How to improve data literacy: 5 best practices

Democratizing data helps empower everyone to make informed decisions. Consider these strategies to foster data literacy across the organization
194 readers like this.
how to run a virtual conference

Astrophysicist Neil deGrasse Tyson once said, “Science literacy is the artery through which the solutions to tomorrow’s problems flow.”

The same can be said for data literacy. It unlocks the answers to business problems and holds the key to business success. But despite the fact that data literacy is now a required skill at many organizations, a data literacy survey by Accenture found that only 21 percent of 9,000 employees were confident in their data literacy skills.

Data literacy involves the ability to read and analyze data and find meaning and patterns in the information, statistics, and charts. It also includes molding and cleaning data to make it easier to process. And perhaps most importantly, it means understanding how to articulate and share what the data shows, enabling people to act upon it with confidence and make better decisions.

Companies are responsible for ensuring not only that their employees gain data literacy, but also that they have access to both data and the necessary tools. Democratizing data helps empower everyone to make informed decisions.

[ Want more digital literacy strategies? Read Digital literacy training: What you need to know. ]

Empowering those on the edge

Edge computing brings computing power closer to the source of data. Data-driven companies recognize the value of this model and are empowering their employees who work “on the edge” by enabling them to access and share critical data. From sales associates to delivery and repair workers, workers on the edge are leveraging data to do their jobs better.

Leveraging data literacy not only helps employees do their jobs better, but it also enables them to gather and share valuable data – which in turn boosts the company’s data wealth and improves the user experience. 

Consider the following examples:

  • Appliance repair technicians can access data on inventory or parts and determine the fastest and most economical delivery of needed components.
  • A retail sales associate can maintain and upload data on a specific customer’s buying preferences to make better recommendations and personalized service.
  • Restaurant servers can leverage data analytics on popular dishes to make more informed recommendations to customers or to quickly identify ingredients. 

There’s a clear give and take to how data is consumed and shared in a data-driven organization – the challenge is in fostering greater data literacy enterprise-wide.

[ How can automation free up more staff time for innovation? Get the free eBook: Managing IT with Automation. ] 

5 data literacy best practices 

Here are five best practices to help leaders and companies do this:

1. Make a top-down commitment

Data analytics has not always been the domain of the C suite, and CEOs have historically turned to analysts to translate data trends. But if senior-level staff become data literate, they can help instill a data-driven culture across the company.

2. Offer both hard- and soft-skills training

 All employees should be offered the opportunity to learn data analytics, including hard skills such as statistics, retrieving data, and reporting or navigating technology as well as soft skills such as communicating with customers, understanding data patterns and using them to solve problems, and more.

3. Reward employees

Frontline workers who leverage their data literacy skills to boost the customer experience, help co-workers, or contribute to company growth through data analytics should be rewarded for their efforts through public recognition, bonuses, gifts, paid time off, and other incentives.

4. Encourage collaboration with IT

Data analytics may no longer be confined to the IT department or data scientists, but they still play a crucial role. It’s important that all workers share what they want to achieve from the data with IT and enable data science teams to optimize the data, cleaning and structuring it as needed.

5. Create a Center of Excellence

Enterprises that take data analytics seriously often create centers of excellence, comprised of power users and data-driven people. This strategy goes a long way toward evangelizing the rest of the company.

Data in all forms is increasingly the lifeblood of successful organizations, informing their every move and strategic business decision. To make the most of this powerful resource, every employee, regardless of their role, must become data literate: able to read data, communicate the message it reveals, and act upon it for a successful business outcome.

[ Get exercises and approaches that make disparate teams stronger. Read the digital transformation ebook: Transformation Takes Practice. ]

Carlos M. Meléndez is the COO and Co-Founder of Wovenware, a Puerto Rico-based design-driven company that delivers customized AI and other digital transformation solutions that create measurable value for customers across the U.S.