Development of a scenario-based approach to evaluating the effectiveness of investment projects in the field of information technology

as you know, the digital transformation of most sectors of the economy ensures their increased efficiency by reducing the time and cost of performing routine processes, as well as simplifying the collection, storage and processing of big data. The practical achievement of the goals of digital transformation is achieved through the implementation of specific projects in the field of information technology. The widespread use of IT projects requires the development of methodological approaches to assess their cost-effectiveness, as well as project risks. This study describes the development of a scenario approach to assessing the effectiveness of investment projects in relation to IT projects. Previously, the calculation of another scenario of an investment project assumed the need for preliminary risk identification based on qualitative risk analysis methods. Then an alternative project scenario was calculated. Our proposal is to programmatically implement the calculation of multiple project implementation scenarios using the Monte Carlo method. During the analysis of a significant array of IT projects, it was found that in about half of the cases, monetization is carried out due to the number of users on a subscription. At the same time, the key risk is the failure to achieve planned sales, which is of great importance in the context of a limited product life cycle. Therefore, we took the deadline for achieving planned sales as a variable parameter in the economic and mathematical model of the project. The revenue function depending on time was taken as the main metric of the project, and the probability density functions of key performance indicators, such as NPV, IRR and payback periods, were also studied. The results of the study, such as the proposed methodological approaches and software implementation, were tested on real IT projects and demonstrated their clarity and usefulness in assessing project risks.

scenario analysis, economic and mathematical models, investment project, Monte Carlo method, IT project