Although recent reviews of executive selection have catalogued much that we as industrial–organizational (I–O) psychologists are doing right in our research and practice, we are confronted with the facts that executive selection decisions are often, if not usually, wrong and that I–O psychologists seldom have a place at the table when these decisions are made. This article suggests that in our thinking we have failed to differentiate executive selection from selection at lower levels and that we have applied the wrong models. Our hope for the future lies not in job analyses, developing new tests, meta-analyses, or seeking psychometric validity, but in viewing executive selection as a judgment and decision-making problem. With the right focus, applying our considerable methodological skills should enable us to contribute toward making better judgments. When we have a better mousetrap, organizations (if not the world) will beat a path to our door.

We propose that I/O psychologists who coach executives have overlooked psychotherapy outcome research as a source of information and ideas that can be used to improve our executive coaching practices. This research, based on thousands of studies and many meta-analyses, has converged on the conclusion that four “active ingredients” account for most of the variance in psychotherapy outcomes. We describe how this literature has identified four primary “active ingredients” that account for most of the variance in psychotherapy outcomes: 1) Client/extratherapeutic factors (40%), 2) The relationship or alliance (30%), 3) Placebo or hope (15%), and 4) Theory and technique (15%). Working on the assumption that psychotherapy and executive coaching are sufficiently similar to justify generalization from one domain to the other, we describe these four active ingredients at length and explore how they may be at work in the executive coaching process. We also suggest that I/O psychologists have training and experience that allows us to leverage some of these active ingredients in our executive coaching (e.g., understanding of client individual differences related to coaching outcomes). But we also have areas of weakness (e.g., building a strong working relationship with an individual client) that may need to be bolstered with additional training and development experiences.

Organizations today are increasingly focused on talent as a strategic asset and a competitive advantage for achieving business success. As a result, most major organizations have recognized the need for and outlined a formal process to identify and assess high-potential talent. There is, however, little agreement within or between organizations on the definition and components of the concept of potential. The existing definitions and models of potential are often narrowly focused on only a few select factors and give little attention to the broad spectrum of potential talent in an organization. This article introduces a new integrated model of potential that incorporates previous literature and current assessment practice regarding high potentials, provides a coherent structure of potential, and is reflective of a variety of different talent pools. The model provides a useful method for answering the key question—Potential for what? Three key components of potential are described by the model: (a) foundational dimensions, (b) growth dimensions, and (c) career dimensions. Implications for assisting organizations in more effectively managing their high potential talent for strategic business objectives are discussed.

Early in 2006, my colleagues and I published an article on unproctored Internet testing (UIT) in employment settings (Tippins et al., 2006). The purpose of that article was to identify the issues surrounding UIT and the ways in which those issues might be resolved. The panel of experts addressed a number of important questions about (a) the uses and applications of UIT and (b) the major issues and known problems associated with UIT, including test security, examinee identification, cheating, ethical use of tests, subgroup and cultural issues, standardization, and context effects. In addition, the panelists attempted to predict the future of UIT, highlight the research needed to facilitate UIT and provide advice to practitioners contemplating UIT. In the present article, “UIT” is used to refer to Internet-based testing completed by a candidate without a traditional human proctor. Thus, nontraditional forms of or alternatives to proctoring may be in place, such as quantitative analyses of response patterns, the use of video cameras, or follow-up testing with traditional proctoring.