The sooner businesses are able to shift away from traditional hierarchical decision-making to a more data-driven culture, the sooner they'll realize a greater ROI from multimillion-dollar investments in big data and analytics technology, experts say. Here are five lessons learned from those who have successfully made the leap.
1. Simultaneously shift from the top down and the bottom up.
Shifting cultural direction necessarily requires an executive sponsor, but involving employees from the very beginning of the effort intensifies and speeds acceptance of data-driven decision-making, says Wolfe.
"We have a chief claims officer who realizes the value of data analytics and has been prepared to invest in the effort," he says. But what has been perhaps even more important is that adjusters and investigators have supported the effort, he notes.
"We selected a team of people in the special investigations unit who we thought would be most receptive to new technology, and we involved them from the beginning of selecting [analytic] tools. That way, they had skin in the game and bought into it," Wolfe explains.
In 2011, when SAS built four predictive data models for CNA to use across its workers' compensation, general liability, commercial property and commercial auto lines of business, fraud investigators and claims adjusters participated in user acceptance testing and offered feedback about the data models.
"What that allowed for is really good collaboration between us and the SAS project team," Wolfe says. "SAS had to learn our business, and we had to understand the limitations of analytics -- what could and couldn't be mined by the tools, and where our data could be misleading."
From this collaborative effort came a very valuable lesson. "You can't just plug in a tool and everything will be fine. You have to constantly look at results and analyze them. It's a constant evolution. Fine-tuning is never done," Wolfe says.
Another giant step CNA took toward creating a data-driven culture was to tie employees' performance evaluations and merit increases to how well they performed using the analytic tools. That was a big change, Wolfe acknowledges, but adds, "When you do that, the message gets out very quickly."
2. Data to-go ensures faster, fact-based decisions.
Getting executives to make decisions based on hard data is contingent on providing them with access to that data when and where they need it, says Doug Mowen, executive director of the year-old chief data and analytics (CDA) office at USAA, a San Antonio-based provider of financial services to the military community.
"We see in meetings that leaders want to make decisions when everyone is available in the room. They're unwilling to wait more hours or days to see data to guide those decisions," he explains.
So Mowen's team is working with IT to build a variety of self-service data dashboards that executives can pull up on their iPads, providing them with the facts and figures they need to collaborate effectively and make decisions in a timely manner.