As organizations become more data-driven, poor data literacy will become an inhibitor to growth. According to Gartner's Annual Chief Data Officer Survey, 2019 poor data literacy is ranked as the second-biggest internal roadblock to the success of becoming data-driven.
According to Gartner by 2023, data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs.
Gartner defines data literacy as 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.
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This all boils down to a simple question, “Do you speak data?
To be data literate you need to have the ability to derive meaning from data and communicate that meaning to others. Data literacy competencies include the knowledge and skills to read, analyze, interpret, visualize and communicate data as well as to understand the use of data in decision-making.
Data literacy also means having the knowledge and skills to be a good data steward, including the ability to assess the quality of data, protect and secure data, and take responsibility for its ethical use. The ethics part of this should be non-negotiable.
Another great question is: "how widely and deeply the staff needs to be trained in data literacy?" This is good question and has been raised by multiple customers. The answer is that you need to define and understand Minimum Viable Data Literacy.
Keep in mind that not all in your company willa be or needs to be top-level in all aspects of data literacy discussed above. Work with your HR and business people to define the "MVP" level of data literacy skills needed in the company, then build a supportive data literacy program and start executing!
As your business and company grow and matures in data utilization, your business needs for the "MVP" level also change. Monitor and change the threshold level of skills by evaluating it periodically.
How to get started with data literacy?
First, start by identifying the fluent and native data speakers as "thought leaders". They carry the data literacy torch for you and act as change agents.
Second, look for areas where communication barriers mean that data isn’t being utilized to its full business potential.
Third, try a data literacy proof-of-concept workshop in an area where language gaps exist. Have participants describe real-life common use cases as well as a use case specific to the organization.
Fourth, ensure that teams are speaking data in all meetings when discussing business outcomes and in other business situations - lead by example.
Finally, ask professionals like Data Product Business for further assistance and guidance to make your data track smooth and efficient.