Visual Enterprise Management: Strengthening C-Level Understanding via Spatial and Narrative Data Experiences

Peter Saghegyi; Attila Karoly Varga

doi:10.2991/978-94-6239-823-8_16

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Visual Enterprise Management: Strengthening C-Level Understanding via Spatial and Narrative Data Experiences

Authors

Peter Saghegyi¹^{, *}, Attila Karoly Varga²

¹József Hatvany Doctoral School for Computer Science and Engineering, University of Miskolc, Miskolc, Hungary

²Institute of Automation and Infocommunication, Faculty of Mechanical Engineering and Informatics, University of Miskolc, Miskolc, Hungary

^*Corresponding author. Email: peter.saghegyi@student.uni-miskolc.hu

Corresponding Author

Peter Saghegyi

Available Online 4 November 2026.

DOI: 10.2991/978-94-6239-823-8_16 How to use a DOI?
Keywords: spatial visualization; interactive sensemaking; situation awareness; decision support
Abstract: Modern enterprises generate large volumes of operational data, yet senior decision-makers often rely on static reports, slide decks, and specialist dashboards that can fragment organizational understanding. This paper proposes Visual Enterprise Management (VEM), an early-stage conceptual framework for representing enterprise information through spatial, interactive, and narrative data experiences.

Drawing on sensemaking theory, cognitive load theory, multimedia learning, and human-computer interaction, the paper argues that visual structure, progressive disclosure, and user-controlled exploration can support executive comprehension of complex organizational dependencies. VEM is positioned between analytical dashboard overload and visually rich but low-information simulation interfaces. The paper defines the conceptual problem, outlines theoretical foundations, identifies AI-supported functions, and proposes research questions for later design-science prototyping and evaluation.
Copyright: © 2026 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the Innovation in Engineering Education 2026 Conference (IEE 2026)
Series: Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date: 4 November 2026
ISBN: 978-94-6239-823-8
ISSN: 2667-128X
DOI: 10.2991/978-94-6239-823-8_16 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Peter Saghegyi
AU  - Attila Karoly Varga
PY  - 2026
DA  - 2026/11/04
TI  - Visual Enterprise Management: Strengthening C-Level Understanding via Spatial and Narrative Data Experiences
BT  - Proceedings of the Innovation in Engineering Education 2026 Conference (IEE 2026)
PB  - Atlantis Press
SP  - 180
EP  - 187
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6239-823-8_16
DO  - 10.2991/978-94-6239-823-8_16
ID  - Saghegyi2026
ER  -

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