision Framework™
- • IPAT Executive Capability Model™
- • Value-versus-feasibility portfolio analysis
- • CRISP-DM analytical lifecycle
- • Model risk management principles (SR 11-7 adapted)
Cohorts
Upcoming cohorts
New dates are being scheduled
Register with your preferred start date and our admissions team will match you to the next available cohort — or contact us to arrange an in-house delivery for your organisation.
Register your interestExplore further
Related programmes
Learners of Supply Chain Analytics & Demand Intelligence frequently pair it with these offerings from the same divisions.
