Technological integration in logistics processes has become a current challenge for the manufacturing industry. The main objective of this study was to evaluate the impact of collaborative technologies on logistics indicators, focusing on variables such as interoperability and the use of digital platforms. To achieve this purpose, a quantitative approach with a correlational design was employed, using logistics efficiency as the main evaluation criterion. Five manufacturing companies were analyzed, assessing variables such as cycle time, delivery punctuality, and inventory. Multiple regression analysis revealed that the level of interoperability (β = 0.62, p = 0.001) and the frequency of use of collaborative platforms (β = 0.48, p = 0.005) were the most impactful factors. Companies with high integration showed a 40% reduction in cycle time and a 13% increase in on-time deliveries. These findings show that not only is technological adoption crucial but so is its effective and collaborative integration. The importance of promoting an organizational culture oriented toward digital transformation is highlighted, as well as policies that encourage continuous training and systematic use of interoperable digital tools. Furthermore, the results suggest that technological integration can act as a catalyst for improving interdepartmental coordination and real-time supply chain visibility. These benefits contribute not only to greater operational efficiency but also to a higher adaptability in changing and demanding environments. This research provides useful empirical evidence for strategic decision-making in companies seeking to optimize their logistics performance through technological solutions. In conclusion, it is confirmed that a well-structured strategy of collaborative technological integration significantly improves logistics efficiency, which has important implications for the digital transformation of the industrial sector and its long-term competitiveness. Future studies could expand the scope to other sectors and consider additional organizational variables.