Developing a digital transformation model to enhance the strategy development process for leadership in the South African manufacturing sector

South African Journal of Business Management

 
 
Field Value
 
Title Developing a digital transformation model to enhance the strategy development process for leadership in the South African manufacturing sector
 
Creator Gaffley, Garth Pelser, Theuns G.
 
Subject — digital transformation; technology; business leadership; data management; digital migration; digital capability; strategy development; CIO; South Africa.
Description Purpose: This study’s aim was to gain insight into the transformative skills of business leaders in the South African manufacturing sector to drive their business’ digital transformation process. Technology recources lead digital transformation requires skills not understood by leadership. Cloud computing has facilitated machine learning and artificial intelligence where human comprehension is limited, using algorithms for analytics requiring size and scale to provide data for decision-making and enabled disruptive technologies that have changed the face of industry sectors.Design/methodology/approach: A pragmatic postmodern paradigm supports the theoretical framing of this study, conducted using descriptive research by e-questionnaire using quantitative analysis for deductive statistical evaluation.Findings/results: The findings formed the basis of a model developed to assist chief executive officers (CEOs) to implement digital transformation successfully.Practical implications: The CEO is responsible for the digital transformation of the business and must understand that data management is the most important asset in the digital era. The collection, storage, analysis, reporting and usage of data are key to competing in the digital economy, which requires the appointment of the chief information officer (CIO) to manage data and who should report directly to the CEO.Originality/value: Reporting to the CIO would be data scientists and analysts who work with data; their roles focus on building algorithms from machine learning and developing predictive models from data and simulation models to test if technologies used to drive digital migration are optimal.
 
Publisher AOSIS
 
Contributor
Date 2021-05-27
 
Type info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion —
Format text/html application/epub+zip text/xml application/pdf
Identifier 10.4102/sajbm.v52i1.2357
 
Source South African Journal of Business Management; Vol 52, No 1 (2021); 12 pages 2078-5976 2078-5585
 
Language eng
 
Relation
The following web links (URLs) may trigger a file download or direct you to an alternative webpage to gain access to a publication file format of the published article:

https://sajbm.org/index.php/sajbm/article/view/2357/1816 https://sajbm.org/index.php/sajbm/article/view/2357/1818 https://sajbm.org/index.php/sajbm/article/view/2357/1819 https://sajbm.org/index.php/sajbm/article/view/2357/1820
 
Coverage — — —
Rights Copyright (c) 2021 Garth Gaffley, Theuns G. Pelser https://creativecommons.org/licenses/by/4.0
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