How Many Hours Per Week Should Data Professionals Really Dedicate to Learning?

Here’s how much time you should dedicate to learning new skills both at work and off-the-clock, according to experts.

If you are a data professional that thinks they have an excuse to avoid up skilling, consider the fact that while in office, for eight years, Former President Barack Obama dedicated an hour a day, seven days a week, to reading. In the tech world, Former Microsoft CEO Bill Gates took a week-long sabbatical each year to dedicate to reading.

With full-time tech employees putting in an average of 52 hours per week, it can feel redundant to add extra time and responsibility to a full workload. Working with the same tech stack can help you incrementally improve programming and engineering skills in programming languages like Python, SQL and cloud platforms like Google Cloud or Microsoft Azure, however, sticking to your organization’s tech stack has a side effect: Your professional growth and organizational growth stagnates.

Making Time to Learn

In the interest of full disclosure I’ll admit that the inspiration for this story comes from my lack of up skilling lately. I’m not overworked. I’ve just become comfortable. While I work on personal projects fairly frequently, including a data analysis project about finding the most expensive watches in the world, it’s been a little while since I’ve branched out beyond my organization’s tech stack to learn something completely new. When it comes to learning or ‘up skilling’, it’s important to ensure that such time is structured and deliberate.

Since I’m not a productivity guru, I’ll defer to the experts and documented research regarding the answer to my original question: How much time should data professionals spend learning new skills? Additionally: How much of the learning process is an employer’s responsibility?

Just 5 Hours Per Week

One potential approach is to apply the same logic college professors use when advising students how to study for their courses. Academic research suggests that students should study 2 to 3 hours per credit. Considering that the average course load is 18 credit hours, a college student that follows this guidance will spend 36 hours per week, nearly the equivalent of a full-time job, but one solely dedicated to learning.

For decades, productivity gurus have used Benjamin Franklin’s 5 hour per week method as a baseline metric for determining the amount of time one should dedicate to learning new skills per week. To be more precise, Franklin used the 5 hours per week timeframe for learning, reflecting and experimenting. If one applies Franklin’s method that’s a commitment of 260 hours per year. For comparison, the average number of hours organizations invested in actively up skilling employees from 2009 to 2019 was 33 hours per year.

The Twenty Percent Rule

Is 33 hours per year enough? According to the World Economic Forum, in order to close the widening skill gaps between rapidly advancing industries in the period from 2018–2022, workers will need the equivalent of 101 days of learning. This includes developing in-demand skills like programming, but also so-called softer skills like analytical thinking, leadership and social influence and emotional intelligence.

Since it may be unrealistic for data professionals to consistently dedicate several hours to structured, concentrated learning, the ideal scenario for up skilling is an employer-sponsored program. Organizations are increasingly partnering with massive open online course providers (MOOCs) like Coursera and Edx to provide employees with on-the-clock training for their roles. Additionally, organizations are sponsoring employees to pursue professional certificates like Google’s Data Engineering certifications and Microsoft Azure’s certificates. However, Google foregoes certifications and takes a different approach to learning. Google has pioneered what has become known in the productivity world as the 20 percent strategy.

The premise is that instead of instituting a formalized employee training program, Google empowers employees to spend at least 20% of their on-the-clock time to work on a passion project with the only prerequisite being that the work must be beneficial to the organization. By the nature of the assignment, when trying to achieve something new, employees were learning new skills. Both Google News and Adsense resulted from Google’s 20% initiative.

Remote Work: A Hidden Advantage

If you’re an in-person data scientist, data analyst or data engineer, you have a right to be skeptical regarding your ability to consistently carve out up to 5 hours per week for additional learning. However, if you’re 100 percent remote, like me, you have a hidden advantage: The lack of a commute. The average commute time in my state, Florida, is 25 minutes per day. Since commutes are round trips that’s 50 minutes per day. There’s no reason I can’t spend 50 minutes per day on up skilling. 50 minutes per day for 5 days a week is a little over 4 hours per week. It’s an hour under Ben Franklin’s recommendation, but it does correspond with another Franklin adage: Time is money — and every hour counts.

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