Excursion 3

In the 1960s, management scholars were attempting to deconstruct every aspect of business operations. This effort was driven by a number of important scholarly questions about management and strategy. Questions such as:

• “How do managers make decisions without full information?”
• “Why do the companies in the same industry look similar? But why aren’t they exactly the same?”
• “Why do some companies consistently outperform others?”
• “Why does change help some companies but hurt or destroy others?”

This was also the point at which computational power was becoming available to researchers in the social sciences. Some management scholars wondered if they could create programs that would replicate the activities that take place inside organizations. Studying companies is incredibly difficult for three key reasons. First, most companies are not thrilled to have researchers wandering the halls, attending important (and possibly confidential) meetings, and generally taking up employee time with a series of fascinating but often odd or apparently irrelevant questions. Second, interesting companies are usually dynamic entities subject to a broad range of forces and factors, undergoing continuous change. Anything observed today might not be relevant next year, next month, or even tomorrow. Finally, the data collected usually suffers from a variety of potential flaws and biases, and may be subject to multiple, dramatically different interpretations. In other words: getting the data is difficult, there is no guarantee the data is valid, and different people might interpret the data differently. A computation simulation of a company looked like a possible solution to all of these problems.

The reality was something different. The computation models of businesses were extremely powerful for evaluating specific macro and micro-level phenomena. For example, in 1964 Herb Simon and Yuji Ijiri simulated the growth profiles of firms to explain distribution of firm sizes across a hypothetical industry. At nearly the same time (1963), Richard Cyert and James March were showing that “rules of thumb” were good predictors of complex decision-making within companies, such as product pricing. It could be imagined that these highly influential management scholars might have progressed towards simulating micro-level “business models.”

As it turns out, computational models of activity within business remain relatively unexplored. The field of management moved away from systemic approaches to organizational activity to focus primarily on decision theory, especially in the context of corporate strategy. The problem was, quite simply, that models of organizations couldn’t easily take into account either the complexity of the broader environment or the non-rational decision-making of organizational participants. The simplifications required to create “business models” made them unconvincing to traditional scholars, especially economists. Herb Simon said this explicitly, if a bit ponderously, in his 1978 Nobel Prize acceptance speech:

However well this characteristic of a business firm model corresponds to reality, it reduces the attractiveness of the model for many economists, who are reluctant to give up the process-independent predictions of classical theory, and who do not feel at home with the kind of empirical investigation that is required for disclosing actual real-world decision processes. Herb Simon - 1978 Nobel Prize acceptance speech

The business model as a "model of a business" never gained traction. It would be 20 years before a very different approach to business models would take hold. The chart below shows how often "business model" was mentioned in Harvard Business Review-- the most highly regarded management practice journal. That approach would be fueled by the most disruptive technology innovation of all, the internet.

Number of articles in Harvard Business Review that mention "business model" from 1926-2008. Prior to 1994, There had been less than one mention per year. Source: EBSCO Business analysis by the author.