Modeling of the reporting activities of a crane manufacturing organization

Abstract

Industrial manufacturing activity has changed significantly in recent years. In addition to standardized - mass production processes, customer - oriented individual production activities have become increasingly strong. In custom manufacturing with a customer focus, the customer is not only a passive observer but also an active participant in the design and manufacturing processes. Due to their unique nature, evaluating the performance of organizations can present a number of challenges. As a result of the development of digitalisation and economic IT innovations, an extensive system of tools is available, and a number of methods can be used to analyze the measured data. Among the analysis methodologies, the Key Performance Indicator (KPI) management, which is the basis of controlling systems, should be highlighted. As a result of the changes, the evaluation and expression of organizational performance should no longer focus on analyzing current conditions, but on forecasting expected future performance. In order to achieve this, the use of efficient infrastructure and professional and statistical-mathematical methods is formulated as a basic requirement. The interpretation of the information content of predictive KPIs and thus management decision support should depend on different assessments and standardization norms. Nowadays, organizational performance evaluation can be regarded as a basic controlling task, during which the goal is the extensive exploration and evaluation of organizational performance. Management is limitedly rational when making decisions, which means that it can only make decisions based on available information. The purpose of the controlling is to provide the management with a reporting activity that is suitable for evaluating the processes and making future-oriented decisions by uncovering extensive information and extensive methodological analysis of the data. It is therefore particularly emphasized that management should no longer be reactive, but proactive, which can be achieved by evaluating predictive analyzes and making decisions based on the information derived from the predictive evaluations.