Data has become a central asset supporting decision-making in modern business environments. Internet of Things (IoT) solutions in particular are designed to gather information from a large variety of monitorable entities, providing companies with seemingly unlimited abilities to measure and analyze factors such as performance and productivity. Considering the reliability and trustworthiness in datadriven decision-making, the accuracy of the leveraged information is critical. While the development of IoT solutions makes them continuously more accurate, caution must be applied not only in terms of potential inaccuracy caused by technical failures but also by human error. Thus, some of the key questions to consider when investigating the accuracy and trustworthiness of data are: is the gathered information itself correct, is the leveraged data contextually correct, and what are the potential issues caused by human error. From an ethical perspective, the justifiability of leveraging potentially incorrect data needs to be addressed. When decisions related to individual employees are being made based on data, it is necessary to not only consider the possible inaccuracy of the data but also to prevent manipulating or distorting the results by applying too limited or falsely selected data, creating a biased basis for analysis and decisions.