Enterprise risk arising from legacy production systems: a probabilistic perspective

Keywords: project risk, expert matrix, full group of events, conditional probabilities, reengineering, business processes


The model of estimation of effective minimization of strategic risks arising at modernization of the software of legacy production systems is presented. It is shown that incompatible hypotheses of strategic risks of the enterprise in the digital economy form a complete group of pairwise incompatible independent events, and their probabilities are found by mathematical methods of processing an inversely symmetric matrix, made by experts in pairwise comparison on a 5-point scale of relative importance errors of calculations of the constructed matrix (no more than 15 %). For these matrices, solutions of characteristic equations are found to determine the maximum values of the eigenvalues of matrices, which appear in the assessment of the adequacy of composite expert matrices together with the corresponding orders of matrices.

To substantiate the statistical measurement under the condition of quantitative or qualitative assessment of the risk of occurrence of events, the a priori value of the probabilities of occurrence of risk in the occurrence of events is taken. The full probability formula is the formula for the probability of occurrence of an event of effective minimization of strategic risks. It is shown that to determine the a priori values of conditional probabilities of hypotheses of effective minimization of strategic risks of the enterprise it is necessary to make statistically significant sections of these hypotheses at selected enterprises for several periods, which may be subject to statistical distribution laws. Thus, the presented model for quantitative measurement, comprehensive analysis of the level of software modernization of legacy production systems of the enterprise is the initial theoretical basis for improving the system of strategic management of the enterprise in terms of digitalization.


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Author Biographies

Tetiana Bludova, Kyiv National Economic University named after Vadym Hetman

Department of Advanced Mathematics

Svitlana Usherenko, Kyiv National Economic University named after Vadym Hetman

Department of Corporate Finance and Controlling

Alla Moskovchuk, Lutsk National Technical University

Department of Accounting and Audit

Iryna Kaminska, Lutsk National Technical

Department of Entrepreneurship, Trade and Logistics

Olga Kyslytsyna, Kyiv National Economic University named after Vadym Hetman

Department of International Management


Yoo, Y., Boland, R. J., Lyytinen, K., Majchrzak, A. (2012). Organizing for Innovation in the Digitized World. Organization Science, 23 (5), 1398–1408. doi: http://doi.org/10.1287/orsc.1120.0771

Westerman, G., Bonnet, D. (2015). Revamping Your Business Through Digital Transformatn. MIT Sloan Management Review, 56 (3), 10–13. Available at: https://www.researchgate.net/publication/285611160_Revamping_your_business_through_digital_transformation

Van der Aalst, W. M. P. (2013). Business Process Management: A Comprehensive Survey. ISRN Software Engineering, 2013, 1–37. doi: http://doi.org/10.1155/2013/507984

Tka, M., Ghannouchia, S. A. (2012). Comparison of Business Process Models as Part of BPR Projects. Procedia Technology, 5, 427–436. doi: http://doi.org/10.1016/j.protcy.2012.09.047

Software Engineering Teams for FinTech. Available at: https://www.insart.com/

Ross, J. W., Sebastian, I. M., Beath, C. M. (2017). How to develop a great digital strategy. MIT Sloan Management Review, 58 (2), 7–9. Available at: https://sloanreview.mit.edu/article/how-to-develop-a-great-digital-strategy

Roeglinger, M., Seyfried, J., Stelzl, S., Muehlen, M. zur. (2018). Cognitive Computing: What’s in for Business Process Management? An Exploration of Use Case Ideas. Business Process Management Workshops. Lecture Notes in Business Information Processing, 308, 419–428. doi: http://doi.org/10.1007/978-3-319-74030-0_32

Ozcelik, Y.; Glykas, M. (Ed.) (2013). Effects of Business Process Re-engineering on Firm Performance: An Econometric Analysis. Business Process Management: Studies in Computational Intelligence. Berlin, Heidelberg: Springer, 99–110. Available at: https://link.springer.com/chapter/10.1007/978-3-642-28409-0_4

