From Strategy to Data & AI Portfolio

From Business Strategy to Data/AI Strategy

• Gartner Hive as a Framework for Guidance
• Business Strategy & Aligned Strategies
• The Ideal Scenario: Data & AI Integrated Directly into Business Strategy
• Reality: From Business Strategy to Data & AI Strategy, Including Use Cases 
• Aligning Business, Data, and AI Strategies

Strategic Filtering: Which Use Cases Are Really a Good Fit?

• Develop a strategic filter: Determine whether a use case aligns with the company's strategic goals and priorities.
• Define gate criteria: Define the minimum requirements that a use case must meet in order to be pursued further.
• Define Knockout Criteria
• Decisions: Go — Explore — Hold — Stop

• Review: Strategy, Maturity Level, Alignment, Filters & Gates
• Introduction to Use Case Evaluation
• Outlook: Self-Study Phase 2

Putting Use Cases to the Test: Evaluating Benefits, Feasibility, and Risk

• Value—Feasibility—Risk Matrix
• ICE and RICE Scoring
• Weighted Scoring Model
• NIST AI Risk Management Framework
• EU AI Act: Risk-Based Assessment
• Comparing Benefits, Feasibility, Effort, and Risk

Building a Portfolio: Prioritizing, Balancing, and Hedging

• Create a Portfolio Matrix (BCG Matrix: Market Growth vs. Relative Market Share)
• Distinguishing Between Quick Wins, Strategic Bets, Enablers, and Must-Dos
• Consider dependencies and resources: Which initiatives build on one another, and which ones compete for the same resources?
• Making Uncertainty and the Evidence Behind the Assessment Visible:
  • High: Benefits and available data support this
  • medium: Assumptions partially validated
  • Low: mostly hypotheses > Use Test Cards & Learning Cards
• Score → Test → Learn → Re-Score

• Review: Scoring, Risk, Portfolio, and Uncertainty
• Insight: Presentation and Discussion of the Transfer Projects
• Insight: Collaborative Portfolio Prioritization
• Launch, test, postpone, or stop initiatives
• From Portfolio to Roadmap
• Final reflection: “Why haven’t you done it yet?”