Amid the push for enterprise digital transformations, one challenge has the potential to significantly stifle progress: a talent shortage.
This challenge has only been exacerbated by the recent wave of workers exiting their roles as part of the “Great Resignation,” for which data teams have been no exception.
Even prior to this movement, some data positions have been more difficult to fill. Since 2016, the demand has surged for certain technical roles such as data scientists, which is considered to be among the top careers in the country today.
As a senior data strategy leader working to fill these employment gaps, you could dedicate an abundance of time and resources trying to compete with tech giants like Facebook or Google, but you may ask yourself, is this the best use of your time?
Many have shifted their focus to developing data talent within their own organizations and found that upskilling their current workforce is an effective way to grow their data team.
McKinsey & Company reported that data and analytics hold the largest talent gap throughout a variety of surveyed organizations. The same study stated that over 40% of companies say it’s an urgent priority to upskill these gaps.
As more organizations initiate data cultural transformations, more positions in data analytics will emerge. The World Economic Forum estimates that by 2030, over one billion employees will need reskilling to keep up with the wave of digital transformations.
Despite the desire and looming pressure to upskill internal talent, roles in data and analytics often require a specific knowledge and skill set. Here are tips for finding transferable skills within your company and encouraging internal mobility toward data.
Where should you begin?
There are a number of advantages to upskilling talent. Perhaps most obvious is that current employees already have general business knowledge. Still, not every employee will hold the skills or have the aptitude required to be successful in the data space.
Your future employees are those with strong analytical capabilities and, preferably, a knowledge of your company’s systems. Aside from the more technical skill sets, they should also express a general eagerness to learn and generate insights and a desire to advance their career.
It’s likely that there are employees who are already producing data work in a number of different departments within your company. While more obvious opportunities stem from IT, other potential employees may hold marketing or sales positions. These departments have experience analyzing dashboards and reporting, which would help them transition into more data-oriented tasks.
Certain positions will always be more difficult to fill — both with internal and external talent — particularly those in data science. Even so, some leaders have found success pulling employees into these roles, often with more straightforward responsibilities.
Waleed Kadous, Head of Engineering at artificial intelligence company Anyscale, is one of those leaders.
“It depends on the complexity of the tasks being undertaken, but in some cases, internal training of candidates who have [computer science] or statistics background is working well,” he told Datamotion.
How do you best support employees as they move into data roles?
Upskilling data talent will not only require a significant commitment from the employee but also from the company — strong talent requires strong training.
Before you begin to upskill employees, you should ensure that your organization has a strong training framework in place. Prior to moving individuals into more data-focused roles, determine the time, scale, and steps needed to set the employee up for success.
Several large companies have already made considerable investments to upskill their workforce. Notably, Airbnb developed its own Data University, Amazon launched a Machine Learning University, and UK-based Marks & Spencer created its retail M&S Data Academy to upskill over 1,000 employees.
These upskill initiatives are driving real results. A McKinsey & Company study found that 70% of enterprises that invested in upskilling reported positive business results that exceed the initial cost.
How do you internally market these roles?
To encourage internal mobility toward data, you’ll likely need to employ some marketing tactics. It’s important to drum up excitement for these opportunities without attracting the negative connotation of poaching talent.
In an effort to market data as a whole, remember to make your wins visible to the company. In part, this could be achieved through word of mouth, but it can be more helpful to regularly meet with executives to share updates on new projects or initiatives.
Some have even found success by launching mentorship programs targeted at employees who are interested in moving into data analytics.
CDO Magazine says, “There are quite a few benefits you can draw from this kind of initiative: Mentees appreciate the opportunities; they learn how your specific company wants to approach this kind of work; mentorships by nature tend to attract candidates with a passion for an interest in the field at hand.”
Where to find leaders who are upskilling effectively?
If you’re one of the many data strategy leaders working to fill gaps in their teams — you’re not alone.
From Airbnb to Amazon, enterprise data strategy leaders are finding creative ways to address this challenge and further implement data-driven cultures at their organizations. Sometimes the most effective way to address your own company’s roadblocks is to connect with industry leaders like yourself.
Senior data leaders use networking groups, peer-to-peer communities like the Data Board, conferences, and other resources to keep their ears to the ground in this ever-evolving industry.
