The management process is an important part of almost every software development project. It is a common practice that the same manager is simultaneously involved in multiple projects. It is difficult to focus attention in time to the stages of particular projects, which have increasing problems and risks. Thereby communication between development and management processes is an essential aspect of a successful project. There is a necessity for automatic communication mechanism between development and management processes. Modern development processes are usually divided into multiple iterations, which consist of tasks in order to achieve more transparency and control. The application of ontologies to define the task structure can make it interpretable for data mining. Data can be analyzed using artificial intelligence or modern declarative programming. Thereby, the attributes of current and completed tasks can be analyzed by an applied information system, which will support and/or warn managers to focus on particular projects, basing on the gathered facts, if necessary. Through focusing on the projects, which require management, decision making speeds up. The artefacts of collected development tasks are not wasted and are used to design new standards of tasks and iterations, which are based on successful previous attributes. It can lead to less management. Considering that some projects are almost self-managed and management tasks are applied to the projects, which require management, fewer human resources are necessary. It also positively affects the quality and strictness of management process.