With the onslaught of data in digital transformation comes a huge demand for data scientists to help slice and dice it. Research shows the demand has grown 29 percent year over year, with a total jump of 344 percent since 2013. The only problem? There aren’t enough skilled people to take on the role. While the number of “data scientist wanted” ads continues to grow, the number of people seeking those jobs has grown far more slowly (by some accounts, just 14 percent). Today’s companies can’t afford to wait for new hires to magically appear before them. If they want to survive the push for big data, they need to invest in their own data scientist skills training—and there are lots of ways to do it.
Upskilling Your Data Scientist
One of the easiest ways to improve your employees’ data scientist skills is to sponsor training—especially those who have a strong sense of the company and industry as a whole. Some companies, such as Carnival, are using online higher degree programs like Udacity and Massive Online Open Courses to help team members stay on top of tech developments AI, predictive analytics and data science. Others, like McAfee, have developed their own Analytic Center for Excellence, creating a culture of data and mentoring companywide. Point being: don’t make your employees go and invest in their own upskilling. Provide it for them, and the investment will pay off. Take it from Micron: half of their data scientists started in other roles within the company.
Making Data Scientist Skills Fun
If you want your employees to get onboard with learning data scientist skills, you need to make it fun. Carnival has implemented retreats. SessionM has established events regarding AI. McAfee has implemented tech talks. It doesn’t matter what you do, just get creative. Whether it’s a brown-bag lunch discussion or an after-hours cocktail party, think of ways to get the entire company talking about data science, not just the tech team.
Breaking Down Silos
One of the most essential parts of digital transformation is the breakdown of silos that hold information and data hostage. One of the strongest data scientist skills is the ability to have a holistic view of the company and a solid understanding of where and how their data can be manipulated into providing value. At Ogury, data scientists are encouraged to join new departments ever 12-18 months to keep their company prowess growing. Ogury’s understanding: data scientists aren’t there to save the company; they need to be trained and nurtured like everyone else. A global view of the company leads to stronger and more insightful algorithms, and bigger payoff overall.
Just like digital transformation requires a culture shift, so does a company’s move to data science. That means that employees across the board need to “drink the Kool-Aid” when it comes to the value of data and how it can serve the company. Research shows the willingness of employees to adopt data-driven mindsets is slow, however. What could help? All of the above opportunities for reskilling, socializing, and moving across silos will make a move to data smoother. But at the end of the day, employees simply need to see data science—regardless of developing data scientist skills or not—become part of the company’s fabric, the company’s communications, department goals, and most especially, they need to see it coming from their leadership, as well. Every person in the company needs to become an evangelist for the power of data science, and that’s something that can only happen through consistent, meaningful, and ongoing communication—and results!—over.
The importance of upskilling is never going away in digital transformation. There will always be technology advancements that grow faster than the number of people able to perform, understand, and manage them. These tips can be applied to any part of the digital transformation process to keep your company from falling behind. But I definitely recommend you start it now—with data science.
The original version of this article was first published on Future of Work.
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