Learning outcomes

• Understand core concepts: Familiarize yourself with the core concepts of the competitive intelligence (CI) cycle, including data, information, intelligence and the CI profession.
• Perform tasking and planning: Identify key intelligence topics and questions, as well as project management strategies.
• Implement collection: Demonstrate effective acquisition of primary and secondary sources to support global intelligence efforts.
• Conduct analysis: Understand and apply competitive and industry analysis techniques in a global business environment. Use CI analytical methods such as Four Corners Analysis, Five Forces Analysis, SWOT Analysis and Scenario Planning.
• Disseminate results: Communicate the findings of your analysis (actionable intelligence) to decision-makers and clients and seek their feedback for ongoing improvement and evaluation.
• Apply legal and ethical dimensions: Ensure adherence to the legal and ethical standards surrounding competitive intelligence.

Course Structure

• Module 1: Introduction to CI as a Strategic Discipline

Students will explore the historical evolution of competitive intelligence, from its military strategy roots to modern corporate applications. A case study on Netflix's shift from DVD rentals to streaming will illustrate CI's role in strategic decision-making. Participants will engage in discussions to analyze CI's relevance in their industries.

• Module 2: Ethics, Compliance and Legal Considerations

This module examines ethical dilemmas through case studies, such as the Waymo vs. Uber trade secrets dispute and Muddy Waters' investigations in Asian markets. Learners will participate in role-play exercises, debating scenarios that balance information collection with legal boundaries.

• Module 3: Key Intelligence Topics Development and Planning

Participants will draft Key Intelligence Questions (KIQs) for a chosen company, using a prioritization matrix to align intelligence needs with business objectives.

• Module 4: Data Collection Methods (OSINT, surveys, trade shows)

In this hands-on module, students will develop an intelligence collection plan to identify primary and secondary sources for the KIQs from Module 3. They will assess the path, cost, timeliness and reliability of the chosen sources.

• Module 5: Analytical Frameworks (SWOT, STEEP, financial analysis)

Participants will use various analytical frameworks and tools to process data from Module 4, addressing the KIQs through analysis and identifying further collection gaps.

• Module 6: Briefing to the Board

Teams will present a detailed analytical report of their findings to the board, providing actionable recommendations. The report should be concise, insightful and supported by strong evidence.

Learning outcomes

The main objective of this course is to teach you to think and act as a professional specializing in the field of technology scouting and intellectual property due diligence. The course objectives include:

• Identify emerging trends: Develop the capacity to identify new developments in a technology space.
• Leverage market information: Find and use data on market players, products and positioning in a technology field.
• Visualize technology landscape: Gain hands-on experience in understanding how the technology landscape is formed and changes over time.
• Communicate technology foresights: Build confidence in the ability to present technology insights logically and persuasively.

Course structure

• Module 1: Introduction to Technology Scouting and Open Innovation

Students will understand the critical needs for efficient and effective scouring capability in corporate R&D, government agencies and venture capitalists to track emerging technology fields.

• Module 2: The Innovation Process and Technology Change

Participants will develop the capacity to identify emerging trends in a technology field and appreciate how technology evolves over time. A few emerging technologies such as flying cars and virtual reality eyeglasses will be used to demonstrate the development/change process.

• Module 3: Technology Scouting in Practice

This exercise session will guide learners in using Crunchbase and PitchBook to identify emerging startups, complemented by insights from a recorded guest speaker with corporate tech scouting experience. The case of Lux Research will be used to illustrate how this has been done in the corporate world.

• Module 4: Patent Analysis and Tech Landscaping (Patsnap, Vantage Point)

Participants will analyze TSMC's patent portfolio to identify R&D trends and collaborate on a group project mapping the renewable energy storage technology landscape.

• Module 5: Technology Forecasting:

Through simulations and methods like the Delphi technique, students will forecast 2030 trends in quantum computing, practicing scenario planning and trend extrapolation. The Techcast approach to conduct the forecasting will be used.

• Module 6: Competitive Technical Intelligence and Trade Show Intelligence:

A virtual trade show simulation will task learners with gathering intelligence from online exhibitors, followed by a workshop on crafting executive debriefs from trade show data.

Learning outcomes

• Conduct global business environment analysis: Analyze the global business environment using the PESTEL framework (Political, Economic, Social, Technological, Environmental, Legal).
• Perform LIST analysis: Conduct Landscape, Issues, Stakeholder and Trends analysis for global industries.
• Explore GenAI tools: Use generative AI tools in competitive intelligence analysis.
• Develop ethical guidelines: Create ethical guidelines for competitive intelligence collection.

 Course Structure

• Module 1: Global Market Analysis (PESTEL, LIST)

Region-specific examples, such as U.S.-China trade wars and EU carbon taxes, will frame group activities like conducting a PESTEL analysis of India’s pharmaceutical sector.

• Module 2: Culture, Law and Ethics in Global CI Practices

Students will go through multiple cases to understand the cultural, legal and ethical differences/implications in CI practices, especially the collection process. Teams will establish their ethical guidelines for a firm of their choice.

• Module 3: LIST (Landscape, Issues, Stakeholder, Trends) Framework

The LIST framework will be introduced to participants, and detailed templates and guidelines will be provided. Multiple cases will be used to demonstrate the process for each step.

• Module 4 - International Semiconductor Industry Deep Dive (LIST and Scenarios)

The LIST framework will be introduced to participants, and detailed templates and guidelines will be provided. Multiple cases will be used to demonstrate the process for each step.

• Module 5 - Performing CI analysis with GenAI Platforms

Teams will conduct the same tasks they did in the previous module using GenAI platforms, and evaluate efficiency and effectiveness of different AI platforms such as ChatGPT, Gemini, Kimi and Copilot.

• Module 6 - Communicating analytical results

Participants will design executive dashboards in Tableau or Power BI (and other GenAI platforms) and deliver a 10-minute briefing to a simulated C-suite panel, honing data storytelling skills.