Company leaders looking to gain a competitive advantage can do this by prioritizing data insights for employees across departments and at all levels of their organization. With data literacy skills, employees gain a better understanding of how a company’s data works and how they can use it, allowing them to be more efficient and streamline processes for the organization. . Read on to learn more about what data literacy is and how to implement data literacy initiatives in your business.
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What is data literacy?
Data literacy refers to the ability to read, understand, communicate, analyze, and derive information from data, all while putting it in the appropriate context. Forbes defines data literacy such as using “effective data everywhere for business actions and outcomes”. Data understanding is often associated with data science, which uses analytical methods to extrapolate insights from data.
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Data literacy is often thought of as a personal skill, but it is also an organizational skill; A broad understanding of data helps organizations achieve better business results as they derive more value from their data.
With the growing importance of data literacy in organizations and the abundance of data, it is increasingly important to establish data literacy training programs and appoint chief data officer to continuously evaluate and improve data insights within the organization.
Why is data literacy important to your business?
Data literacy skills are not only required by the analytics team 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, collect the right data, and connect the right data points for meaningful and useful business insights. It also ensures that all employees understand how to manage and use data in ethical and compliant ways.
According to a recent Qlik . data understanding survey Out of 6,000 employees, including 1,200 executives, 85% of business leaders believe data literacy will be critical to future business success. The survey also highlights that the majority of business leaders expect their teams to make data-driven decisions.
Significant technological strides have been made in machine learning, artificial intelligence, and big data. However, there is still a shortage of data-savvy professionals with the skills to use data effectively. With the right 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 critical to user and customer experience. It helps with faster decision making, improved productivity, and data-driven critical thinking. Employees can use data-savvy skills to make their operational processes more efficient, increase 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 an entire organization is made up of data-savvy staff:
Data Ecosystem
Data literacy is useful in establishing and maintaining a trusted data ecosystem, which may include physical infrastructure such as cloud storage or the service space and non-physical components, such as software and data sources.
Data Management
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 group; The entire workforce must have the right level of data literacy 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 it remains safe, and other data processes.
Conflicting data
Data wrapping is the process of converting raw data into a more structured and usable format. Wrapping data helps to reduce errors in the data. An organization may have individuals or automated software to process data, but every employee who works with any type of data plays a role in keeping the data in an acceptable format. receive.
Data visualization
Creating a visual representation of the data, such as a chart or graph, allows data professionals to more effectively communicate the insights derived from the data. Visuals can include infographics, tables, videos, charts, and maps. Both the creators of these visualizations and the stakeholders they are presented with need at least some level of understanding of the underlying data to make sense of the data in front of them.
Critical 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 identify data sources is also an important part of data basics. Knowing the type of data and being able to judge its quality helps to minimize data fallacies and biases and maximize data intelligibility.
At a more advanced level of data literacy, individuals begin to recognize the nuances and limits of data. For example, a survey question framed in different ways can lead to wildly different qualitative data outcomes and responses. Similarly, data visualization can be misleading. Data literacy helps professionals reduce visual data misinterpretation, as data-savvy individuals can identify trends, gaps, outliers, and patterns in the data.
Whether their general understanding of data is basic or advanced, it is of utmost importance that employees understand data concepts relevant to their individual roles. For example, anyone working in digital marketing would benefit from understanding marketing data terms like web traffic, page views, number of visitors and impressions. town.
Inference
For organizations to be truly data-driven, it’s not just tech experts who become data savvy; Everyone in the workplace must develop data-savvy skills to keep the business competitive and compliant.
Smart business data scientists and experts can coach their colleagues to become data savvy. However, it should be an organizational commitment that includes all employees taking data literacy trainings and other resources to 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-savvy individuals can can competently question and analyze data logic, applying their data-driven knowledge to each business the problem they claim to solve.
