Business intelligence is the process of analyzing business information, usually by computer software designed to provide data and analysis on which business decisions are made. Business intelligence software can supply information about basic business statistics such as sales revenue, inventory, production costs and employee benefits. It can also be used to generate reports, sort and store data, set and measure benchmarks for performance and perform business forecasting functions.
The term business intelligence dates back to the late 1950s, when it was coined by a researcher at IBM who described business intelligence as the ability of a company or manager to see how data are interrelated and use that information to make decisions and take actions to benefit the business. Beginning in the 1960s, computer software developers created special tools for business intelligence. The design of software systems grew in the 1980s and by the end of the 20th century had become a specialized sector within the business computing market. Business intelligence specialists are employed in nearly every industry as this role has become more important for business operations and management.
Business intelligence methods depend on the existence of data that can be analyzed. With the growth of technologies such as point-of-purchase sales reporting, data warehousing and shared records management tools, businesses have ever-increasing amounts of data at hand. Business intelligence techniques are designed to make sense of this data as a usable basis for performance evaluation and decision-making.
Business intelligence also helps to solve a problem faced by many enterprises. As email, chat, social media, call centers, word processing, the Internet and new media have grown, so has the volume of unstructured data. Unstructured data, or information that cannot be neatly contained in a spreadsheet, are valuable but difficult to search, store and classify. This information can be essential data for business intelligence. Software designed to maximize the retrieval and analysis of unstructured data is an important component of business intelligence. It attempts to solve the problem of accessing such data, which can be stored in many different and incompatible formats, making it searchable and developing a standardized terminology for unstructured data that can be used across different industries.
While business intelligence methods are largely standardized and can be used by almost any business of any kind and size, the applications of business intelligence differ according to the industry in which they are used. For example, online retailers use business intelligence techniques to gather vast amounts of information about their customers and quickly translate what it tells them into their customer service operations. Restaurant chains use business intelligence software to make decisions about adding new menu items, locate places in the supply chain where costs can be cut and identify poorly performing locations. Sports franchises even use business intelligence methods to analyze their performance, manage probability and maximize their rosters while remaining within the leagues' salary caps.
Despite these benefits and the growth of the business intelligence field, many professional analysts report lingering resistance to the approach among managers and employees when they are asked to participate in business intelligence exercises. In addition to persuading business leaders about the value and efficacy of business intelligence, there are other barriers to its successful implementation. Many businesses also lack awareness of how their own systems work. Without that knowledge, business intelligence processes will be ineffectual. Business intelligence processes must be relevant to the enterprises they serve and take into account how individual businesses and even managers operate.
Even more important, success in using business intelligence depends on high quality, standard and accessible data. For companies to benefit from business intelligence, they must have reliable, secure and "clean" data to work with. If the data that goes into business intelligence software and analysis is flawed, inaccurate or incomplete, decisions made on the basis of the business intelligence exercise will likely fail.
Finally, business intelligence tools must be user-friendly to be effective. As software develops and gains popularity, it is becoming easier to navigate, but the complex calculations and statistical analysis that goes into business intelligence methods are often a barrier for managers and other users who lack expertise in these areas.
Experts agree that business intelligence systems are only valuable if the decisions they help corporations to make are successful. The rapid pace of communications and the need to make decisions more quickly and more often than ever in today's business world mean that managers need more support, more focused information and protection against the often counterintuitive nature of business. While business information systems can provide these, they must serve the specific, personal function of human decision-making.