Artificial Intelligence and Decision Making

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Conference Paper · July 2017
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Nelson Sizwe Madonsela
University of Johannesburg
Kehinde Sobiyi
University of the Witwatersrand
Bhekisipho Twala
Durban University of Technology
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©Copyright 2017 by the Global Business and Technology Association
Nelson Sizwe Madonsela, Kehinde Sobiyi and Bhekisipho Twala
University of Johannesburg, South Africa
Today, both the management of organizations and the public sector depend on real-time information, particularly
accurate information, for decision making. Most industries realize that the business environment is so complex
because of the influx of data from multiple sources, which needs to be collected, stored, analyzed, protected and
utilized for better decision making. Industries find it challenging to stay adaptive in such an environment and rely on
information they collect to make executive decisions. From a business perspective, data has become an asset for
competitive advantage. Accordingly, nowadays industries are adopting business intelligence and analytics (BI&A)
systems to mine data from multiple sources in order to make well-informed business decisions. The emphasis on BI&A
systems derives from the ability of BI&A tools, technologies, practices, methodologies and applications to provide
real-time accurate information and predict the future, which leads to better decision making. This information can be
related to customers, competitors and the business environment itself. It is believed that Small, Medium and Microsized Enterprises (SMMEs) are reluctant to adopt such technologies owing to the perception that BI&A systems are
very expensive and require expertise that they lack. The study reported on in this paper suggests a strategy for SMMEs
that will allow them to adopt competitive BI&A systems as a sustainable business strategy. The study demonstrates
different approaches to the adoption of BI&A systems and addresses inaccurate perceptions of BI&A, such as that
BI&A technologies are more costly than other technologies. A scientometrics analysis of BI was conducted using a
theory of knowledge for literature reviews in the IS domain. The findings suggest that competitive BI&A systems exist
in the majority of large-sized businesses, while SMMEs still struggle to implement or adopt BI&A tools. As a result,
these businesses are seeking appropriate ways of integrating BI&A tools that are more applicable to their business
nature. The study also shows the need for developing strategies that can enable SMMEs to adopt BI&A systems.
Therefore, this study proposes strategies for SMMEs to use in adopting BI&A tools to enhance competitiveness.
Keywords: competitive intelligence, business intelligence systems, business analytics, small business enterprises,
decision making, information analysis, decision support systems, knowledge discovery process, knowledge
Organizations’ management and the public sector depend for their decision making on real-time information,
particularly accurate information. Most industries realize that the business environment is as complex as it is because
of the influx of data from multiple sources. This data needs to be collected, stored, analyzed, protected and used for
better decision making. It is certain that industries find it challenging to stay adaptive in such an environment and rely
on information they collect to make executive decisions. From a business perspective, data has become an asset for
competitive advantage. Accordingly, nowadays industries and the public sector are adopting business intelligence and
analytics (BI&A) systems to mine data from multiple sources to make well-informed decisions. Over the past decades
the South African government has addressed issues of unemployment, underemployed and equity, which even today
present a challenge. The perception exists that small, medium and micro enterprises or SMMEs could be key players
in addressing some of these issues. In fact, SMMEs have been emphasized as a pillar for sustaining economic growth
by large economies such as New Zealand, Nigeria, Greece, the Czech Republic, Turkey and Malaysia, to name but a
few. For example, in Turkey 77 percent of the Gross Domestic Product (GDP) is contributed by SMMEs. In South
©Copyright 2017 by the Global Business and Technology Association
Africa SMME contribution is at 63 percent while the private sector contributes 60 percent (Dilver, 2015). It is not
surprising then that South African academics are paying serious attention to SMMEs. This is evident from the
increasing number of studies regarding SMMEs, with a particular emphasis on the adoption and use of Business
Intelligence (BI) to sustain competitive intelligence in the SMME sector. It is almost certain that South Africa is not
lagging behind in terms of understanding the importance of BI. However, while Boonsiritomachai, McGrath and
Burges (2014) strongly argue that in the highly competitive marketplace making effective and instant decisions
requires BI applications, Grabova (2010, in Horakova and Skalska, 2013, p.50) is of the opinion that the “high price
for BI tools, difficult implementation and complex deployment are the reasons, why small and medium-size businesses
are seeking for their solutions” rather than adopting BI tools. With SMMEs in South Africa significant from both the
government and researchers’ perspectives and consensus that SMMEs can play a role in reducing poverty, addressing
job creation and strengthening economic growth – it is important to address the hindrances that prevent SMMEs from
using BI systems. In 1995, the South African government released a White Paper on National Strategy for the
Development of Small Business in South Africa, which suggested that the hindrances to SMME sustainability are a
lack of skills and admittance to suitable technology along with poor infrastructure and policies. Chimucheka and
Mandipaka investigated the challenges faced by SMMEs, discovered that there is a “lack of support from key
stakeholders” (2015, p.309). There is sufficient evidence that these issues need a collective approach from all
stakeholders such as government and the private and public sectors, along with academics, who we believe are experts
in understanding some of these hindrances. This paper addresses the technological aspect by proposing a strategy for
SMME organizations through the lens of competitive BI&A systems or applications. The study intended to establish
approaches that SMMEs can utilize to take advantage of these advanced tools to forecast or predict the future to
strategize on how to drive improvement. The paper also addresses the perception that BI&A tools are expensive and
complex to deploy. The paper has been structured into five main parts, beginning with the introduction, which
highlights the importance of SMMEs in both developed and developing economics and presents the problem statement
and the rationale for the study. The second part, the literature review, provides the theoretical framework that informs
the proposed competitive BI&A systems. The third part of the paper concerns the methodology adopted for this study.
