12 tips for developing data mastery in 2022

The digitization of our workplace is driving the automation of more and more tasks, resulting in another shift in the way we value human contributions. A business strategy, process, and way of interacting with customers requires fewer workers to produce work and more workers to exercise judgment and make decisions.

Still, workers must learn to use data to make better decisions faster if they are to be successful. Data is proliferating faster than ever, and we have more of it than ever.

From top to bottom, data literacy is becoming an essential skill as businesses evolve into data-driven decision-making and operating models. We need to equip frontline workers with the skills to make informed decisions, even and maybe especially.

Employee data literacy should not be confused with technical literacy, and it does not include the high-level skills required by a data scientist.

Instead, it is:

  • Read, analyze and work with data
  • Use data to tell a story, argue and persuade
  • Decisions made based on data insights aligned with business goals
  • Improve efficiency, personalize and resolve data issues

What is data literacy?

Reading, analyzing and communicating data is part of data literacy. Numeracy is more than just being able to work with numbers. It is also about knowing:

  • Methods and sources of data evaluation
  • What can be done with a given dataset?
  • Understanding the data is important

12 tips for building data literacy

  1. Assess employee skills from the start

    Understanding existing skills and agreeing on the skill level for different types of jobs is the first step in developing data literacy. Subsequently, companies can develop development plans.

  1. Democratize your data

    In technology, democratization is a constant trend. With the advent of new tools, once complex and specialized fields will become more accessible.

    The value of separating data from silos is now recognized by companies. As a result, they use tools like Power BI to centralize their data, making it easily accessible and increasing the number of apps they can use. Having a single source of truth also helps them achieve this. Everyone has access to the latest information and the most current view without fragmented opinions or inconsistencies clouding the waters.

  1. Use the right tools

    Like technology, data has a steep learning curve. In addition, less qualified employees would be attracted to sophisticated Big Data tools.

    Provide easy-to-understand tools for your organization. Data analysis and interpretation is made easy with the right tool. Use everyday tools that your employees are familiar with instead of creating a new tool. It will be easier for employees to learn about data and generate information when they have easy access to data processing tools.

  1. Perform evaluations

    Conducting an assessment is the first step, before you even begin training and developing data manipulation tools.

    You can use ratings to determine what needs improvement. Additionally, you can measure existing levels of data literacy before implementing new programs.

    Plus, the assessment lets you know where the gaps exist, how much training is needed, and what tools and resources you need to put in place to help your team communicate better.

  1. Set a good example

    63% of companies think mastery of data is important. Many companies do not sufficiently support data literacy. Data literacy is not seen as important to the success of an economy by most decision makers. When management lacks confidence in data literacy programs, employees automatically perceive them that way as well.

  1. Show your support

    By encouraging employees to use their data manipulation skills, you can help them build confidence and believe in themselves. As they gain experience in dealing with data, give them more responsibility or ask them to provide data for their ideas or plans.

  1. Have a goal in mind

    Success is built on goals. Leadership is impossible without goals. Consider mapping data literacy for different levels of the organization in your data literacy program.

    Depending on your role, you will need different data literacy programs. A higher level of management may require a different set of data skills than those at a lower level. By setting goals, you can allocate resources and efforts more efficiently.

  1. Offer incentives

    Most likely, you will find data analysis and interpretation boring until you get used to it. Offer incentives or rewards to motivate employees to improve their data literacy skills.

    Prizes, team building events, or conference attendance may be offered to improve their data literacy skills. Employees will be motivated to achieve the desired level of success and expertise.

  1. Develop a skills database

    Do you want your employees to reach a certain skill level? At some point, employees should be able to perform certain tasks with data. Skills include recognizing data, asking the right questions, understanding the logic behind data, and communicating effectively.

    Therefore, define qualifications for all employees. You can track employees’ understanding of data, how they use the data, and how they interpret the results using these skill levels. To master data, employees must achieve a certain milestone or score.

  1. Decentralize data access

    Many organizations make the mistake of trying to improve data control but denying their employees access to the data. Thus, they have a team that has mastery of the data but whose skills are eroding. Give your team more access to the data so they can use it and understand the information on their own.

  1. Promote knowledge exchange events

    The organization of knowledge exchange events can be internal (bringing together a specific department or aspect of the organization, for example, HR) or external (allowing employees to interact with experts or groups from within the organization. ‘industry).

    Data and analytics events allow you to exchange ideas effectively, learn the basics, see how other professionals manage data, and compare data literacy skills.

  1. Reduce barriers to mastery of data

    Controlling a company’s data is often hampered by several factors. Culture is one, and apps supporting data are another. Complex or new applications may require multiple learning curves, or they may not fully integrate with existing applications or tools, hampering decision making.

    Moreover, if administrators and managers adopt a discouraged attitude and aspiration, they can block any data literacy program as well. By removing all barriers to mastering data, the whole team will embrace progress.

Final thoughts

Developing data literacy doesn’t just mean helping your employees get the most out of the information they have. It is widely accepted that one of the biggest hurdles businesses face today is a lack of mastery over data.

Businesses continue to rely on data to generate actionable insights, but if your workforce is not kept up to date, it could hamper their long-term growth.

Danni White

| Danni White is the Director of Strategy and Content Development at Bython Media and the Editor-in-Chief of TechFunnel.com, a leading B2B digital destination for C-level executives, technologists and marketers. Bython Media is also the parent company of OnlineWhitepapers.com, BusinessWorldIT.com, List.Events and TheDailyPlanIOT.com.

About Shirley L. Kreger

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