Abstract
Recent research show that 70% of the digitalization initiatives do not reach their goal [1, 2], posing an obvious challenge to digitalization leaders. Enterprises reconsidering their investments into digitalization, while technology push stays high: current epidemy-forced home office based working proves value add of digitalization, while the second wave of digitalization is already on the doorsteps [3,4,5]. Digitalization is demanding major changes in the organizations with the promise to conduct business still (or more) profitably. As markets keep evolving, competitive enterprises have to adapt core value-added processes with unprecedented speed, to act appropriately regardless of the situation [6]. For this, well designed and continuously improved process models must be implemented in the real world with real employees interacting with real software applications and physical automation devices which must be integrated with real integration platforms to achieve and sustain the intended change results. Modern BPM suites are evolving to automate the modeling, monitoring and redesign of complex, collaborative processes to achieve these goals [7]. In this paper we reason for utilizing research made into business process management, to address investment efficiency challenges in digitalization. We will also share the first results of our case study based research that is conducted to verify our hypothesis.
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Acknowledgements
This research was supported by the project “Aspects on the development of intelligent, sustainable and inclusive society: social, technological, innovation networks in employment and digital economy” (EFOP-3.6.2-16-2017-00007). The project has been supported by the EU, co-financed by the European Social Fund and the budget of Hungary.
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Gaspar, D., Ternai, K. (2020). Towards a Process Based Approach to Address Investment Inefficiencies in Digitalization. In: Kő, A., Francesconi, E., Kotsis, G., Tjoa, A., Khalil, I. (eds) Electronic Government and the Information Systems Perspective. EGOVIS 2020. Lecture Notes in Computer Science(), vol 12394. Springer, Cham. https://doi.org/10.1007/978-3-030-58957-8_5
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