L'IA pour les Directeurs des Opérations : Excellence Opérationnelle

Ce qu'elle couvre

Ce programme offre aux COO et responsables opérationnels un cadre structuré pour identifier, prioriser et piloter les initiatives IA tout au long de la chaîne de valeur opérationnelle. Les participants explorent le process mining, l'automatisation intelligente, les systèmes qualité pilotés par l'IA et les outils de planification des effectifs à travers des études de cas concrets et des exercices pratiques. À l'issue de la formation, ils repartent avec une feuille de route IA priorisée liée directement aux KPI opérationnels et une boîte à outils d'évaluation des fournisseurs et de mesure du ROI. Le format combine des sessions courtes animées par des experts avec des groupes de travail entre pairs et une présentation finale de la feuille de route.

À l'issue, vous saurez

• Map your operational value chain and pinpoint the three highest-ROI AI intervention points using a structured prioritisation matrix
• Evaluate process mining tools (e.g. Celonis, UiPath Process Mining) against your own operational data to surface hidden inefficiencies
• Design an intelligent automation blueprint that covers RPA scope, exception-handling logic, and human-in-the-loop checkpoints
• Build a 90-day AI roadmap linked to measurable ops KPIs such as cycle time, defect rate, and workforce utilisation
• Apply a vendor scorecard to assess and compare operational AI solutions across cost, integration complexity, and scalability

Sujets abordés

• Process mining: discovering and analysing operational bottlenecks with AI
• Intelligent automation: RPA, agentic workflows, and exception handling
• AI-powered quality management and predictive maintenance
• Workforce planning and scheduling optimisation with AI
• Building an ops-KPI-driven AI investment framework
• Vendor evaluation and build-vs-buy decisions for ops AI tools
• Change management and workforce adoption for automation
• Governance, risk, and compliance for operational AI

Modalité

Typically delivered as a blended programme over three to four days (in-person or virtual instructor-led), split into half-day modules with peer working groups between sessions. Participants receive a digital workbook, process mining sandbox access, and AI investment scorecard templates. Hands-on exercises account for roughly 50% of contact time. In-person cohort format is strongly recommended for the capstone roadmap session; remote delivery is viable for earlier modules.

Ce qui fait que ça marche

• Anchor every AI initiative to a named KPI owner and a measurable baseline before kick-off
• Run a small process mining pilot on one process end-to-end before committing to enterprise-wide tooling
• Embed a change management workstream alongside the technical deployment from day one
• Establish a cross-functional AI ops steering group that meets monthly to review KPI progress and course-correct

Erreurs fréquentes

• Investing in automation tools before completing a process mining diagnostic, automating broken processes at scale
• Framing AI projects around technology capabilities rather than specific ops KPIs, making ROI invisible to the board
• Underestimating workforce change management, leading to low adoption and shadow workarounds
• Treating vendor selection as an IT decision, missing the operational integration and exception-handling requirements

Fournisseurs à considérer

• Desired Path (process mining & ops AI for executives)www.desiredpath.com →
• MIT Sloan Executive Education — AI for Leadersexecutive.mit.edu/course/artificial-intelligence-implications-for-business-strategy →
• Celonis Academy (process mining practitioner tracks)academy.celonis.com →
• DataScientest — IA pour Managers et Décideursdatascientest.com/formation-ia-managers →

Sources

• Gartner — Predicts 2024: Intelligent Process Automation →
• McKinsey — The state of AI in operations (2023) →