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Description

Data and AI Projects: Defining, Visualising and Tracking Performance Indicators

Equip a data and AI project with clear indicators that genuinely reflect how it performs day to day

  • 0.43 days — 3 h
  • In-person or virtual
  • Intermediate
  • Up to 6 participants

A data and AI project generates a mass of measurements: model quality, processing times, adoption rates, volumes handled. Without deliberate choices, dashboards display everything and say nothing. Technical teams track indicators that business stakeholders do not understand, while business teams ask for figures the technical chain does not produce.

Unlike a purely financial approach, this short format works at the level of operational project tracking: selecting quality, adoption and service indicators, building the dashboard and running review rituals with stakeholders.

Learning objectives

  • Select a limited set of indicators aligned with the project objectives
  • Distinguish model quality indicators, usage indicators and service indicators
  • Define each indicator through its formula, source and calculation frequency
  • Build a dashboard that is readable by business and technical audiences alike
  • Run a periodic review that leads to decisions on the project

What makes this programme different

Participants narrow an over-long list of indicators down to a small, well-argued set
Each indicator is documented on a sheet covering formula, source and frequency
A dashboard mock-up is built and submitted to group critique

Programme

1Choosing the right indicators

Fewer indicators, but linked to objectives

  • Project objectives translated into observable effects
  • Indicator families: model quality, usage, service and data
  • Indicators that drive counterproductive behaviour
  • Selecting the limited set presented to stakeholders

2Documenting and securing measurement

An undefined indicator is a contested indicator

  • Indicator sheet: formula, scope, source and frequency
  • Series breaks and changes of definition
  • Consistency checks between technical and business indicators
  • A named owner for each indicator

3Building and running the dashboard

A document that triggers decisions

  • Visual hierarchy and reading levels for different audiences
  • Variance commentary and warning signals
  • Review ritual and follow-up on findings
  • Evolution of the dashboard across project phases

Who is it for

Project managers, data analysts, product owners and business leads involved in tracking a data or AI project.

Prerequisites

Be involved in the monitoring of a data or AI project that is under way or in preparation.

Dates & locations

12 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.