Effectiveness of Business Intelligence Tools for Supporting Decision-Making

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Individuals and organizations within current information society have at their disposal vast amount of data which potential has not fully been used. With the increasing availability of data there is a need to organize data and to extract knowledge from such data. Data are being accumulated in different formats and databases, which are usually not connected together, therefore leading to the inefficient use of valuable information.
Contemporary organisations are therefore seeking the opportunities to improve decision-making. With different people participating in decision-making, the scope of particular decisions is in many cases of global nature (Olszak & Ziemba, 2006). Thus there is a great need for tools that are able to
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Business intelligence represents the use of series of tools to collect, analyze and extract information which can be used to aid the management process and decision making. It can help to reduce costs and increase revenue.
According to Petrini (2009) business intelligence has been evolving over the last 35 years. 1970s saw the appearance of initial versions of analytical packages. In the 1980s, the spreadsheet software, Excel, was realised. In 1980s and early 1990s executive information systems (EIS) were introduced to provide senior managers with information from internal and external data, that are relevant in decision making. However, since EIS required a lot of manual work to convert data, their popularity decreased. This opened up the opportunity for emergence of business intelligence in 1990s.
Business intelligence can provide companies with accurate data that can be analyzed to support business strategy therefore enabling companies to better predict effectiveness of their business goals and ultimately result in a business profit. “Business intelligence is already in use in many organizations today, by finance departments to analyze financial performance, sales and marketing to identify customer trends, and operations to enhance the efficiency of supply chains. Using real data helps them answer who, what, where, why and when of related performance” (Rylander,2009).
Business Intelligence tools have evolved

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