Enterprises are increasingly gravitating towards data analytics to reduce guesswork and intuition in their decision-making processes. Despite data’s growing presence and business value, organizations are still struggling when it comes to data literacy.
Gartner’s recent survey shows that poor data literacy is the second-biggest internal roadblock when determining the success of a Chief Data Officer’s role. The findings also highlight that by 2020, 50% of organizations will lack sufficient AI and data literacy skills to achieve business value.
If data literacy is a growing concern within your organization, here are some of the actions you should take.
What is Data Literacy?
Data literacy is an organization’s ability to read, write, analyze, and communicate data in context. It is a common language that people speak when sharing business information with one another.
Data literacy is a core component that drives a data-driven culture within an enterprise. Everyone must have at least a basic ability to communicate and interpret data conversations. If only a handful of people understands what’s being said through data, your data and analytics investments will offer limited business value.
When an enterprise becomes data literate, it’s easier to experiment with data, uncover opportunities for improvement, identify key insights, and improve overall business performance.
Establish Data Literacy Across Your Enterprise
Data literacy helps your enterprise teams continue to develop and hone their skills in judgment, comprehension, and problem-solving. Creating a data-literate enterprise may seem daunting, but once you begin with a step-by-step process, the only way to go is up.
Define Data Expectations and Build a Roadmap
To ensure the success of your data literacy initiatives, define data expectations and build an appropriate roadmap. Establishing a vision will clarify the level of data literacy required at different levels across various business units.
Leadership needs to collaborate with analysts to create a data literacy framework. The framework should include:
- The assessment of required skills.
- A unit to measure success based on predefined objectives.
- The extent of data to be used by different sectors—in context with their strategic goals.
Organizational leaders must identify and prioritize areas where data can produce maximum value and make optimum use of their data resources. Building a roadmap also includes determining available and necessary technological resources in various sectors and making data governance considerations.
Educate Anyone Involved with Data
Emphasizing data literacy as a part of your organization’s basic training module will save time and expenditure. Foster an environment where curiosity is rewarded and distinguish the best way for your teams to learn. Consider investing more in hands-on technical training from data analytics experts.
Establishing a shared vocabulary is equally important. For example, if analysts are working with advertisers to optimize the return on ad spend (ROAS) and one or both teams don’t understand a term, they will not get the best insights or outcomes. Data literacy programs should be tailored based on different applications and use cases.
Data literacy improves team productivity while providing a learning opportunity and the confidence to do better at work. HR and executives should construct personalized and efficient learning programs based on the department’s data skill requirements. Online modules are available at low cost, but you can also invest in an instructor-led training program for better assessment.
Make Things Easier
Once you set off for your data-driven endeavor, you need to simplify things progressively. Adopting frameworks and methodologies to set clear ownership and expertise will help team members know who to seek answers from. The more transparent and structured the data is, the easier it is to act upon.
A flexible data analytics tool will offer multitudes of features, such as comprehensive and personalized visuals, which will help recognize, test, and validate relevant data seamlessly. Business intelligence tools, such as Microsoft’s Power BI, let your teams develop or download interactive, custom visuals that help them literally visualize the data they need to comprehend and act upon.
BI tools come with data governance features, allowing you to balance data accessibility with data protection. Initially, only a select few people in your organization will have access to the full version of data. However, gradually democratizing data and providing more comprehensive access to your teams will allow them to uncover their own insights for decision-making.
Trace, Quantify, Repeat
Laying down a successful data literacy framework takes time and entails extensive experimentation. Every “failure” should be seen as a learning opportunity and used as a stepping stone for improvement.
Map data skills based on roles and responsibilities and determine where there are gaps. Continual evaluation of your data-literacy program will eventually lead you to robust analytics outcomes to drive long-term enterprise success.
Data literacy is more than just “understanding numbers.” The human side of data analytics will always be fundamental within the process since your data is only meaningful when people at your enterprise understand its meaning…and know how to use insights to their advantage.
Having a data literate enterprise team has become a competitive differentiator. Recognize data literacy as a valuable skill to develop and hone as you continue to foster your data-driven culture.