Description
The digital transformation cluster consists of three main groups namely, E-Participation, Marginalised Community Development and Business Policy Analytics. The two groups are further classified into sub-research groups which are described below:
- E-learning: The focus of this sub-research group is to explore the use of digital technologies to support learning. This sub-research group also focuses on the adoption, challenges and benefits of digital technologies in learning.
- E-health: The focus of this sub-research group is to explore how digital technologies are transforming the provision of healthcare services. Research within this sub-research group includes but is not limited to the development of mobile apps, telemedical systems, web applications for health data management, disease diagnosis and self-management.
- E-government: The focus of this sub-research group is to explore the use of digital technologies to support government services. This sub-research explores various technologies such as mobile technologies and web technologies in the provision of government services.
- E-business: The focus of this sub-research group is to explore the use of digital technologies in business. The primary aim of this research group is to support services such as electronic banking, fintech, online shopping and agricultural systems, electronic payment systems. Currently, there is a funded project in the sub-research group led by Dr Iyawa titled Development of Machine Learning Datasets for Crop Pest and Disease Diagnosis.
- ICT4D: The focus of this sub-research group is to explore how digital technologies can be developed to support services in rural and underserved communities. The main focus of this research is on rural communities. Currently, there is a funded project in this sub-research group led by Dr Chikohora titled Veld fire detection & notification system (NCRST project). Other funded projects under this sub-research group include Havana Youth Project, Homeless project, Donkerbos innovation under Tech Hub, and Edtech Innovation led by Prof Heike Winschiers-Theophilus.
- Business and Data Analytics: Research within this domain focuses on the analysis of huge data sets for better interpretation to provide insights about trends, prediction and insights into customer preferences.
- Gender and ICT: Research within this domain focuses on the addressing challenges relating to gender issues such as violence against women, limited access to girl’s education, reproductive and sexual health challenges, and traditional harmful practices with the use of digital technologies. Currently, there is one project in this domain titled: Women as Citizen Scientists led by Dr Iyawa.
What is Digital Transformation?
To understand digital transformation, we need to look at a period in the technologisation of society when major changes occurred in our current world. For instance, while arguing for the complexity of the current social system, Merali (2006) posits that the advent of the Internet and its related technologies had resulted in a step change in our current world. The emphasis on the use of Internet and other technologies as change enablers marked the beginning of a transformation process, involving redefinition of commercial sector business models, changes in public governance mechanisms, and ICTs becoming more and more embedded in society and in individual affairs. Thus, the commercialisation of the Internet since in the 1990s marked the beginning of societal digital transformation.
Digital transformation as an innovation is increasingly becoming popular. For instance, Yoo, Henfridsson, and Lyytinen, (2010) consider digital transformation as the new organizing logic (architecture) for innovation; comprising of layers of devices (computing), networks, services, and contents created using digital technology; which will profoundly impact how we innovate in our current and future world. While Zhu et al., (2006)’s perspective of digital innovation focused on a more physical and product view, the conceptualisation of digital transformation by Fichman et al., (2014) recognises that there are at least three types of digital transformations related to the concepts of product, process and new business models. In line with these perspectives, we conceptualise Digital Transformation (DT) as change enabled and intertwined with IT, which impacts on product and process innovations as well as innovative ways of organizing human affairs (governance, business models, and individual /society life-worlds).
Research Domains of Digital Transformation in FCI
According to MIT Sloan Management Review and Deloitte’s 2015 global study, digital transformation maturity is realised through the integration of digital technologies, such as social media, mobile, analytics and cloud. Therefore, the kind of “Big” research questions that we seek to answer in FCI focuses on how mature digital transformation can be realised by commercial sector organisations, public and not for profit institutions, individuals and the society at large. In forming research clusters and projects to drive research in DT, key challenges and opportunities are related to the Nature of DT; alignment of human systems to a DT paradigm and how DT is impacting human affairs.
Contact:
Dr Gloria Iyawa (giyawa@nust.na)
Dr Samuel Akinsola (sakinsola@nust.na)
E- Participation: Informatics - Prof Fungai Bhunu Shava
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Marginalised Community Development – Prof Heike Winschiers-Theophilus
Project: (Havana Youth Project, Homeless Project, Donkerbos Innovation under Tech Hub)
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Project: Edtech Innovation Prof Heike Winschiers-Theophilus (PPS under Tech Hub Project)
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Project: Veld fire detection & notification system (NCRST project) – Dr Edmore Chikohora
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Business & Policy Analytics - Informatics
Business analytics also allows organizations to automate their entire decision-making process, so as to deliver real-time responses when needed. One of the apparent importance of business analytics is the fact that it helps to gain essential business insights. It does this by presenting the right data to work it
Organizations employ Business analytics so they can make data-driven decisions. Business analytics gives businesses an excellent overview and insight on how companies can become more efficient, and these insights will enable such businesses to optimize and automate their processes. It is no surprise that data-driven companies also make use of business analytics usually to outperform their contemporaries. The reason for this is that the insights gained via business analytics enable them to; understand why specific results are achieved, explore more effective business processes, and even predict the likelihood of certain results.
There are three primary methods of business analysis:
- Descriptive: The interpretation of historical data to identify trends and patterns.
- Predictive: The use of statistics to forecast future outcomes.
- Prescriptive: The application of testing and other techniques to determine which outcome will yield the best result in a given scenario.
Deciding which method to employ is dependent on the business situation at hand.
