5 steps to building a learning culture in your organization

Five Steps to Building a Learning Culture

1. Make Learning an Organizational Value

Learning cultures are built throughout the entire organization. The process starts with support at the executive level from CEOs. This PwC survey shows that 80% of CEOs are worried that the key skills their organizations require will not be available. This survey suggests that many executives rely on upskilling within their organizations rather than hiring outside from other industries and competitors. It also argues that executives must restructure performance evaluation to focus more on continuous feedback related to learning and acquired skills.

Amy Edmondson suggests that learning environments can be developed through what is called “psychological safety.” Employees must feel safe that they will not face negative consequences for taking risks that lead to high-quality learning outcomes.

2. Engage Middle Managers and Individual Contributors

Once leadership has made it known that learning is an organizational value, middle managers and individual contributors are in charge of implementing these strategies. Middle managers must work directly with their direct reports on a learning plan that fits their personal and team’s ambitions, and that are aligned with desired business outcomes.

It is very important that middle managers effectively communicate with their employees both on why learning is a top priority in the organization and how they can improve on their performance for this objective. In a panel DataCamp hosted earlier in the year with L&D leaders from Bloomberg and NatWest Group, Marcus Robertson, Global Curriculum Lead at NatWest pointed out that middle managers need to communicate with both direct reports and leadership, argued that teams can only deliver results if they develop their skills.

Moreover, people learn in unique ways. Some people prefer a more direct approach to feedback while others prefer indirect communication styles. Middle managers understand the people who directly report to them the best. They can use this information to effectively provide feedback on employees’ learning and development in their direct reports.

3. Make Learning Resources Accessible

Once the organization is built properly for encouraging and providing proper feedback for learning, it is important to develop high-quality resources for learning, specifically for analytics skills. As intelligent, data-driven organizations scale, they are developing learning resources for their employees to help them upskill and keep up with the changing demands for their roles.

For example, Airbnb created “The Data University” to provide over 30 data-skill-related classes to help their employees develop data awareness, data collection, and visualization skills, and to help them understand how to work with data at scale.

Another example is from Allianz Benelux, which leverages a combination of DataCamp courses and other learning resources to scale its own data analytics Academy.

4. Develop Personalized Learning Paths

Every employee in an organization has unique learning preferences and reasons for learning analytics skills. As resources are created to empower employees to learn new analytics skills, these unique goals need to be considered to make the learning journey more impactful. This article suggests that personalizing learning and development for employees can lead to better retention, better productivity, and better customer outcomes.

Within every data analytics, there are eight data personas found in every organization. These range from data consumers and leaders in more non-technical roles to data engineers with significantly more technical backgrounds and requirements. Tailoring learning paths to each of these personas is critical to generating valuable results from learning programs.

5. Experiment with Different Learning Modalities

Learning and development curriculum should be created with different approaches, including self-led and more traditional instructor-led training.

This approach, known as blended learning, allows organizations to reduce costs, vary learning styles to include methods like webinars and gamification, and significantly increase return on investment. An example of blended learning for data science comes from Sheil Naik from Bloomberg, who leverages a combination DataCamp and in-house live training code-along on Bloomberg data as part of an upskilling program on Python.

Building a Learning Culture Underpins Data Transformation

Upskilling is the only way for organizations to become data fluent. Creating a learning-driven culture within an organization is a high ROI opportunity that leads to better insights and business outcomes. Young employees expect this culture. It is also the only way to meet the high demand for data analytics skills in our digital, data-driven environment.