Complex planning as digitalized tasks for sustainable supply chain and process management

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Authors

Harald Kitzmann¹ , Petre Lameski²

1. University of Tartu, Narva College
2. University of Sts. Cyril and Methodius in Skopje

Conference / event

10th Annual Entrepreneurship and Innovation Conference (EIC), October 2022 (Tallinn, Estonia)

Poster summary

To achieve the company's goals in a VUCAD environment, managers are forced to make faster decisions but also to revise them as quickly as possible. These developments are increasing the complexity and the importance of planning on the operational management level in organizations, especially when considering different set-up of planning approaches and regularly changing the planning processes. The aim of the research is to outline a digitalized solution, so that it can be implemented as tool for supporting complex digitalized management task. The study creates a model of integrated planning as a supporting tool for management tasks by using approaches that are suitable to realize as Artificial Intelligence (AI) solution. The results show that management tasks when fragmenting into different, smaller steps, allow enabling the usage of proper methodologies so that they can be used for implementing machine learning (ML) algorithms and solutions like process mining or digital decisioning.

Keywords

Budget planning, Digitalized management, Complex planning, Sustainable supply chain management

Research areas

Business, Economics and Finance, Computer and Information Science

References

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3. Yukalov, V.I.: Evolutionary Processes in Quantum Decision Theory, Entropy, vol. 6, no. 22, p. 681, 2020.
4. Urbánek J. F., Král, D.: MODELLING AND IMPLEMENTATION OF ADDED VALUE CONTROLLING IN SMALL AND MIDDLE ENTERPRISES CONTINUITY, Prague, 2014.
5. Kitzmann, H.: Development of a model for managing flexibility on strategical and operation level in production companies, Moscow, 2018.
6. Kitzmann, H.: Holistic Modelling Approach for the Management of Organisations, in International Scientific and Practical Conference “Sustainable Development in the Post-Pandemic Period” (SDPPP-2021), Tallinn, 2021.
7. Zdravevski, E., Lameski, P.; Apanowicz, C., Ślȩzak, D., "From Big Data to business analytics: The case study of churn prediction," Applied Soft Computing, vol. 90, no. May 2020, p. 106164, 2020.

Funding

No data provided

Supplemental files

No data provided

Additional information

Competing interests

No competing interests were disclosed.

Data availability statement

The datasets generated during and / or analyzed during the current study are available from the corresponding author on reasonable request.

Creative Commons license

Copyright © 2023 Kitzmann et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.