2019. No. 2 Vol.13

      This paper presents the results of studies aimed at analyzing the effectiveness of a research center. The study focuses on the process of self-organization of project teams (groups of co-authors) for project implementation (writing a scientific article). The initiative to create a team comes from one of its members. The paper describes a formal model, based on a competence approach, which considers the types of tasks to be solved and the necessary skills of the staff. The paper also presents the results of simulation in the AnyLogic environment and problems for further research.
      The competency profile of each employee is a vector where each coordinate describes the level of mastery of the corresponding skill. The competency profile of the team is a vector obtained as the result of simple addition of the competency profiles of the participants. The proposed model assumes that each task requires a certain set of competencies and that the list of competencies and the level of experience are the criteria for deciding whether to join the team. The logic of decision making at various stages of team creation is modelled by functions. At each step of the modelling, the next employee is chosen randomly. To calibrate the team member’s competency profile, internal data on employee qualifications of the Gazpromneft Research Center was used. The constructed model is the basis for further studies of the process by which project teams are created and function in a scientific environment and for developing a methodology to assess the effectiveness of the work of research teams. It helps to predict the need for personnel with different competencies, plan activities to improve the skills of employees and strengthen communication in the team.

      Large distributed information systems (LDIS) are the basis for digitization of production processes in industry, transport and public administration. Organization of their engineering servicing (ES) for timely restoration in case of failure is a topical issue of scientific research. LDIS consists of computer complexes which include both major and additional elements. The literature provides no solution which allows us to define the engineering servicing resources (ESR), considering the variable significance of elements of computer complexes. The task was first set and solved in this publication.
      For solution of this task, we applied the mean dynamic method. This method was chosen because it makes it possible to obtain a system of differential equations for describing the change over time of the mean number of elements in different states.
      Analysis of the differential equations system solution allowed us to find analytical expressions for determining ESR – the number of staff and the number of spare elements- at which the mean number of computer complexes in perfect state reaches its maximum. The results are applicable when calculating the ESR of real LDIS. They can also serve in simulation modeling as initial approximations of the optimal volume of ESR if it necessary to take into account the specific features of the system. In addition, the solution of differential equations makes it possible to solve the problem of optimizing the resources for servicing the LDIS according to economic criteria, when the costs of staff and spare elements are comparable with the income from operating the computer complexes.

      In this paper, we discuss the construction of fuzzy classifiers by dividing the task into the three following stages: the generation of a fuzzy rule base, the selection of relevant features, and the parameter optimization of membership functions for fuzzy rules. The structure of the fuzzy classifier is generated by forming the fuzzy rule base with use of the minimum and maximum feature values in each class. This allows us to generate the rule base with the minimum number of rules, which corresponds to the number of class labels in the dataset to be classified. Feature selection is carried out by a binary spider monkey optimization (BSMO) algorithm, which is a wrapper method. As a data preprocessing procedure, feature selection not only improves the efficiency of training algorithms but also enhances their generalization capability. In the process of feature selection, we investigate the dynamics of changes in classification accuracy, iteration by iteration, for various parameter values of the binary algorithm and analyze the effect of its parameters on its convergence rate. The parameter optimization of fuzzy rule antecedents uses another spider monkey optimization (SMO) algorithm that processes continuous numerical data. The performance of the fuzzy classifiers based on the rules and features selected by these algorithms is tested on some datasets from the KEEL repository. Comparison with two competitor algorithms on the same datasets is carried out. It is shown that fuzzy classifiers with the minimum number of rules and a significantly reduced number of features can be developed with their accuracy being statistically similar to that of the competitor classifiers.

      Digital transformation is a highly topical task for many companies. Implementation and use of breakthrough technologies are an essential part of this process. Nowadays the terms “innovation” and “information technologies (IT)” are treated as equals insofar as IT is exactly what can provide execution of innovative strategy and the digital transformation of a company’s business.
      Due to the high speed of IT market growth and the emergence of new technologies, companies usually implement them without justified selection and prioritization, and this leads to the high rate of failed innovative IT projects. Often such projects fail to result in commercially successful products or services by which a company can distinguish itself from competitors to consumers. Still the most widespread approach for evaluation and ranking of innovative IT projects concentrates on the expected financial outcomes without due attention to strategic alignment of a project.
      This research suggests an approach for ranking innovative IT projects in big companies. The approach entails complex evaluation of expected results of projects on the strategic, environmental, organizational and technological domains of a company. This approach is based on a modified Tornyatzky–Fleischer IT innovation adoption model.
      During the first stage of research, the term and definition of innovation have been discussed as well as features of innovative IT projects. The second stage is dedicated to comparison analysis of evaluation approaches for innovative projects as well as to choosing an IT adoption model for further adaptation. On the third stage approbation of the method developed been carried out in one of the Russian big IT/internet companies. The results of two-year period of approach approbation have proved its suitability and suggested the prospects for further development.

      Digital transformation is one of the current trends of business development in modern economies. This article discusses the main problems faced by Russian companies in the course of digital transformations of their activities, and the tools for preliminary diagnosis of the company’s readiness for such transformations.
      Based on the analysis and synthesis of information from reports of Russian and international research and consulting companies, and relying on the results of scientific research by Russian and foreign experts, the authors identified seven key typical problems that most Russian companies may encounter in the initial stages of implementing digital transformation. The problems identified are ranked in order of their importance for the successful implementation of digital transformations.
      For the effective implementation of digital transformation, the authors propose to use the architectural approach in accordance with the recommendations of the TOGAF standard, which allows managing changes in a comprehensive manner, taking into account the needs, opportunities and constraints of both the business system and the IT infrastructure.
       The work substantiates the need for conducting the diagnosis of the company’s readiness at the initial stage of digital transformations. Such diagnosis can reveal the existing internal constraints that may become an obstacle to achieving the desired result of digital transformation. To identify the main adverse events, causes and problems of organizations with low levels of digital maturity, a method for constructing a tree of current reality has been implemented - an analytical toolkit for studying cause-effect relationships with undesirable features. Practical recommendations on the classification of causes and problems are provided to assess current readiness and plan for transition to the desired state of business system and IT infrastructure.
      The proposed approach will allow organizations to identify their problem areas, drawing on the consolidated experience of other companies, as well as to determine the possibility of their adjustment in order to create favorable conditions for digital transformations.

      At present, enterprise performance management (EPM) systems are widely used in practice, because they facilitate strategic decision-making and contribute to improved information transparency of organizations. However, methodological issues related to managing the development of such systems seem to be insufficiently investigated and elaborated.
      The purpose of the study is to formulate and justify fundamental principles for managing EPM systems’ development. These principles derive from peculiarities of EPM systems themselves and the features of their development management. In particular, the features of EPM systems are complexity and modular structure, large-scale scope, the long-term nature of planning, monitoring and analysis, use of aggregated information – both financial and non-financial. The features of managing development of EPM systems include the implicit nature of the resulting economic benefits, influence of stochastic factors, as well as availability of “complicated” projects (with uncertain outcomes, ability to re-execute and multiple variants of implementation).
      As a result, the basic principles of managing development of EPM systems can be formulated. There are the principles of a system, the going concern, business alignment, value for money, program management, alternativeness, feasibility, stochasticity, as well as resources aggregation.
      The significance of these principles is explained by the fact that they can be used as a basis for an integrated process of managing the development of EPM systems. These principles are also valuable for formalizing certain elements of the management process, such as assessment of the maturity level of EPM systems, the formation of potential development programs, simulation of implementation of the development programs, as well as decision-making regarding selection of development programs for implementation.