Skip to main content

IT Project Risk Management Model

  • Conference paper
  • First Online:
Distributed Sensing and Intelligent Systems

Abstract

The chapter develops a knowledge-based IT project risk management model, which, unlike the existing ones, allows to take into account the dynamic and incremental way of executing IT projects, whereby the requirements for the information product and the ways of their realization are refined taking into account new information and experience gained. According to the model, the inputs to the risk management decision-making process should be stored in the knowledge base of the project, based on which the rules for the operation of the expert system are formulated.

It is suggested to use such components of the knowledge base as the risk database and the risk management knowledge repository. The Risk Database contains information on the tasks of IT project implementation, a concise description of problem situations, directions for solving the problem, quantification of risks, and the effectiveness of risk management measures. Updated risk database information, along with implicit knowledge (project stakeholder experience and qualifications, domain laws, etc.), is used to replenish the risk management knowledge repository to derive conclusions and patterns reflecting key project risk management policies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 239.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 309.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 299.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Kuznetsov, A., Kavun, S., Smirnov, O., Babenko, V., Nakisko, O., & Kuznetsova, K. (2019). Malware correlation monitoring in computer networks of promising smart grids. In 2019 IEEE 6th international conference on energy smart systems, ESS 2019 – Proceedings (Vol. 8764228, pp. 347–352). https://doi.org/10.1109/ESS.2019.8764228

    Chapter  Google Scholar 

  2. Ramazanov, S., Antoshkina, L., Babenko, V., & Akhmedov, R. (2019). Integrated model of stochastic dynamics for control of a socio-ecological-oriented innovation economy. Periodicals of Engineering and Natural Sciences, 7(2), 763–773. https://doi.org/10.21533/pen.v7i2.557

    Article  Google Scholar 

  3. Kaminsky, A. B. (2006). Economic and mathematical modeling of financial risks. Monograph, Publishing and Printing Center “Kyiv University”.

    Google Scholar 

  4. Galicin, V. K., Suslov, O. P., & Galicina, O. V. (2016). Modeling the mechanism of management of organizational projects. Business Inform, 2, 160–164.

    Google Scholar 

  5. Teslenko, P. A. (2010). Evolutionary theory and synergetics in project management. Project Management and Production Development, 4(36).

    Google Scholar 

  6. Danchenko, A. B. (2014). Modern approaches to deviation management in projects. Management of Complex Systems Development, 19.

    Google Scholar 

  7. Rach, D. V. (2013). Management of uncertainty and risks in the project: Terminological basis. Project Management and Production Development, 3(47).

    Google Scholar 

  8. Sviridova, S. S. (2011). Risk management of the innovation project lifecycle. Economics: Realities of Time, 1, 103–108.

    Google Scholar 

  9. Skopenko, N. S., Evseeva, I. V., & Moskalenko, V. O. (2013). Risk management in project management. Investments: Practice and Experience, 24, 41–44.

    Google Scholar 

  10. Archibald, R. (2010) Managing high-tech programs and projects (Trans. with English, 3rd ed., revised. and ext. ITT Company). DMK Press.

    Google Scholar 

  11. Boehm, B. A. (2019). Prioritized top-ten list of software risk items. http://users.humboldt.edu/smtuttle/s12cs435/435lect06-2/435lect06-2-boehm-top10-risks-to-post.pdf

  12. Schwalbe, K. (2012). Information technology project management. Cengage Learning.

    Google Scholar 

  13. Demarco, T., & Lister, T. (2003). Waltzing with bears: Managing risk on software projects. Dorset House.

    Google Scholar 

  14. Goldratt Eliyahu, M. (1997). Critical chain. The North River Press-Publishing Corporation.

    Google Scholar 

  15. Leach, L. (2010). On time and within budget: Critical-chain project management/Lawrence Leach. Alpina Publishers.

    Google Scholar 

  16. Machac, J., & Steiner, F. (2014). Risk management in early product lifecycle phases. International Review of Management and Business Research, 2(3), 1151–1162.

