For theoretical as well as practical reasons, applied decision analysts have shown considerable interest in decomposed multi-attribute utility assessment procedures. These procedures require that the decision maker first specify the value attributes of interest, then evaluate each outcome with respect to each attribute, and finally specify a composition rule and scaling factors so that utility may be arithmetically aggregated across attributes. The decomposition approach may be contrasted with holistic scaling procedures in which the decision-maker simply makes an over-all intuitive assessment of the utility of each multi-attribute outcome. The paper begins with a discussion of the relative merits of the two approaches. Then decomposition procedures for both risky and riskless decision-making are described. Finally, an experiment comparing holistic and decomposed assessment procedures is discussed in which the two approaches to scaling assigned very similar utilities to three-dimensional job descriptions for both risky and riskless decisions. © 1977.