How do you develop data literacy and skills across your organization?

1 Assess your current data maturity

The first step to developing data literacy and skills is to understand where your organization stands in terms of data maturity. Data maturity is the degree to which your organization can collect, manage, analyze, and use data to achieve its goals. You can use a data maturity model or framework to assess your current capabilities, gaps, and opportunities for improvement. For example, you can use the Data Culture Index, a tool developed by the European Data Portal, to measure your data culture across four dimensions: data skills, data sharing, data availability, and data impact.

2 Define your data vision and strategy

The next step is to define your data vision and strategy, which should align with your overall organizational vision and strategy. Your data vision should articulate the value and purpose of data for your organization, and your data strategy should outline the objectives, actions, and resources needed to achieve your data vision. You should also define your data governance model, which should specify the roles, responsibilities, policies, and standards for data quality, security, privacy, and ethics. Your data vision and strategy should be communicated and endorsed by your senior leadership and stakeholders, and reviewed and updated regularly.

3 Develop your data skills and competencies

The third step is to develop your data skills and competencies, which are the abilities and knowledge required to use data effectively. Data skills and competencies can be classified into three levels: data literacy, data proficiency, and data expertise. Data literacy is the basic level of understanding and using data, such as finding, interpreting, and communicating data. Data proficiency is the intermediate level of applying and analyzing data, such as cleaning, transforming, and visualizing data. Data expertise is the advanced level of creating and innovating with data, such as modeling, mining, and machine learning. You should assess the data skills and competencies of your employees, and provide them with appropriate training, coaching, and mentoring opportunities to enhance their data capabilities.

4 Create your data culture and environment

The fourth step is to create your data culture and environment, which are the attitudes and behaviors that support and encourage the use of data in your organization. Data culture and environment can be influenced by several factors, such as leadership, values, incentives, collaboration, and infrastructure. You should foster a data culture that promotes data curiosity, data confidence, data ethics, and data accountability. You should also create a data environment that enables data access, data quality, data security, and data innovation. You can use various tools and platforms, such as data portals, data dashboards, data catalogs, and data labs, to facilitate data discovery, sharing, and collaboration.

5 Monitor and evaluate your data performance and impact

The fifth step is to monitor and evaluate your data performance and impact, which are the outcomes and benefits of using data in your organization. Data performance and impact can be measured by various indicators, such as data quality, data usage, data satisfaction, data value, and data influence. You should establish a data performance and impact framework, which should define the objectives, metrics, and methods for assessing your data results and achievements. You should also collect and analyze feedback and data stories from your employees, customers, and partners, and use them to improve your data processes and practices.

6 Celebrate and share your data successes and learnings

The sixth and final step is to celebrate and share your data successes and learnings, which are the recognition and dissemination of your data accomplishments and insights. Celebrating and sharing your data successes and learnings can help you to motivate and inspire your employees, showcase and promote your data value, and learn and grow from your data experiences. You can use various channels and formats, such as newsletters, blogs, podcasts, webinars, and events, to celebrate and share your data successes and learnings with your internal and external audiences.