Data Driven Managerial Decision Making in Ethiopian Export Sector

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With the development and deployment of ICT in different sector of an Economy, the type and amount of data collected by organizations is increasing from time to time. This created the concept of big data, data analytics, business intelligence and or data driven decision making. In line with this, almost all organizations are collecting and maintaining some sort of data/ information about their business. But it is not common to see many organizations analyzing their collected data and use for decision making. This problem is common among organizations in developing countries. Ethiopia is not an exception. From this perspective, the objective of this study is toexplore the hidden insight behind the data by applying business intelligence tool tableau. The study followed exploratory research approach; it intends to see the relationship among product category, value, volume, destination and year of export and used visualization as research design. The study used secondary data from the period 2007 to 2020 G.C, collected from Ethiopian Ministry of Trade.Business intelligence software Tableau was used to analyze the data. The finding is very impressive. The analytics tool revealed that there is much insightful information hidden inside the huge data set. Insights related to trend and relationships among some key data variables is interesting particularly for CEOs that don’t have to crunch every data in detail. The different tables that results from the analysis revealed the importance of data analytics. Particular emphases can be given to the visualization feature of the tools.



Business Analytics, Data driven decision making