Click for the Ralph Gomory profile at the IBM archives
One of my activities on my recent blogging hiatus was an oral history interview with Ralph Gomory. The interview was originally instigated as part of the AIP History Center’s History of Physics in Industry project, on which I’ve helped out here and there. Our discussions with researchers at IBM all pointed to Gomory as a crucial figure in that company’s history. Personally, I had a strong interest in the interview, because Gomory’s background is in mathematics, and he is a notable figure in the operations research (OR) community, primarily on account of his foundational work on integer programming. (For those keeping track, I wrote my dissertation, and am currently polishing up a book manuscript, on the history of certain sciences of policy analysis, including OR.) This post is mainly based on the background research I did ahead of the interview.
Gomory was director of research at IBM from 1970 to 1986. IBM Research had been established in its present form in the late 1950s by Emanuel Piore. Piore had spent much of his postwar career at the Office of Naval Research, culminating in a stint as Chief Scientist. Careful readers of Zuoyue Wang’s recent book on the President’s Science Advisory Committee (to be discussed on this blog presently) will know that Piore became a ubiquitous figure on various high-level government panels (i.e., though not well-known to historians, he was a big deal).
The idea behind establishing IBM Research was the general sense, widespread in the 1950s and ’60s, that technologically-oriented companies would be well-served by conducting their own basic research. Piore’s goal was to establish an environment — housed in a modern building designed by Eero Saarinen — where researchers could freely explore their own ideas. Gomory had originally been brought in to be part of the new mathematics department (along, incidentally, with fractal geometry pioneer Benoît Mandelbrot).
Now, going back to my previous post’s interest in basic research and the “linear model” in history: once one had established the importance of the link between research and technological development, one was faced with a series of subsidiary questions, to which one would have devoted more or less thought. At what level should this research be funded, overall? What sorts of organizations should house research activities? In what ways, and to what degree, should research activities be connected to, or liberated from, organizational (or simply others’) goals? Of all possible specialties, what sorts of specialists should particular organizations hire? According to what criteria should organizational managers initiate, discontinue, prioritize, and fund competing research projects? Answers to these questions necessarily depended on more specific notions of the importance and character of research activities and their connection to technological work.
Gomory’s long term as director of research was, in many ways, centered around an attempt to better integrate IBM Research’s to-that-point freestanding activities into corporate strategy. He became convinced that the best opportunities for research contributing to IBM’s products were generally limited to very certain points in the product development cycle (the succession of generations of products). Developers and manufacturing engineers were often better positioned to offer judgment on what research results would prove the most useful to them, even as their ability to do so was predicated on researchers effectively communicating potential implications of their work to the engineers. IBM Research, meanwhile, would continue to pursue open-ended academic-type work — including Nobel Prize-winning work — but the research division also began to concentrate more on problems suggested by difficulties and challenges foreseen in the product development and manufacturing processes.
In the 1980s and ’90s, at IBM, and then as president of the Sloan Foundation, Gomory began to publish short articles about the management of research, initially concentrating on the problem of the Japanese challenge to American competitiveness. IBM, of course, experienced first-hand the threat from surging Japanese electronics firms. Gomory’s articles responded to what he believed were misguided appeals to American underinvestment in research and science education as explanations for the challenge. For example, some commentators, particularly academic researchers, were likely to point to large Japanese research investment and state projects, notably those at MITI (now METI), as a key source of the challenge. (Incidentally, the international polemical/political arc leading from DSIR to MITI would be well worth tracing.) Gomory preferred to point to particular Japanese methods of integrating design, manufacturing, and marketing, and their contraction of the product development cycle, to explain their successes.
Accordingly, while Gomory supported funding American basic science to maintain competitiveness in all fields, he argued that it was unlikely to make a substantial contribution to pressing problems of national economic competitiveness. He attributed the idea that it could to what he referred to as the “ladder of science” model (essentially the linear model). He asserted that whatever advantages might accrue from success with that model were fleeting as new industries based on novel technologies were quickly replicated in other nations. Most economic advantage and long-term success was grounded in large industries’ ability to put low-cost, high-quality products through the development cycle more rapidly than their competitors. Academic researchers were even less likely than industrial researchers to know what research results could be fruitfully applied in the cycle.
One lesson we could draw from the arc at IBM Research from the ’50s to the ’80s is a progression in ideas from Piore to Gomory. This would map well onto existing narratives detailing a widespread questioning of the wisdom of unalloyed support for research in the 1960s and ’70s, which has been linked to a decline of the perceived validity of the linear model more generally. The classic example is the increased Congressional questioning of military support for university research, punctuated by the Defense Department’s mid-1960s “Project Hindsight”, a study that failed to find a substantial link between advances in military technology and investment in research.
Framing this story in terms of the rise and fall of the linear model makes sense, because it renders a rationale for the support for research as a path to technological and economic prowess. However, my own preference (and I think this mainly accords with David Bruggeman’s suggestion for thinking of the linear model as “incomplete”) is to think of a sort of undefined virtue as having been attributed to research, with little further reflection being given to problems such as who should be responsible for supporting research, and what institutional frameworks best mediate between university research, industrial research, and technology development communities.
This could all reduce down to “I say po-tay-to, you say po-tah-to”, but my feeling here, also expressed in my previous post, is that doing away with the historical idea of a linear model frees us up to look at, and evaluate the relative significance of the history of other rhetoric, other ideas, and other practices. For example, while it seems likely that high-level managers and policymakers were convinced to support research perhaps out of some vague notion that it would yield occasional windfalls, this support would likely have been disconnected from their management or policymaking regarding technology development activities, which do not seem to have been substantially chained to any linear model, even though these activities were ostensibly a part of it.
From this perspective, the focus in the IBM Research narrative can be detached from Gomory’s reforms and criticsm; instead those reforms and criticism become an invitation to look at the significance of the history of company management, technology engineering, and marketing, and its relationship to scientific research for what it was, rather than for what it failed to be. Fortunately for us, the house history of computing leaves us with a good head-start in the case of IBM, and studies such as Christophe Lécuyer’s of Silicon Valley, or Joan Bromberg on the joint-history of quantum optics and the laser industry, give us a good look at what a more integrated history would look like (although one should note both these cases focus on novel industries).
Indeed, we have a good start on a long-term historiography of these areas, as early modern technology-knowledge confluences in areas such as naval architecture, waterworks, practical medicine, and chemical dyes have found historians’ interest, and there is also good work in later periods on topics such as metrology, telegraphy, and forestry. The difficulty, as ever, is broader survey and synthesis. To develop what I would view to be a satisfying historiography, it is not enough to say, “but so-and-so did their case study of X, which amply demonstrates the historical connection between science and technology; how can you say there is not a sufficient historiography on the matter?”
The point is, we need to find better ways to talk about developments and trends en masse, to get out of the “view from the archive folder”, to deal not with just the actions of a single committee, for instance, but to describe how the work of thousands of committees coordinated the scientific and technological world. I am convinced that if this happens, the historiographical importance of things like some “linear model” will start to seem very odd in retrospect, that, somehow, we became distracted by a few snippets of rhetoric that, while prominent and even influential in some respects, can only be properly evaluated amid a much larger, and more complex context. From this view to focus historiography on a few items of rhetoric would be to make the same mistake of incompleteness as those who deployed that rhetoric in the first place.