The search for fundamental laws, unfortunately, has seldom, if ever, been applied to professional communication. Most how-to books on the subject seem content with long lists of phenomenological principles. Useful as each of these might be, a long list of them will always be hard to assimilate, at least without some perception of a simpler underlying logic. This article proposes three fundamental "laws of professional communication," on the model of Asimov's three laws of robotics. It motivates them on the basis of a simple premise, illustrates them with examples of oral, written. and graphical communication, and discusses their precedence and their subordination to a zeroth law.

Ask any specialist of professional communication how many items we can hold in short-term memory: almost certainly, he or she will answer seven (possibly, seven plus or minus two). Ask that person where this answer comes from: very likely, he or she will refer to an article published almost fifty years ago in Psychological Review (G.A. Miller, 1956). Equally likely, however, he or she will never have read this article and will happily go on quoting it out of context. The article denounces the seven-plus-or-minus-two myth. It first reviews George Miller's original paper, placing the limit of seven in a proper perspective and drawing other, possibly more useful lessons from the research presented. Next, it explores the guiding value of integers below seven and proposes other, equally magical, but more pragmatic limits for effective professional communication.

When it comes to graphing data, most professionals show little method or creativity. They typically limit themselves to a small repertoire of graph types and select from it on the basis of habit, if not sheer ease of production. Similarly, the many books on graphing devote much attention to graphical integrity and readability, but little or none to graph selection. We developed a methodology to help engineers, scientists, and managers choose the "right graph" on the basis of three criteria: the structure of the data set in terms of number and type of variables, the intended use of the graph, and the research question or intended message. The first and third criteria allow one to construct an effective two-entry selection table.