What is Business Intelligence?
Originally published June 1, 2010
What's in a name? That which we call a rose by any other name would smell as sweet.
I was looking at a knowledge management website, and all I found was information that basically described business intelligence. The site did talk about classic knowledge management issues, such as knowledge transfer, tacit knowledge and knowledge sharing, but the business intelligence issues were more dominant. The issues described included such things as the role of the data server and the buoyancy of business intelligence software sales, and business intelligence vendor market share.
Being naturally curious, I decided to check out some other knowledge management sites where I discovered that they too provided a lot of coverage about business intelligence issues. In fact, one prominent knowledge management (KM) periodical routinely covers business intelligence (BI) issues. Topics include CRM analytics, business intelligence and medical practices, Web-based business intelligence, and various business intelligence software products.
I thought it curious that KM periodicals had co-opted business intelligence into their coverage, and I wondered how [or even if] this was justified to their readers. Personally, I am okay with including business intelligence in knowledge management as I have written on this subject, but I pondered whether business intelligence professionals think of looking at KM sources for business intelligence articles. My suspicion is that the KM field is pretty broad, so including a field such as business intelligence is plausible and even desirable, especially since business intelligence is a “hotter” topic in the United States than KM is.
I then decided to search online to determine how other areas were opting to include business intelligence within their domains. In doing this, I found that what quickly jumps out is the cooptation of business intelligence by the information systems field. Here, business intelligence is most frequently discussed relative to software applications, data management activities, data warehousing, and decision support. If someone searches the web to learn about business intelligence, then they are going to think that business intelligence has everything to do with information technology.
I don’t like the fact that business intelligence is often described in terms of data “something” (bases, mining, and warehouses) because I really think it diminishes the importance of analytics. In evidence-based decision making, data “something” is the source of the evidence, but analytics determines its usefulness and value. Data and analytics are together the foundations of business intelligence.
Having said this, I am annoyed by the fact that “analytics” periodicals ignore or minimize the term business intelligence. They will talk about things like supply chain, forecasting, data mining, heathcare, etc., but they rarely specify the association of analytics to business intelligence. I noticed this same phenomenon in my review of Analytics at Work: Smarter Decisions Better Results by Thomas Davenport, Jeanne Harris, and Robert Morison.
Some periodicals discuss both analytics and business intelligence. In an issue of IBM Systems Magazine, analytics are described as a component of BI. Business intelligence itself is referenced as a “system,” “environment,” a “solution,” and an “offering.” It is also described as a combination of “statistical and data-mining capabilities.”
A CRM magazine article distinguishes between business intelligence and analytics. BI is stated to be more about a source of data that you want to slice and dice, and then report to a group of people. Analytics are something you use when you want to analyze data in the context of a specific issue, such as understanding segmentation trends or propensity to buy.
A supply chain periodical described how supply chain analytics and business intelligence work together. Here, analytics are seen as a part of BI, but the term analytics becomes a way to distinguish various BI applications. The BI applications mentioned include operations analytics, finance analytics, IT analytics, customer service analytics, marketing analytics and supply chain analytics.
A blog post by James Kobielus entitled, “What’s Not BI? Don’t Get Me Started…” [April 30, 2010] speaks to the issue of describing what BI is and whether it is somehow different from analytics. In this article, a contributor describes BI as “referring to whatever supports access, delivery, presentation, visualization, and exploration of information. Consequently, it's the core of what people normally identify as BI: reporting, query, online analytical processing clients, dashboarding, portal integration, Excel integration, mashup, and the like.” It’s a nice description, though I would like to have seen a reference to why these things are done – decision making.
In this blog post, the question is posed whether BI and analytics should be differentiated. The answer given includes the following quote:
"BI" is simply a catchall term for the underlying platforms and tools (reporting, ad hoc query, OLAP, dashboarding, etc.) that support analytic applications. Hence, analytics is the superset, because its supporting infrastructure includes not only BI, but also DW, ETL, and the like.
I have an opposing viewpoint. Let’s look at the term “business intelligence.” It contains two words – “business” and “intelligence.”
BusinessDictionary.com defines “business” as an “economic system in which goods and services are exchanged for one another or money, on the basis of their perceived worth. Every business requires some form of investment and a sufficient number of customers to whom its output can be sold at profit on a consistent basis.”
The psychologist L. L. Thurstone provides a good definition of intelligence. He said that intelligence is the ability to think rationally, act purposefully, and deal effectively with one’s environment.
It would seem logical then to presume that successful businesses behave in an intelligent manner, employing fact gathering, problem solving, reasoning, and learning. So “business intelligence” involves a process of gathering, problem solving, reasoning, and learning to enable the successful functioning of the business system through effective decision making.
This conclusion contradicts the quote from Intelligent Enterprise (see above). That is, business intelligence is not a catchall term for tools that support analytical applications. Rather, business intelligence is the superset of tools and analytics. It is a goal, not the means.
Military intelligence is employed with the intent of increasing the probability of successful outcomes in battles and wars. Business intelligence is the means by which organizations learn about their environment and functioning so as to increase the probability of their success in business.
Here is the point of my article. Many of the discussions about business intelligence capitalize on business’s interest in it. The problem is, however, that most of them minimize their opportunity by digressing to assessments of and/or debates about “BI” components, rather than factors that foster or impede BI’s ultimate objectives. The discussions in periodicals really should be about whether the intelligence provided by data, technology, and analytics is increasing business success. Describing technology or analytics as business intelligence is like describing arms and legs or critical thinking as what a human being is. It results in the essence of the thing being understated and made confusing!
So I would like to plead that we all try to get on the same page and use a common and productive definition of business intelligence. Here is one that I would like you to consider:
Business intelligence is the application of data, technology, and analytics to gain insight and knowledge that enables decisions about people, processes, products, and services that yield positive economic outcomes.
If this definition were uniformly adopted, then discussions about BI could be made more consistent and constructive. We could all focus on what matters – outcomes. That would mean that IT articles about BI would talk about technology’s ability to contribute to successful business results, not simply about components and their capabilities. Analytics articles would discuss BI willingly and actively, seeking to enhance awareness of their relevance, importance, and value to the practice and success of BI efforts.
SOURCE: What is Business Intelligence?
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