Evaluating the Impact of Business Intelligence on Decision-making

Abstract

The cost of logistics in Kenya is very high accounting for as high as 25% of production costs in some sectors. Kenya Association of Manufacturers have listed “cost, time and complexity of transport and logistics system in the country” as one of the major challenges to the Manufacturing sector. This is despite the Kenyan logistics industry embracing and using technology by implementing particularly company-wide ERP frameworks as their most vital processing platforms. Further, a good number have now integrated BI capabilities to their ERP systems to pick up an upper hand. The motivation behind this research was to decipher the role of BI to Logistics companies in Kenya, investigate its impact to business decision making and propose a model for BI use in decision making. The study adopted a descriptive transverse research design. The response rate for the target population was 82.5% which is statistically significant to analyze the data. Information gathered was broken down utilizing both illustrative and inferential insights. The study established that Analytical and Intelligent Decision Support (AIDS), Experiment and Integration with Environmental Information (EIEI), Optimization and Recommended Model (ORM) and Reasoning were the main BI functions affecting business decision making. The study also brings out the various bottlenecks in existing BI systems used in the logistics industry in Kenya and offers suggestions on how to deal with various challenges in the BI environment. Keywords: Business Intelligence (BI), business decision making, logistics, BI functions, BI benefits.