It’s a story you’ve heard before: Large organization wrestling with many different data sources controlled by different business units, different formats, some monthly, some quarterly—analyzed in spreadsheets. This was the old world at Bank of America, as described by Senior VP Jessica Dunn, whose team was charged with evaluating the company’s 186 new business segments. A shift in 2010 to Enterprise BI Server and SAS 9.2 has enabled more rapid, self-service analysis, including use of analytics by the company’s executives.

But, according to Dunn, “That’s actually where the real story starts.”

The next chapter at Bank of America is about creating a stable platform to enable analytics more efficiently. “As we were demoing to other teams, I would have to send an email out and make sure no one was on the system because I have to be able to log on.” This was new territory for Dunn, a self-proclaimed “non-technical person.”  She knew there were improvements to be made on the back end, but wasn’t sure what they were. “I never had to worry about what happened on the back end – I just focused on doing the analytics and driving business.”

Through a technical assessment with SAS, Dunn’s team determined three things were holding the company back from establishing a stable environment and an analytic infrastructure:

• Hardware was not optimized. According to Jessica, “probably the easiest thing to overcome.” Re-architecting the environment improved performance, and in a future phase, the team will evaluate technologies like grid computing.
• Skillsets were not optimized. Dunn made a strong case for establishing and hiring people with specialized analytics skills. She created the term “hybrid administrator,” someone who can speak the languages of both the platform administrator and the developers.
• Need for education. Bank of America sent both management and technical teams to SAS training. Including managers was important, “so they could really understand the capabilities of the software,” said Dunn.

Underlying all of these efforts, Dunn says, is a mindset change toward processes that are more iterative, agile, and flexible. For example, platform administrators often want to lock data down and work within very controlled processes. “But I need to work faster and more flexibly. Now, requests that used to go to a production team, we’re doing within the line-of-business teams.”

Bank of America is moving full speed ahead in its analytical transformation, looking at additional technologies like high-performance analytics. In fact, the new capabilities and platform optimization they’ve undertaken have allowed them to now look at more than 3,000 customer segments, compared to the previous 186. “Can you imagine doing that in Excel?” Dunn balks, “You just can’t do it, you need to bring in a more powerful tool.”