    Google Scholar 

  17. Choetkiertikul, M., Dam, H. K., & Tran, T. (2015). Predicting delays in software projects using networked classification (T). In Automated software engineering (ASE), 30th IEEE/ACM international conference (pp. 353–364).

    Chapter  Google Scholar 

  18. Jeon, C., Kim, N., & Peter, H. (2015). Probabilistic approach to predicting risk in software projects using software repository data. International Journal of Software Engineering and Knowledge Engineering, 6(25), 1017–1032.

    Article  Google Scholar 

  19. Kumar, C., & Yadav, D. K. (2015). A probabilistic software risk assessment and estimation model for software projects. Procedia Computer Science, 54, 335–361.

    Article  Google Scholar 

  20. Teslya, Y. M., & Kubiavka, L. B. (2014). The concept of construction and function of the project risk management system in informatization programs. Management of Development of Complex Systems, 19, 93–97.

    Google Scholar 

  21. Babenko, V., Lomovskykh, L., Oriekhova, A., Korchynska, L., Krutko, M., & Koniaieva, Y. (2019). Features of methods and models in risk management of IT projects. Periodicals of Engineering and Natural Sciences, 7(2), 629–636. https://doi.org/10.21533/pen.v7i2.558

    Article  Google Scholar 

  22. Babenko, V. A. (2013). Formation of economic-mathematical model for process dynamics of innovative technologies management at agroindustrial enterprises. Actual Problems of Economics, 139(1), 182–186.

    Google Scholar 

  23. Shorikov, A. F., & Babenko, V. A. (2014). Optimization of assured result in dynamical model of management of innovation process in the enterprise of agricultural production complex. Economy of Region, 1(37), 196–202. https://doi.org/10.17059/2014-1-18

    Article  Google Scholar 

  24. Rishnyak, I. V. (2011). Risk management system for IT projects. In Information systems and networks. Collection of scientific papers (pp. 250–259). Publisher of Lviv Polytechnic National University.

    Google Scholar 

  25. Rishnyak, I. V. (2010). Application of imitation models for risk management of IT projects. In Information systems and networks. Collection of scientific papers (pp. 171–181). Publisher of National University “Lviv Polytechnic”.

    Google Scholar 

  26. Melnik, G. V. (2013). Modeling the information risk management system in the corporate information system. Business Inform, 9, 95–99.

    Google Scholar 

  27. Kolesnikova, E. V. (2013). Modeling of poorly structured systems of project management. Proceedings of the Odessa Polytechnic University, 3, 127–131.

    Google Scholar 

  28. Onishchenko, I. I. (2016). Cognitive modeling as a method of qualitative risk analysis of IT projects. Bulletin of the National Technical University of KhPI. Series: Strategic Management, Portfolio, Program and Project Management, 2, 88–81.

    Google Scholar 

  29. The Kanban Way. Speed up project delivery using Critical Chain. http://www.kanbanway.com/speed-up-project-delivery-using-critical-chain#.VdrP4_ntmko

  30. Renard, L. Essential frameworks and methodologies to maximize the value of IT. http://www.isaca.org/Journal/archives/2016/volume-2/Pages/essential-frameworks-and-methodologies-to-maximize-the-value-of-it.aspx,last

  31. Handzic, M., & Durmic, N. (2015). Knowledge management, intellectual capital and project management: Connecting the dots. Electronic Journal of Knowledge Management, 1(1), 51–61.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vitalina Babenko .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Babenko, V., Yalyzaveta, K., Shylovtseva, N., Marenych, T., Myrna, O., Serdiuk, O. (2022). IT Project Risk Management Model. In: Elhoseny, M., Yuan, X., Krit, Sd. (eds) Distributed Sensing and Intelligent Systems. Studies in Distributed Intelligence . Springer, Cham. https://doi.org/10.1007/978-3-030-64258-7_3

Download citation

Publish with us

Policies and ethics