Impact of the product master data quality on the logistics process performance

Background: The importance of up-to-date product master data in the digital age should not be underestimated. However, companies still struggle to ensure high-quality product data, especially in the field of logistics. Hence, the focus of our research lies in the disregard of the importance of product data quality to the performance of logistics processes. Methods: The analysis of the influence of product data on the performance of logistics processes was carried out using data from two fast-moving consumer goods (FMCG) distribution and retail companies. Data were gathered via interviews, while process activities were timed using a stopwatch, and interruptions were documented. The significance of the impact was determined using inferential statistical procedures based on the variable and the measurement scale type employed. Results: The quality of product master data has a significant impact on the performance of logistics processes; while managers are aware of the complications, they lack the motivation to detect and analyse such inaccuracies. Conclusions: The findings enhance comprehension of the obstacles generated by inadequate product data in logistics, which obstruct optimisation, and offer numerical proof of the impact of product data quality on logistics performance, thus expanding the current body of research.