The concept of Customer Order Decoupling Point/CODP is a popular approach to increasing the diversity of end items, while taking advantage of standardization/unification due to increased repetitiveness of operations devoted to components and/or subassemblies manufacturing. CODP marks the place (the operation, the phase of the process etc.) where customer intervention occurs, in order to define, according to his/her wishes, the final mode of the end item (product or service). An underlying issue here is to make an economically motivated decision about the exact CODP position (1) among different end items of the company's product mix, and (2) inside a particular product/service line. Inside the operations process, before CODP, forecasts are usually used (Make-To-Stock), and after it-Make-To-Order. Consequently, the opportunities to achieve economies of scale are different before and after CODP. Therefore, the opportunities for optimizing the total operating costs are different as well. In the present paper, an approach is suggested for applying the Analytical Hierarchy Process/AHP in solving such a problem. Some examples of criteria are also presented to give reasons for the "pros" and "cons" during the decision making process about CODP position.

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Nowadays, one of the most dynamically developing knowledge areas is the one of Project Management (PM)-both in the fields of Business and Public Administration. This is truth, partially because of constantly increasing customization of products and services, and the way to successfully cope with fulfilling customer orders, no matter if they are individual, industrial, or government ones. The key is the usage of Project Management tools and methods. On the other hand, the concept of Customer Order Decoupling Point (CODP) is a popular approach to increasing the diversity of end items, while taking advantage of standardization due to increased repetitiveness of operations devoted to producing components and/or subassemblies. It is widely used in Operations Management, but it could also be applied on a "secondary" level during the process of project implementation, and thus an increased customer customization could be achieved. In the present paper, the usage of methods and techniques such as Design Structure Matrix (DSM), Analytical Hierarchy Process (AHP) and others is discussed in a model developing, which helps in defining places throughout the project implementation process the interaction with the customer is to be realized, while avoiding undesirable violations in the project workflow.

In modern conditions of rapidly developing technology, increasing competition and globalization increasingly becomes clearly outlines the need for flexibility of enterprises. The flexibility of an enterprise is expressed in its ability to react quickly and effectively to market changes and to adapt to the dynamically changing conditions of the external environment, to quickly create and market new and innovative products and services, to meet changing requirements, consumer expectations and needs. In order to remain competitive, companies need to adopt an open technology architecture and collaborate with partners who take advantage of modern solutions of problems. Teams should be open to accepting external experts to manage specific internal functions. Also, companies need to be prepared to integrate data between ecosystems in the way few do today. At the same time, flexible teams with multifunctional skills should be established within the organizations themselves, in order to promote intra-company mobility and the development of individual skills.

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).