My final semester at HBS was a unique experience studying the business models of technology‐based ventures from two different perspectives. From late March to May, Competing Through Business Models (CTBM) class with Professor Hanna Halaburda equipped me with frameworks for how firms create and sustain competitive advantage through their business model designs. From January to early March, Launching Tech Ventures (LTV) class with Professor Tom Eisenmann exposed me to the approaches entrepreneurs use to erect attractive and scalable business models from scratch.
Despite the clear interrelatedness of the two topics, the content of the courses could not have been more different. CTBM defines a business model as the logic of a firm, the way it operates to create and capture value for its stakeholders. Expressed as a set of policy, asset, and governance choices (and the consequences derived from those choices), business models are most effective when they support virtuous loops of value creation aligned with a company’s mission. The diagram below captures a simplified representation of the business model for Microsoft’s operating systems and productivity applications business. Here, management decides to set low prices for its operating system, set high prices for its applications, and invest heavily in R&D for next generation operating systems, putting in motion a series of consequences that are self‐reinforcing and defensible, creating a sustainable business model.
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| Source: CTBM Introductory Note, Jan. 2011 |
In the world of CTBM, analytical techniques such as game theory and classic optimization are the tools of choice for decision‐making. Changing the pricing scheme is about finding the Nash Equilibrium. Augmenting the product portfolio is about evaluating and optimizing the payoff matrix. The CTBM toolset must be familiar to any entrepreneur building a new business model in practice, right?
So why the fundamental disconnect? The answer seems to lie in the fact that business model design from scratch is a messy undertaking. The number of decisions that must be made is often astounding. The interactions between various sets of choices are often complex. Competitive dynamics are constantly altering the viability of certain approaches. In situations of such uncertainty, designing a business model is a highly strategic exercise that does not lend itself to white‐boarding in a vacuum or deriving purely analytical solutions. Instead, one increases the likelihood of success through a balance of other factors. Experience accumulated over time provides the intuition to develop accurate hypotheses about what works and what does not. Experimentation provides a constant stream of market feedback to update and refine initial assumptions.
The Lean Start Up Methodology works because it prescribes how the entrepreneur should apply these factors in a manner that best conserves cost and risk. The CTBM toolkit, in contrast, is best applied in situations where the uncertainty is more manageable—e.g., to identify incremental improvements to business models that are already in operation. Here, the interactions between choices are better understood, and the range of outcomes more limited. In such a case, decisionmaking takes place at the tactical (not the strategic) level, making analytical approaches more tractable.
The Lean Start Up Methodology is less appropriate in such a situation; while experience and experimentation are still fundamental elements of the business model design process, analysis rises in importance as the scope of uncertainty becomes more manageable. LTV and CTBM each provide frameworks for addressing the challenge of designing business models for technology companies. Contrasting the two clarifies the context in which each toolkit is appropriate.
