What is Big?

The risks of big are reflected in these interactions, but often not in theories of big, which is why such theories often get the risks of big wrong.

Whether something is big seems obvious enough. Yet the construct of big and the related ideas of large, large-scale, major, mega, giga, huge, etc. prove deceptively elusive when subjected to scrutiny. A literature review of definitions of big and related words reveals a non-exhaustive list of multiple dimensions of the construct of big such as:*

• Physical proportions measured in height, length, mass, weight, area, or volume;
• Inputs required to build and run the thing measured in terms of quantities (and quality) of land, labor, or equipment required;
• Financial outlay measured in upfront capital expenditure, recurrent operational expenditure, or end-of-life costs;
• Supply measured in the units of output that the thing can produce or the multiplicity of outputs;
• Demand being served measured not only in terms of units of demand but also the quality, speed, and functionality;
• Temporality measured in time it takes to build the thing or the length of its life span;
• Spatial fixity or immobility and the cost of moving an asset—big tends to “spatial fixity”;
• Complexity measured, for example, with a focus on the technical aspects of the asset or its delivery; or with a focus on the social and political complexity;
• Impact measured in number of people who might benefit or be harmed; number of functions enabled or disabled; or the magnitude and pace of change the thing can cause in its environment.

The relationships among these multiple dimensions—and even the indicators within each dimension—are seldom straightforward. For instance, it is often taken for granted that in order to reduce the amount of time required to complete a venture, e.g. a software IT project, a manager would need to mobilize more programmers, which will also increase the capital expenditure of the venture.

Bigness entails multiple and unpredictable interactions across the dimensions listed above with which theories of big—such as the notion of economies of scale—have not meaningfully engaged. The risks of big are reflected in these interactions, but often not in theories of big, which is why such theories often get the risks of big wrong.

Read more here.

*) For the full text with references, see Atif Ansar, Bent Flyvbjerg, Alexander Budzier, and Daniel Lunn, 2017, "Big Is Fragile: An Attempt at Theorizing Scale," in Bent Flyvbjerg, ed., The Oxford Handbook of Megaproject Management (Oxford: Oxford University Press), Chapter 4, pp. 60-95, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2741198.