The purpose of the present study was to examine the impact of culture and human-related elements on the On-line Analytical Processing (OLAP) usability in generating decision-making information. The use of OLAP technology has evolved rapidly and gained momentum, mainly due to the ability of OLAP tools to examine and query large amounts of data sets according to varying decision attributes. The evolution of OLAP technology has its share of benefits, problems and challenges as in the case of many other technology advancements. Scholars and practitioners indicated that human-related elements were consistently the most common problems associated with using OLAP tools. The present study used a quantitative design and a sample of 156 completed attitudinal surveys of OLAP users, decision makers and system professionals in 20 companies in the United States. The goal was to measure the impact of users' attitudes toward OLAP (ATO), users' satisfaction level with OLAP tools (SLO), willingness to share knowledge (WSK), users' technical skills (UTS), and users' abilities in interacting with OLAP tools (AIO) on OLAP usability. Two-way ANOVA, correlation, and hierarchical regression analyses revealed that ATO (F = 28.36, df = 1,153, p ≤ .000), UTS (F = 65.824, df = 2,150, p ≤ .000), and AIO (F = 71.469, df = 1,152, p ≤ .000) have statistical significant impacts on overall OLAP usability. Conversely, SLO (F = 20.86, df = 1,153, p ≤ .191) and WSK (F = 2.429, df = 2,149, p ≤ .0920) did not have statistical significant impact on OLAP usability. The present study applied and expanded the usage of the Technology Acceptance Model (TAM). Understanding the factors that affect OLAP usability is essential for companies that have invested in OLAP technology. The recommendations of the present study are helpful for top managers and business executives to improve OLAP usability in generating decision making information. Finally, the evidence of the present study has contributed to the body of knowledge and opened the field for future studies of OLAP target users based on socio-demographic factors and based on different types of organizational cultures.