What Your Organization Needs to be Data Literate

To run a successful organization, it’s always been critical to foster a culture based on key tenets like collaboration, transparency and accountability. For the modern data-driven organization, add the principle of data literacy to that list. 

Simply put, data is the lifeblood of business. For an organization to operate at peak performance, all employees—not just those in data-centric roles—must understand how to access data, talk about it in a business context and apply it to make the best decisions possible.

What is Data Literacy?

Data literacy, as described by Gartner, is “the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied, and the ability to describe the use case, application and resulting value.”

Think of it like this: the more members of your organization that can think and speak fluently about data, the easier it becomes to establish data-integrated workflows across every aspect of your organization. And with better workflows comes better decision making from top to bottom. 

From the late 1980s through the early 2000s, general computer literacy—like the ability to navigate operating systems and use tools like email and word processors—expanded rapidly from a small, specialized subset of the population to nearly everyone. Some analysts believe that data literacy is on the cusp of a similar transition as more and more people understand how to find, evaluate and use data to create actionable insights.

Everyone has unconscious biases that can stand in the way of data-driven decision making. When we’ve done something one way for years, we come to feel a certain mastery for the process, and in doing so, limit our innovative capacity. Data literacy demands that we look beyond our preconceived frameworks for thinking—no matter how successful they may seem—and confirm that our decisions are supported by data. 

But cultivating a data literate culture involves creating a data management platform that allows for both the governance and democratization of data for all employees. It requires skills assessment and training to drive home a basic understanding of advanced data concepts and the ways in which data flows through the organization. Lastly, it relies on a leadership style that reinforces this shift in mindset to overcome any barriers to putting the data into action. 

Democratizing Data Access

To establish a culture that properly values data, you’ll first need to make that data as accessible as possible. This requires a data architecture such as a data fabric that can facilitate the storage and retrieval of data across your organization, regardless of where it resides. A data fabric should also help organize relevant information for specific or department needs in a curated, clear manner. This can be accomplished by standardizing the data terminology being used across all business units, fostering an understanding of data lineage and implementing role-based dashboards.

For example, my team at IBM implemented a unified data platform that provides governed data and allows users to load, transform and analyze data. Since its launch, the platform has improved business outcomes for the Global Chief Data Office at IBM. In about 18 months, our office generated $1.3 billion in business benefits and a 10x ROI from data and AI-based transformation initiatives by creating a data platform that not only operated at-scale, but also helped us develop and test new AI models faster, while also performing AI analytics and migrating data to the public cloud at faster speeds. 

Beyond just making data more accessible, a good data fabric solution will incorporate tools that assess relevant data-access rights, licensing and sharing, and will maintain data privacy, security, and compliance measures. 

Training for Data Literacy

With a data architecture that enables access to the right data, at the right time, to the right people, you can then begin to train employees on how to properly use it. 

Before delving into functional training, people should begin with an understanding of the kinds of insights that can be derived from data. In a data literate organization, we must see ourselves not as owners, but as stewards of data: seeking to promote its use, break down silos and grant access to business functions that benefit. 

To garner actionable insights, employees should understand the concepts of descriptive, prescriptive, predictive, artificially intelligent, and other forms of data modeling. Of course, not everyone in the organization needs to be able to perform regression and modeling of data sets—but it’s helpful if they appreciate what these complex procedures are and the insights they unlock. 

There are many approaches to educating employees on how to use and analyze data, but the best methods will demonstrate a clear link between the data and business outcomes of a data user’s daily activities. Instead of imparting a heap of knowledge on what’s possible, outline how your organization’s data tools can be used to accomplish each team’s unique goals. Teach just the data visualization and storytelling techniques best suited to the stakeholders’ day-to-day business objectives and implement an effective communication plan which enables the training curriculum.

While role-specific education is important, it’s also beneficial to instill a basic understanding of the enterprise’s data architecture so that individuals can more fully appreciate the way data flows through the organization. 

Finally, make sure the training is continuous: to maximize adoption, it’s key to track and evaluate how the organization is evolving, and support your efforts with dashboards that define metrics and KPIs that meaningfully capture progress. 

Focus Leadership to Reinforce Literacy

To sustain a culture of data literacy, it’s important to find champions of the approach within your organization and harness their influence. Elevate their example as a model for others in their position, and reward collective efforts that produce results.

As your data-driven organization evolves, employees will be fueled by a natural curiosity to ask “why” and expect answers backed by data. Therefore, it’s critical to provide the opportunity to share feedback: open a path to dialogue at all levels of the organization to provide all employees with information that will enable them to collaborate on solving problems and amplify the value that data can deliver.  

Further, it’s important to close gaps in your workforce by recruiting new hires with technical certifications or P-tech program degrees who are curious and have a quantitative mindset.

Instilling data literacy at all levels of your organization is an ongoing endeavor that gives your organization a competitive advantage. By continuing to reinforce this approach, you will create a collaborative, open, iterative and experimental culture where it is okay to test things, fail fast and pivot based on data-driven decisions. 

About the Author

Inderpal Bhandari is the Global Chief Data Officer at IBM. He has leveraged his extensive experience to lead the company’s data strategy to ensure that IBM remains the number one AI and hybrid cloud provider for the enterprise. Under his leadership, the Cognitive Enterprise Blueprint — a roadmap for IBM’s clients on their transformation journeys — was created.

Bhandari is an expert in transforming data into business value and improved customer experiences by delivering strategic, innovative capabilities that use analytic insights to enable growth and productivity. In 2017, he was named U.S. Chief Data Officer of the Year by the CDO Club, and he has been featured as an industry expert by The Wall Street Journal, The Washington Post, US News & World Report, CNN, and FOX.

Bhandari earned his Master of Science degree in electrical and computer engineering from the University of Massachusetts and holds a Ph.D. in electrical and computer engineering from Carnegie Mellon University.