Build a Data Fluent Workforce: Challenges & Top Solutions

Ineffective communication between data stakeholders is the top barrier to data and analytics success. Modern businesses need to speak data; it’s the common language that people share when expressing concepts about data.

We live in a growing digital economy and data fluency is a necessary digital skill that everyone needs to thrive in a modern data-driven workplace culture. Employees across all levels of the organization must cultivate this skill to contribute to business outcomes and promote data proficiency. Yet only 32% of C-Suite is considered data literate - a main precursor to data fluency.

Ronald van Loon is an Infocepts partner and is applying his expertise as an industry analyst to examine the data fluency gap plaguing today’s organizations.

Limited data fluency can lead to stalled, unreliable business decision-making. But it’s becoming increasingly critical in today’s world as more companies rely on data to inform decisions.

Data Fluency vs Data Literacy

Data fluency is often used interchangeably with data literacy. These two skills are closely related but aren’t the same.

Data literacy refers to the basic ability to read, understand and communicate data. A data literate person can identify different types of data, comprehend rudimentary statistical concepts, and use data to support their arguments. It’s a foundational skill for anyone who wants to work with data, but it doesn’t necessarily require advanced statistical or technical knowledge.

Data fluency involves a deeper understanding of statistical concepts and tools, and the ability to work with complex data sets to identify trends, patterns and insights. It typically requires a richer level of technical knowledge and analytics skills, and is often associated with roles like data analysts, data scientists, and other data-focused professionals.?

Business teams can’t accurately interpret data results and apply them for intentional business applications, or communicate insights and findings to others in a clear and understandable way, without data fluency.

Top Data Fluency Skills & Challenges

To equip their workforce to work with data effectively and drive the organization’s success, some of the main skills that data and analytics executives should focus on collectively improving include:

• Data analysis skills: The ability to analyze and interpret data is a fundamental skill for data fluency, and includes data manipulation, data cleaning, data visualization, and statistical analysis.
• Data visualization skills: Visualizing data effectively is critical for communicating data insights to stakeholders. Data fluency requires skills in creating and interpreting visualizations, including the use of charts, graphs, and other visual formats.
• Programming skills: Many data analysis tasks require programming skills, particularly in languages like Python and R.?
• Data management skills: Efficient data management is critical for data fluency, including skills in data governance, data security, and data quality management.
• Business acumen: To apply data insights effectively, employees must have a deep understanding of the organization's business objectives and strategy. This requires business analysis, strategic thinking, and problem-solving skills.
• Communication skills: Effective communication is critical for data fluency and involves the ability to share complex data insights with stakeholders, work effectively in teams, and collaborate across functions.
• Continuous learning: Data fluency is a rapidly evolving field, and employees need to be committed to continuous learning to stay current with the latest tools and techniques.

However, building enterprise-wide data fluency and nurturing a data-driven culture is a complex process. Executives often encounter obstacles, such as lack of skilled personnel with the necessary technical and analytical skills. Demand for data talent is high, which can drive up costs, making this particularly difficult for smaller organizations without the resources to compete for top talent.?

Limited availability of training and resources for employees to develop their data fluency skills is another challenge. Without comprehensive training programs, many employees are left to develop skills on their own, leading to inconsistencies in skill level.?

Resistance to change can also be an issue; some employees are hesitant to learn new tools, techniques or work processes that incorporate data analysis. Additionally, lack of clarity on roles and responsibilities can cause uncertainty among employees as to what is expected of them or how they can contribute to the organization’s data fluency goals.?

Finally, limited access to data is another significant challenge; some employees may not have access to the data needed to develop their skills, or the tools and resources required to analyze the data effectively. This hinders their ability to learn and apply new data analysis techniques.

How to Build a Data Fluent Workforce

Overcoming these challenges requires a comprehensive, coordinated effort that involves leadership support, employee training and development, and a clear vision and strategy for building data fluency across the organization.

Define what data fluency means for your organization

Defining data fluency involves settling clear goals and expectations for what skills and knowledge employees need to develop to meet those objectives.

Assess current skills and identify gaps

After the unique data fluency goals have been established, your organization must evaluate the business-data-literacy of their employees who create and consume data, and identify the gaps that must be filled to align with those goals.?

Provide training and resources

Organizations must provide their workforce with training and resources to develop their data analysis skills. This might include classroom training, online courses, webinars, workshops, and other educational assets that enable employees to learn how to work with data effectively.

Encourage knowledge sharing?

Building a data fluent workforce requires a culture of knowledge sharing, where employees are encouraged to share their expertise and insights with others. This can be achieved through regular team meetings, brown bag sessions, and other forums that promote collaboration and idea sharing.

Foster a data-driven culture

To develop a data fluent workforce, businesses must foster a data driven culture where decisions are based on data insights. This encompasses setting clear data-driven goals, increasing data accessibility, establishing a culture of experimentation and learning, and recognizing and rewarding data-centric behaviors.??

Use data visualization tools

Data visualization tools can be a powerful way to help employees understand and communicate data insights. Organizations should invest in tools that simplify how personnel create and share visualizations that help explain complex data concepts.

Provide career growth opportunities

Cultivating a data fluent workforce requires a commitment to career growth and development. Companies should provide employees with opportunities to develop new skills and take on roles that leverage their data analysis expertise.

Building data fluency is complicated for even mature organizations. For example, a leading luxury travel retailer wanted to build a data fluent workforce that could comprehend data, use tools correctly, and transform information into trusted insights. Their goal was to better pinpoint buying behaviors, make sound pricing decisions, leverage promotional sales, and increase revenue.?

Despite investing in self-service tools and training, less than one-tenth of users embraced the data solutions and dependency on their IT team to create reports and ad-hoc data requests resulted in skyrocketing costs and employee frustration.?

The retailer engaged an experienced partner to identify the barrier to data fluency. Users from various departments were interviewed to uncover their primary challenges with tools and data, and interpreting insights. A structured training program was created with the help of the retailer’s data owners, data stewards and power users that incorporated metadata tools and documentation. Organized events and user communities, a data help desk, and a business glossary were made available via a collaboration portal to help employees empower themselves and collaborate.

As a result, the retailer experienced an increase in self-service adoption by four times in the first six months, the emergence of over 250 data champions, and the advancement of analytics usage from simple queries to advanced data science use cases.

Meaningful Data Strategies Include Data Fluency

Becoming a data-driven enterprise starts with acknowledging the advantage of new approaches and tools, and ongoing dedication to embrace the changes that enhance organizational performance.

Organizations must evaluate the unique barriers preventing their workforce from accessing, interpreting and trusting data and the tools used to support important decisions, and create a meaningful strategy to build and encourage data fluency.?

Check out Infocepts for more on building data fluency.