Course Overview

(2-day workshop) – Focus on how to instill and support innovation within the organization's ecosystem to become a truly innovative organization. Participants explore techniques for encouraging productive thinking in teams, managing R&D innovation processes (from idea generation to prototype), and developing a culture that rewards experimentation and continuous improvement.

Learning Objectives

Understand innovation's strategic importance and common pitfalls.

1. Identify types and levels of innovation.
2. Learn stage-gate, agile, and design thinking models.
3. Manage innovation funnels, portfolios, and governance.
4. Prioritize and balance risk vs opportunity in initiatives.
5. Overcome biases using tools like SCAMPER.
6. Alternate between divergent/convergent thinking.
7. Build value propositions and pitch effectively.
8. Recognize leadership's role in fostering innovation.
9. Develop personal plans to support innovation in their teams.

Workshop Structure

Day 1: Building the Data-Aware Executive

Topics Covered: 

1. Fundamentals of Big Data, Analytics, and AI for Executives.
2. The Strategic Role of Data in Evidence-Based Decision Making.
3. Identifying and Prioritizing Data-Driven Use Cases Across Business Functions.
4. Interpreting Dashboards, KPIs, and Predictive Indicators.

Case-Based Discussion: Missed Decisions Due to Hidden Data Signals.

Hands-On Lab: Reverse-Engineering a Decision Using Data Models Delivery.

Format Highlights: Practical exercises using anonymized enterprise datasets, peer benchmarking, and case-driven discussions.

Day 2: Operationalizing AI-Driven Leadership

Topics Covered: 

1. Designing Decision Architecture that Scales with Organizational Growth.
2. Integrating AI into Governance, Compliance, and Risk Decisions

Case-Based Simulation: Responding to Dynamic Data in Crisis and Planning Scenarios.

Executive Blueprint: Building a Roadmap Toward Data-Intelligent Leadership.

Final Workshop Lab: Team Challenge on Data-Backed Strategic Recommendations

Format Highlights: Simulation, team scenarios, structured data interpretation tasks, and guided post-decision impact reflection.