Omidia, A., Khoshtinata, B. (2016). Factors affecting the implementation of business process re-engineering: taking into account the moderating role of organizational culture (Case Study: Iran Air). Procedia Economics and Finance, 36, 425–432. doi: http://doi.org/10.1016/s2212-5671(16)30058-2

Olson, D. L., Dash, Wu. D. (2015). Enterprise risk management. World Scientific Publishing Co.ptc.ltd. doi: http://doi.org/10.1142/9378

Denner, M.-S., Püschel, L., Röglinger, M. (2018). Discussion Paper: Ho to Exploit the Digitalization Potential of Business Processes. Business & Information Systems Engineering, 60 (4), 331–349. doi: http://doi.org/10.1007/s12599-017-0509-x

Looy, A., Poels, G., Snoeck, M. (2017). Evaluating Business Process Maturity Models. Journal of the Association for Information Systems, 18 (6), 461–486. doi: http://doi.org/10.17705/1jais.00460

Loebbecke, C., Picot, A. (2015). Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. The Journal of Strategic Information Systems, 24 (3), 149–157. doi: http://doi.org/10.1016/j.jsis.2015.08.002

Qiaoxing, L., Tunhua, J. (2017). Summary of the research onthe business model innovation of “Internet +” health care industry. Journal of Guizhou University, 35 (5). 150–156.

Leshchuk, V., Polinkevych, O., Ishchuk, L. (2015). Strategy of engineering enterprises' business process management in reengineering and redesign. Economic Annals-XXI, 1–2 (1), 57–61.

Lehnert, M., Röglinger, M., Johannes, S. (2018). Prioritization of Interconnected Processes. Business & Information Systems Engineering (BISE), 60 (2), 95–114. doi: http://doi.org/10.1007/s12599-017-0490-4

Kohlbacher, M., Reijers, H. (2013). The effects of process‐oriented organizational design on firm performance. Business Process Management Journal, 19 (2), 245–262. doi: http://doi.org/10.1108/14637151311308303

Klun, M., Trkman, P. (2018). Business process management – at the crossroads. Business Process Management Journal, 24 (3), 786–813. doi: http://doi.org/10.1108/BPMJ-11-2016-0226

Kerpedzhiev, G., König, U., Röglinger, M., Rosemann, M. (2017). Business Process Management in the Digital Age. Available at: https://www.bptrends.com/business-process-management-in-the-digital-age

Kabaale, E., Kituyi, G. M. (2015). A theoretical framework for requirements engineering and process improvement in small and medium software companies. Business Process Management Journal, 21 (1), 80–99. doi: http://doi.org/10.1108/bpmj-01-2014-0002

Janse, B. (2018). Business Process Reengineering (BPR). Available at: https://www.toolshero.com/quality-management/business-process-reengineering-bpr/

Gens, F., Whalen, M., Mohan, D., Carnelley, P., Carvalho, L., Chen, G. (2019). IDC FutureScape: Worldwide IT Industry 2020 Predictions. Available at: https://www.idc.com/getdoc.jsp?containerId=US45599219

Hull, R., Motahari Nezhad, H.; La Rosa, M., Loos, P., Pastor, O. (Eds.) (2016). Rethinking BPM in a Cognitive World. Transforming How We Learn and Perform Business Processes. Business Process Management, 9850, 3–19. doi: http://doi.org/10.1007/978-3-319-45348-4_1

Hess, T., Matt, C., Benlian, A., Wiesböck, F. (2016). Options for Formulating a Digital Transformation Strategy. MIS Quarterly Executive, 15 (2), 123–139. Available at: https://www.researchgate.net/publication/291349362_Options_for_Formulating_a_Digital_Transformation_Strategy

Chmeruk, H., Tokar, V., Sybyrka, L., Shaposhnik, O., Melnyk, O. (2019). Assessing the Level of Enterprise Reengineering in the Context of Global Digitalization. International Journal of Recent Technology and Engineering, 8 (4), 4103–4109. doi: http://doi.org/10.35940/ijrte.d8731.118419

