Image: VectorMine/Adobe Stock Company leaders that are looking to gain a competitive edge can do this by prioritizing data literacy for employees across departments and at all levels within their Continue Reading
Company leaders that are looking to gain a competitive edge can do this by prioritizing data literacy for employees across departments and at all levels within their organization. With data literacy skills, employees better understand how company data works and how they can use it, allowing them to be more effective and streamline processes for the organization. Read on to learn more about what data literacy is and how to implement data literacy initiatives within your business.
What is data literacy?
Data literacy refers to the ability to read, understand, communicate, analyze and derive information from data, all while putting it into proper context. Forbes defines data literacy as using “data effectively everywhere for business actions and outcomes.” Data literacy is often associated with data science, which uses analytical methods to extrapolate insights from data.
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Data literacy is usually thought of as an individual skill, but it’s also an organizational skill; widespread data literacy helps organizations achieve better business outcomes as they gather more value from their data.
With the growing importance of data literacy in organizations and the abundance of data, there is increased emphasis on establishing data literacy training programs and appointing chief data officers to continuously assess and improve data literacy in the organization.
Why is data literacy important for your business?
Data literacy skills are not only required by the analytics or the IT team; all departments and roles within an organization can benefit from data literacy skills. Data literacy enables employees to ask the right questions, gather the right data and connect the right data points to derive meaningful and actionable business insights. It also ensures that all employees understand how to manage and use data in ways that are ethical and compliant.
According to a recent Qlik data literacy survey of 6,000 employees, which included 1,200 executives, 85% of business leaders believe data literacy will be critical for business success in the future. The survey also highlighted that the majority of business leaders expect their teams to make a decision based on data.
Remarkable technological strides have been made in machine learning, artificial intelligence and big data. However, there is a lack of data-savvy professionals who have the skills to use data effectively. With appropriate data literacy training, organizations will have the in-house knowledge to optimize these emerging technologies for a variety of industrial and consumer use cases.
Data literacy is also important to the user and customer experience. It helps with faster decision-making, improved productivity and data-driven critical thinking. Employees can use data literacy skills to make their operational processes more efficient, grow sales performance, and make other improvements in their job duties and responsibilities. These improvements trickle down to customers who benefit from higher quality products.
Data literacy examples and use cases
The following data management frameworks and tasks work best when the entire organization is made up of data-literate staff:
Data literacy is useful in establishing and maintaining a reliable data ecosystem, which can include physical infrastructures such as cloud storage or service space and non-physical components, such as software and data sources.
Organizations use data governance to manage their data assets so that they are complete, accurate and secure. Data governance is not the sole responsibility of any particular team; the entire workforce must have the appropriate data literacy levels to contribute to its success.
Many organizations have a data policy that all employees must understand and adhere to. This includes how to access sensitive data, how to ensure data remains secure and other data processes.
Data wrangling is the process of converting raw data into a more structured and usable format. Data wrangling helps reduce errors in the data. An organization might have individuals or automated software for data wrangling, but every employee that works with any form of data also plays a role in keeping data in an acceptable format.
Creating a visual representation of data, such as a chart or graph, allows data professionals to more effectively communicate insights derived from data. Visualization can include infographics, tables, videos, charts, and maps. Both the creators of these visualizations and the stakeholders to whom they are presented need at least baseline levels of data literacy to understand the implications of the data in front of them.
Important data literacy skills
The most basic data literacy skills involve knowing the difference between different types of quantitative and qualitative data, including nominal, discrete, continuous and ordinal data. Being able to determine the source of data is also an important part of basic data literacy. Knowing the type of data and being able to assess its quality helps to minimize data fallacies and biases and maximizes data comprehension.
At a more advanced level of data literacy, individuals start to recognize the nuances and limitations of data. For example, a survey question framed in different ways can lead to extremely different answers and qualitative data results. Similarly, data visualizations can be misleading. Data literacy helps professionals to minimize misinterpretation of visual data, as data-literate individuals can identify trends, gaps, outliers and patterns in data.
Whether their general understanding of data is more basic or advanced, it’s most important for employees to understand data concepts that are relevant to their individual roles. For example, anyone working in digital marketing would benefit from understanding marketing data terms such as web traffic, page views, unique visitors and impressions.
For organizations to be truly data-driven, it should not just be the tech experts who become data literate; everyone in the workplace must develop data literacy skills to keep the business competitive and compliant.
Business intelligence experts and data scientists can coach their peers on becoming data literate. However, it has to be an organization-level commitment that covers all employees with data literacy training courses and other resources for support.
Businesses may not immediately see the value of providing data literacy education to all of their employees, but the long-term benefits are clear: Data-literate individuals are able to expertly question and analyze data logic, applying their data-driven knowledge to each business problem they’re asked to solve.