Machine Learning for Impact Evaluation
Heterogeneity, targeting, and prediction in development research.
The executive challenge
The problem this program solves
A vendor promised that your machine learning programme would transform the institution in ninety days. Eighteen months later, the invoices keep arriving and the transformation is still a slide. Institutions that cannot show return eventually cut the capability — and then pay consultants to rebuild what they dismantled. This is where machine learning stops being a technology conversation and becomes an executive discipline you can defend in any boardroom.
Context
Why this matters now
Capability
What you will be able to do
- Commission machine learning work and interrogate its outputs with an operator’s confidence.
- Distinguish machine learning automation opportunities from decisions where human judgement remains strategically important.
- Price the build, buy and partner options for machine learning capability with real economics.
- Govern machine learning models and data with controls that satisfy both boards and regulators.
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™
Six Weeks to Prove Machine Learning
A newly appointed chief data officer at a pan-African retail bank inherits a machine learning mandate, one budget cycle to show value, and three functions that each claim ownership of the same dataset. The CEO wants a decision improved this quarter — not a strategy deck.
Your decision: Choose the single machine learning initiative worth proving in six weeks, name what gets stopped to fund it, and decide who owns the result.
IPAT Data Lab™
Three functions at a national revenue authority report three different truths about the same machine learning question.
Dataset: Synthetic multi-source machine learning 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 machine learning 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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