How to Ensure your Data Team’s Skills Remain Up-to-date

When it comes to data analysis, if you’re not moving forwards, you’re moving backwards. Data science tech, trends and tools are constantly evolving, and best practices can become outdated in the blink of an eye.

Data team

The good news is that data scientists are generally curious and eager to keep making new discoveries. They chose to enter a profession that is a center of innovation and change, and they’ll embrace opportunities to keep on pushing the cutting edge of data science a little further forward.

However, it’s easy for a busy data team to get so involved in one project after another that they lose the habit of reading up around their area. The daily grind of work tasks can pull you away from exploring, innovating, and learning new skills and approaches.

Additionally, according to research from Clutch, only 23% of employees agree that they are the ones most responsible for their own continuing professional development, while 66% place responsibility on their leadership team or supervisor. This only highlights the wisdom of setting up policies that encourage your data team to keep their skills and processes up to date.

Understand the lay of the land

It’s impossible to create an effective plan for continuing professional development within your business unless you know the extent to which your employees are succeeding or falling short.

The best approach is to conduct a regular skills gap analysis, on both a team and an individual level, to identify current and emerging skills gaps and spot the areas where continuing professional development needs to be shored up.

Your skills gap analysis can include examining team and individual employee KPIs; running surveys and/or interviews with employees; reviewing individual and team performance reports; and/or carrying out a 360° feedback process for each employee.

Foster a culture of continuous professional education

One of the most valuable things you can do is to create a corporate culture that values continuous development throughout the company. This involves concrete steps for rewarding employees for self-directed study like covering costs (all or partial) for pursing a masters (or other advanced degree) in data science or completing external or internal training courses, and a management layer that sets an example of ongoing learning and knowledge-sharing.

You want your employees to learn from and teach each other, so you need to make it clear that prestige belongs to those who share and help others, rather than those who silo their achievements. It’s vital to cultivate an atmosphere of team improvement that encourages employees to share their knowledge, rather than one of internal rivalry and competition, which sees colleagues jealously hoarding their knowledge in order to get ahead of each other.

This also requires your management to create a safe space for admitting mistakes without censure or penalty, often leading the way by admitting to their own previous failures.

Data scientist training program

Create time for professional advancement

With data arriving all the time and increasing calls for data support from different departments within the business, your data team is perennially busy. If you expect them to increase their workload with continuing education, you’ll need to help them to make time for it. It’s no real surprise that 70% of employees say that they prefer retraining that takes place during the work day, according to the same Clutch survey.

This could involve paying for training courses; supporting regular time off for career development and study; reducing your data team’s workload at intervals so that they can learn new approaches; or extending quiet periods between projects for data scientists and analysts to refresh their skills and knowledge. If you use a good online course platform to set up in-house training modules, your analytics team will be able to engage with educational modules asynchronously, whenever fits their schedules best.

Conferences and seminars are excellent occasions for data teams to discover innovative practices and the latest processes within their field, while also swapping trends and ideas with their peers in different industries and verticals. Encourage your employees to participate in these events. With so many now taking place online because of the pandemic, it’s easier and less expensive than ever for your workforce to take part, so seize the opportunity.

Provide the necessary resources

You expect your data team to maintain their skills and best practices, but it’s only fair to help them along by providing access to the right resources. New graduates in particular often come with a great deal of enthusiasm and technical know-how, but aren’t sure where to look to learn more about specific data science fields, soft analysis skills, or how to maintain their abilities independently.

Support your data team to keep up their knowledge by directing them to specific programs or publications that provide high-quality material and information. Your employees will be more motivated to act on your recommendations because they’ll feel that you’re involved in their progress and have their best interests at heart.

You may wish to partner with third parties like local community colleges, universities, or technical training centers to create external courses and seminars that match your business needs and fill skills gaps that you’ve identified in your workforce.

Staff training and development

Assisting your data team to maintain its edge isn’t rocket science

With the foundation of curiosity and a strong desire for professional development already laid within most employees, you’ll find that ensuring your data team keeps its skills and processes up to date shouldn’t be too difficult.

Carrying out regular assessments of the skills gap in your business, fostering a culture of ongoing education, and proving the time, support, and resources for continuous professional development are the building blocks to create a data team that is always at the cutting edge of best practices and industry trends.


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