Analysis of the Sequence of Risk States in the Implementation of Information Projects

Abstract

The article deals with the issues of risk management of information projects. We propose not a deductive approach traditionally used in risk analysis, based on knowledge of the main provisions and their concretization in a real situation, but an inductive approach that requires data accumula- tion and the construction of training data sets as a result of a retrospective analysis of the progress and implementation of individual projects. It is proposed to use methods of trajectory analysis of sequences of events, each of which characterizes the state of risk of project implementation. To test this approach, random sequences of risk events are generated and data analysis methods are applied to these sequences.

Keywords

• information project
• project execution risks
• risk management methods
• random process
• discrete markov chain
• random sequence of events
• random sequence indicators
• machine learning methods
• cluster analysis