SAS and the Business Analytics Innovation Centre

Last Friday, SAS announced that it was partnering with Teradata and Elder Research Inc. (a data mining consultancy) to open a Business Analytics Innovation Centre.  According to the press release,

“ Recognising the growing need and challenges businesses face driving operational analytics across enterprises, SAS and Teradata are planning to establish a centralised “think tank” where customers can discuss analytic best practices with domain and subject-matter experts, and quickly test or implement innovative models that uncover unique insights for optimising business operations.”

The center will include a lab for pilot programs, analytic workshops and proof of concept for customers.  I was excited about the announcement, because it further validated the fact that business analytics continues to gain steam in the market. I had a few questions, however, that I sent to SAS.  Here are the responses. 

Q. Is this a physical center or a virtual center?  If physical – where is it located and how will it be staffed?  If virtual, how will it be operationalized?

R. The Business Analytics Innovation Center will be based at SAS headquarters in Cary, North Carolina.  We will offer customer meetings, workshops and projects out of the Center. 

Q. Will there be consulting services around actually deploying analytics into organizations?  In other words, is it business action oriented or more research oriented?

R.  The Business Analytics Innovation Center will offer consulting services around how best to deploy analytics into organizations, as well as conduct research-based activities to help businesses improve operational efficiency. 

Q.  Should we expect to hear more announcements from SAS around business analytics, similar to what has been happening with IBM?

R.  As the leader in business analytics software and services, SAS continues to make advances in its business analytics offerings. You can expect to hear more from SAS in this area in 2010

I’m looking forward to 2010!

Decisions and Consequences

Not everything is easy.  I analyzed data for decision-making for many years using advanced techniques such as predictive modeling, machine learning and even influence diagrams.  With the rush to pervasive BI we often forget about the need for truly sophisticated analysis to aid in complex decision making.    I’m talking about decision support for critical strategic initiatives such as managing a portfolio of investments, preparing for terrorist threats, or modeling sales spending for drug marketing when dealing with competing products.  In other words, analysis of dynamic situations where multiple outcomes are possible. 

Past performance is not a guarantee of future results

 What is constant is that the world does not remain constant. The future is dynamic, change is expected and traditional BI can only take you so far in the decision game. Often, it is necessary to determine a series of plausible futures or explore the consequences of possible decisions.  DecisionPath [] a Boston based company uses the “past performance” phrase above to drive home some of the limitations of BI.   I had a very interesting briefing with Richard Adler, the CTO of DecisionPath, the other week.  He correctly pointed out the following:

  • BI technology helps to examine the past and today and how we got there
  • Predictive analysis is useful if the future doesn’t change, which of course it will, necessitating updating the models (if possible).
  • BI can provide high quality input into decision-making, but it doesn’t provide the whole picture because the world is dynamic.
  • BI does not actually support the process of decision-making (i.e., actively enabling or enhancing it).  Think about the word process here. 

DecisionPath offers a product called ForeTell that helps to develop and test decisions.  ForeTell combines various complementary simulation techniques in one framework.  So, whereas a software vendor might provide some of these techniques, DecisionPath has put them together in one framework that works together with BI systems to model, simulate, and explore possible decision outcomes and test alternative decisions.   Here is an illustration, provided by DecisionPath, that describes the relationship between BI and ForeTell:


source: DecisionPath

This is not your ma and pa BI and it clearly not for everyone.  DecisionPath has made good inroads in the government, pharmaceutical, and financial sectors where complex analysis is the norm.  However, alternative decisions with complex tradeoffs exist in all industries to some degree so certainly the approach is applicable to a wider range of verticals than those listed here.


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