Data Literacy Skills Every Organization Should Build

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Since we live in a data-driven world, companies with the appropriate talent to derive insights from business data do far better than their competitors. In today’s competitive global business landscape, modern businesses must treat their prime asset – data and data literacy skills – as a top priority to thrive and prosper in the global business landscape.  

In an ideal business world, all employees would possess data literacy and analytics skills to uncover insights, trends, and patterns that are relevant for solving business problems. However, to reach that ideal state, the business leaders and operators should first be familiar with current employee skills related to creating, using, and communicating data across all critical business processes.

Recently, Gartner’s Survey of CDOs reported that poor data literacy is the greatest hurdle to building a data-driven organization – despite Gartner having stated in 2019 that “by 2020, 80% of organizations will initiate deliberate competency development in the field of data literacy.”

Accenture’s survey of about 190 U.S.-based executives revealed that American firms are still struggling to take advantage of their data assets due to “cultural and operational challenges that extend beyond just technology.” Another Accenture research report states that while 75% of organizational employees have access to data tools, only 21%  demonstrated confidence in their data skills. This research report is a grim admission of the actual state of data literacy in global organizations.

Gartner defines data literacy as the “ability to read, write, and communicate data in context.” While “technical literacy” indicates the ability to comprehend and use a particular technology or tool, data literacy hints at the ability to understand, use, and communicate in terms of data in specific use cases and applications.

The biggest challenge facing organizations looking to embrace data analytics power is getting employees across all departments trained and ready to use business intelligence in their day-to-day work. To meet that challenge and emphasize the importance of data literacy in the organization, business leaders can begin by explaining decisions made in their day-to-day business environment through the use of data. 

Here are several data literacy skills that management teams can emphasize throughout any organization to help employees become data-literate: 

  • Engage teams to contribute to crafting strategies, messaging, and approaches for assessing data literacy skills gaps across your organization, conducting data literacy pilot tests, and measuring and communicating results. 
  • Develop an enterprise-wide data-driven culture. It’s widely known that about 65% of data science efforts face resistance, simply because average business staff neither have the ability nor the willingness to embrace data-driven insights beyond their comprehension. So, it’s not enough to be data-literate. The newly inducted data-literate employees must be able to demonstrate that they can read, use, visualize, and interpret data in order to make data-driven decisions. Without that data-driven decision-making culture, no matter how literate your employees are about data, unless you enable them, they cannot really make decisions and act on that literacy.
  • Encourage employees with advanced data skills to apply techniques to extract meaning from data and communicate what they discover to other employees in simple business language, so an average business staff gets a chance to learn how data-driven results correlate to business insights.
  • Mix and match teams of data analysts, data-literate employees, and novices for data-enabled problem-solving. The employees with advanced data knowledge can groom and lead the novices to learn data literacy and then immediately apply their learning in problem-solving and in business communications.  
  • Employees must be provided with dedicated time and data resources to nurture their data literacy skills, especially if they are new to data analytics. In this respect, the employees may be categorized as “novices,” “data trainees,” “data literates,” or even “data analysts.” The data resources have to be mapped and distributed according to the current skill levels and expertise of specific employee categories. 
  • On-premise seminars or workshops may be set up for employees to collaboratively participate in and contribute to, engaging in data-enabled problem-solving. These live sessions can also serve as recorded testing sessions for corporate skill-development teams to measure and evaluate the effectiveness of the sessions, as well as the data literacy scores of individual participants.
  • Employees need to be encouraged to leverage data both independently and collaboratively to inform their roles and responsibilities within an organization. The best form of skill development can come from day-to-day work situations.
  • Employees can participate in cross-departmental data literacy programs to gain first-hand knowledge of how data is being used across the organization. Exploration with enterprise-wide data in use will not only broaden the creative horizons of ordinary business employees, but also provide the program evaluators a chance to discover hidden and unknown talents in employees that surface during these programs. In a similar way, cross-departmental education programs can help non-technical teams to develop a holistic view of how data is being used across their business.
  • Custom Learning & Development (L&D) tracks can be set up for individuals after assessing their current data literacy skills. The L&D courseware should contain examples from actual data problems faced by departments, so that the learner gets first-hand experience of applying data literacy skills to everyday business issues.

As the technical proficiency of dealing with data is usually connected to an employee’s roles and responsibilities within an organization, the data literacy assessment tests will have to be adapted and tailored to meet the varying data competency needs and requirements of departments or work roles. 

As employees become more adept at data processing, assign more responsibilities or have them supply data to support their ideas or plans. You can monitor employees’ data comprehension, how they use data, and how they interpret results using qualifications for all employees. Perhaps the biggest reward of enterprise-wide data literacy is more divergent views to mitigate the risk of algorithmic bias that still echoes human bias in decision-making.  

Data literacy is one piece of the bigger picture that includes the overall data maturity of an organization. The end goal of a data-driven business is to make data easily accessible across your organization, and drive decision-making through data. Data is the new language of business, and every organization needs to be fluent in its use in order to drive results.

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