Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 7 hours
Course Outline
Discovery Before Development
- Why the majority of AI projects fail at the scoping stage.
- Treating discovery as a core engineering activity.
- Setting time limits and clear exit criteria for the discovery phase.
Analyzing the Workflow
- Observing tasks as they are performed in real-world settings.
- Creating process maps, identifying handoffs and 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.
- Using data to justify the rejection of specific use cases.
Value Architecture and the Business Case
- Establishing baselines, quantifying benefits and analyzing cost to serve.
- Selecting metrics that satisfy finance and audit requirements.
- Maintaining a register for risks, compliance issues and dependencies.
Commitments, Gates and Transition
- Defining scope statements, assumptions and exclusions.
- Implementing stage gates and criteria for project termination.
- Preparing a handover brief for the build team.
Requirements
- Practical experience in a customer-facing technical or delivery position.
- Working knowledge of business processes in at least one industry sector.
- Foundational skills in 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 leads responsible for evaluating AI portfolios.
