Systems, Nontrivial Machines, Circular Causality, and Other Ghosts Haunting Performance Improvement Technology

by

Wittkuhn, K. D. (2004). Systems, nontrivial machines, circular causality, and other ghosts haunting performance improvement technology. Performance Improvement, 43(3), 33-37. Retrieved from http://search.proquest.com/docview/237230813?accountid=13360

In this article, Wittkuhn argues against a number of human performance technology practices to better help his readers more accurately address and understand performance issues they come across. He concludes that systemic approaches, nontrivial machines, and performance gaps are inherently flawed due to elements such an unreliability and lack of knowledge or understanding. As a part of his argument, he doesn’t suggest that these practices be avoided; rather, that the considerations he makes be considered by professionals as they use such practices within their organizations.

Wittkuhn’s argument is convincing. In particular, his claim that human performance cannot be engineered is both appropriate and curious; on one hand, such engineering seems to be an inherent part of human performance technology. On the other hand, his discussion of the unreliability of human reactions – that we cannot predict with 100% accuracy how humans will respond to different elements of a system – is entirely correct. What he fails to mention, though, is the reliability with which we can predict a number of behaviors through thorough learner analysis. Simply put, Wittkuhn’s argument suggests that the engineering of human performance is more abysmal than it is. While performance systems cannot be 100% accurate, learner attitudes and reactions can be predicted with a degree of reliability.

He makes a similar argument in regards to defining problems and performance gaps. Essentially, Wittkuhn seems to suggest that problems cannot be defined with accuracy because of the individual’s existing presuppositions, which would distort his or her ability to see the solution. Despite this, he seems to have few thoughts on how human performance professionals can limit such presuppositions in the workplace.

Overall, Wittkuhn’s argument, while convincing, is remarkably pessimistic and lacking solutions to the problems he suggests. While many of the practices he discusses are inherently flawed, it would be interesting to read his thoughts on how human performance professionals may use their understanding of such flaws to better impact their own success in the field.