Motives and Prerequisites for Big Data Analysis in Shipbuilding Enterprises

In the context of the rapid digitalization of business processes and intensifying international competition among shipyards, the capacity of shipbuilding enterprises to process large volumes of structured and unstructured information has become an important factor of competitiveness. The aim of the article is to examine the economic aspects of using Big Data analytics in shipbuilding enterprises and clarify its role in supporting managerial decisions aimed at improving production efficiency and strengthening competitiveness. The study employs a systems approach, analysis and synthesis, a review of recent academic and analytical publications, structural analysis, and an analytical-synthetic method for identifying and generalizing international digitalization practices in shipbuilding. It is established that shipyards generate large data flows from tender and contract documentation, ship owners’ technical requirements, engineering models, production equipment, supply chains, market databases, customer relationship management systems and operational feedback. The analysis shows that Big Data has acquired the characteristics of an economic asset and that its use can improve the substantiation of design solutions, synchronize production with supply chains, support workforce and equipment planning, predict maintenance needs, reduce downtime and assist in forecasting changes in demand for ships. Market evidence also indicates steady expansion of digital shipyard technologies, especially digital twins, the Internet of Things, automation, robotics, and data analytics; however, the reported growth rates should be interpreted as forecasts produced by commercial research providers rather than as observed outcomes. The contribution of the study lies in the generalization of the economic opportunities associated with Big Data analytics in shipbuilding and its role in supporting managerial decisions. The practical value of the results consists in their potential use when developing digital transformation strategies for shipbuilding enterprises, selecting priority analytical tools, and improving decisions on production, maintenance and supply-chain coordination.