Adoption of Big Data Analytics to Drive Decision Making

Abstract

The current business environment has been experiencing rapid change brought about by high intensity of competition, disruptive technologies, creativity, innovations and strategic marketing. To sustain competitiveness in the current uncertain environment, organization need to make accurate decisions regarding their market, operations and investment. This can be achieved by having evidence-based decision making approaches. Global companies have adopted big data analytics to facilitate evidence decision making. This study pursued to examine the extent by which telecoms, telecommunication service providers, Information Communication Technology companies and service providers and a major institute of higher learning in Kenya had adopted big data analytics, the factors which influenced adoption process and the suitability of the model used to establish this adoption in their operations. To accomplish the objectives of the study, a descriptive research design was employed by the study. The data was collected from telecoms, telecommunication service providers, Information Communication Technology companies and service providers. A major institute of higher learning was also part of the sample due to its rich ICT bias and presence of ICT innovation hub. Semi structured questionnaires were used. Data analysis was done using Statistical Package for the Social Sciences (SPSS) and presented using tables, charts and percentages. Multiple linear regression was applied to find out the significance of each variable towards adoption of big data analytics to drive decision making. The study found that big data analytics had been adopted to a great extent by this companies. Organizations used business intelligence, big data as well as predictive analytics in their operations. The adoption of big data analytics was influenced by technological, organizational and environmental factors. The degree of compatibility of big data analytics to the existing IT systems, top management support, size and structure of the organization and the intensity of the competition were identified as the factors with highest significant effect on the adoption of big data analytics. Other factors such as the perception of the customer on their data privacy, the availability of data and international trends were also considered as important. Some of the challenges highlighted included inadequate legal framework, need for employee culture change and inadequate presence of skilled staff on big data analytics. The limitation of the study was that data was mostly collected using online questionnaires hence people’s emotions and expressions could not be captured, however this was the most efficient way to reach a great number of respondents. It was recommended that the legal framework be made adequate to enable more organizations to adopt this technology, organizations also need to train their employees to acquire skills in big data analytics as well as establish networks with data driven companies.