“Business intelligence is an over-used term that has had its day, and business analytics is now the differentiator that will allow customers to better forecast the future especially in this current economic climate.” | ||
Jim Davis | ||
SVP and Chief Marketing Officer, SAS Institute Inc. |
The above quote is courtesy of an article reported on Network World, the full piece may be viewed here.
In the same article, Mr Davis went on to add:
I don’t believe [BI is] where the future is. The future is in business analytics. Classic business intelligence questions support reactive decision-making that doesn’t work in this economy because it can only provide historical information that can’t drive organizations forward. Business intelligence doesn’t make a difference to the top or bottom line, and is merely a productivity tool like e-mail.
The first thing to state is that the comments of this SVP put me more in mind of AVP — should we be anticipating a fight to the death between two remorseless and implacably adversarial foes? Maybe a little analysis of these comments about analytics is required…
“Business intelligence is an over-used term that has had its day, and business analytics is now the differentiator that will allow customers to better forecast the future especially in this current economic climate.” | ||
Jim Davis | ||
SVP and Chief Marketing Officer, SAS Institute Inc. |
The above quote is courtesy of an article reported on Network World, the full piece may be viewed here.
In the same article, Mr Davis went on to add:
I don’t believe [BI is] where the future is. The future is in business analytics. Classic business intelligence questions support reactive decision-making that doesn’t work in this economy because it can only provide historical information that can’t drive organizations forward. Business intelligence doesn’t make a difference to the top or bottom line, and is merely a productivity tool like e-mail.
The first thing to state is that the comments of this SVP put me more in mind of AVP — should we be anticipating a fight to the death between two remorseless and implacably adversarial foes? Maybe a little analysis of these comments about analytics is required. Let’s start with SAS Institute Inc. who describe themselves thus on their web-site [with my emphasis]:
SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market.
It is also worth noting that the HTML title of sas.com is [again with my emphasis]:
SAS | Business Intelligence Software and Predictive Analytics
Is SAS’s CMO presaging a withdrawal from the BI market, or simply trashing part of the company’s business, it is hard to tell. But what are the differences between Business Intelligence and Business Analytics, and are the two approaches merely different facets of essentially the same thing?
To start with, let’s see what the font of all knowledge has to say about the subject:
Business Intelligence (BI) refers to skills, technologies, applications and practices used to help a business acquire a better understanding of its commercial context. Business intelligence may also refer to the collected information itself.
BI applications provide historical, current, and predictive views of business operations. Common functions of business intelligence applications are reporting, OLAP, analytics, data mining, business performance management, benchmarks, text mining, and predictive analytics.
and also:
Business Analytics is how organizations gather and interpret data in order to make better business decisions and to optimize business processes. […]
Analytics are defined as the extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based decision-making. […] In businesses, analytics (alongside data access and reporting) represents a subset of business intelligence (BI).
Rather amazingly for WikiPedia, I seem to have found two articles that are consistent with each other. Both state that business analytics is a subset of the wider area of business intelligence. Of course we are not in the scientific realm here (and WikiPedia is not a peer-reviewed journal) and the taxonomy of technologies and business tools is not set by some supranational body.
I tend to agree with the statement that business analytics is part of business intelligence, but it’s not an opinion that I hold religiously. If the reader feels that they are separate disciplines, I’m unlikely to argue vociferously with them. However, if someone makes a wholly inane statement such as BI “can only provide historical information that can’t drive organizations forward,” then I may be a little more forthcoming.
Let’s employ the tried and test approach of reductio ad absurdum by initially accepting the statement:
Business intelligence is valueless as it is only ever backward-looking because it relies upon historical information |
Where does a logical line of reasoning take us? Well what type of information does business analytics rely upon to work its magic? Presumably the answer is historical information, because unless you believe in fortune-telling, there really is no other kind of information. In the first assertion, we have that the reason for BI being valueless is its reliance on historical information. Therefore, any other technology or approach that also relies upon historical information (the only kind of information as we have agreed) must be similarly compromised. We therefore arrive at a new conclusion:
Business analytics is valueless as it is only ever backward-looking because it relies upon historical information |
Now presumably this is not the point that Mr Davis was trying to make. It is safe to say that he would probably disagree with this conclusion. Therefore his original statement must be false: Q.E.D.
Maybe the marketing terms business intelligence and business analytics (together with Enterprise Performance Management, Executive Information Systems and Decision Support Systems) should be consigned to the scrap heap and replaced by the simpler Management Information.
All areas of the somewhat splintered discipline that I work in use the past to influence the future, be that via predictive modeling or looking at whether last week’s sales figures are up or down. Pigeon-holing one element or another as backward-looking and another as forward-looking doesn’t even make much marketing sense, let alone being a tenable intellectual position to take. I think it is not unreasonable to expect more cogent commentary from the people at SAS than Mr Davis’ recent statements.