Summary: Business Models Consulting

Read the summary and the most important questions on Business Models Consulting

• 1 Week 1

• 1.3 De Jong, M., & van Dijk, M. (2015). Disrupting beliefs: A new approach to business-model innovation. McKinsey Quarterly, 3, 66-75.

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• How can companies successfully achieve business model innovation

  2. The core argument: Disruption happens by reframing underlying beliefsEvery industry operates on a set of deep, implicit beliefs about how value is created. These beliefs shape:
  

  • what customers want,
    
  • how technology can be used,
    
  • what drives costs,
    
  • how regulation works,
    
  • and what competition looks like.
    

  Most companies follow these beliefs without questioning them.
  The core insight of the paper:
  Business-model innovation = identifying a dominant industry belief → breaking it → building a new model around the reframed belief.
  
  
  The authors give examples like Bitcoin, Coursera, Tencent, and Uber, all of which overturn the traditional logic of their industries.

• 1.4 De Man, A.P., De Man, M. & Stoppelenburg, A. (2015). The business model mixer for consulting, Sioo.

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• Traditional firms are built on three elements:

  
  

  1. Expertise transfer: Consultants know more than the client.
     
  2. Time-based billing: Revenue is based on hours sold.
     
  3. The leverage model: A small group of partners and many juniors deliver work.
     
     

  These models create predictable revenue but limit innovation.

• 1.6 Sorescu, A. (2017). Data‐driven business model innovation. Journal of Product Innovation Management, 34(5), 691-696.

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• What is the core idea of the paper

  The paper argues that big data is a major driver of business model innovation (BMI).
  Instead of innovating through new products or technologies, firms can use data to change how they create, deliver, or capture value, resulting in powerful new business models (e.g., Airbnb, Uber, Netflix).
  BMI does not need to be:
  

  • disruptive,
    
  • based on new technology,
    
  • or based on radical product innovation.
    

  It only requires a significant improvement in the firm’s value proposition.

• 1.7 Teece, D. J. (2010). Business models, business strategy and innovation. Long range planning, 43(2), 172-194.

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• Explain what the authors mean with this statement: The business model outlines the architecture of revenues, costs, and profits associated with delivering value. It is, in essence, a conceptual, rather than financial, model of a business, embodying the organizational and financial 'architecture'.

  this structure is conceptual, not a detailed financial spreadsheet. In other words, a business model is a high-level blueprint of how the business is organized and how the money is supposed to flow — the “organizational and financial architecture” — rather than the precise numerical budgets, forecasts, or accounting figures. It shows the logic of the business, not the exact math.

• Why does Teece argue that the concept of a business model has weak grounding in traditional economics?

  Traditional economics assumes perfect markets where prices and full information solve all coordination problems.
  Under these assumptions, firms don’t need to think about value propositions, delivery mechanisms, or how to capture value — so business models never appear in economic theory.
  But in the real world, markets are imperfect and involve intangible goods, platforms, and customers who want solutions, so managers must design business models to create, deliver, and capture value.

• What does Teece mean by “learning and adaptation” in business models?

  Teece argues that a business model is essentially a management hypothesis, so the correct model is rarely obvious at the start. Firms must experiment, learn, and adjust their model over time.
  Because markets, technologies, and regulations continually change, successful business models must evolve (morph) as well.
  Companies that fail to update their model—even if it is currently profitable—risk serious problems when external conditions shift.

• 2 Week 2

• 2.1 Black, N.J., Lockett, A., Ennew, C., Winklhofer, H., & McKechnie, S. (2002). Modelling consumer choice of distribution channels: an illustration from financial services. International Journal of Bank Marketing, 20(4), 161-173.

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• III. Expanded Final Model (Four Factors)After the focus groups, the authors integrate:prior research,theory,and the interview results→ to build a more complete conceptual model.This final model identifies four distinct factors influencing channel choice:

  1. The Consumer characteristics: Personal traits shape channel choice:
  

  • age, income, lifestyle, confidence, tech skills.
    
  • Financial knowledge especially matters.
    

  2. The Product characteristics: Two product characteristics matter most:
  

  • Complexity (simple vs. complicated)
    
  • Perceived risk (low vs. high risk)
    

  Simple → online is fine
  Complex → face-to-face preferred
  3. The characteristics of the channel: Consumers evaluate each channel based on:
  

  • convenience
    
  • accessibility
    
  • perceived risk
    
  • cost
    
  • ease of use
    

  Channels differ, so choice depends on situational fit.
  4. The Organization’s Reputation/characteristics: Reputation carries over as a major predictor:
  A trusted brand makes consumers more comfortable using technology channels.

• The conclusion summarizes the dominant forcesThe authors step back and ask:What really drives channel choice the MOST in financial services?

  The authors propose a four-factor model (consumer, product, channel, reputation), but in their conclusion they emphasize the three strongest and most decisive forces in financial services:
  
  

  • Trust represents → organizational reputation
    
  • Risk represents → perceived risk of product AND channel
    
  • Product–channel fit represents → the matching of complexity + convenience
    

  
  The other factors (like demographic variables) are weaker predictors, so they don’t appear in the final concluding sentence.

• 2.3 Lindič, J., & Marques da Silva, C. (2011). Value proposition as a catalyst for a customer focused innovation. Management Decision, 49(10), 1694-1708.

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• What is the main idea of the paper regarding value propositions in regards to innovation?

  The paper argues that value propositions become powerful drivers of innovation when they are broken down into clear, structured elements. By decomposing the value proposition, companies can better understand what customers truly value and use this insight to create more effective and customer-focused innovations.

• 3 Week 3

• 3.2 Duncan, D.S., Anderson, T., & Saviano, J. (2025). AI Is Changing the Structure of Consulting Firms

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• Why is the pyramid structure crumbling?

  2. How AI is destroying the pyramidAI systems can now perform:
  

  • data gathering
    
  • modelling
    
  • scenario analysis
    
  • research
    
  • synthesizing reports
    
  • crafting slide decks
    

  Examples cited:
  

  • McKinsey’s Lilli (used by 72% of workforce; ~30% labour reduction in research/synthesis)
    
  • BCG’s Deckster (generates slides in minutes)
    
  • Bain’s Sage
    
  • Deloitte’s Zora
    
  • PwC’s agent OS
    

  These tools replace thousands of billable junior hours.
  Consequences:
  

  • The base of the pyramid becomes unnecessary
    
  • Automation begins to reach middle-tier tasks, not just junior-level work
    
  • A large junior workforce is no longer economically justified
    

  → The pyramid collapses under its own weight