In today's dynamic business environment, the success and competitiveness of any production organization is ensured by continuous improvement, sustainable development, effective planning and management. There is a growing scientific interest in the importance and relevance of production management in view of the strong need to redefine the policies and priorities within the respective strategic plan for business development - with increased focus on capacity planning in order for the industrial enterprises to adapt successfully to the dynamically changing conditions of the global environment and intense competition. Accordingly, full advantage is taken from the ample opportunities to study the impact of a number of factors on capacity planning and management. Based on an in-depth literature analysis, interviews and surveys, selected were 18 key factors  that have a profound influence on the effective planning and capacity management of the production organization. Using  the relationship between each of these factors and the capacity management is closely examined by applying the method of Interpretive Structural Modeling (ISM). Additionally, the interrelationships between the key factors under study are further analyzed by means of a Structural self-interaction matrix (SSIM).

This publication presents an experimental model for assessing the competence of production managers, which is based on classical management and modern mathematical tools. The research was done in response to a real practical need set as a research task by the business. As a result, a model for selection of specialists and experts for solving complex management problems related to production management in industrial enterprises and an algorithm for application of this model is proposed. Key indicators for assessing the competence of production managers have been identified. To create the model, surveys conducted among functional experts in the field of production management were used. The model can be successfully applied in other functional areas of management, modifying the key indicators so that they are applicable in these areas.