Strategic use of analytics to support enterprise goals
JMP wasn’t around when Anne Milley was taking quantitative analytics courses in college.
“Back then, it was all programming,” explained Milley, an economics major. “The visuals were just hideous.”
Today, as senior director of analytic strategy in JMP Product Marketing at SAS, Milley appreciates the value that robust and interactive graphics in JMP bring to the analytical experience.
“Now you can visually wallow in your data,” she says. “You can see what you need to pay attention to immediately, visually, and that’s wonderful.” Outliers and trends that can remain hidden in columns of numbers become apparent immediately when displayed graphically.
With organizations today collecting more data than ever before, the ability to more quickly derive meaning from vast stores of raw data is becoming increasingly important. Milley advocates a strategic approach to analytics that increases its value across the enterprise.
She enjoys helping organizations increase their “analytic bandwidth” to get more bang from their technology buck by creating analytic centers of excellence – internal teams that promote the strategic use of analytics to support enterprise goals. That will be the topic of her complimentary SAS TALKS webcast at 1 p.m. ET on Thursday, June 23.
Tune in and you’re likely to hear Milley refer to the 80-20 rule: Most analysts spend 80 percent of their time preparing their data and only 20 percent of their time exploring and analyzing it to make discoveries. She’ll talk in the webcast about strategies for moving that ratio in favor of analysis, which will integrate ways to communicate results.
“Matching the right technology paradigms to the right skill sets is very important,” she explains. “Some people prefer to write code, some prefer to work visually, and some like both.” JMP lets users choose which approach to take. Using JMP, programmers can connect to SAS and R, while users who need graphical representations can use JMP with Excel to make data more interactive.
Whichever approach individual users take, finding ways to use data to greater competitive advantage is a universal goal. “Analytics is relevant everywhere, and it’s something that you can’t get away from, so you might as well recognize its power and invest in it,” says Milley.