IEB Oral Exam
Preparation Dashboard

Focused on your synopsis about the partnership between Novo Nordisk and OpenAI, while preparing you for broader questions across the full Information Economics & Business curriculum.

Main Theory

Dynamic Capabilities

Main Case

Novo Nordisk × OpenAI

Biggest Risk

Being too descriptive instead of analytical

Course Sessions & Likely Oral Exam Connections

Session 1: Digitalization, AI & Data

How does digitalization influence business performance and competitive advantage?

Oral relevance: High

Core Concepts

  • Digital mindset
  • AI-driven firms
  • Data as strategic asset
  • Prediction & feedback loops

Connection to Your Synopsis

Foundation for arguing why Novo Nordisk partners with OpenAI and why AI changes firm strategy.

Examiner-Style Questions

Why is AI strategically important for incumbent firms?
How does data become a source of competitive advantage?
What distinguishes digital transformation from traditional IT implementation?

Session 2: Network Effects & Digital Markets

How can firms compete in newly vulnerable markets?

Oral relevance: High

Core Concepts

  • Network effects
  • Winner-take-all dynamics
  • Platforms
  • Positive feedback loops

Connection to Your Synopsis

Useful if examiner asks whether AI ecosystems create dependency on dominant firms like OpenAI.

Examiner-Style Questions

Does OpenAI benefit from network effects?
Could pharma become dependent on AI platforms?
Are AI markets winner-take-all?

Session 3: Pricing & Revenue Models

How can firms price digital products and services?

Oral relevance: High

Core Concepts

  • Versioning
  • Bundling
  • Price discrimination
  • Platform pricing

Connection to Your Synopsis

Less central to your synopsis but useful for broader course discussion.

Examiner-Style Questions

How do AI firms monetize their products?
Why do AI firms use freemium models?
How does bundling work in digital markets?

Session 4: Dynamic Capabilities

How does digitalization influence dynamic capabilities?

Oral relevance: High

Core Concepts

  • Sensing
  • Seizing
  • Transforming
  • Asset orchestration

Connection to Your Synopsis

Probably the single most important theory for your synopsis.

Examiner-Style Questions

How does the Novo–OpenAI partnership reflect sensing capabilities?
What resources must Novo reconfigure to exploit AI?
Why are dynamic capabilities more relevant than traditional RBV here?

Session 5: Strategy Formulation & Managerial Cognition

How does digital transformation challenge managerial cognition?

Oral relevance: High

Core Concepts

  • Mental models
  • Search mechanisms
  • Strategic cognition
  • Environmental uncertainty

Connection to Your Synopsis

Strong connection to whether incumbents can recognize AI disruption early enough.

Examiner-Style Questions

Why do incumbents struggle with AI transformation?
How can managerial cognition become a barrier?
How does uncertainty affect strategic decision-making?

Session 6: Smart Data & Digital Strategy

How does competition change with connected products?

Oral relevance: High

Core Concepts

  • AI economics
  • Smart data
  • Data-driven competition
  • Connected products

Connection to Your Synopsis

Useful for discussing AI-driven pharma R&D and operational optimization.

Examiner-Style Questions

How does AI alter competition in pharma?
Can AI lower entry barriers?
Why is data strategically valuable in drug discovery?

Session 7: Platforms & Organizing

How does data provide value in multi-sided platforms?

Oral relevance: High

Core Concepts

  • Transaction platforms
  • Innovation platforms
  • Ecosystems
  • Governance

Connection to Your Synopsis

Very useful for analyzing OpenAI as an innovation platform.

Examiner-Style Questions

Is OpenAI an innovation platform?
What governance challenges emerge in AI ecosystems?
How do platforms create value differently from traditional firms?

Session 8: Transaction Costs & Digital Transactions

How do digital transactions influence transaction costs?