The fourth part highlights the findings and the paper concludes with recommendations for future research.
SMMEs appear unable to sustain business in South African despite the support provided by government, such as
incubator programs and financial assistance. This inability can be associated with the lack of knowledge management
and use of advanced technologies as evidenced by the high failure rate, with Chimucheka and Mandipaka observing
in 2015 that 70 percent of SMMEs fail within three years. Clearly this raises a serious concern as well as the question:
where are the stakeholders? As academia what can we do to assist the SMME sector? Because in the 21st century era
the business environment is volatile and “pressures to accelerate performance have led many organizations to enhance
their performance management practices and adopt Business Intelligence and Analytics technology to improve
decision making process” (Abi, Yahaya & Deraman, 2015, p.5), it is vital to play our part as BI&A experts with the
belief that the proposed strategy might address some of the issues. In addition, the paper enlightens SMMEs about
several approaches that can be of assistance with regard to competitive intelligence and sustainable business
The study is vital for the development of strategy that will enable SMMEs to strengthen their competitive advantage
and for innovation to generate new ideas that will lead to sustainability. Equally, this approach might have a significant
impact on job creation and poverty alleviation and consequently enhance economic growth. It has been noted that
some business owners fall short of adequate skills for managing for quality and performance excellence. Thus, the
proposed strategy aims at incorporating experts that will empower SMMEs. The University of Johannesburg
academics have already started a project that puts this into practice in Soweto, the largest township in South Africa.
In this project, university graduates are involved in their community, empowering the business owners of sewing
cooperatives. On the basis of the growth of researchers in BI, it can be said that South African researchers can
definitely provide the necessary expertise to strengthen SMMEs.
©Copyright 2017 by the Global Business and Technology Association
The literature review was conducted in the form of a scientometric analysis in which the researchers mapped the
progression of BI over the past 40 years using the Scopus database. Prakash and Nirmala (2015) define scientometric
analysis as an empirical study of a field’s literature, which entails the quantification of the published knowledge.
Cronin, Ryan and Coughlan (2008, p.39) concede the usefulness of such an approach but specify that “systematic
review should detail the time frame within the literature was selected, as well as the methods used to evaluate and
synthesize findings of the studies in question”. Mapping the progression of BI broadens the understanding of the BI
application usage and establishes what industries are using BI&A systems. In addition, the scientometric analysis
indicates the areas that have been adequately addressed and the aspects that have been overlooked or understudied, in
order to identify a gap in the literature. The study adopted Levy and Ellis’s (2006) systematic approach to conducting
an effective literature review within the IS domain, which was incorporated within the scientometric analysis. These
authors argue that an effective literature review “creates a firm foundation for advancing knowledge. It facilitates
theory development, closes areas where a plethora of research exists, and uncovers where research is needed” (2006,
p.182). As a result, this “input-processing-output” approach of Levy and Ellis (2006) was integrated into the
scientometric analysis.
a) Business Intelligence and Analytics
Kumari (2013, p.969) defines BI “as the ability for an organization to take all its processes and capabilities
and then convert these into knowledge, ultimately getting right information for the right people, at the right time,
through the right channel”. The key words in the above definition are knowledge and information. We are of the
opinion that SMMEs lack knowledge management and the ability to access accurate information for better decision
making. Concerning the progression of the BI field, there has been a significant progression in terms of the empirical