Developing the Applied AI & ML Expertise to Win
Applied Operations Optimization AI & ML Best Practices
Workshop
Optimize critical operations with AI/ML—reliably and at scale
Operations optimization succeeds when teams target the right processes, design decision workflows, and validate results against real-world outcomes. This workshop helps leaders identify high-impact.
Leave with an optimization blueprint—use case targets, decision workflow, validation plan, and scaling priorities.
The Challenge
Organizations often see optimization potential, but struggle to turn it into sustained operational performance.
- Use cases aren’t well-scoped: Teams pick processes that are visible, not necessarily measurable, controllable, or feasible.
- Decision workflows are unclear: Even strong models fail when ownership, inputs, and operating decisions aren’t defined.
- Results don’t hold in reality: Without calibration and testing against real outcomes, performance degrades and trust drops.
Without a disciplined approach, optimization becomes experimental—creating disruption without consistent gains.
Our Solution
We guide your team through a practical approach to design, validate, and scale AI/ML-driven optimization for critical operations.
- Operational Use Case Identification: Prioritize optimization opportunities based on impact, feasibility, data readiness, and process control.
- Optimization Workflow and Decision Design: Define how decisions are made, what inputs matter, and how recommendations flow.
- Decision Modeling Approach: Align on the right mix of techniques to model constraints, tradeoffs.
- Testing and Calibration Plan: Establish methods to test performance, calibrate models, and validate outcomes in real.
- Measurement and Scaling Strategy: Define efficiency and performance metrics, then plan how to scale solutions.
Area of Focus
- Identifying Operational Use Cases for AI & ML Integration
- Designing Optimization Workflows for Critical Processes
- Modeling Decisions Using Operations Research and Machine Learning
- Testing and Calibrating Models Against Real-World Outcomes
- Measuring Efficiency Gains While Scaling Optimization Solutions
Participants Will
- Identify and prioritize operational optimization use cases with clear value and feasibility.
- Define decision workflows that connect models to real operational actions and ownership.
- Align on a modeling approach that reflects constraints, objectives, and practical tradeoffs.
- Establish a testing and calibration plan to validate performance against real outcomes.
- Leave with measures and a scaling plan to deliver and sustain efficiency.
Who Should Attend:
Solution Essentials
Format
Facilitated working session
Duration
8 hours
Skill Level
Intermediate to Advanced
Tools
Slides, workshop templates, key worksheets, checklists, and collaboration tools.