Oral relevance: High

Core Concepts

  • Transaction cost theory
  • Search costs
  • Monitoring costs
  • Outsourcing

Connection to Your Synopsis

Excellent for discussing why Novo partners externally instead of building everything internally.

Examiner-Style Questions

Why partner with OpenAI rather than develop internally?
How can AI reduce transaction costs?
Can digitalization also increase transaction costs?

Session 9: Algorithmic Decision-Making & Trust

How do organizations evaluate algorithmic alternatives?

Oral relevance: High

Core Concepts

  • Trust
  • Algorithmic opacity
  • Black box AI
  • Explainability

Connection to Your Synopsis

Highly relevant for healthcare and pharma where explainability matters.

Examiner-Style Questions

Can pharmaceutical firms trust black-box AI systems?
What risks emerge from algorithmic opacity?
How should firms govern AI decision-making?

Session 10: Ethics & Responsibility

What are the ethical implications of digitalization?

Oral relevance: High

Core Concepts

  • Algorithmic bias
  • AI ethics
  • Environmental costs
  • Fairness

Connection to Your Synopsis

You should absolutely expect at least one ethics-related question.

Examiner-Style Questions

What ethical risks emerge when using AI in healthcare?
Should firms be responsible for environmental costs of AI?
How can AI create social injustice?

Weaknesses the Examiner May Attack

Your synopsis is broad

The paper discusses many organizational implications of AI without narrowing down to a sharply defined strategic problem.

Theory integration may be challenged

You mention several themes. The examiner may ask how the theories connect rather than simply coexist.

Limited empirical depth

Your case relies heavily on announcements and strategic expectations rather than observable outcomes.

Causality may be questioned

Be careful claiming AI will necessarily improve efficiency or innovation. The examiner may push you on evidence.

Strong Model Answers

Why is dynamic capabilities theory relevant here?

Because the case concerns how Novo Nordisk adapts to technological disruption under conditions of uncertainty. The issue is not only owning resources, but the ability to sense AI opportunities, seize them through partnerships, and transform organizational processes.

Why partner instead of building AI internally?

Transaction cost theory and capability gaps both matter. OpenAI already possesses specialized AI competences, infrastructure, and learning capabilities that would be extremely costly and slow for Novo to replicate internally.

What strategic risks exist in the partnership?

Dependency on external AI providers, data governance risks, algorithmic opacity, regulatory concerns, and potential erosion of internal capabilities if too much knowledge creation is outsourced.

Rapid-Fire Oral Exam Practice

Synopsis Defense

Why did you choose Novo Nordisk and OpenAI as your case?
What is your main argument in the synopsis?
What exactly is the strategic problem you are analyzing?
Why are dynamic capabilities the most appropriate theoretical lens?
What are the limitations of your analysis?

Theory Application

Apply transaction cost theory to the partnership.
Explain how AI changes competitive advantage in pharma.
How does the partnership relate to platform economics?
Could Novo become dependent on OpenAI? Why?
How would RBV interpret this partnership differently from dynamic capabilities?

Critical Discussion

What could go wrong with AI adoption in pharma?
What assumptions does your argument rely on?
Are there ethical concerns related to AI-driven drug discovery?
Could AI reduce rather than strengthen competitive advantage?
How sustainable is this strategy long-term?

Most Important Strategic Advice

1. Move from Description to Analysis

Your synopsis currently spends substantial space describing AI trends and the partnership itself. During the oral exam, you must continuously explain WHY these developments matter strategically.

2. Tie Every Point to Theory

Avoid generic statements like "AI improves efficiency." Instead say: "From a dynamic capabilities perspective, AI enables faster sensing and resource reconfiguration."

3. Expect Cross-Session Questions

The examiner will likely move beyond your exact synopsis and ask broader questions about platforms, transaction costs, data strategy, algorithmic trust, and ethics.

4. Show Critical Reflection

High grades usually require discussing trade-offs and limitations. You should be able to explain both the strategic opportunities and the risks of AI adoption.