- Title
- Data Visualization of Budgeting Assumptions: An Illustrative Case of Trans-disciplinary Applied Knowledge
- Creator
- Cuthbert, Carol E, Pearse, Noel J, Bradshaw, Karen L
- Subject
- To be catalogued
- Date
- 2024
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/440236
- Identifier
- vital:73759
- Identifier
- xlink:href="https://doi.org/10.54808/JSCI.22.01.130"
- Description
- Trans-disciplinary research combines different fields into new conceptual and methodological frameworks. In this study, the SECI model of knowledge creation, which consists of Socialization, Externalization, Combination, and Internalization conversion modes, is used to analyze the implementation of a structured budgeting visualization system by a trans-disciplinary team. Through applied research in implementing a global budgeting system, budgeting assumptions are made explicit through visualization, transforming the approach to the budgeting process and its accuracy. This visualization, in turn, is enabled by assumptions underlying revenue planning, business services and employee compensation, and a visual process. The system displays a stepped approach, indicated by icons, representing the tasks involved in the budget process. For example, the system requires uploading the previous year’s information, setting the assumptions, calculating the suggested figures based on assumptions, and amending the proposed outcome. As adapted by Rice and Rice (2005), SECI is applied as the socialization of tacit-to-tacit budgeting assumption knowledge is solidified during the design phase of this transformation exercise. The externalization phase, in which budgeting assumptions are transformed from tacit to explicit, is evidenced during the configuration phase of the new system. The systemic collaboration results in the explicit assumptions being collectively leveraged across the regions during and after the “go-live” phase of system development. Finally, the internalization phase involves the explicit assumptions being transformed into new tacit knowledge as the experts evolve new assumptions derived from the transformation process. Semiotics provides variance information through hue, with, for example, darker colours indicating higher variances. This trans-disciplinary communication provides the means for increased efficiency and effectiveness. The resulting budget framework is visually validated through a heatmap by comparing the budgeting accuracy and assumption complexity between the different regions where it was implemented. In summary, value is added in developing a new data visualization process, focusing on the role of budgeting assumptions and using planning process visualizations. This approach improves communication efficiency, effectiveness, and understanding of budgeting while enhancing accuracy.
- Format
- computer, online resource, application/pdf, 1 online resource (20 pages), pdf
- Publisher
- International Institute of Informatics and Cybernetics
- Language
- English
- Relation
- Journal of Systemics, Cybernetics and Informatics, Cuthbert, C.E., Pearse, N.J. and Bradshaw, K., 2024. Data Visualization of Budgeting Assumptions: An Illustrative Case of Trans-disciplinary Applied Knowledge. Journal of Systemics, Cybernetics and Informatics, 22(1), pp.130-149, Journal of Systemics, Cybernetics and Informatics volume 22 number 1 p. 130 2024 1690-4524
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of the Creative Commons CC BY-NC-ND 4.0 License (Attribution-NonCommercial-NoDerivatives 4.0 International) https://creativecommons.org/licenses/by-nc-nd/4.0/
- Rights
- Open Access
- Hits: 103
- Visitors: 99
- Downloads: 4
Collections
Pearse, Noel James (Prof)
RU Business School
Bradshaw, Karen Lee (Assoc Prof)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Data Visualization of Budgeting Assumptions An Illustrative.pdf | 664 KB | Adobe Acrobat PDF | View Details Download |