The dawning of the digital age
While the exact origin of the term ‘ Business Intelligence ’ is unknown, there have been mentions of it as far back as the 1950s, when H.P.
Luhn described Business Intelligence as an automated system to spread information to different sections of an organization.
The system, in theory, would use data-processing machines to automatically abstract and encode documents and create actionable points and profiles from the data.
Then said documents would be automatically processed and sent to the responsible department for action.
In the 1950s, Information Management systems were pretty rudimentary, and the concept of Business Intelligence just at its very beginnings.
Over the next three decades, Business Intelligence began to emerge, taking on different forms during that evolutionary process.
Between the 1960s and 1980s, “decision support” systems were very popular with businesses.
Decision support systems are computer programs that analyze the data of the business and then present it to users in order to help them make decisions.
These systems work through a knowledge base or database, a model (composed of the user’s input and the context of the decision), and a user interface.
Some of the typical things found in a decision support system include comparative sales results, estimated revenue figures, and various outcomes of different decision alternatives using historical data and events (predictive modeling).
In the late 1980s, Howard Dresner came up with a definition for Business Intelligence that is still currently in use: A set of methods and concepts that helps you make better decisions.
These concepts and methods utilize support systems that are based on evidence.
Business Intelligence, as Dresner puts it, helps ensure business success when adapting to environmental changes.
Collecting and managing data is now a competitive advantage.
Initially, much of the focus of Business Intelligence initiatives was trained on technologies, processes, tools, and standards.
Companies were more interested in different ways to collect, store, rationalize and retrieve data, as well as create reports.
As such, more emphasis was placed on data marts, warehouses, dictionaries, and the ETL ( extract, transform, load ) process.
In the 1990s, Business Intelligence was still an emerging discipline.
Today, it is a fast changing discipline and a critical business tool for maintaining competitive edge – whether for large enterprises or startups.
It may have taken on several names, and many different forms of software and applications over its evolutionary journey, but Business Intelligence always had one aim: To help people make better business decisions.
That explains, in large part, why the focus shifted to the delivery of understandable and actionable analytics and statistics to end-users.