How does the functioning of a business change as it grows? What factors determine the sizes of businesses that we see today? There are two theoretical extremes for the distribution of business sizes. One is that all businesses are sole proprietorships, which might arise if there were no advantage to scale. The other extreme is that all business activity occurs under a single megacorporation, which might arise if there were no disadvantages to scale. The fact that neither of these extremes are observed suggests that the current distribution of business sizes results from an equilibrium between economies and diseconomies of scale.
Business Scaling Defined
Several researchers have posed different definitions for scaling in business, leaving the precise definition of the term ambiguous.
Bohan et al. (2024) define scaling as a “time-limited process of exponential growth”. The term “exponential” is often misused in the literature to mean merely fast growth; in Bohan et al. (2024), the term is used precisely to refer to a process in which the growth rate is proportional to the current size, so that there a fixed percentage growth in every time period. The “time-limited” aspect of the definition is needed, as exponential growth in any physical system can continue only for a limited time. Thus in Bohan et al. (2024)’s formulation, scaling is a process that has a beginning and an end.
In Bohan et al. (2024), “scaling” is a from of growth, but growth is a broader concept that is not necessarily exponential, and thus is not necessarily scaling under the definition. For that, they cite the definition of the Organization for Economic Co-operation and Development (Eurostat and OECD 2007) of a High-Growth Firm, which is a firm that has an average employment or sales growth of at least 20% per year over three years and has at least 10 employees at the start of the period.
Although not strictly part of the definition of scaling, Bohan et al. (2024) add two elaborations that help point to the nature of the process. The first is increasing returns to scale, or that the ratio of output revenue to input costs should grow with size. This feature of growth creates a natural competitive advantage to size and an incentive toward scaling. The second is that the scaling process should necessitate internal transformation of the firm to cope with a larger size.
Palmié et al (2023) define scaling as an
increase in the size of a focal subject that is accompanied by a larger-than-proportional increase in the performance resulting from the said subject.
This definition is more general than that of Bohan et al. (2024), in that it can apply to many kinds of systems, rather than just firms. The definition of Palmié et al (2023) does not require that the rate of growth be exponential, and thus slow, linear rates of growth may be considered scaling. On the other hand, increasing returns to scale, which are a nonessential elaboration in Bohan et al. (2024), are inherent to the definition of Palmié et al (2023). For a business, “size” may be defined over four metrics: market scaling, volume scaling, financial scaling, and organizational scaling.
Shephard and Patzelt (2020) define scaling as “spreading excellence within an organization as it grows”. Here, “excellence” refers to those practices that are necessary to the thriving of the organization. This definition highlights the challenge that a growing business faces of maintaining its competitive advantages as it becomes necessary to install more bureaucracy to cope with size.
Drivers of Scaling
Bohan et al. (2024) identify three factors that motivate scaling. The first factor is economies of scale, an idea Adam Smith (1776) discusses in The Wealth of Nation, which holds that the unit cost of production tends to decrease with volume. The essay Dikshit (2022) outlines several well-established economies of scale. With higher volume, it is possible to specialize in the roles that employees perform, thereby improving production efficiency. Certain fixed costs, such as research and development, are lower on a per-unit basis with higher production.
The second factor of Bohan et al. (2024) is economies of scope. Economies of scope are closely related to economies of scale, and they refer to decreased unit cost for a wider range of products, as opposed to increased production of a single product. As is the case with economies of scale, Dikshit (2022) points out that a company with a larger set of products can divide certain fixed costs, such as research and development between them, thereby lowering per-unit costs.
Both economies of scale and economies of scope are enhanced by learning effects, as Bohan et al. (2024) assesses. Learning curves were introduced by Wright (1936) and hold the unit cost for producing a good should decreased by a fixed percentage for every doubling of cumulative production of that good.
The third factor that Bohan et al. (2024) identifies as a motivation for scaling is external economies of scale. An especially important example is a network effect, whereby a product gains value for the more people who use it. Metcalfe’s Law (Metcalfe 2013), for instance, finds that the total economic value of a network, such as Ethernet, grows with the square of the number of users of the network.
Limits to Scaling
As Bohan et al. (2024) discuss, the number of possible one-on-one relationships within an organization grows with the square of the number of people: specifically, if there are n employees, then there are n(n-1)/2 possible relationships. Equivalently, each person can interact with n-1 other people. As an organization grows, the number of possible relationships becomes unmanageable without hierarchy.
McAfee and McMillan (1995) develop a model of how a business’ costs rise with the hierarchy length, which is the number of layers of management between the principle and the agents, who are assumed to do the actual production. Their model is based on rent-seeking on the basis of asymmetric information. Agents engaged in production have useful information pertaining to the production process, such as techniques for keeping tools fully utilized, that is not readily available to the agent who is making decisons about the company. The information asymmetry allows agents to extract rents, whereby they inflate cost estimates and underestimate production capacity. When multiple layers of management exist, as is necessarily the case in a large company, each layer is able to extract rents in this fashion, and thus the informational rent grows exponentially in the number of layers of management.
Citing Schiff and Lewin (1968), McAfee and McMillan (1995) estimate that in a typical corporate division, 20-25% of the budgeted operational expenses are informational rents of this nature. This value was estimated by observing the budget estimates of three large corporations in the United States during both good and lean times and finding that the estimates differ much less than they should based on external conditions. To validate the model, McAfee and McMillan (1995) observe a decrease in firms’ budget estimates in China after economic liberalization, which removed a level of hierarchy between the individual firms and state planning boards.
The model of McAfee and McMillan (1995) focuses only on the cost of information rents, acknowledging but not modeling other costs associated with firm size, such as increased communication costs. The authors also do not model advantages of firm size, and they attribute the existence of informational rents to imperfectly competitive industries; were an industry fully competitive, firms with such inefficiencies would not be able to function, and the industry would be dominated by small firms.
References
Bohan, S., Tippmann, E., Levie, J., Igoe, J., Bowers, B. “What is scaling?”. Journal of Business Venturing 39(1): 106335. January 2024.
Eurostat and OECD. “Eurostat-OECD Manual on Business Demography Statistics”. ISBN 978-92-79-04726-8. December 2007.
Palmié, M., Parida, V., Mader, A., Wincent, J. “Clarifying the scaling concept: A review, definition, and measure of scaling performance and an elaborate agenda for future research”. Journal of Business Research 158: 113630. March 2023.
Shepherd, D.A., Patzelt, H. “A Call for Research on the Scaling of Organizations and the Scaling of Social Impact”. Entrepreneurship Theory and Practice 46(2), pp. 255-268. September 2020.
Smith, A. “An Inquiry into the Nature and Causes of the Wealth of Nations”. 1776.
Dikshit, S. “Exploring the Economies of Scale, Scope, and Changing Technology”. Media Economics, ed. Shaikh, J. and Naik, N. S. 2022.
Wright, T. P. “Factors Affecting the Cost of Airplanes”. Journal of the Aeronautical Sciences 3(4), pp. 122-128.
Metcalfe, B. “Metcalfe’s Law after 40 Years of Ethernet”. Computer 46(12), pp. 26-31. December 2013.
McAfee, R. P., McMillan, J. “Organizational Diseconomies of Scale”. Journal of Economics & Management Strategy 4(3), pp. 399-426. September 1995.
Schiff, M., Lewin, A. Y. “Where traditional budgeting fails”. Financial Executive 36, pp. 50-62. 1968.