Companies like Amazon, Netflix, Zappos and Pandora have changed what consumers expect from a brand – they want brands to “know” what they want before they ask for it. To provide those kinds of personalized products and services, brands have to collect and analyze huge quantities of customer and industry data. That requires specialized talent – a commodity that’s in short supply.
Jennifer Priestly is a Professor of Applied Statistics and Data Science and the Director of the Center for Statistics and Analytical Services at Kennesaw State University. She cites a recent McKinsey research report showing that by 2018, the US alone could reach a shortfall in analytic talent of somewhere between 140,000 and 190,000.
Companies will be looking for creativity and critical thinking skills even more than they need industry expertise says Priestly. She gives two examples of companies you might not think of as big data companies so that you, I and our upcoming graduates can see the amazing opportunities that can be had.
Two of the many:
Coca Cola: In 2009, Coca Cola introduced Coca Cola Freestyle, a touch screen soda fountain that lets customers to choose from more than 100 flavors to create a personalized drink combination. There are more than 50 thousand of those machines around the globe transmitting real-time data, all of the time. And the Freestyle app lets customers save their favorite concoctions and share them directly from the app to the machine. Coca Cola is still a refreshment manufacturer and retailer, but now the really, really big data – time of day, location and taste preference data – allows the company to personalize down to the individual’s level and make informed choices of future locations and product options.
Southern Company: This electric co-op has replaced its traditional meters with smart meters and is now getting usage data from more than 4.4 million customers in real-time. Sure – Southern Company is still an electric company, but its advanced metering infrastructure now provides big data that it can use to “offer more innovative rate options” and help its customers manage their energy use and control their energy bill.
There are hundreds more examples, and all of them are chasing the same talent.
What should you do?
Priestly says it is the job of the universities and current data professionals to fix the gap. She says that universities need to innovate just as the private sector is. “We can’t teach the way we have always taught,” she says. “Universities need to use the new resources and tools to change their thinking to fit this generation of problems and this generation of learners.”
And current data professionals can be an invaluable resource to the university and its students. “We need you guys to come into the classrooms and help us. You guys are on the front lines,” she says.
Connect with your local university and see what you can do to help. Some of her suggestions include volunteering to present or tutor. The most valuable thing you can contribute though is data – real data. You know – the messy, pain-in-the-neck data.
Students are given data sets for their course work, but that isn’t the type experience they need. Provide internship opportunities that introduce the students to real-world uses of analytics. Assign them to projects that can capitalize on their creativity. If you really want to help, bring them a problem that you want an answer to and let them run with it. “It’s a heck of a lot cheaper than hiring a consultant firm and while you’re at it you will help create a pipeline of experienced talent.”
Read more tips on developing analytic talent on AllAnalytics.
