Requirements of Adopting SMEs for Business Intelligence Systems: A Field Study in the Industrial Zone of Setif in Algeria

Introduction

As it is known, small and medium-sized industrial enterprises play a prominent developmental role for any national economy. They effectively contribute to positive impacts on various economic, social, and technological variables. This can be achieved through their continuous contribution to creating innovative utility value, maximizing the Gross Domestic Product (GDP), promoting the country's external exports, and positively influencing its trade balance. In addition to providing both permanent and temporary employment opportunities, they contribute to the development of technology patterns within the country, thereby reducing technological dependence on foreign entities and establishing national sovereignty in this field. However, there are many other positives that cannot be fully discussed here. In line with this, many researchers currently observe a significant increase in the adoption of Business Intelligence (BI) systems by economic institutions. Therefore, it transforms the traditional form of the enterprise's working environment into a more complex and digitally distinctive form. Products supported by the analysis of big data shift from their personalized form to a collective one. Despite their limited resources and capabilities, small and medium-sized industrial enterprises need to adapt more and more to the changing nature of consumer pathways. They also require the adoption of business intelligence and analytics in the midst of the digital economy era (Kotler, 2017, pp. 10, 11, 13, 14).

Currently, technologies are evolving continuously and rapidly, and industrial enterprises are adopting modern methods and tools to ensure sustainability and gain a competitive edge. This necessity arises from the need to keep up with developments affecting the business sector, such as the emergence of Business Intelligence systems, which are considered as the latest and most important cost management tools (Blocher, Stout, & Cokins, 2010). These systems are based on shaping big data, establishing mechanisms for accurate and efficient data collection, analyzing it, and innovating methods to process and understand it. Evidently, the information derived from this process is then used to make various decisions within the industrial enterprise. BI is one of the most crucial mechanisms currently relied upon to control and reduce product costs, enhance production quality to meet market demands, and achieve the desired consumer surplus. Additionally, it facilitates timely responses to customer needs, known as the strategic triangle which represents: cost, quality, and timeliness (Poluha, 2016, pp. 22, 23). Many researchers believe that BI systems are the optimal and most effective solution to meet the needs of modern industrial enterprises. Reports from global companies such as “Australian Computer”, “Oracle”, “Gartner Group”, and “Teradata” emphasize the paramount importance of information in overcoming various obstacles faced by economic institutions. By adopting and applying BI principles, enterprise management can simplify decision-making processes, improve customer relationship management, and remain highly alert to changes in its working environment (Olszak, 2020, p. 35). BI can provide an upward value for the enterprise when it is used in the right way by individuals. Cindi Howson sees that there is a positive correlation between the efficint use of business intelligence and the performance of the enterprise, since reaching data does not necessarily lead to efficiency and good results, but dealing, understanding, and using it in the right way is the key criterion. (Howson, Successful Business Intelligence: unlock the value of BI and big data, 2014, pp. 5, 6)

This chapter will attempt to study the nature of Business Intelligence (BI) systems that are compatible with small and medium-sized industrial enterprises, considering the distinctive characteristics of this type of institution compared to large enterprises. It will identify and analyze the various organizational, technical, and human requirements necessary for the successful adoption of BI systems by these enterprises, making it an effective tool for creating value, improving performance, and making the right decisions.