Like any newly recruited CFO, Mona Leung wanted to dedicate her first 6 months to learning everything there was to know about her new employer, Alliant Credit Union â€“ the seventh-largest credit union in the nation.
Ultimately, everything she learned in those first few months helped her to answer one central question: How does Alliant make decisions?
“This begins with a lot of listening and talking with your own peers,” says Leung, whose “listening tour” also provided an opportunity for her to begin educating Alliant executives about how investing in analytics software could give the company's enterprise risk management efforts a shot in the arm.
In Leung's view, the fact that Alliant was many times smaller than her previous employers (Quaker Oats; Sears, Roebuck & Co.) was not a reason to ignore the value that advanced analytics could bring to the company's growing risk management ambitions. But at the same time, Leung knew that realizing that value would depend largely on Alliant's culture and how it made decisions.
“You can have the right tool and the right talent, but if the culture isn't ready, none of it will matter,” explains Leung, who says that in order to really use analytics effectively, companies must be collaborative when it comes to their decision-making.
“You have to establish a structure where that collaboration can take place, and in order to establish this structure, there was a lot of 'presell' on my part. I would say: This is something that we need. We should do this,” she says. Leung credits a monthly business review with Alliant's senior executive team with helping to give the collaborative aspects of Alliant's culture a lift.
“We structured a process where people could gather and discuss results. Every month, the finance team supplied a packet and together we'd go through the packet. It was really a learning experience for my peer group as well as me, and we got to a comfort level where people could talk about what we did well and what we did not do so well. Then people began to ask the question: What does the data say? If there was no data, the question became: How can I help you build that data?” explains Leung, who says that the approach was validated when more junior executives began asking to be part of the data discussions, because they not only wanted to share their insights, but also wanted to listen to what others were doing to get at the data.
Meanwhile, as Alliant's decision-making become more data-centric, the movement to overhaul its data-mining process heated up. The initial goal was to produce twice as many models within its planning and forecasting processes -- a feat that it met after adopting a new analytics software package, known as Enterprise Miner, from SAS.
For the moment, Alliant appears to be ahead of the curve when you compare its ERM strategy and analytics savvy to that of similar-size competitors. Certainly, having a CFO who rejects the notion that analytics software is only for large companies removed a significant obstacle from Alliant's ERM path. As for removing cultural obstacles, Leung appears to have succeeded one meeting at a time. ###