Data literacy: A how-to guide for leaders

The digital transformation of industries across the spectrum, from technology to logistics, is now allowing organizations to make smarter, more data-driven business decisions.

However, doing so requires an employee-base that can work with and communicate data in useful and actionable ways. In other words, you must invest in helping employees become data literate.

In this article, we’ll dive into what data literacy is and ways you can ensure all members of your organization can leverage data to make your business more efficient and data-driven.

What is data literacy?

Data literacy is the ability to create, manage, analyze, understand, and communicate data. Unlike technical literacy which requires the ability to operate a technical tool or technology, data literacy is broader and much more context-dependent on specific use cases and applications.

Because of this, data literacy can mean different things to different members of an organization. For instance, while a data scientist may have a more granular understanding of how data is procured and data models are trained, a line of business executive must still be data literate to have the means to understand and communicate the implications of data for the broader organization.

Why is data literacy important?

Data literacy empowers every employee to build and share knowledge and take smarter, more data-driven actions. However, this data-driven approach doesn’t mean that only managers and executives will be utilizing more data assets. In fact, 87% of surveyed business leaders say that their organizations will be more successful when their front-line workers have the data resources and technical capabilities to make important decisions in the moment. And yet even young people who are digital natives are not very confident in their data literacy, with just 43% of surveyed 16-21 year olds believing they are data literate.

This means that everyone from support staff to the C-Suite needs to understand how to work with data and make data-driven decisions. For this reason, the entire organization needs to be data literate regardless of their position.

How to create a data literacy framework in 5 steps

Start with leadership

Management and executives drive not only process but also culture. In order to create a data-driven organization, leaders from all departments must be proactive in fostering an environment that thinks and acts with a data-first approach.

In addition to buying into programs to teach employees how to be data literate, leaders themselves should communicate using data and let it inform and drive their own strategic decisions. Doing so will set the common language and best practices that other employees will follow.

Assess your organization’s current data literacy

To improve an organization’s overall data literacy, its leaders must first understand the current state of how employees are creating, using, and communicating data in all key business processes.

Data literacy efforts are often part of larger digital transformation initiatives. While these efforts typically focus on new systems and data sources, they must be paired with increasing everyone in the organization's ability to understand the insights those systems generate.

There’s also no one-size-fits-all approach to data literacy, thus leaders will need to analyze how each department is leveraging data. Some more technical departments may already be fluent in complex data topics, while others are still relying on manual and less data-driven approaches.

Create measurable goals

For large organizations, helping every employee at every level become sufficiently data literate will take time and is often an ongoing process. Therefore, it’s important to set specific goals, targets, and KPIs for understanding progress.

For example, for departments that use repeatable and well-documented business workflows, like an accounting department, a helpful metric might be the percentage of the workflows that are incorporating key data sets. Furthermore, you could even track how many of these departments are contributing data back to key datasets to encourage a community of shared inter-departmental knowledge.

In setting up these goals, it’s important to make sure that an organization leverages best practices to manage and centralize data. Otherwise, there’s a risk of data becoming fragmented between different departments with no one source of truth, which can lead to significant friction, redundancy, and uncertainty in performing data-driven tasks.

Develop a data literacy training plan

With the different learning styles in mind, leaders should develop a training plan that involves many different types of educational content — seminars, group classes, quizzes, online courses, games, and more.

Just like in other educational situations, it’s important to consider how different people learn. Are the employees visual, auditory, or reading and writing learners? Are they better in group classes or through independent exercises? What are their educational experiences or even language skills? Everyone is different, so data literacy training should allow all different types of learners to feel comfortable and gain these new skills in an environment that encourages them to do their best. This will ensure that different groups don’t get left behind simply because they don’t fit into a generic mold.

This also shouldn’t be a one-time process. Best practices in data analysis, statistics, and software change constantly, so training should be an ongoing part of the business to ensure that employees are up to date in their understanding of all these facets.

Reward learning

Rewarding or incentivizing employees to become data literate can help to encourage faster adoption. For some departments, it may even make sense to tie compensation to data-related goals and KPIs.

In doing so, employees will be much more open to learning and adopting new systems, and they will likely be more willing to work with their colleagues to ensure its success. This should reduce friction and pushback that you might see when trying to get employees to change how they’re operating.