Dijkman, R., Vanderfeesten, I., Reijers, H. A. (2016). Business Process Architectures: Overview, Comparison and Framework. Enterprise Information Systems, 10 (2), 129–158. doi: http://doi.org/10.1080/17517575.2014.928951

Cherukupalli, P., Reddy, R. (2015). Reengineering enterprise wide legacy BFSI systems. Industrial case study: ACM International Conference Proceeding Series, 40–49. doi: http://doi.org/10.1145/2723742.2723746

Berger, S., Denner, M.-S., Röglinger, M. (2018). The nature of digital technologies. Development of a multi-layer taxonomy. Proceedings of the 26th European Conference on Information Systems. Portsmouth. Available at: https://www.researchgate.net/publication/330881198_The_Nature_of_Digital_Technologies_-_Development_of_a_Multi-layer_Taxonomy

Basole, R. C. (2016). Accelerating Digital Transformation Visual Insights from the API Ecosystem. IT Professional, 18 (6), 20–25. doi: http://doi.org/10.1109/mitp.2016.105

Barrett, M., Davidson, E., Prabhu, J., Vargo, S. L. (2015). Service Innovation in the Digital Age: Key Contributions and Future Directions. Management Information Systems Quarterly, 39 (1), 135–154. doi: http://doi.org/10.25300/misq/2015/39:1.03

Andriole, S. J. (2017). Five Myths About Digital Transformation. MIT Sloan Management Review, 58 (3), 20–22. Available at: https://sloanreview.mit.edu/article/five-myths-about-digital-transformation/

Akam, G. U., Okeke, M. N., Kekeocha, M. E., Onuorah, A. N. (2018). Business Process Re-engineering Resources and the Performance of Quoted Brewing Firms in Nigeria. Asian Business Research Journal, 3 (1), 15–25. doi: http://doi.org/10.20448/journal.518.2018.31.15.25

Birchall, C. (2016). Re-Engineering Legacy Software. Manning Publications, 232. Available at: https://www.goodreads.com/book/show/24850349-re-engineering-legacy-software

After Deployment Storms, Skies Turn Sunny for Multi-Cloud Environments. MIT Technology Review. Available at: https://www.technologyreview.com/2017/12/12/241573/after-deployment-storms-skies-turn-sunny-for-multi-cloud-environments/

Mohanani, R., Salman, I., Turhan, B., Rodriguez, P., Ralph, P. (2020). Cognitive Biases in Software Engineering: A Systematic Mapping Study. IEEE Transactions on Software Engineering, 46 (12), 1318–1339. doi: http://doi.org/10.1109/tse.2018.2877759

Chotisarn, N., & Prompoon, N. (2013). Forecasting software damage rate from cognitive bias in software requirements gathering and specification process. 2013 IEEE Third International Conference on Information Science and Technology (ICIST), 951–956. doi: http://doi.org/10.1109/icist.2013.6747696

Stacy, W., MacMillan, J. (1995). Cognitive bias in software engineering. Communications of the ACM, 38 (6), 57–63. doi: http://doi.org/10.1145/203241.203256

Overcoming cognitive bias in senior executives (2018). Strategic RISK Knowledge. https://www.strategicrisk-asiapacific.com/the-knowledge/overcoming-cognitive-bias-in-senior-executives/1428016.article Last accessed: 01.08.2022

Wang, H. E., Landers, M., Adams, R., Subbaswamy, A., Kharrazi, H., Gaskin, D. J., Saria, S. (2022). A bias evaluation checklist for predictive models and its pilot application for 30-day hospital readmission models. Journal of the American Medical Informatics Association, 29 (8), 1323–1333. doi: http://doi.org/10.1093/jamia/ocac065

The main hypotheses and their conditional probabilities of strategic risks

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How to Cite
Bludova, T., Usherenko, S., Moskovchuk, A., Kaminska, I., & Kyslytsyna, O. (2022). Enterprise risk arising from legacy production systems: a probabilistic perspective. EUREKA: Physics and Engineering, (5), 150-161. https://doi.org/10.21303/2461-4262.2022.002529