Causal Inference & Impact Evaluation Analytics
Beyond correlation: randomized trials, difference-in-differences, and regression discontinuity.
The executive challenge
The problem this program solves
Your teams adopt causal inference tools faster than the institution can govern them, and leadership cannot answer the board's simplest question: which decisions are now made by machines? Executives who cannot arbitrate between competing analytical claims end up outsourcing judgement to whoever presented last. You will practise the hardest part — deciding what not to do — and leave with a causal inference agenda your executive committee can approve.
Context
Why this matters now
Capability
What you will be able to do
- Commission causal inference work and interrogate its outputs with an operator’s confidence.
- Defend a causal inference investment case before a board that has been disappointed before.
- Construct a causal inference roadmap sequenced by value, feasibility and risk.
- Read causal inference evidence — dashboards, model outputs, vendor claims — and know exactly what to trust.
The IPAT Course Standard
The five-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.
IPAT Signature Case™
The Causal Inference Model Nobody Can Explain
A a regional telecommunications group deployed a causal inference 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 national revenue authority report three different truths about the same causal inference question.
Dataset: Synthetic multi-source causal inference 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 causal inference decision view and the data architecture behind it.
Data → Analysis → Decision, not Data → Code → Certificate
Day 5 · 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.
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