This article was contributed by TechnologyAdvice
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).
The dawning of the digital age
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. We started seeing success stories as Business Intelligence and analytics became a not-so-secret weapon for the world’s leading companies in some of the most competitive industries.
Time for another renaissance
However, for each success story, there are countless others that fail. In 2011, Bill Goodwin at ComputerWeekly cited Gartner, reporting that eight out of ten Business Intelligence projects are doomed to fail. This was due mainly to poor synergy between the business and its IT department, asking the wrong questions, and not knowing the business’ real needs.
Businesses still often find a disconnect between their reporting and analytics needs, the required workflows between technical and business users to communicate and deliver on those needs effectively, and what their Business Intelligence software offers. There are plenty of tools to choose from, but few people know how to use them. That’s why Business Intelligence and analytics need to evolve again. IT professionals who choose, implement, and configure Business Intelligence systems have the skills necessary to do so. But, line-of-business users often have a hard time communicating what they need.
The solution? Build Business Intelligence and analytical tools that are easy to understand, implement, and use for all, which assist business users to collaboratively work with technical users to deliver timely, meaningful results. Solutions like Yellowfin are designed to help regular business users harness Business Intelligence and analytical apps quickly and easily. Meanwhile, the IT department can maintain data governance, ensure data analysts produce trustworthy reports and analysis via access controls and metadata layer, and give end-users just the right amount of information with customized dashboards.
Modern BI tools
As more and more businesses find themselves swamped with data, it makes sense to store it in the cloud. Also, more employees work from mobile devices away from the office. Today’s Business Intelligence platforms need to give customers a choice of deployment options. Instead of being constrained to a server-based, desktop application, businesses have to be able to choose a system that accommodates mobility and places less burden on their own resources.
A good Business Intelligence platform for today’s companies should also provide collaborative features to help teams share information, annotate, and inform other employees – even extend access to reports and dashboards to any stakeholders connected to the business decision at hand.
Over the past 60 years, Business Intelligence technology and needs have evolved from a limited scope of information, provided to a limited audience of technically proficient users, to something from which everyone in your organization should be able benefit.
About the author
Michael Gabriel Sumastre is a writer for TechnologyAdvice with more than 11 years of industry experience. He has written more than a thousand articles related to tech and gadgets, cloud computing, IT management, big data, the Internet of Things, SEO, SEM and software solution.