I recently read a research paper that stated the Business Intelligence (BI) industry is still relatively immature. The truth of this statement is almost self-evident, given the number of different definitions I've heard for Business Intelligence. I'd say this is confirmation that we are still trying to figure it out ourselves.
At Klipfolio, we've always approached BI and split it down the middle – we talk about the analytical aspects and the operational aspects (see Lyndsay Wise's article "Operational dashboard vs. Analytical dashboards"). This makes sense if you think about the analytical tasks of uncovering trends and patterns, versus the operational tasks of monitoring tactical or real-time data. For example, Klipfolio plays in the operation BI space; Cognos focuses on analytical BI.
But then I heard the term operational analytics – although I can understand the concept here, it cast a shadow on our pure and simple division of BI into two camps. Let me share with you some other definitions I've come across over the years – used by analysts, used in our employee training sessions, and used by our customers.
Let's start with Google's top result, Wikipedia. Wikipedia states that "Business intelligence (BI) refers to computer-based techniques used in identifying, extracting, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes. BI technologies provide historical, current and predictive views of business operations."
Here is an idea that has its origins in a 1958 article by IBM researcher Hans Peter Luhn, where he defined Business Intelligence as "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."
Building upon this idea, Howard Dresner in 1989 (later a Gartner Group analyst) proposed "Business Intelligence" as an umbrella term to describe "concepts and methods to improve business decision making by using fact-based support systems."
Forrester further develops this idea with the following broad definition: "Business Intelligence is a set of methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making."
Wayne Eckerson used this rather simple concept a few weeks ago: "BI consists of two diametrically opposed activities: top-down, metrics-driven reporting, and dashboarding where you know in advance what things you want to monitor, and bottom-up, ad hoc analysis to answer unanticipated questions."
If you are like me, you have already opened a new tab and are searching Google. Use "Business Intelligence definition" as your search term, and you'll find a slew of results. One worth checking out is an article at BeyeNetwork published in 2005. In this article, Larry English emphasizes that "Business Intelligence requires information quality." English goes on to propose this definition of BI: "The ability of an enterprise to act effectively through the exploitation of its human and information resources."
The Toolbox blog recently posed the question to LinkedIn users, and generated many interesting and insightful responses. I think Bill Cabiró's response illustrates the potential of operational BI. He states BI is "Getting the right information to the right people at the right time."
All these definitions provide a roadmap for where people in the BI space are hoping to go. Although BI seems to be topping every CIOs wish list for the past few years, we are at a waypoint where our efforts are only yielding moderate results – which is probably why Forrester gives BI space a 2.75/5 on the maturity scale. On the bright side, the BI space is entering a new phase fueled by cool technology like mobile BI and new KPI dashboards. As with any rapidly evolving space, lots of people are throwing their two cents into the ring and helping to foster the evolution of Business Intelligence.
