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Description

AI-Assisted Decision-Making: Modelling, Explaining and Documenting Your Choices

One day to design decision support whose every recommendation can be explained

  • 1 day — 7 h
  • In-person or virtual
  • Expert
  • Up to 6 participants

A score appears on screen and nobody knows how it was produced. The team follows the recommendation when it suits them and ignores it the rest of the time. Without explanation, without a record of past decisions and without an escalation rule, a decision-support tool becomes an object of mistrust whose real contribution is never measured.

This 7-hour day treats decision-making as a complete chain. Participants frame the decision problem, select suitable data and methods, build an output that end users can understand, and put in place the traceability needed to explain a trade-off after the event.

Learning objectives

  • Frame a decision problem in terms of variables and criteria
  • Select methods suited to a given type of decision
  • Design an output that end users can understand
  • Explain a recommendation produced by an automated system
  • Document decisions taken so that they can be analysed later

What makes this programme different

A real decision problem formalised into criteria during the session
An output mock-up tested with the other participants
A method for explaining recommendations that works in front of a user

Programme

1Framing the decision problem

Criteria come before models

  • Distinguishing recurring decisions from one-off decisions
  • Identifying the decision-maker and their margin of judgement
  • Trade-off criteria and constraints to respect
  • Available data and missing data

2Methods and models

Choosing the tool to match the question

  • Prioritisation scores and rankings
  • Forecasting and scenario simulation
  • Anomaly detection and associated alerts
  • Model limitations and sources of bias
  • Validation conditions before going live

3Output, explanation and traceability

Driving adoption of the recommendation

  • Designing an output the decision-maker can read
  • Explanatory elements displayed with each recommendation
  • Handling cases of disagreement with the tool
  • Recording decisions and the reasons behind them
  • Periodic review of system performance

Who is it for

Operational directors, performance management leads, analysts and project managers responsible for equipping recurring decisions with tools.

Prerequisites

Command of a business decision area and the ability to read quantitative indicators.

Dates & locations

36 scheduled dates between November 2026 and December 2027. Seats are confirmed in the order enquiries are received.

November 2026

December 2026

January 2027

February 2027

March 2027

April 2027

May 2027

June 2027

September 2027

October 2027

November 2027

December 2027

None of these dates suit you? We open additional sessions on request, and any programme can be run privately for your team.

Practical details

Before the programme
Online positioning questionnaire. Your development objectives are shared with the trainer, who tailors the practical case studies to your context.
Teaching methods
Theoretical input, workshops and practical case studies. Digital course materials and method sheets provided.
Assessment
Multiple-choice tests and role-play exercises. Assessment of learning at the start and end of the programme, with immediate and 60-day follow-up evaluations.
After the programme
One year of access to the e-learning platform. Self-assessment of the skills acquired and a 30-day follow-up session with your trainer.
How to register
Registration online or on the basis of a quotation.
Lead time
11 working days after confirmation of registration.
Accessibility
Accessible to people of determination. Contact our accessibility coordinator to design a suitable solution: contact@mpf-academy.ae
Start dates
Rolling intake: in addition to the scheduled sessions, this programme can start on request.