In a tough hiring market, providing data science corporate training may help you attract, hire, and retain talent to drive business success.
As the COO of a data talent start-up, I have a unique opportunity to work with dozens of data science and analytics organizations each year – and to meet with hundreds of top data executives. Through these conversations, we explore the most common “people problems” that data organizations have to overcome, and how team leaders are responding to today’s macro conditions.
Among the things we’ve discovered?
It has never felt more challenging to build a high-quality data team. In the past 18 months, hiring costs have skyrocketed for data analytics, data science, and data engineering professionals. Meanwhile, the great resignation and other covid after-effects have increased turnover, decreased engagement, and fractured organizational alignment.
In a tough hiring market, the best data organizations will be built from within. You obviously need employees trained in your policies, tools and techniques, but you also need them working well together. Institutional know-how is invaluable, and transparent, consistent data governance is critical.
So, how are executives tackling these problems? One way is by investing in more robust data training programs. Let's take a closer look.
5 Reasons Why Companies Invest in Data Science Corporate Training
1. Data training programs can help fill common vacancies faster.
In today’s market, it can take four months or more to hire an outside data analyst, much longer than most organizations can afford to wait. Training existing employees has the potential to help companies routinely fill open seats much sooner – and with talent that is more familiar with the organization’s unique data systems, policies, and business applications.
Once a data training foundation is in place, leaders can then build upon it with specialized tracks and sample cases, so their employees progress further up the sophistication curve.
2. Data training can improve retention rates and employee experience. A 2022 Forrester report found that 97% of employees who were highly satisfied with their organization’s “data training initiatives, data culture, and use of data in decision-making” said they were likely to stay with their employer for the next two years. (The same percentage reported high overall satisfaction with their organization, too.)
3. Data training can enhance an employer’s brand. One factor driving the Great Resignation is workers’ desire to find employers willing to invest in their professional development.
For example, Gallup found that 66% of workers in the 18-to-24 age bracket ranked “learning new skills” among the top three benefits they seek when considering a job, right behind health insurance and disability coverage.
And among the 57% of U.S. workers who want to update their professional skills, 48% “would consider switching jobs” if the move would provide them with the opportunity to grow their professional skills.
4. Training can close real and perceived data skills gaps. One of the most surprising findings in the 2022 Forrester report was the gap between how well decision-makers think they’re doing with data skills training and how well-trained employees themselves feel.
While 79% of managers said that their department was doing a good job of giving its people “the data skills they expect employees to have,” just 40% of employees agreed that they had the skills they need.
One data point that makes that disparity less surprising: Less than half (47%) of employees said their organization had offered them data training.
5. Training can contribute to a more data-driven company culture. Organizations that train current employees – or “upskill” them – can also derive another long-term-benefit: the creation of a savvy, data-focused culture that is primed to get the most value from its data.
Corporate Data Science Training Solutions: What to Look For
Notably, two of the top three obstacles to in-house data training cited by decision-makers in the Forrester survey were “lack of skilled staff to lead training” and the need for information and support to help them improve their employees’ data skills.
That’s a big reason why large employers are increasingly designing custom programs in partnership with companies like ours.
But what should you look for when selecting or evaluating a data science corporate training provider? Here are some things to consider:
- Reputation and track record: Competition among data training programs will likely heat up, but that doesn’t mean they’re equal in quality and deliverables. Ask industry peers for referrals and recommendations. Read case studies. Seek out recent reviews from employers and trainees alike.
- Quality of data instruction: A strong training program should blend both theory and real-world practice in ways that engage learners. Ideally, experienced instructors should also guide your trainees as they work with data directly related to your specific business or field – and as opposed to assigning bland, cookie-cutter content.
- Cohort-based vs. self-directed courses: Massive Online Open Courses (“MOOCs”) offer immediate scale and flexibility, but have notoriously poor engagement. Meanwhile, in-person programs are great for participation and retention, but difficult to grow beyond a single group or office. (We’ve found that live online, cohort-based programs capture the best of both worlds.)
- Ability and willingness to tailor curriculum to specific roles: Your hourly wage workers will need a different set of data skills than your mid-level managers. Your C-suite will have a different set of questions than your data engineers. A strong training program provider should be able to provide bespoke learning opportunities reflecting your company’s specific needs.
Finally, in a world where an employee’s tenure with even the most engaging company is more likely to be measured in years than decades, it can be helpful to work with a training provider who can also provide access to an external pool of skilled data talent that is routinely replenished.
For example, Correlation One offers Employer Partners custom enterprise training solutions as well as opportunities to interact with talent developed through our award-winning Data Science for All (DS4A) training. Additionally, our DS4A programs identify and develop talent from historically underrepresented backgrounds, providing forward-thinking businesses the opportunity to further diversify their workforces.
The Takeaway
With more companies seeking to provide data science corporate training to staff at every organizational level – and with more employees expecting employers to invest in professional development, it makes sense to explore training solutions.
And when seeking to outsource data science corporate training, it’s wise to seek out top-flight providers offering quality solutions.