Developing the Applied AI & ML Expertise to Win
Applied AI & ML Predictive Analytics Best Practices
Workshop
Build predictive analytics that scales beyond pilots
Predictive analytics delivers value when teams align on the right use cases, build models with clear success criteria, and plan for repeatable deployment. This.
Leave with a predictive analytics blueprint—use case targets, model approach, validation plan, and scaling.
The Challenge
Predictive analytics efforts often produce models—but not reliable, repeatable outcomes in the business.
- Use cases aren’t tightly defined: Teams build predictions without clear decisions, owners, or measurable value tied.
- Model choices don’t match goals: Algorithms and features are selected for novelty or convenience instead of the.
- Scaling is an afterthought: Validation and deployment planning come late, slowing adoption and increasing rework.
Without an end-to-end plan, predictive analytics stays stuck in prototypes—delivering insights that don’t translate.
Our Solution
We guide your team through a practical approach to design, validate, and scale predictive analytics in an enterprise.
- Use Case and Value Framing: Identify high-value predictive use cases and define the decisions they support.
- Modeling Approach Selection: Align on fit-for-purpose algorithms and model types based on goals, constraints.
- Feature Strategy and Model Tuning: Define how features will be engineered and how models will be tuned.
- Validation and Iteration Plan: Establish testing, review, and iteration steps that build confidence before scaling.
- Enterprise Scaling and Deployment Priorities: Identify the deployment patterns, ownership, and adoption needs to operationalize predictive solutions.
Area of Focus
- Exploring Predictive Analytics Use Cases and Value
- Selecting Algorithms and Models Aligned with Goals
- Engineering Features and Tuning Models for Accuracy
- Validating Models Through Testing and Iteration
- Scaling and Deploying Predictive Solutions Enterprise-Wide
Participants Will
- Identify and prioritize predictive analytics use cases tied to real decisions.
- Define a modeling approach aligned to goals, constraints, and adoption needs.
- Establish a feature and tuning strategy to improve accuracy and reliability.
- Create a validation plan that builds confidence through testing and iteration.
- Leave with scaling priorities and next steps to deploy predictive solutions consistently.
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.