Prelude to Chapter 13
GENERATING OPTIMAL ORGANIZATIONS
SOMEONE ONCE ASKED the intriguing question, “What is Beethoven's Ninth?” Surely, it is not merely the printed orchestral score of Beethoven's Ninth, since the Ninth Symphony is a beautiful piece of music, while the score is a silent pile of paper with ink marks all over it. By the same token, there are as many audible realizations of that single printed score as there are conductors and orchestras (each with their idiosyncratic tempi, dynamics, phrasings, and other expressive particularities), open air amphitheaters, and intimate concert halls (each with their individual acoustics). It seems to me that “Beethoven's Ninth” can only denote the complete set of possible realizations generable under (encoded in) the score.1 If the cardinality of this set were one, we'd need only one recorded performance of Beethoven's Ninth. Yet we have new ones each year. The score encodes a seemingly infinite generative capacity.
The agents you are about to meet in the adaptive organization model have fixed behavioral rules and fixed numerical parameters. One can think of this agent microspecification as a fixed genome analogous to a printed score. The agents face dynamic environments to which they must adapt in some way. Even with a fixed genome, different environments produce radically different adaptive histories. In certain environments, the agents endogenously generate hierarchies; in others, they forgo hierarchy and engage in internal trade. While the fixed genome is analogous to the printed symphonic score, the dynamic environment is analogous to the pressures exerted by conductor, orchestra, concert hall, and so on, each of which generates a different performance.
In this chapter, we are going to pose a question whose musical analogue would be strange. It would be: What is the optimal score for the Berlin Philharmonic to perform? We will introduce a notion of fitness that will allow us to rank performances. We will fix a dynamic environment (fix the orchestra, and so on). And, by combinatorial optimization, we will determine the optimal genome (the optimal score) in that environment (for that orchestra). And then we'll “listen” to it (will watch the optimal history of organizational adaptation as a movie)!
Verticality
The models presented thus far unfold on various spaces—two-dimensional lattices, one-dimensional rings, environmental landscapes, towns, social networks. But they are all “flat.” There is no hierarchical aspect; no agent really has “authority” over any other. There are no superiors or subordinates. The principal way in which the adaptive organization model differs from the rest is precisely that agents generate and dissolve hierarchies locally.
At the most abstract level, the organization's problem is long-range resource allocation, and it must discover when (very expensive but highly efficient) “top down” global reallocation dominates (cheap but sluggish) reallocation through a series of short-range tradelike transactions. In the neoclassical picture, management structure is absent and inputs are adjusted to maximize something (e.g., profit). Here, inputs (labor) are fixed, and it is the management structure that is varied to optimize.
Variable Geometry Firms
For the particular environmental dynamic used in this study, the optimal history of structural adaptation involves oscillations between “flat” trading regimes and hierarchies, in perpetual motion up and down a spatial market as a traveling wave. So the optimal organization does not have a fixed structure. It is a variable-geometry firm.
1 So, in a sense, it remains, and ever will remain, a work in progress. In this sense, all symphonies are unfinished!