Introducing New, Flexible Ways to Learn with Metis! Read Founder's Note

Managing Your Team's Professional Development by Implementing Skill Paths

By Douglas Noll • November 15, 2019

Many employees feel stuck in jobs where everything is just “status quo.” They might feel happy or content at times, but many also have a lingering feeling that there’s far more they could be doing to contribute to the company – if they only knew where to start. 

What could help bridge this gap between employee desire and company need? What skills are needed for these employees to make added contributions and grow in their roles? And how can they talk to management about obtaining these skills? 

Today, we’re going to explore some of the benefits of developing skill paths for your employees. In the data science world in particular, though the concept of learning new skills or programming tools (such as SQL or Python to analyze data) is pretty commonplace, many still lack the skills needed to excel in their current roles. Employees can greatly benefit from a skill path in place that drives performance, demonstrates company investment, and increases career satisfaction.

First, What is a Skill Path?

Skill paths help take the guesswork out of learning, as it’s often difficult to know where to start a learning journey. A skill path combines specific courses and tools into one unified experience with the goal of teaching a specific skill or skillset from start to finish. Typically, these paths are aligned to an employee’s knowledge level in order to help them develop the right skills in the right order.

Leading into my current role as Sales Director at Metis, I have to admit I was never clear on the types of transferable skills, certifications, or courses I needed to increase my skill set and be more competitive to prospective employers in the marketplace. Somewhere along the way, I worked for some great organizations that offered sales training and strategic selling workshops; these provided transferable and industry-accepted skills that have proven valuable in my professional journey.

Now that I’m working within the data science and analytics landscape, I see that many employees are running into similar situations, unsure where to turn to skill up. This represents a huge opportunity for employers, who have the ability to establish skill paths to help them learn, grow, and in turn, help the company reach established goals. 

How to Build an Effective Skill Path

Step 1: Understand Existing + Desired Skills

If you’re a manager or leader in charge of a team of data professionals, I recommend having a discussion with your team to ensure understanding of both the skills and technologies necessary for their jobs, as well as any additional skills they have a strong desire to learn. 

If you want a clearer picture of your team’s skills and interests before the discussion, you can start by sending out a short assessment to determine what types of tools and technologies your team knows well compared to what they might need additional training on. 

Step 2: Make the Personal Effort to Understand In-Demand Industry Skills

Employers should also play an active role in understanding the in-demand skills related to their teams’ areas of focus. How can they do that? Some examples include attending regular industry networking events or talks, or going to conferences, which, given the right audience, can provide great opportunities for peer-to-peer networking and thought leadership discussions. 

Be on the lookout for local or regionalized Meetup events as well. Here at Metis, we’re committed to both building and connecting with the data science community by offering events in cities throughout the U.S. We’re able to host speakers and others who can shed light on the types of skills, tools, and technologies that are in demand across industries, which can help you build solid skills paths for your employees.

Step 3: Start Mapping Out Paths

Once you’ve become more familiar with what’s out there, and after you’ve reviewed the assessments and discussed with your teams, you can start mapping out the skill paths, starting with skills or tools that are important to the job in the near future – perhaps the next 6 months. These might include learning data analysis and programming tools such as Excel, SAS, Tableau, SQL, R, or Python. 

Then, you can proceed to map out a path with the longer term in mind, which can include skills or topics of extreme interest to the employee, and also cutting-edge technology you think could help the employee’s development while also moving your company forward. For example, you could offer an optional course like machine learning for your data analysts. While not every analyst works with machine learning, the overall related tools and concepts are important for them to learn in order to get ahead in their field.

Most importantly, as you develop the skill paths, keep in mind that maintaining a healthy balance between necessary skills or courses, and topics of interest or passion to the employee, is vital to ensure the employee remains engaged throughout the learning journey.

Step 4: Create Learning Schedule

Once the path is created and agreed upon by manager and employee, sit down and map a learning schedule, which includes specific dates or realistic timeframes related to when each skill should be learned and mastered. Be realistic with the schedule, and map out a multi-year plan if necessary. 

Step 5: Regularly Check on Progress and Make Adjustments as Needed
This will show your employee that, not only do you have a vested interest in their professional development, you’re also interested in retaining them for years to come.


Learn more about Metis Corporate Training, which enables businesses to capitalize on the talent already working under their roofs through on-site training on topics like Data Literacy, Machine Learning, Data Engineering, and much more.

Similar Posts

business resource
Understanding the Business Cycle

By Tony Yiu • September 22, 2020

Despite this rollicking bull market, there is such a thing as the business cycle. And whether you’re a data practitioner or an MBA, it’s worth taking your time to understand what drives its ebbs and flows. Read Data Scientist Tony Yiu's latest post here.

business resource
Metis Sr. Data Scientist Javed Ahmed Featured in BuiltIn Article

By Metis • September 03, 2020

In a recent article published on BuiltIn, writer Stephen Gossett interviews Metis Sr. Data Scientist Javed Ahmed about the differences between Data Scientists and Data Engineers. Javed breaks down the two distinct roles, helping readers grasp the central difference: design vs. implementation.

business resource
VIDEO: 21st Century Lending with AI

By Metis • March 18, 2021

At the recent Ai4 Finance Summit, Metis Sr. Data Scientist Javed Ahmed spoke on a panel about 21st Century Lending with AI along with other industry leaders. Watch the recording here.