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Duration 7 hours
Course Outline
Discovery Prior to Development
- Why scoping errors are the primary cause of AI project failures
- Treating discovery as a core engineering practice
- Establishing time limits and termination criteria for the discovery phase
Analyzing Workflows
- Observing tasks in their actual operational context
- Creating process maps, identifying handoffs, and tracing exception paths
- Interviewing end-users, managers, and control functions
Evaluating Use Cases
- Applying filters for feasibility, value, and readiness
- Scoring a portfolio of ideas rather than focusing on a single concept
- Rejecting use cases with supporting evidence
Value Architecture and Business Case
- Defining baselines, benefits, and service costs
- Selecting metrics acceptable to finance and audit departments
- Registering risks, compliance issues, and dependencies
Commitments, Milestones, and Handover
- Defining scope statements, assumptions, and exclusions
- Setting stage gates and termination criteria
- Preparing a handover brief for the development team
Requirements
- Background in customer-facing technical or delivery roles
- Understanding of business processes within at least one industry
- Proficiency in basic spreadsheets and documentation for modeling and reporting
Target Audience
- Forward-deployed engineers and solution consultants
- Presales and solution architects
- Product owners and delivery leads involved in AI projects
- Transformation leaders evaluating AI portfolios