Tips for improving data literacy skills in an organization

While the exact approach to building data literacy in an organization can vary, there are a number of tips that can apply to most businesses:

Educate employees on working with data

Employees need to trust the insights they gather from data. If data is messy or out-of-date, it provides much fewer actionable insights and can even lead to incorrect decision making. That’s why capabilities like Live Analytics, which ensure employees are always working with the freshest, most up-to-date data possible, are critical to building this trust.

Furthermore, they must know how to manipulate the data in a way that makes it usable for their given use case. While raw data is certainly important, it often needs to be processed into an accessible format for people of different technical backgrounds or domains, such as data visualizations like charts and graphs.

Utilize intuitive tools

Many organizations fall into the trap of trying to train employees to use complex tools to analyze data. However, most employees aren't software engineers or data scientists. For this reason, it's necessary to procure and build software that allows people of all technical backgrounds to access and analyze data. Platforms like ThoughtSpot give everyone quicker, easier access to the insights they need, making it the perfect tool for any data-driven organization.

These tools should be intuitive for all proficiency levels. Any tool used should also work directly with a cloud data platform to ensure data is up-to-date while minimizing fragmentation. Doing this ensures that employees in different departments have a shared view of data to make decisions, regardless of their technical skills.

Grow employee confidence

Many employees — particularly those with a less technical background — are usually nervous to start working with data. They may think that doing so requires programming experience or a deep understanding of complex mathematics and statistics.

By leveraging intuitive business intelligence, business leaders can assure their employees that they too can become data literate — even without deep technical proficiency. Simplifying tasks into easy-to-understand examples and giving employees hands-on experience will grow their confidence in working with data.

Separate data literacy from technical literacy

When helping employees of different technical backgrounds get more comfortable working and communicating with data, it can be useful to differentiate data literacy from technical literacy.

Unlike technical literacy, data literacy does not require the operation of specific technology tools. Rather, data literacy is a broader approach to understanding and using data regardless of whether it’s in the context of programming and data science or business analysis and communications.

Have a data leader guiding efforts

All leaders — from middle management to the C-Suite — should embrace data literacy. However, it can still be very valuable to have a specific individual or set of individuals in charge of educating employees, standardizing data processes and systems, and setting the general narrative for how data is communicated. In organizations with a Chief Data Officer or other data leader, it often makes sense for them to fill this role.

Doing so will ensure that there is consistency across the organization so that departments can easily communicate and work together with a common language and process. This will maximize efficiency and reduce confusion caused by otherwise inconsistent standards.

Reduce employee resistance

As with all changes, some employees will be resistant to learning and implementing new processes. In addition to rewards and incentivization, it is often worthwhile to communicate to employees why the changes are being made, what’s in it for them, and how they can voice their feedback and concerns.

In reality, no company will be the same in how it speaks about data and what its common processes look like, so creating an ongoing conversation about how to best utilize data for the good of the broader company and for their specific role can ensure that the processes make sense and employees feel like they are heard.

Bring analytics to existing workflows

Asking employees to leave existing workflows and patterns causes friction, because it disrupts how they've gotten used to operating. Instead, consider ways to bring data to their current workflows by embedding analytics right into existing tools and software. This encourages employees to use data without alienating them with too much change.

Plan for data-driven decision-making

Once processes are in place and employees have an understanding of how to view and analyze data, it should become standard practice that these systems are utilized to make smarter, data-driven decisions. This will require employees to really understand and trust the data and the systems around the data. It also requires connecting systems together so that employees can use data insights to fuel actions in other applications. Over time as leaders and others throughout the organization start to make this the norm, the culture should become more data-driven.

Emphasize constant learning

Building data literacy is an ongoing and iterative process. Leaders should embrace new technologies and ensure all employees are kept up to date on how to use them and communicate their results. This will ensure that the business does not fall behind and can leverage the latest and greatest technologies to make it more efficient.

Grow data literacy with better analysis

Becoming a data-driven organization requires that all employees are data literate. However, doing so requires leveraging intuitive technologies that allow employees of all technical backgrounds to easily engage with data.

ThoughtSpot provides a powerful Live Analytics platform that empowers everyone to create personalized, actionable insights at the point of impact, from all of your cloud data. Through a variety of features, you can easily connect to your cloud data, automate worksheet model creation, search for new insights, utilize AI-driven analysis, and create meaningful visualizations with Liveboards. Try a free trial of ThoughtSpot to see how you can help make your business more data literate.