Programme Content
Pillar 1: CRO as a strategic leader (6 weeks)
Module 1: Strategy in a Disruptive World.
Module 2: Ecosystems, Platforms and Competition.
Module 3: Generating New Business Models for Competitive Advantage.
Module 4: AI and Data-Driven Strategy.
Module 5: Strategic Growth and Corporate Strategy.
Module 6: Strategy Design and Execution.
Pillar 2: Revenue management and analytics (6 weeks)
Module 7: Marketing Strategy to Drive Revenue Growth.
Module 8: Market Segmentation.
Module 9: Product Strategy for Growth.
Module 10: Pricing Strategy and Revenue Models.
Module 11: Data-Driven Decision Making and Analytics.
Module 12: Customer Journey and Performance Analytics.
Pillar 3: Leading innovation and organisational transformation (10 weeks)
Module 13: Organisational Elements of Digital Disruption.
Module 14: External Impact — Focus on the Customer.
Module 15: External Impact — Focus on Competitive Strategy.
Module 16: Open Innovation.
Module 17: Internal Impact and Opportunities.
Module 18: Managing the Digital Transformation.
Module 19: Leading innovation.
Module 20: Innovation Culture.
Module 21: Leadership Requires Letting Go.
Module 22: Changing Culture.
In-person Capstone module in Cambridge (2.5 days)
Meet your cohort peers and faculty in Cambridge during a 2-and-a-half-day in-person capstone module. During this module, you will get the opportunity to complete your capstone project and interact with peers and faculty to create a lifelong community of global executives.
Business analytics and AI
Equip yourself to make informed, data-driven decisions and lead AI-enabled initiatives with clarity and confidence. You will explore how emerging capabilities in big data, machine learning, generative AI and causal analytics can be applied to real organisational challenges to drive innovation and business impact. You will also strengthen your ability to build a data-driven culture, guide responsible AI adoption and develop the analytical mindset needed to support sustainable, intelligence-led growth.
Topics include:
Mapping Business Decisions to Data
Getting Creative with Big Data
experimental Design
Machine Learning
Causal Analytics
Generative AI
Legal and Ethical Use of Data and AI
Making Business Analytics and AI Happen
