Business Intelligence Application Adoption In The Nigeria Retail Sector

Classification of retail industry in Nigeria

The Nigeria retail sector is modelled in-line with the North American Industry Classification System (NAICS) according to BusinessDay Intelligence, (2014). This type of classification allows for data collection, analysis, and publication of information that is related to the economy. For that reason, and based on the company system and operation, the Nigeria retail sector is classified into the following:

• The traditional open market outlets;
• Unit neighbourhood stores;
• Multiple branch supermarkets (convenience stores);
• Mega supermarkets/shopping malls.

The traditional open market outlets

As of 2014 according to BusinessDay intelligence, (2014) the traditional open market accounted for 70% of the retail sector, and it is commonly patronised in Nigeria. The stakeholders in this informal trade include; the street traders (hawkers, selling on traffic), and those carrying out their trade in open stalls in the open market. As the sector’s landscape is changing very fast so as the percentage of this type of system dwindles as other forms grow.

Unit neighbourhood stores

The unit neighbourhood stores or mini-markets are small-scale supermarkets or mini-market that operates in one store according to BusinessDay intelligence, (2014) definition. They are stores situated in the neighbourhood that caters for the resident in those surroundings.

Multiple branch supermarkets (convenience stores)

These are small to medium size retail stores that offer varieties of products which are largely situated in different locations. The difference between unit neighbourhood stores and the multiple branch supermarkets is that unit neighbourhood stores operate from one store while multi-branch supermarkets have various branches.

Mega Supermarkets/shopping malls

These types of retail outlets are large and mega stores offering arrays of different products. Their products are of high quality and in some cases at low prices.

E-tailer (E-commerce)

The adoption of online payment in Nigeria has given rise to online (doing business over the electronic network such as the internet) transaction. In an online transaction, retailers display their goods and services through websites and mobile apps. In turn, consumers search for goods and services on various websites. In Nigeria e-tailer setting payment can be made in various forms, either through online payment or pay as products are delivered. There are various plays in this type of trade, such as; Jumia, OLX, JiJi, and Konga. Jumia is the leading company in this form of trade and it offers various products, such as clothes, toys, children wear, cosmetic, fashion, mobile devices, and range of other goods.

Related works

This part of the literature reviews related works that have been carried out in the field of Business Intelligence application adoption.

A literature search shows that a research was carried out by Olexova, (2014). The aim of the research was to examine BI adoption in a retail chain. The research analysed BI lifecycle and evaluates its adoption from the Diffusion of Innovation (DOI) position. The research revealed that infrastructure requirement was the most vital in the BI adoption process. Also, it was revealed that managers view a well-taught decision-making to be a major advantage. However, the research further finds that even small (minor) issues can pose a major challenge in the adoption process. If that is the case, how does an organisation define minor issues?

Minor issues could be relative depending on individual’s or an organisation’s capability. What an organisation with high technical skills will define as small issues will differ from what a less technical organisation call minor issues. Therefore, in other to enable readers and would be BI implementers to clearly diffuse the research findings, it is imperative that the researcher make its findings clearer and without ambiguity. Furthermore, the research was conduct based on qualitative research method and mainly focused on a retail chain. Qualitative research method on its part according to Panneerselvam, (2004) tends to be without structure and heavily reliance on individual viewpoint, which is characterised with bias and in the end leads to poor results. For this reason, a quantitative research method which is regarded as research approach that offers a great assistant to a researcher that enables him or her to demonstrate statistical proof on the degree of relationships between both internal and external constructs, according to Waters (2011) would be suited for such a research in other to reach a conclusion without interference or bias. Furthermore, it is a view held by this research that a research tailored towards an industrial sector will have a wider patronage as the findings will not only benefit an individual company, rather to other stakeholders such; government agencies, and BI developers alike.

Another research was conducted by Owusu et al, (2017) on the determinant of BI systems adoption in developing countries, with an empirical analysis from the banking sector in Ghana. The research was set to empirically look at the factors that influenced BI systems adoption in Ghana banks and to determine the extent of adoption in banks. The research devised nine factors which were derived from various adoption theories to investigate the factors that influence adoption. The findings revealed the following:

• BI adoption is influenced by the relative advantage of BI application;
• The complexity of BI application;
• Presence of a champion;
• Organisational readiness;
• A regulatory body.

Ipomai, (2016) carried out a study entitled: adoption of Business Intelligence solutions: a case of Kenyan insurance industries. The objective of the study was to find and proposed the right model for BI solutions adoption in the Kenyan insurance industry and further validate the proposed model within the same industry. The targeted companies are the duly registered insurance companies operating in Kenyan in 2016. The study focused on the following key independent variables, namely; user’s characteristics, technological characteristics, environmental characteristics, organisational and key decision makers characteristics. The findings revealed organisational and key decision makers characteristics plays a significant role in BI adoption. While user’s characteristics, technological characteristics and environmental characteristics show to play no significant role in BI adoption. Although, the research finding was consistent with adoption frameworks, however, the researcher would have laid more emphasis on users (people). Because from a literature review standpoint, users had shown to play a significant role on how successful and practicability of any Information Systems (BI) implementation in an organisation. In doing so, the research would have aided organisations that are in the process of BI implementation, thereby enabling them (organisation) to put users at the core of their BI adoption and implementation process.

Lautenbach et al, (2017) conducted a research to find out the factors that influence business intelligence and analytics extensive usage in South African organisations. The research adopted the Technology-Organisation-Environment (TOE) framework for the research. The findings revealed data-related infrastructure capabilities was a catalyst for BI adoption and usage. Furthermore, top management support and external market influence were also found to be a driving force for BI adoption. Nevertheless, regulatory compliance and data management challenges were not found to be a factor in BI adoption. This research was based on South African organisations in general, whereas a research based on an industrial sector would have had a great impact and contribution to BI adoption process. Therefore, there is a need for a research on BI adoption based on an industrial sector to clearly show an understanding of BI adoption processes and strategies.

While there is a body of literature on BI adoption and implementation in various fields such; banking, insurance, and SMEs. However, literature review indicates there is no significant academic research on BI adoption in the retail industry in the developing countries. Even in the light of the huge consumer spending which is projected to rise to US$ 1 trillion by 2020 according to Ornico Group 2014 report In addition, IT spending in retail industry in developing nations are thriving. IT spending in African countries such as Nigeria, Ghana, Kenya, Rwanda is estimated to go up in the next years. With that in mind and coupled with the lack of literature on this very issue, hence, there is no adequate information to inform different actors on BI adoption strategies in the retail industry. These form the basis of this research, with the primary task to look at the BI adoption in this sector. In this research, the Nigeria retail sector has been chosen to analysis the BI adoption process.

Summary

The most significant determining factor to the degree of success or failure of a new technology adoption is characterised by the users. From the literature review, it was evident that the usefulness of a technology to users, the difficulties for users to use the new technology, how it will help users do their work in an effective and efficient way are issues that must be resolved when technology (innovation) adoption is being considered. Furthermore, infrastructure requirements (data warehouse), the relative advantage of BI application, top management support, external market influence, the presence of a champion, regulatory body, and organisational readiness plays an important role in BI adoption and subsequent use.