To BI and beyond: A BI primer


I remarked in an earlier post (“BI and Better Decisions”) that, prior to joining SAS, while I understood analytics and performance management just fine, the phrase ‘business intelligence’ was not in my vocabulary”.  Turns out I’m not the only finance professional so inflicted.  I was invited last week to give a talk on business intelligence to my local finance colleagues at the RTP CFO Forum, where this question of, “exactly what is BI” was something on their minds as well.

You’d get no such equivocality from your IT colleagues, our own uncertainty in finance an indication that we need to get out and talk with our business partners a little more often.  They know precisely what BI is about, and why.

A little history will help here.  While the first use of the term “business intelligence” was in a 1958 paper by IBM researcher Hans Peter Luhn, it was Howard Dresner in 1989 (later with Gartner) who defined the term and the practice as we now recognize it.  Even I could have invented the concept in 1999, but it was Dresner’s talent that he recognized a decade earlier that the disparate data warehouse, analytic and reporting projects and initiatives needed to be unified under a single umbrella.

The fundamental problem that BI addresses is: scarce IT resources.  By the 1980’s data warehouses were being developed with no easy way for users or other systems to access the data.  A hundred business users trying to access just twenty systems or warehouses required 2000 separate log-in procedures to be maintained, with no role-based security to handle the complexity and prevent accidental ‘write access’ from touching the data.

Next, these one hundred business users, unable to directly access the systems themselves, were overwhelming IT with requests for data, for reports, or for changes to existing report formats.  What IT needed was some sort of self-service approach.

Lastly, enterprise-wide reporting was a shambles – a different format for every report, a different format from each business user or financial analyst.  And while the aesthetics of the reporting formats was disconcerting enough, the variations in formats implied another more serious issue – differences in data/field definitions, meaning and usage.  The term “revenue” could mean a dozen different things across the company.  Something had to be done.

What was done was the BI suite - business intelligence platforms that integrated data management with query, analysis, reporting, and information delivery across the enterprise.  IT could not have managed the increasing workload without it, especially once the big data impacts of the internet began to take hold.

Which brings me finally to a satisfactory resolution to the unsettled conundrum with which I ended that previous blog post.  At the many IE Group conferences I have chaired these past three years (I’ll be chairing Day 2 of their FP&A Innovation Summit this Thursday and Friday, September 13-14, in Boston) I have been witness to more than one presentation whose less than dramatic conclusion was something along the lines of:  after spending a year and $4 million dollars all I got was this big honking data cube and a lousy tee-shirt.  Turns out I should have had more sympathy than I may have exhibited.

Compared to the rest of the organization, we are a bit spoiled in finance.  I know that’s hard to believe; we are usually last on the list for capital/IT investments, but when it comes to financial data and financial reporting we generally have a leg up on our operational counterparts in that our financial packages already incorporate a data mart/warehouse, some master data and user management capability, some basic ad-hoc query functionality, and fairly decent reporting.

What I’ve come to understand is that different parts of the organization come to the resolution of their data management and reporting problems from two different perspectives:  1) the packaged solution, or, 2) the business intelligence approach.

While each have their advantages and disadvantages, allow me to focus my concluding comments on BI.  What BI does very, very well is in delivering the foundation for consistent, enterprise-wide information management and reporting, and in providing a platform for the integration of advanced analytics for insight and action.  It is this final aspect, a platform for advanced analytics, be that risk, fraud, customer intelligence, social/text analytics, supply chain and quality management, or operations, that I typically find lacking in a standard BI implementation.  There is no “so what” at the end of the project, no compelling “there”, there, because there is no further connection from the data to the rest of the operational organization beyond just the basic reporting.

With the importance of a solid BI foundation in mind, SAS continues its support of our robust and comprehensive BI platform with the recent announcement of our latest SAS EBI/BI Server release, including better performance, navigation, customization, display and design.  For those who want to know more, please join Rick Styll, SAS BI product manager, this Thursday, September 13, at 1:00PM EDT for his SAS Talks Webinar where he will explain not just the new features but also how BI can positively impact your real world business problems.

The future of both performance management and business intelligence is the continued integration and incorporation of analytics into the foundation solutions.  On the performance management side, SAS tightly integrated business-user forecasting capability into its SAS Financial Management solution earlier this year.  On the BI side there is SAS Visual Analytics, combining extremely powerful analytical tools with a user-friendly visual interface and display.  As I’ve said before, “Data + Context = Business Intelligence”, and there is no better way to add context then visually.

So, when it comes to business intelligence – think BIG, think bold, think visually, think analytically.  Work backwards from the business decision to the required supporting data, processes and analysis.  Make certain there is a big, operational “SO WHAT” at the end of your BI initiative.


About Author

Leo Sadovy

Marketing Director

Leo Sadovy currently manages the Analytics Thought Leadership Program at SAS, enabling SAS’ thought leaders in being a catalyst for conversation and in sharing a vision and opinions that matter via excellence in storytelling that address our clients’ business issues. Previously at SAS Leo handled marketing for Analytic Business Solutions such as performance management, manufacturing and supply chain. Before joining SAS, he spent seven years as Vice-President of Finance for a North American division of Fujitsu, managing a team focused on commercial operations, alliance partnerships, and strategic planning. Prior to Fujitsu, Leo was with Digital Equipment Corporation for eight years in financial management and sales. He started his management career in laser optics fabrication for Spectra-Physics and later moved into a finance position at the General Dynamics F-16 fighter plant in Fort Worth, Texas. He has a Masters in Analytics, an MBA in Finance, a Bachelor’s in Marketing, and is a SAS Certified Data Scientist and Certified AI and Machine Learning Professional. He and his wife Ellen live in North Carolina with their engineering graduate children, and among his unique life experiences he can count a singing performance at Carnegie Hall.

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